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1
Comber, Alexis. "Automated land cover change detection". Thesis, University of Aberdeen, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248628.
Testo completoAbstract (sommario):
This thesis describes a generic approach for automated land cover monitoring. Knowledge about land cover is acquired through a knowledge acquisition exercise and used to augment image analysis in order to determine land cover change direction. It is demonstrated that taking a task-oriented approach to the change problem avoids the specificity of more traditional data-oriented approaches. The approach described here involves four key analyses that have contributed to the overall problem solution: Identifying the knowledge used to determine different land cover elements (elicitation and modelling); Land cover remote sensing characteristics; Land cover bio-geographic characteristics; Investigation of the most suitable approach for combining evidence. The results of these investigations were applied to semi-natural change problems: evidence about areas known to have changed was reasoned with and change directions identified by applying the knowledge and interpreter rules of thumb. The results were compared with field surveys of the change areas, and were shown to have correctly identified the land cover change direction in each case.
2
Leach, Nicholas Persak. "Hydrologic response of land use and land cover changes". Thesis, University of Iowa, 2015. https://ir.uiowa.edu/etd/1870.
Testo completoAbstract (sommario):
Throughout the years, land use and land cover (LULC) changes have directly impacted the water cycle in Iowa. To better understand the hydrological response to LULC change, the Hydrological Simulation Program - FORTRAN (HSPF) model will be used to qualitatively evaluate the effects of different LULC’s and quantify the associated adjustments to model parameters. Anecdotal and observational evidence of the hydrologic response will be employed to define how model parameters should be adjusted to represent certain LULC changes. The hydrologic assessment will be of the Turkey River Watershed located in northeast Iowa, which covers approximately 1,693 square miles.
3
Skelsey, Chris. "A system for monitoring land cover". Thesis, University of Aberdeen, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361785.
Testo completoAbstract (sommario):
Underlying the majority of remotely-sensed data analysis is the assumption that geographical phenomena, such as rivers, heather-moors and the dynamics associated with such objects, can be adequately detected and identified through the use of spectral and other visual information alone. There is a common misconception that any major deficiencies of quantitative analyses are "hardware problems": that by increasing the spectral, spatial, radiometric and temporal resolutions of sensors, geographical phenomena will be identified with similarly increasing accuracy and reliability. This, however, is an unrealistic viewpoint. This thesis has developed a prototype of an automated system based on the principle that by considering the "real-world" properties of the land, a more effective and robust analysis of its dynamic nature can ensue. SYMOLAC is an automated SYstem for MOnitoring LAnd Cover based upon theories of artificial intelligence. It has been developed within a specifically designed hybrid software environment called ETORA, an Environment for Task-Orientated Analysis. This prototype environment allows SYMOLAC to utilise disparate sources of spatial data, to reason with both quantitative and qualitative knowledge, to model disparate domain uncertainties, and to exploit the functionality of third-party software components. Unlike standard approaches, it allows an automated analysis to focus on each particular domain task and how it may best be performed with the available data, knowledge and software resources. The detection of forest felling and the subsequent update of the Land Cover of Scotland (1988) dataset forms the initial application of SYMOLAC. It is concluded that the system's approach is flexible, extensible and adaptable, and demonstrates one way in which satellite imagery can offer potential to the future monitoring of complex land cover change without the need for human intervention.
4
Zollet, Simona <1986>. "ANALYSIS OF LAND COVER AND LAND COVER CHANGE THROUGH REMOTE SENSING IN THE DOLOMITI BELLUNESI NATIONAL PARK". Master's Degree Thesis, Università Ca' Foscari Venezia, 2015. http://hdl.handle.net/10579/7015.
Testo completoAbstract (sommario):
This work focuses on the spatial changes in semi-natural grasslands habitats over the past 60 years in the Dolomiti Bellunesi National Park, Italy. Semi-natural grasslands have been created and maintained over the centuries by human activities, resulting in biodiversity-rich landscape mosaics, but the progressive abandonment of traditional grassland management activities such as low-intensity grazing and haymaking after World War II resulted in a widespread phenomenon of forest expansion, declining biodiversity and shrinking or disappearance of grassland areas.
Remote sensing technologies and Geographic Information Systems (GIS) represent invaluable tools for understanding the dynamics of this phenomenon; GIS software greatly improves image processing, data organization and quantitative analysis of the multi-temporal remote sensing da-tasets used for studying the dynamics of environmental patterns and processes at the spatial and temporal scale of interest. This in turn can provide support for decision-making and nature con-servation management, an aspect of fundamental importance for semi-natural ecosystems be-cause they require active management to sustain their ecosystem services.
In the first part of this work, high-resolution maps of distribution of semi-natural grassland habitats within the Dolomiti Bellunesi National Park (Italy) was created based on two aerial image-ry datasets: the 1954 GAI flight (the oldest available photographic record of the study area, dating back to before the start of mountain abandonment) and the 2012 TELAER flight. The distribution maps were created through the visual interpretation of aerial photographs and manual digitization of grassland polygons with the aid of GIS software. The two distribution maps were subsequently combined and compared to assess the spatial distribution and magnitude of changes over the 58-years time period.
The second part of the study explores the potential of studying the reduction of semi-natural grassland habitats by using Landsat satellite images, employing supervised pixel-based methods for classification and change detection and the NDVI vegetation index to increase the separability between different vegetated surfaces. First, a seasonality study was carried out to identify the most suitable period for ensuring maximum land cover separability during the vegetative season; for this purpose, a series of 5 Landsat TM images from 2005 (May-October) were classified inde-pendently through a semi-automated algorithm and their classification accuracies compared.
Based on the best date identified by the seasonality study, two Landsat images (from the beginning and the end of Landsat TM data availability period) were chosen for NDVI calculation and NDVI differencing change detection. In this change detection procedure, the NDVI values of the two images were subtracted pixel-by-pixel, resulting in a ΔNDVI change image that can be classified by setting an appropriate threshold to distinguish significant changes (increase or decrease of vegetation cover, where an increase is associated to forest expansion or densification) from situations where the land cover remained essentially unchanged.
5
Maluki, Peter Masavi. "MAPPING LAND COVER LAND USE CHANGE IN MBEERE DISTRICT, KENYA". Miami University / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=miami1187030316.
Testo completo
6
White, Claire McKenzie. "Analysis and Comparison of a Detailed Land Cover Dataset versus the National Land Cover Dataset (NLCD) in Blacksburg, Virginia". Thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/46322.
Testo completoAbstract (sommario):
While many studies have completed accuracy assessments on the National Land Cover Dataset (NLCD), little research has utilized a detailed digitized land cover dataset, like that available for the Town of Blacksburg, for this comparison. This study aims to evaluate the information available from a detailed land cover dataset and compare it with the National Land Cover Dataset (NLCD) at a localized scale. More specifically, it utilizes the detailed land cover dataset for the Town of Blacksburg to analyze the land cover distribution for varying land uses including single-family residential, multi-family residential, and non-residential. In addition, an application scenario assigns an area-weighted curve number to watersheds based on each land cover dataset. This study exhibits the importance of obtaining detailed land cover datasets for cities and towns. Furthermore, it shows the comprehensive information and subsequent quantifications that can be surmised from a detailed land cover dataset.Master of Science
7
Lawrence, Peter. "Climate impacts of Australian land cover change /". [St. Lucia, Qld.], 2004. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe18055.pdf.
Testo completo
8
Rosa, Isabel Maria Duarte. "Modelling land cover change in tropical rainforests". Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/40148.
Testo completoAbstract (sommario):
Tropical deforestation is one of the most important drivers of biodiversity loss and carbon emissions. This thesis seeks to analyse the dynamics of tropical deforestation and develop a probabilistic model that predicts land cover change (LCC) in the tropics. The main findings from the analysis of the Brazilian Amazon deforestation dynamics are that large clearings comprised progressively smaller amounts of total annual deforestation while the number of smaller clearings remained unchanged over time. These changes were coincident with the implementation of conservation policies by the government. The review of LCC models presented here showed that this modelling community would benefit from improving: the openness to share model inputs, code and outputs; model validations; and standardised frameworks to be used for model comparisons. The modelling framework developed aimed to tackle the limitations found before and two scenarios of deforestation in the Brazilian Amazon were simulated. For both scenarios forest next to roads and areas already deforested were found to be more likely to be deforested. States in the south and east of the region showed high predicted probability of losing nearly all forest outside of protected areas by 2050. The release of carbon to the atmosphere is an important consequence of tropical deforestation. Even if deforestation had ended in 2010 there would still be large quantities of carbon to be released. The amount of carbon released immediately is higher than the one committed for future release in the first few years of analysis, but presently these accounted for at least two-thirds of total carbon emissions. Finally, the drivers of LCC were found to vary among transition types, but less so through time. The accuracy of the model predictions was heavily dependent on the year calibrated, suggesting that a widespread reliance on single calibration time period may be providing biased predictions of future LCC.
9
Makido, Yasuyo Kato. "Land cover mapping at sub-pixel scales". Diss., Connect to online resource - MSU authorized users, 2006.
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10
陳章偉 e Cheung-Wai Jonathan Chan. "A neural network approach to land use/land cover change detection". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31238166.
Testo completo
11
Saxena, Rishu. "Towards a Polyalgorithm for Land Use and Land Cover Change Detection". Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/93177.
Testo completoAbstract (sommario):
Earth observation satellites (EOS) such as Landsat provide image datasets that can be immensely useful in numerous application domains.
One way of analyzing satellite images for land use and land cover change (LULCC) is time series analysis (TSA). Several algorithms for time series analysis have been proposed by various groups in remote sensing; more algorithms (that can be adapted) are available in the general time series literature. However, in spite of an abundance of algorithms, the choice of algorithm to be used for analyzing an image stack is presently an open question. A concurrent issue is the prohibitive size of Landsat datasets, currently of the order of petabytes and growing. This makes them computationally unwieldy --- both in storage and processing. An EOS image stack typically consists of multiple images of a fixed area on the Earth's surface (same latitudes and longitudes)
taken at different time points. Experiments on multicore servers indicate
that carrying out meaningful time series analysis on one such interannual, multitemporal stack with existing state of the art codes can take several days.
This work proposes using multiple algorithms to analyze a given image
stack in a polyalgorithmic framework. A polyalgorithm combines several basic algorithms, each meant to solve the same problem, producing a strategy that unites the strengths and circumvents the weaknesses of constituent algorithms. The foundation of the proposed TSA based polyalgorithm is laid using three algorithms (LandTrendR, EWMACD, and BFAST). These algorithms are precisely described mathematically, and chosen to be fundamentally distinct from each other in design and in the phenomena they capture. Analysis of results representing success, failure, and parameter sensitivity for each algorithm is presented. Scalability issues, important for real simulations, are also discussed, along with scalable implementations, and speedup results. For a given pixel, Hausdorff distance is used to compare the distance between the
change times (breakpoints) obtained from two different algorithms. Timesync validation data, a dataset that is based on human interpretation of Landsat time series in concert with historical aerial photography, is used for validation. The polyalgorithm yields more accurate results than EWMACD and LandTrendR alone, but counterintuitively not better than BFAST alone. This nascent work will be directly useful in land use and land cover change studies, of interest to terrestrial science research, especially regarding anthropogenic impacts on the environment, and in much broader applications such as health monitoring and urban transportation.M. S.
12
Howard, Madeleine A. "Patterns of land cover change in Kanyati communal land in Zimbabwe". Master's thesis, University of Cape Town, 1999. http://hdl.handle.net/11427/19518.
Testo completoAbstract (sommario):
Bibliography : pages 138-149.Expanding areas under cultivation and settlement are a global trend with significant effects on existing land cover types and ecosystems. High rates of human population growth in southern Africa and subsequent increased pressure on land has led to the extension of cultivation and settlement into marginal lands. This study investigates the spatial patterns ofland cover change in a communal land in Zimbabwe over the period 1973 to 1993, and their likely ecological effects. The study site is in the Zambezi Valley and has a well preserved area ofmiombo woodland and has the potential to become an important wildlife corridor between a national park, safari area and communal lands with local community based wildlife management projects. The area is divided into wildlife and settled areas by a game fence so provided an opportunity to compare patterns ofland cover change vvith and without extensive human impact within the same administrative area. The land cover types were derived from manually interpreted aerial photographs as multispectral satellite imagery is not available before the 1980's and is expensive. Geographical Information Systems were used to analyse the spatial patterns ofland covers identified, the sizes and shapes of spatial entities and the spatial distribution of land cover types in relation to slope and proximity to rivers. The likely ecological effects of land cover change were investigated by deriving habitat suitability maps using the habitat requirements of seven large herbivore species: buffalo, bushbuck, elephant, kudu, sable, waterbuck and zebra.
13
Batunacun. "Modelling land use and land cover change on the Mongolian Plateau". Doctoral thesis, Humboldt-Universität zu Berlin, 2020. http://dx.doi.org/10.18452/21796.
Testo completoAbstract (sommario):
Der Bezirk Xilingol wurde als geeignetes Beispiel ausgewählt, weil es zu einem großen Flächenanteil von Grassteppe bedeckt ist und fast alle Phasen der Umweltpolitik Chinas durchlaufen hat. Es wurden zwei deutlich voneinander abgrenzbare Phasen identifiziert, von 1975 bis 2000 und von 2000 bis 2015. Während der ersten Phase, bis 2000, war Landdegradation der dominante Landnutzungswandelprozess, der 11.4 % der Gesamtfläche betraf. In dieser Phase war die menschliche Einflussnahme der Hauptfaktor in acht Landkreisen, die sich ändernden Wasserverhältnisse war es in sechs Landkreisen. Während der zweiten Phase, ab 2000, setzte ein spürbare Erholung des Zustandes auf 12 % des Gesamtgebietes ein, während die Degradation jedoch weiter voranschritt und zusätzliche 9,5 % des Landes veränderte. Während dieser Phase wurde die Städtebildung zum dominanten Treiber für die Landdegradierung in sieben Landkreisen, während der Einfluss menschlicher Störungen und der Wasserverfügbarkeit wieder zurückging.
Nach der Identifizierung der Haupttreiber für die Landdegradation, wurde die komplexe Beziehung zwischen verschiedenen Treibern und der Grassteppen-Degradation untersucht. Die Ergebnisse zeigten, dass die Beziehung zwischen dicht bedeckter, moderat bedeckter, und spärlich bedeckter Grassteppe und die Dichte des Schafbesatzes für die Degradationsdynamik in der Grassteppe verantwortlich waren.
In dieser Arbeit wurden die Methoden der Clusteranalyse, der Partial-Order-Theorie, und der Hasse Diagramme eingesetzt, um die Haupttreiber der Landdegradation auf Landkreisebene zu identifizieren. Dann wurde ein Ansatz aus dem maschinellen Lernen, XGBoost (eXtreme Gradient Boosting) verwendet, um die Dynamik der Grassteppen-Degradation vorauszusagen. Darüber hinaus wurde SHAP (SHapley Additive exPlanations) eingesetzt, um das von XGBoost erstellte Black-Box-Modell zu in seine Bestanteile zu zerlegen und für jedes Degradations-Pixel in der Karte den Haupttreiber zu extrahieren.The aims of this thesis are to gain an integrated and systematic understanding of the processes and determinants of land degradation on the Mongolian Plateau. Xilingol was chosen as a suitable example, mainly since it is covered by vast grassland, and has experienced almost all ecological policies that have been implemented in China. Two distinct phases were identified in this region: 1975-2000 and 2000-2015. During the first phase (up to 2000), land degradation was the dominant land use change process, accounting for 11.4% of the total area. During this phase, human disturbance was the major driver in eight counties, whereas the water condition was the dominant driver in six counties. During the second phase (post-2000), land restoration increased (12.0% of the total area), whereas degradation continued, resulting in a further 9.5% of degraded land. During this phase, urbanisation became the dominant driver of land degradation in seven counties, while effects resulting from human disturbance and water availability decreased after 2000. After identifying the major drivers of degradation, the complex relationships between drivers and grassland degradation were captured. The results indicated that the distance to dense, moderately dense grass and sparse grass and sheep density were responsible for the grassland degradation dynamics. In this thesis, a clustering method, partial order theory and Hasse diagram techniques were first used to identify the major drivers of land degradation at the county level. Subsequently, an approach from machine learning, XGBoost (eXtreme Gradient Boosting), was used to predict the dynamics of grassland degradation. Moreover, SHAP (SHapley Additive exPlanations) values were used to open up the black box model, and the primary driver was extracted for each pixel showing degradation.
14
Chan, Cheung-Wai Jonathan. "A neural network approach to land use/land cover change detection /". Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B21415067.
Testo completo
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Guardiola-Claramonte, Maria Teresa. "EFFECTS OF LAND USE / LAND COVER CHANGE ON THE HYDROLOGICAL PARTITIONING". Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/145730.
Testo completoAbstract (sommario):
Current global population growth and economic development accelerates the land cover conversion in many parts of the world and compromises the natural environment. However, the impacts of this land cover change on the hydrologic cycle at local to regional scales are poorly understood. The thesis presented here investigates the hydrologic implications of land use conversion in two different settings using two different approaches. The first study focuses in Southeast Asia and the expansion of rubber monocultures in a middle-sized basin. Field measurements suggest rubber has distinct dynamics compared to the area's native vegetation, depleting and exhausting the local water balance more than native vegetation. A phenology based evapotranspiration function is developed and used in a hillslope based hydrologic model to predict the implications of rubber expansion at a basin scale. The second study is centered in the semi-arid southwestern United States. This study challenges the traditional assumption that deforestation increases water yield at regional scales. Observations of water yield in basins affected by a regional piñon pine die-off show a decline in water yield during several years after die-off. These results suggest an increase in landscape sensitivity to vegetation disruption in semi-arid ecosystems as scale increases. Consequences of both studies have important implications for land and water managers in these different ecosystems.
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Knorn, Jan. "Studying land-use and land-cover change with high resolution data". Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2012. http://dx.doi.org/10.18452/16513.
Testo completoAbstract (sommario):
Naturschutzgebiete sind ein essentieller Bestandteil zur Wahrung natürlicher Lebensräume. Oft verfehlt die Einrichtung solcher Schutzzonen jedoch den erwarteten Effekt. Die größte Gefahr liegt hierbei neben dem Klimawandel im direkten Einfluss des Menschen. Besonders in Phasen sozioökonomischen Umschwungs und damit verbundenen Landnutzungsveränderungen oder auch illegaler Nutzung natürlicher Ressourcen, sind Naturschutzgebiete in ihrer Funktion gefährdet. Ziel dieser Arbeit ist somit, Ursachen des Landnutzungswandels sowie dessen Auswirkungen und Ausmaß am Beispiel des rumänischen Teils der Karpaten-Ökoregion abzuleiten. Das Untersuchungsgebiet ist ein wichtiges Zentrum für Biodiversität und in ihm befindet sich Osteuropas größte gemäßigte Waldregion sowie einige der letzten europäischen Urwälder. Rumänien umschließt mehr als die Hälfte der Karpaten und es ist hiernach von besonderem Interesse, Gründe und Auswirkungen des rezenten post-sozialistischen Landschaftswandels zu untersuchen. Mit Hilfe von Landsat Aufnahmen sowie einer ad hoc entwickelten Methode zur Klassifizierung großräumiger Gebiete, wurden Veränderungen in der Waldbedeckung für die post-sozialistische Zeit abgeleitet. Die Ergebnisse offenbaren großflächige Forstveränderungen, auch innerhalb von Naturschutzgebieten und Urwäldern. Institutionelle Umbrüche und eine rapide Umgestaltung in den Eigentumsverhältnissen, wurden als Hauptursachen herausgestellt. Rumänische Naturschutzgebiete erreichen nicht die gewünschte Effektivität und Urwäldern werden weiterhin dezimiert. Die Arbeit verdeutlicht den Einfluss sozioökonomischer Veränderungen auf die Entstehung von Raubbau und legt Defizite in der Effektivität von Schutzbemühungen zum Erhalt der Biodiversität und verbundener Ökosystemleistungen offen.Protected areas are one cornerstone of conservation efforts to safeguard natural habitats from destruction and overexploitation. Still, many of these areas remain less effective than initially envisioned. Besides climate change, main threats originate from enduring human activities. Protected areas are particularly at risk during periods of rapid socio-economic changes, which can trigger widespread land-use change and illegal resource use. The main goal of this thesis is to assess the extend and underlying causes of land-use change in protected areas and forest habitats within the Carpathian Ecoregion. The Romanian Carpathians were selected as a focus area in this study, because they comprise Eastern Europe’s largest continuous temperate forest region as well as some of the last and largest tracts of European old-growth forests, and they are a major hotspot of biodiversity. Romania comprises more than half of the Carpathian Ecoregion and it is of particular interest to study the causes and effects of land-use changes, which have emerged after the collapse of socialism in 1989. Post socialist forest cover change was quantified for the last 25 years using Landsat images and an ad hoc developed large area classification technique. Results show widespread forest disturbances, even inside protected areas and old-growth forests. Drivers of these disturbances can be related to institutional change and changes in ownership. The effectiveness of Romania’s protected area network in terms of its ability to safeguard biodiversity is most likely decreasing, and intact old-growth forests continue to disappear. This thesis reveals how rapid socio-economic changes may lead to overexploitation, and highlights substantial shortcomings in the effectiveness of protection efforts to safeguard biodiversity and related ecosystem services.
17
Pearlman, Daniel I. "Patterns and Processes of Land Use/Land Cover Change, 1975-2011, at Mt. Kasigau, Kenya". Miami University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=miami1416571718.
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18
English, Amanda M. "Land Cover Change Analysis of the Mississippi Gulf Coast from 1975 to 2005 using Landsat MSS and TM Imagery". ScholarWorks@UNO, 2011. http://scholarworks.uno.edu/td/1306.
Testo completoAbstract (sommario):
The population, employment and housing units along the Gulf Coast of Mississippi have been increasing since the 1970s through the 2000s. In this study, an overall increasing trend in land cover was found in developed land area near interstates and highways along all three coastal counties. A strong positive correlation was observed in Hancock County between developed land and population and developed land and housing units. A strong negative correlation was observed between vegetation and housing units. Weak positive correlations were found in Harrison County between developed land and population, marsh and population, and marsh and housing units. A weak positive correlation was found in Jackson County between bare soil and population. Several study limitations such as unsupervised classification and misclassification are discussed to explain why a strong correlation was not found in Harrison and Jackson Counties.
19
Altaf, Muhammad 1961. "Area-average representation of land surface covers in large atmospheric models based on remotely sensed land surface cover data". Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/282572.
Testo completoAbstract (sommario):
The research described in this dissertation is predicted on the hypothesis that remotely sensed information on vegetation cover classes can be used to improve the representation of heterogeneous continental surfaces in global climate models. The problem it addressed was that current understanding of soil-vegetation-atmosphere interactions is considered only to be relevant to small plots of uniform vegetation with dimensions of the order 10-1000 m but, in order to provide realistic simulation of climate, General Circulation Models require description of such interactions for large areas of mixed vegetation with dimensions of the order 100-1000 km. The methods used to investigate this issue was to create and apply a coupled model that provided realistic representation of both surface and atmospheric boundary layer processes, and to use this model to simulate surface-atmosphere interactions with explicit representation of patches of vegetation on the one hand, and with a single, area-average representation of exchanges on the other. These modeling studies were given credibility by initiating and validating the coupled model using appropriate data from the FIFE site in Kansas and the ABRACOS site in Brazil. The results showed that when quite simple aggregation rules are used to derive the effective area-average values of the vegetation-related parameters, these parameters give adequate simulation of surface-atmosphere interactions. These aggregation rules were then applied using remotely sensed maps of land cover to derive parameter values. Significant differences were found in the resulting parameters, and in the surface energy fluxes and modeled climate calculated using those parameters. Thus, it has been shown that remotely sensed data can indeed be used to improve the representation of heterogeneous land surfaces in global climate models using the methods developed in this research, and that using these data significantly alters the simulated global climate.
20
Bates-Lanclos, Melissa Marie. "Assessing urban land use/land cover change in Springfield, Missouri 1972-2000 /". free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p1426046.
Testo completo
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Bradley, Andrew Vincent. "Land-use and land-cover change in the Chapare region of Bolivia". Thesis, University of Leicester, 2005. http://hdl.handle.net/2381/9586.
Testo completoAbstract (sommario):
This research examines the impacts of coca leaf cultivation (an ingredient for cocaine paste) on land-use and land-cover change (LULCC) in a colonised, humid-tropical forest area of central Bolivia. The socio-economic driving forces affecting the way farmers have utilised their land and the resulting effects on land-cover change are studied. Satellite imagery from 1975 to 2000, methods of participatory rural appraisal and socio-economic data has been combined to determine deforestation patterns, changes and the driving forces of LULCC. Three communities were studied: Arequipa, dominated by coca production and alternative development crops; Bogota, a cattle rearing community; and Caracas where fruit cultivation dominated. Three major periods were determined from a land-management synopsis in each community: (i) pre-coca dominant, driven by weak national policies and economics, with high rates of deforestation; (ii) coca-dominant, influenced by the international coca / cocaine economy, with the lowest rates of forest clearance; and (iii) post coca-dominant, driven by strong international anti-narcotics policies, when forest clearance accelerated again. The deforestation trajectories (rates) differ from published models and the variations are attributed to the rising dominance of coca being ascended by an enforced substitute economy. These driving forces have been conceptualised at local, national and international levels. Specific fragmentation patterns developed because of the spatial arrangement of plots planned in the 1960s and the subsequent variations in land-use management strategies between, as well as, within individual plots over time. A five stage conceptual model has been constructed to represent forest fragmentation at the community level. Overall, in the pursuit of global social gains, anti-narcotics policies caused rapid consumption of limited land resources and because of non-conservationist planning the connectivity between montane and humid tropical forests at the margins of a biodiversity hotspot is severely compromised -a message to planners and policymakers where conservation and development currently conflict in humid tropical regions.
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Anibas, Kyle Lawrence. "Land cover, land use and habitat change in Volyn, Ukraine : 1986-2011". Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/17682.
Testo completoAbstract (sommario):
Master of ScienceDepartment of Geography
Douglas G. Goodin
Volyn Oblast in Western Ukraine has experienced substantial land use/land cover change over the last 25 years as a result of a change in political systems. Remote sensing provides a framework to quantify this change without extensive field work or historical land cover records. In this study, land change is quantified utilizing a post-classification change detection technique comparing Landsat imagery from 1986-2011(Post-Soviet era began 1991). A variety of remote sensing classification methods are explored to take advantage of spectral and spatial variation within this complex study area, and a hybrid scheme is ultimately utilized. Land cover from the CORINE classification scheme is then converted to the EUNIS habitat classification scheme to analyze how land cover change has affected habitat fragmentation. I found large scale agricultural abandonment, increases in forested areas, shifts towards smaller scale farming practices, shifts towards mixed forest structures, and increases in fragmentation of both forest and agricultural habitat types. These changes could have several positive and negative on biodiversity, ecosystems, and human well-being.
23
Maus, Victor Wegner. "Land use and land cover monitoring using remote sensing image time series". Instituto Nacional de Pesquisas Espaciais (INPE), 2016. http://urlib.net/sid.inpe.br/mtc-m21b/2016/06.01.14.07.
Testo completoAbstract (sommario):
Land system change has a wide range of impacts on Earth system components. Tropical forests in particular have been identified as crucial ecosystems for climate regulation, global biodiversity, and hydrological cycling. The Brazilian Amazon has experienced a high rate of deforestation in the last decade and it is the main source of Brazils anthropogenic CO$_{2}$ emissions. The growing global population will further increase the demand for food and therefore increase the pressure on agricultural systems. High quality, fine resolution, and near-real time land use and land cover monitoring systems play a crucial role in generating information to advance our understanding of human impact on land cover. Earth Observation satellites are the only source that provides a continuous and consistent set of information about the Earth${'}$s land. The current large-scale classification systems such as MODIS Land Cover and GLC 2000 have limitations and their accuracy is not sufficient for land change modeling. Therefore, new techniques for improving land system products are urgently needed. The contribution of this thesis to Earth System Science is threefold. Firstly, the thesis presents a new method for analysis of remote-sensed image time series that improves spatio-temporal land cover data sets and has a substantial potential for contributing to land system change modeling. The developed Time- Weighted Dynamic Time Warping (TWDTW) method is a time-constraint variation of the well-known Dynamic Time Warping (DTW) method, which has in the extensive literature proved to be a robust time series data mining. Secondly, this thesis contributed to open and reproducible science by making the algorithms available for larger audience. TWDTW is implemented in an open source R package called dtwSat available in the Comprehensive R Archive Network (CRAN). Thirdly, this thesis presents an analysis of land cover changes in the Amazon, focusing on the Brazilian state of Mato Grosso that has gone through high rate of deforestation and cropland expansion in the last decade. This study identified and estimated the land cover change using MODIS image time series, contributing to better understand the land dynamics in the Brazilian Amazon. In the study area the pasture is the dominant land use after deforestation, whereas most of the single cropping area comes from pasture, and the cropping system is undergoing intensification from single to double cropping. Moreover, the regenerative secondary forest comes mainly from pasture. The study showed the potential of the TWDTW method for large-scale remote sensing data analysis, which could be extended to other Brazilian biomes to help understand land change in the whole Brazilian territory.Mudanças na superfície da terra têm uma ampla gama de impactos sobre o sistema terrestre. Florestas tropicais, em particular, são ecossistemas cruciais para regulação climática, manutenção da biodiversidade, a ciclo hidrológico. Na última década a Amazônia brasileira tem experimentado uma alta taxa de desmatamento, sendo a principal fonte de emissões antropogênicas de CO$_{2}$ no Brasil. O crescimento da população mundial vai aumentar ainda mais a demanda por alimentos e, portanto, aumentar a pressão sobre agrícultura e pecuária. Dados com alta qualidade, melhor resolução espacial e temporal, e o desenvolvimento de sistemas de monitoramento desempenham um papel crucial na geração de informações para avançar nossa compreensão sobre os impactos humanos na cobertura da terra. Os satélites de observação da Terra são a única fonte que fornece um conjunto contínuo e consistente de informações sobre nosso planeta. Sistemas de classificação em grande escala, como MODIS Land Cover e GLC 2000 têm limitações e sua acurácia não é suficiente para a modelagem de mudanças de use da terra. Portanto, são necessárias novas técnicas para melhoramento dos dados de use e cobertura da terra. Esta tese traz três contribuições para a Ciência do Sistema Terrestre. Primeiramente, esta tese apresenta um novo método para análise de séries temporais de imagens satélite que melhora a classificação de cobertura da terra. O método tem grande potencial para contribuir para a modelagem de mudanças do sistema terrestre. O método desenvolvido, Time-Weigted Dynamic Time Warping (TWDTW), é uma adaptação ponderada por tempo do método clássico Dynamic Time Warping (DTW), que tem em uma extensa literatura provando ser um método robusto para mineração de dados em séries temporais. Em segundo lugar, esta tese contribuiu para a ciência aberta e reprodutível, tornando algoritmos disponíveis para o público. TWDTW está implementado em um pacote R de código aberto chamado dtwSat disponível no Comprehensive R Archive Network (CRAN). Em terceiro lugar, esta tese apresenta uma análise as mudanças do uso e cobertura da terra na Amazônia, com foco no estado do Mato Grosso, que passou por alta taxa de desmatamento e expansão agrícola na última década. Este estudo identificou e estimou mudanças de cobertura da terra com séries temporais de imagens MODIS, contribuindo para melhor compreender a dinâmica de ocupação da terra na Amazônia brasileira. Na área de estudo, a pastagem é o uso dominante após o desmatamento, ao passo que a maior parte da área de cultivo com um ciclo anual provem da área de pasto, com o sistema de cultivo passando por intensificação, mudando de cultivo simples para cultivo duplo. Além disso, áreas de regeneração vêm, principalmente, de áreas de pastagem. O estudo mostrou o potencial do método de TWDTW para análise de dados de sensoriamento remoto em grande escala, que poderia ser estendido a outros biomas brasileiros para ajudar a entender as mudanças da terra em todo o território brasileiro.
24
Tizora, Petronella Chenayi. "Modelling land use and land cover change in the Western Cape Province". Diss., University of Pretoria, 2018. http://hdl.handle.net/2263/65948.
Testo completoAbstract (sommario):
The Western Cape Province is currently faced with population growth, declining household sizes, increasing household numbers, high levels of migration, urbanization and escalating development pressures. These factors have consequently triggered changes in land use and land cover (LULC) and incited issues such as urban sprawl, marginalization of the poor, limited public access to resources, land degradation and climate change. Furthermore, the issues surrounding LULC in the Province emanate from past inequities in access to land coupled with unsustainable land use practices. This poses a challenge to the government which strives for a sustainable nation that safeguards democracy by providing basic access to services, managing limited resources and advancing effective and efficient integrated planning whilst maintaining ecosystem functions. Understanding drivers of LULC change and how various factors influence LULC is important in meeting this challenge. Models which integrate and evaluate diverse factors of LULC change can be used to guide planners in making more informed decisions and achieving a balance between urban growth and preservation of the natural environment. The implementation of these models at a regional scale is however very limited in South Africa. LULC change models are valuable if their structures are based on deep knowledge of the system under investigation and if they produce credible results. This study therefore investigates the suitability of LULC change models in simulating LULC changes at a regional scale by quantifying changes in LULC in the Western Cape Province, determining the driving factors of LULC changes and exploring and implementing a regional land use change model. An investigation of changes in LULC was conducted by integration of a desktop study of LULC maps using the 1990 and 2013-2014 South African National LULC datasets; document analysis; and expert opinion in the form of semi-structured interviews with municipality town planners. An adapted Driver-Pressure-State-Impact-Response (DPSIR) Framework was used to analyse and present LULC changes in the study area. A literature review was conducted in shortlisting of models and further evaluations involved analysis of the models using selection criteria which focused on the model’s relevance to the study area, linkage potential to other models or software, transferability, user friendliness, data requirements and cost. The results of this study show that LULC changes in the Western Cape Province are driven by political, economic, technological, demographic, environmental and cultural factors which must be considered in strategies and policies in future planning to avoid detrimental impacts on the environment whilst maintaining socio-economic benefits. These factors were integrated in a hybrid model that was successfully implemented in the study area by combining Dyna-CLUE and Markov concepts. The hybrid model produced probability maps and simulation maps for the years between 1990 and 2014. Validation of the simulated maps was conducted using both visual and statistical analysis and the results indicated that the simulated maps were in good agreement with the validation map. Data availability was observed as the main drawback which influenced both the implementation of other suitable models and the accuracy of simulated maps. This study however contributes to the understanding of driving factors of LULC change and implementation of LULC change models at a regional scale in the South African context. Knowledge derived from this study can be used by planners as a guide to effectively gauge the impacts that planning policies and other driving factors might have on future LULC patterns in the Western Cape Province.Dissertation (MSc)--University of Pretoria, 2018.
Geography, Geoinformatics and Meteorology
MSc
Unrestricted
25
Bhattarai, Shreejana. "Understanding the relationship between land use/land cover and malaria in Nepal". Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/96214.
Testo completoAbstract (sommario):
Malaria is one of the leading causes of mortality and morbidity globally. Land use/land cover (LULC) change have been found to affect the transmission and distribution of malaria in other regions, but no study has attempted to examine such relationships in Nepal. Therefore, this study was conducted in Nepal to assess LULC change between 2000 and 2010, to study the spatial and temporal trend of malaria incidence rate (MIR) between 1999 and 2015, and to understand the relationship between LULC and malaria. The land cover types used for this study are forest, water bodies, agriculture, grassland, shrubland, barren areas, built-up areas and paddy areas. Change detection techniques were used to study LULC change. The temporal trend of MIR in 58 districts, and the relationship between MIR and LULC were evaluated using Poisson and negative binomial regression. Forest, water bodies, snow cover, and built-up area increased in Nepal by 28.5%, 2.96%, 55.12% and 21.19% respectively while the rest of the LULC variables decreased. MIR decreased significantly in 21 districts; however, four districts namely Pyuthan, Kaski, Rupandehi and Siraha had a significantly increasing trend of MIR. During 2001, 2002, and 2003, MIR was positively related to water bodies and paddy areas. Similarly, MIR of 2010 was negatively related to grassland. However, there was no relationship between LULC and MIR in 2000, 2011, 2012 and 2013. It may be because MIR is decreasing significantly in the country and thus the influence of LULC change is also decreasing.MS
26
Goffredo, Stefania. "Automatic generalization of satellite-derived land cover informatiion". Thesis, University of Leicester, 1998. http://hdl.handle.net/2381/30394.
Testo completoAbstract (sommario):
The generalization process works on independent image-objects formed by a closed-boundary and a corresponding enclosed-region on the classified image. Initial image-objects are obtained by integrating the classified image with a geographically corresponding satellite-derived edge-segmented image. The generalization process is organised in two main levels of abstraction. Firstly Geometric generalization, responsible for the spatial and thematic simplification of the classified image, elaborating the initial image-objects in to higher-level polygons (the spatial basis of the final product). Secondly Semantic generalization, responsible for the thematic conversion of the simplified product, associating each higher-level polygon to the most appropriate land use class. The CORINE land cover classification scheme was taken as the target product during this thesis. The classification scheme is however overly detailed for direct comparison with satellite-derived products. To overcome this an intermediate classification was defined in this thesis: Pseudo CORINE (Pcor), which is a 1-level scheme containing: bottom-level CORINE classes which are automatically recognisable by image processing techniques, and 2nd-level CORINE classes as substitutes for those CORINE classes not automatically recognisable. The definition of the Pcor scheme allowed an automatic nomenclature conversion, organised in two steps: 1)re-labelling, based on syntax matching, of low-level classes presenting a one-to-one relationship with a single Pcor class. 2)contextual reasoning, based on mutually exclusive hierarchical rules, for the conversion of low-level classes which present a one-to-many relationship with Pcor classes. A fully automatic generalization process has been developed and verified during this work. The automatic generalization process has produced generalized products which are in excellent agreement with the target CORINE map. The simplification of geometry and content of the input information based on image-statistics and contextual rules is fully automatic, unsupervised, consistent, objective, repeatable and generally applicable.
27
Berberoglu, Suha. "Optimising the remote sensing of Mediterranean land cover". Thesis, University of Southampton, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.285646.
Testo completo
28
Cuaron, Alfredo D. "Land-cover changes and mammal conservation in Mesoamerica". Thesis, University of Cambridge, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.368617.
Testo completo
29
Ahmed, Kazi Iashtiak. "ENVISAT ASAR for Land Cover Mappingand Change Detection". Thesis, KTH, Geodesi och satellitpositionering, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-199863.
Testo completoAbstract (sommario):
The principal objective of this research is to investigate the capability of multi-temporal,multi-incidence angle, dual polarization ENVISAT ASAR imagery for extractinglanduse/land cover information in the rural-urban fringe of the Greater Toronto Area (GTA)using different image processing techniques and classification algorithms. An attempt todetermine the temporal change of landuse is also made.The multi-temporal ASAR imagery was first orthorectified using NTDB DEM and satelliteorbital models. Different image processing techniques, such as, Adaptive Speckle Filtering,Texture measures, Principal Component Analysis (PCA) were applied to the ASAR images.Backscatter profiles were generated for selected land cove classes. K Nearest neighbor (kNN)classifier was used to extract eleven land cover classes. Artificial Neural Network (ANN) wasalso tested with some selected combinations of ASAR imagery. The classification schemewas adopted from USGS alnuse/land cover classification scheme. Average accuracy, overallaccuracy and Kappa coefficients were calculated for all classifications.The raw ASAR images gave very poor results in identifying landuse/land cover classes due tothe presence of immense speckle. Enhanced Frost (EF) filtering significantly improved theclassification accuracies. For texture measures, eleven date Mean images produced the bestresult among all single set processed data. Combined Mean and Standard Deviation,combinations of different texture measures, further improved the results. Standard deviationprovided vital auxiliary boundary information to the classification resulting in theimprovement. The best kNN was achieved with combined Mean and Standard Deviation withmulti-incidence angle, dual polarization eleven date ASAR images. ANN further improvedthe classification results of the textured images. As for comparison of classifiers, It was foundthat, with complex combinations (dual polarization, multi-incidence angle), ANN performssignificantly better than kNN. The overall accuracy was 9.6% higher than that of kNN. Theresults were more or less similar in filtered images.Post classification change detection is largely dependent on classification accuracy ofindividual images. Even though, the classification results were somewhat satisfactory, theclassified ASAR image still had a significant amount or omission and commission errors withsome classes. The classification errors contributed a significant amount of noise in changedetection. The change detection procedure, however, was able to identify the areas ofsignificant change, for example, major new roads, new low and high built up areas and golfcourses.In brief, ENVISAT ASAR data was found to have vast potential in extracting land coverinformation. Especially with its all weather capability, ASAR can be used together with highresolutionoptical images for temporal studies of landuse/land cover change due to urbansprawl.
30
Shakeel, Mohammad Danish. "Land Cover Classification Using Linear Support Vector Machines". Connect to resource online, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1231812653.
Testo completo
31
Samaniego, Eguiguren Luis E. "Hydrological consequences of land use, land cover and climatic changes in mesoscale catchments". Stuttgart : Inst. für Wasserbau, 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=968806724.
Testo completo
32
GuimarÃes, ClÃcia Cristina Barbosa. "Landscape hitherland: land use/ land cover and adequability in central sertÃo of CearÃ". Universidade Federal do CearÃ, 2013. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=9497.
Testo completoAbstract (sommario):
The unit fitoecogeografic called Caatinga is unique and characteristic of the brazilian semiarid
region. Its natural landscape, formed by various mosaics, has been losing its primary
characteristics due unplanned socioeconomic activities, hindering sustainable development. In
recente years, it has been observing an extreme landscape modificationâs caused by strong
anthropic activity manifested by soil erosion, microclimate changes, loss of biodiversity and
agricultural productivity reduction. Landscapeâs Ecology studies, Land use/Land Coverâs
maps and suitability of land use are importante for better management in the region. Thus, in
this study, I evaluated how suitable is the land use in specifc central semiarid region of CearÃ
State and I have qualified the landscape fragmentation. For this, I drew up land use and land
coverâs map and I crossed this map with agricultural suitability and slope informations, using
Geografic Information System and Remoting Sensing, which allowed me to assess the land
use suitability. I used landscapeâs metrics of the structure on the same land use and land
coverâs map to characterize and evaluate the landscape fragmentation process. The results
show the region presents itself with land used inappropriately and inappropriate use could
become an increasingly common practice due to greater need of land for local population
subsistence. There isnât environmental planning for land use suitable and, beyond the
problems caused to soil conservation, the natural landscape is becoming increasingly
fragmented.A unidade fitoecogeogrÃfica denominada Caatinga à Ãnica e caracterÃstica do semiÃrido brasileiro. Sua paisagem natural, formada por diversos mosaicos, vem perdendo suas caracterÃsticas primÃrias em funÃÃo das atividades socioeconÃmicas mal planejadas, dificultando o desenvolvimento sustentÃvel. Nos Ãltimos anos, vem se observando uma extrema modificaÃÃo da paisagem ocasionada pela intensa aÃÃo degradadora antrÃpica que se manifesta pela erosÃo dos solos, alteraÃÃes microclimÃticas, perda da biodiversidade e produtividade agrÃcola reduzida. Estudos que envolvam a Ecologia de Paisagens e levantamentos do uso e cobertura e adequabilidade do uso da terra, a partir de mapas, sÃo importantes para um melhor manejo na regiÃo. Assim, neste trabalho, avaliou-se quÃo adequado està sendo o uso da terra em um polÃgono localizado no SertÃo Central do Estado do Cearà e caracterizou-se a fragmentaÃÃo da paisagem. Para isso, foi feito o mapa de uso e cobertura das terras e cruzou-se as informaÃÃes resultantes desse mapa com outras de declividade, fazendo-se uso de Sistema de InformaÃÃo GeogrÃfica e Sensoriamento Remoto, que possibilitou avaliar a adequabilidade do uso das terras. Aplicando-se mÃtricas de estrutura da paisagem sobre o mesmo mapa de uso e cobertura foi possÃvel caracterizar e avaliar o estado de fragmentaÃÃo da paisagem. Percebe-se, pelos resultados encontrados, que a regiÃo apresenta-se com terras inadequadamente utilizadas e o uso inadequado pode se tornar uma prÃtica cada vez mais comum, uma vez que hà a necessidade crescente de terras para satisfazer as necessidades das populaÃÃes locais. NÃo hà um planejamento ambiental para o uso adequado da terra e, desta forma, alÃm dos problemas ocasionados à conservaÃÃo do solo, a paisagem natural està se tornando cada vez mais fragmentada.
33
Jack, Sam. "Changing land use / land cover around an urban estuary : implications for ecosystem functioning". Bachelor's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/24958.
Testo completoAbstract (sommario):
The changing spatial and temporal patterns in land use/land cover surrounding Zandvlei estuary were investigated over the period 1944 to 2005. Changes in the extent of four terrestrial and two aquatic land use/land cover categories were mapped from high quality aerial photographs using ArcView GIS. Basic spatial analyses were performed to quantify changes in area, 'edge-effects' and relative dominance through time. Semi-natural and seasonally inundated classes accounted for over 70% of land cover in 1944, but declined steadily as urban land use and permanently inundated land cover expanded to a present-day extent of 42% and 19% respectively. The following major drivers of change were identified: 1) the construction of the railway embankment bisecting Westlake wetland and Zandvlei estuary, which led to sedimentation and a change in plant species composition of the wetland, but decreased nutrient inflows into the vlei; 2) agricultural practices within the catchment at the start of the 20th century which increased sediment and nutrient inflows; 3) elevated water levels due to dredging operations between 1947 and 1961, which resulted in a significant loss of seasonally inundated land cover with concomitant changes in species composition and nutrient dynamics; and 4) urban development surrounding the vlei (with particular reference to Marina da Gama), which has expanded at the expense of semi-natural areas and significantly increased effluent and litter inputs into the vlei. A socially and ecologically balanced management policy governing the entire catchment is required to mitigate future impacts.
34
Magee, Kevin S. "Segmentation, Object-Oriented Applications for Remote Sensing Land Cover and Land Use Classification". University of Cincinnati / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1298040118.
Testo completo
35
Samaniego-Eguiguren, Luis Eduardo. "Hydrological consequences of land use - land cover and climatic changes in mesoscale catchments". [S.l. : s.n.], 2003. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB10720630.
Testo completo
36
Stabile, Marcelo C. C. "Deconstructing the complexity of land use and cover classification and land change modelling". Thesis, The University of Sydney, 2011. http://hdl.handle.net/2123/8640.
Testo completoAbstract (sommario):
Land use and land cover (LULC) dynamics are an integral component of global change. In this thesis, various approaches were developed to unravel the complexity of LULC classification and the subsequent application of the multi-temporal LULC data for land change modelling. This complexity is particularly relevant in this study, whereby the available multi-temporal remote Landsat images are noisy and of relatively low spatial resolution. First, a semi-automated object-based method using rulesets and supervised classification was developed. This method was applied to the multi-temporal Landsat images to produce LULC maps. As the outcomes of the classification were not sufficiently accurate for land change modelling, the LULC maps were subsequently augmented using expert knowledge and input from landowners. Second, since high-resolution aerial photos were available for portions of the study area for 1998 and 2004, a case study was done with image fusion. The case study compared LULC maps derived from the different levels of fusion to those from the non-fused images. The results indicated that the feature- and decision-level fusion produced LULC maps which could be used for land change modelling. Third, in order to develop a land change model, the augmented multi-temporal LULC maps were used for extracting transition probabilities for a Markov-chain land change model. However, the classical Markov-chain method does not consider the neighbourhood influence, whereas the cellular automata does. A flexible hybrid approach, combining the Markov-chain and cellular automata algorithms, was developed. This was done to model the LULC dynamic transition probabilities to drive the change. The model’s sensitivity was assessed and the hybrid approach was tested by simulations of contemporary and future LULC patterns in the lower Hunter Valley, NSW with transition probabilities derived from various methods.
37
Mancini, Adriano. "A new methodological framework for land use/land cover mapping and change detection". Doctoral thesis, Università Politecnica delle Marche, 2010. http://hdl.handle.net/11566/242247.
Testo completo
38
Germer, Sonja. "Near-surface hydrology and hydrochemistry under contrasting land-cover". Phd thesis, Universität Potsdam, 2008. http://opus.kobv.de/ubp/volltexte/2008/1904/.
Testo completoAbstract (sommario):
Human transformation of the Earth’s land surface has far-reaching and important consequences for the functioning of hydrological and hydrochemical processes in watersheds. In nowadays land-use change from forest to pasture is a major issue in particular in the tropics. A sustainable management of deforested areas requires an in-depth understanding of the water and nutrient cycle. On this basis we compared the involved hydrological pathways for rainfall to reach streams and the nutrient budgets of a tropical rainforest and a pasture. In addition we studied the links of hydrochemical differences to differences of the relative importance of flowpaths. This study was conducted in the southwestern part of the Brazilian Amazon basin. An intensive hydrological and hydrochemical sampling and monitoring network was set up. The results indicate that the hydrology was modified in many ways due to land-use change. The most important alteration was the increased importance of the fast flowpath overland flow. Solute exports were in particular linked to the increased volume of overland flow that resulted from the land-use change. An additional reason for the increased nutrient exports from the pasture are the high concentrations of these nutrients in pasture overland flow probably as a due to cattle excrements. Tight nutrient cycles with minimal nutrient losses could not be maintained after the land-use change. This study provides the first attempt to quantify the respective nutrient losses.Die Zerstörung von natürlicher Vegetation kann weit reichende Folgen auf den Wasser- und Nährstoffhaushalt von Ökosystemen haben. Der Landnutzungswandel vom Wald zur Weide ist heute in den Tropen ein wichtiges Thema. Eine nachhaltige Nutzung abgeholzter Gebiete setzt ein fundiertes Wissen des Wasser- und Nährstoffhaushaltes voraus. Darauf aufbauend wurden in dieser Studie das Abflussverhalten und die Nährstoffbilanzen von einem tropischem Regenwald und einer Weide verglichen. Außerdem wurde untersucht inwieweit die Nährstoffbilanzen vom Abflussverhalten abhängen. Die Untersuchungsgebiete liegen im südwestlichen brasilianischen Amazonasgebiet. Ein umfangreiches System zur Aufnahme von hydrologischen Daten und zum Sammeln von Wasserproben wurde aufgebaut. Die Ergebnisse haben gezeigt, dass sich das Abflussverhalten durch die Landnutzung geändert hat. Die wichtigste Änderung vom Wald zur Weide war der gesteigerte Anteil des schnellen Wasserabflusses auf der Geländeoberfläche. Hieraus resultierten gesteigerte Nährstoffausträge aus der Weide gegenüber dem Wald. Ein weiterer Grund für die gesteigerten Nährstoffausträge sind die hohen Konzentrationen dieser Stoffe im Oberflächenabfluss der Weide, die vermutlich mit den Ausscheidungen des Viehs zusammenhängen. Es hat sich also gezeigt, dass der quasi-geschlossene Nährstoffkreislauf nach der Landnutzungsänderung nicht aufrecht erhalten werden konnte. Diese Arbeit liefert den ersten Versuch diese Nährstoffverluste zur quantifizieren.
39
Garba, Samuel Sule. "Assessment of land cover change in north eastern Nigeria". Thesis, Cranfield University, 2008. http://dspace.lib.cranfield.ac.uk/handle/1826/3489.
Testo completoAbstract (sommario):
Land cover change provides a means of understanding and managing the problems of degradation and shortage of land and water resources and the conflicts therewith in the north eastern Nigeria. This research assessed how tree, shrub grass, bare ground changed from 1986 to 2005 using the NigeriaSat-1 and Landsat images calibrated with field survey data. Thirteen subclasses of the land cover were spectrally analysed and classified severally, however uncertainties in the classification made the merger into four classes necessary. Changes were analysed according to persistence, swapping, loss and gain analysis, multi-year transition of each land cover in succession, location of intensive change, and regional change density. Uncertainties were analysed by confusion and transition error matrices. The overall accuracies of the classifications were between 60% and 75%, and the transition and change accuracies were between 45% and 60%. Approximately 60% of the area of study remained unchanged during the period. Of the remainder, approximately 11% of the area interchanged between shrub grass and bare ground. Shrub grass was found to be the most unstable category and the source of most misclassification. The loss of tree was general but more intensive in the Fadama making it the most vulnerable. How local people perceived land cover change was sought through group interview and the results concurred generally with the assessment of the changes. NigeriaSat-1 imagery was tested for its quality and whether the addition of the middle infrared wavebands improved the classification. NigeriaSat-1 failed to classify the 13 classes and the middle infrared did not improve the classification, thus comparable to Landsat data, although the test was done with dry season images and the result may likely be different for wet season imagery. The 8 km AHVRR-NDVI was found to be useful in assessing the timing of image acquisition, but the data could not provide sufficient spatial resolution to warrant its usage for local scale studies.
40
Tylka, Megan L. "Interactions between Lake Water Quality and Urban Land Cover". Fogler Library, University of Maine, 2009. http://www.library.umaine.edu/theses/pdf/TylkaML2009.pdf.
Testo completo
41
Jobe, Addison Scott. "CONSERVATION RESERVE PROGRAM EFFECTS ON FLOODPLAIN LAND COVER MANAGEMENT". OpenSIUC, 2018. https://opensiuc.lib.siu.edu/theses/2433.
Testo completoAbstract (sommario):
Growing populations and industrialized agriculture practices have eradicated much of the United States wetlands along river floodplains. One program available for the restoration of floodplains is the Conservation Reserve Program (CRP). The current research explores the effects CRP land change has on flooding zones, utilizing Flood Modeller and HEC-RAS. Modelling in both one-dimensional and two-dimensional approaches were tested and analyzed for the same river reach. Flood Modeller is proven a viable tool for flood modeling within the United States when compared to HEC-RAS. Application of the software is used in the Nodaway River system located in the western halves of Iowa and Missouri, to model the effects of introducing new forest areas within the region. Flood stage during the conversion first decreases in the early years, before rising to produce greater heights. Flow velocities where CRP land is present are reduced for long-term scopes. Velocity reduction occurs as the Manning’s roughness values increase due to tree diameter and brush density. Flood zones become more widespread with the implementation of CRP. Comparing one-dimensional and two-dimensional flood mapping zones, the two-dimensional model shows less inundation. CRP land cover effects evolve over time, with the greatest impact appearing at the end of the contract.
42
Manjunatha, Bharadwaj Sandhya. "Land Cover Quantification using Autoencoder based Unsupervised Deep Learning". Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99861.
Testo completoAbstract (sommario):
This work aims to develop a deep learning model for land cover quantification through hyperspectral unmixing using an unsupervised autoencoder. Land cover identification and classification is instrumental in urban planning, environmental monitoring and land management. With the technological advancements in remote sensing, hyperspectral imagery which captures high resolution images of the earth's surface across hundreds of wavelength bands, is becoming increasingly popular. The high spectral information in these images can be analyzed to identify the various target materials present in the image scene based on their unique reflectance patterns. An autoencoder is a deep learning model that can perform spectral unmixing by decomposing the complex image spectra into its constituent materials and estimating their abundance compositions. The advantage of using this technique for land cover quantification is that it is completely unsupervised and eliminates the need for labelled data which generally requires years of field survey and formulation of detailed maps. We evaluate the performance of the autoencoder on various synthetic and real hyperspectral images consisting of different land covers using similarity metrics and abundance maps. The scalability of the technique with respect to landscapes is assessed by evaluating its performance on hyperspectral images spanning across 100m x 100m, 200m x 200m, 1000m x 1000m, 4000m x 4000m and 5000m x 5000m regions. Finally, we analyze the performance of this technique by comparing it to several supervised learning methods like Support Vector Machine (SVM), Random Forest (RF) and multilayer perceptron using F1-score, Precision and Recall metrics and other unsupervised techniques like K-Means, N-Findr, and VCA using cosine similarity, mean square error and estimated abundances. The land cover classification obtained using this technique is compared to the existing United States National Land Cover Database (NLCD) classification standard.Master of Science
This work aims to develop an automated deep learning model for identifying and estimating the composition of the different land covers in a region using hyperspectral remote sensing imagery. With the technological advancements in remote sensing, hyperspectral imagery which captures high resolution images of the earth's surface across hundreds of wavelength bands, is becoming increasingly popular. As every surface has a unique reflectance pattern, the high spectral information contained in these images can be analyzed to identify the various target materials present in the image scene. An autoencoder is a deep learning model that can perform spectral unmixing by decomposing the complex image spectra into its constituent materials and estimate their percent compositions. The advantage of this method in land cover quantification is that it is an unsupervised technique which does not require labelled data which generally requires years of field survey and formulation of detailed maps. The performance of this technique is evaluated on various synthetic and real hyperspectral datasets consisting of different land covers. We assess the scalability of the model by evaluating its performance on images of different sizes spanning over a few hundred square meters to thousands of square meters. Finally, we compare the performance of the autoencoder based approach with other supervised and unsupervised deep learning techniques and with the current land cover classification standard.
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Stewart, Rebecca M. "Land Cover Influences on Stream Nitrogen Dynamics During Storms". Thesis, Virginia Tech, 2012. http://hdl.handle.net/10919/76799.
Testo completoAbstract (sommario):
Previous studies on the effects of land cover influence on stream nitrogen have focused on base flow conditions or were conducted specifically within urbanized or primarily agricultural watersheds. While these studies have shown relationships between land cover and nitrogen, this relationship and the scale of influence could change during storms. The purpose of my study was to understand how land cover influences nitrogen in streams during storms. This was address using nine watersheds within the Little Tennessee Basin in North Carolina. While this basin is primarily forested, the nine watersheds have mixed agricultural, built, and forest land cover. Land cover influences were addressed through nitrogen concentration/discharge patterns, nitrogen concentration relationship to land cover, and comparison of storm and base flow nitrogen concentrations over time. Weekly base flow samples and samples from six storm were collected in 2010-2011. Total dissolved nitrogen (TDN), nitrate (NO??), dissolved organic nitrogen (DON), and ammonium (NH?⁺) concentrations were compared among sites. During most storms, DON peaked before the peak of the discharge while NO?? peaked after the peak of the storm. This suggest that DON could be coming from a near stream source or surface runoff while NO?? could be from longer pathways such as subsurface flow or from sources further away on the watershed. NO?? concentration varied among sites, while DON concentration varied more between base flow and storm samples. Examining the different landscape scales from 200-m local corridor, 200-m stream corridor, and entire watershed, watershed land cover was the best predictor for all the nitrogen concentrations. Agricultural and built combined best predicted TDN and NO??, while agricultural land cover was a better predictor of DON. For storms, nitrogen concentrations did not show seasonal patterns but was more related to discharge. Nitrogen concentration increased with discharge during storms and the more intense and longer storms had higher TDN and NO?? concentrations. However, conflicting seasonal trends were seen in monthly base flow. The more forested watersheds had high NO?? during the summer and low NO?? in the winter. For sites with higher NO??, the seasonality was reversed, with higher winter NO?? concentration. The least forested site had relatively constant nitrogen through the year at base flow and concentration decreased for most storms. Further studies on storms and nitrogen transport are needed to understand better the seasonal patterns of nitrogen input during storms.Master of Science
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Morton, David Dean. "Land Cover of Virginia From Landsat Thematic Mapper Imagery". Thesis, Virginia Tech, 1998. http://hdl.handle.net/10919/36851.
Testo completoAbstract (sommario):
Knowledge of land cover is important in a variety of natural resources applications. This knowledge becomes more powerful within the spatial analysis capabilities of a geographic information system (GIS). This thesis presents a digital land cover map of Virginia, produced through interpretation of 14 Landsat Thematic Mapper (TM) scenes, circa 1991-1993.
The land cover map, which has a 30m pixel size, was produced entirely with personal computers. Hypercluster aggregation, an unsupervised classification method, was used when hazy and mountainous conditions were not present. A haze correction procedure by Lavreau (1991) was used, followed by a supervised classification on coastal areas. An enhanced supervised classification, focusing on topographic shading, was performed in the mountains. Color infrared photographs, digital maplets, expert knowledge, and other maps were used as training data. Aerial videography transects were flown to acquire reference data.
Due to the spatial inaccuracies inherent in the videography reference data, only homogeneous land cover areas were used in the accuracy assessment. The results of the overall accuracy for each scene determined the ordering of scenes within the statewide land cover mosaic (i.e., scenes with higher accuracy had a higher proportion of area represented). An accuracy assessment was then performed on the statewide land cover mosaic. An overall accuracy of 81.8% and a Kappa statistic of 0.81 resulted. A discussion of potential reasons for land cover class confusion and suggestions for classification improvements are presented.
Overall deciduous forest was the most common land cover in Virginia. Herbaceous areas accounted for 20% of the land area, which was the second largest. Mixed forest and coastal wetlands were the cover types with the least area, each under 3%.Master of Science
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Yang, Fen. "Change detection of land cover using visual texture measures". Thesis, University of Aberdeen, 2007. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU225730.
Testo completoAbstract (sommario):
It is important to detect land cover changes from remotely sensed data for monitoring environment. Although there are a few applications of visual textures to land cover classification, they are limited to a few major land cover categories with the application of one textural measure. For a semi-natural environment, such as Scottish land cover, there are many land cover categories, which differ from each other by subtle differences. For this situation it is not enough to apply one textural measure to characterise land cover categories. Moreover because land cover change cannot happen between any two land cover categories, it is possible to detect land cover change by discriminating between pairs of land cover categories which could change from one to the other. This thesis, therefore, attempts to present descriptions of various texture measures for land cover categories and apply them to detect land cover changes by pairwise discrimination. Three different bandpass filter banks: Haar masks, Laws masks and Gabor filters are applied to extract land cover textures. In order to learn the difference between the three filter banks, we analyse the properties and the spatial frequency for each filter bank. Their abilities to discriminate different land cover categories are evaluated by discriminant analysis. Because the three filter banks divide the spatial frequency domain differently, their abilities are different. In order to learn which filter bank is the best for the discrimination of a specified pair of land cover categories, we compare the performance of the three filter banks and obtain a ranking table which could be used as a textural knowledge for a system for monitoring land cover. Experiments on the Elgin area of Scotland show that texture measures are promising for discriminating land cover categories. And for each permissible land cover change, the best filter bank is shown.
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Broxton, Patrick. "Improving Distributed Hydrologic Modeling and Global Land Cover Data". Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/307009.
Testo completoAbstract (sommario):
Distributed models of the land surface are essential for global climate models because of the importance of land-atmosphere exchanges of water, energy, momentum. They are also used for high resolution hydrologic simulation because of the need to capture non-linear responses to spatially variable inputs. Continued improvements to these models, and the data which they use, is especially important given ongoing changes in climate and land cover. In hydrologic models, important aspects are sometimes neglected due to the need to simplify the models for operational simulation. For example, operational flash flood models do not consider the role of snow and are often lumped (i.e. do not discretize a watershed into multiple units, and so do not fully consider the effect of intense, localized rainstorms). To address this deficiency, an overland flow model is coupled with a subsurface flow model to create a distributed flash flood forecasting system that can simulate flash floods that involve rain on snow. The model is intended for operational use, and there are extensive algorithms to incorporate high-resolution hydrometeorologic data, to assist in the calibration of the models, and to run the model in real time. A second study, which is designed to improve snow simulation in forested environments, demonstrates the importance of explicitly representing a near canopy environment in snow models, instead of only representing open and canopy covered areas (i.e. with % canopy fraction), as is often done. Our modeling, which uses canopy structure information from Aerial Laser Survey Mapping at 1 meter resolution, suggests that areas near trees have more net snow water input than surrounding areas because of the lack of snow interception, shading by the trees, and the effects of wind. In addition, the greatest discrepancy between our model simulations that explicitly represent forest structure and those that do not occur in areas with more canopy edges. In addition, two value-added Land Cover products (land cover type and maximum green vegetation fraction; MGVF) are developed and evaluated. The new products are good successors to current generation land cover products that are used in global models (many of which rely on 20 year old AVHRR land cover data from a single year) because they are based on 10 years of recent MODIS data. There is substantial spurious interannual variability in the MODIS land cover type data, and the MGVF product can vary substantially from year to year depending on climate conditions, suggesting the importance of using climatologies for land cover data. The new land cover type climatology also agrees better with validation sites, and the MGVF climatology is more consistent with other measures of vegetation (e.g. Leaf Area Index) than the older land cover data.
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Bengana, M. (Mohamed). "Land cover and forest segmentation using deep neural networks". Master's thesis, University of Oulu, 2019. http://jultika.oulu.fi/Record/nbnfioulu-201905101715.
Testo completoAbstract (sommario):
Tiivistelmä. Land Use and Land Cover (LULC) information is important for a variety of applications notably ones related to forestry. The segmentation of remotely sensed images has attracted various research subjects. However this is no easy task, with various challenges to face including the complexity of satellite images, the difficulty to get hold of them, and lack of ready datasets. It has become clear that trying to classify on multiple classes requires more elaborate methods such as Deep Learning (DL). Deep Neural Networks (DNNs) have a promising potential to be a good candidate for the task. However DNNs require a huge amount of data to train including the Ground Truth (GT) data. In this thesis a DL pixel-based approach backed by the state of the art semantic segmentation methods is followed to tackle the problem of LULC mapping. The DNN used is based on DeepLabv3 network with an encoder-decoder architecture. To tackle the issue of lack of data the Sentinel-2 satellite whose data is provided for free by Copernicus was used with the GT mapping from Corine Land Cover (CLC) provided by Copernicus and modified by Tyke to a higher resolution. From the multispectral images in Sentinel-2 Red Green Blue (RGB), and Near Infra Red (NIR) channels were extracted, the 4th channel being extremely useful in the detection of vegetation. This ended up achieving quite good accuracy on a DNN based on ResNet-50 which was calculated using the Mean Intersection over Union (MIoU) metric reaching 0.53MIoU. It was possible to use this data to transfer the learning to a data from Pleiades-1 satellite with much better resolution, Very High Resolution (VHR) in fact. The results were excellent especially when compared on training right away on that data reaching an accuracy of 0.98 and 0.85MIoU.
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Donnelly, Shanon P. "Linking land use, land cover, and land ownership at the parcel scale in the midwest United States". [Bloomington, Ind.] : Indiana University, 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3380075.
Testo completoAbstract (sommario):
Thesis (Ph.D.)--Indiana University, Dept. of Geography, 2009.Title from PDF t.p. (viewed on Jul 12, 2010). Source: Dissertation Abstracts International, Volume: 70-12, Section: A, page: 4807. Adviser: Tom P. Evans.
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Alavi, Shoushtari Niloofar. "Land Use and Land Cover Change Detection in Isfahan, Iran Using Remote Sensing Techniques". Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/22848.
Testo completoAbstract (sommario):
Rapid urban growth and unprecedented rural to urban transition, along with a huge population growth are new phenomena for both high and low income countries, which started in the mid-20th century. However, urban growth rates and patterns are different in developed countries and developing ones. In less developed countries, urbanization and rural to urban transition usually takes place in an unmanaged way and they are associated with a series of socioeconomical and environmental issues and problems. Identification of the city growth trends in past decades can help urban planners and managers to minimize these negative impacts. In this research, urban growth in the city of Isfahan, Iran, is the subject of study. Isfahan the third largest city in Iran has experienced a huge urban growth and population boom during the last three decades. This transition led to the destruction of natural and agricultural lands and environmental pollutions.
Historical and recent remotely sensed data, along with different remote sensing techniques and methods have been used by researchers for urban land use and land cover change detection. In this study three Landsat TM and ETM+ images of the study site, acquired in 1985, 2000 and 2009 are used. Before starting processing, radiometric normalization is done to minimize the atmospheric effects. Then, processing methods including principal component analysis (PCA), vegetation indices and supervised classification are implemented on the images. Accuracy assessment of the PCA method showed that the first PC was responsible for more than 81% of the total variance, and therefore used for analysis of PCA differencing. ΔPC1t1-t2 shows the amount of changes in land use and land cover during the period of study. In this study ten vegetation indices were selected to be applied to the 1985 image. Accuracy assessments showed that Transformed Differencing Vegetation Index (TDVI) is the most sensitive and accurate index for mapping vegetation in arid and semi-arid urban areas. Hence, TDVI was applied to the 2000 and 2009 images. ΔTDVIt1-t2 showed the changes in land use and land cover especially the land use transformation from vegetation cover into the urban class. Supervised classification is the last method applied to the images. Training sites were assigned for the selected classes and accuracy was monitored during the process of training site selection. The results of classification show the expansion of urban class and diminishment in natural and agricultural lands.
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Carneiro, Tiago Garcia de Senna. "Nested-ca: a foundation for multiscale modelling of land use and land cover change". Instituto Nacional de Pesquisas Espaciais, 2006. http://urlib.net/sid.inpe.br/mtc-m17@80/2007/01.03.11.57.
Testo completoAbstract (sommario):
Este trabalho apresenta a base matemática do modelo chamado Autômatos Celulares Aninhados (Nested-CA), um modelo de computação destinado ao desenvolvimento de modelos de mudança de uso e cobertura do solo em múltiplas escalas. As principais propriedades do modelo nested-CA são descritas e comparadas aos modelos de computação baseados em agentes e em autômatos celulares. O modelo nested-CA foi implementado em uma ambiente computacional, chamado TerraME, que oferece uma linguagem de alto nível para a descrição de modelos, um conjunto de estruturas de dados espaço-temporais para a representação e simulação dos modelos, um modulo para o gerenciamento e análise de dados espaço-temporais integrado a um sistema de informações geográficas, e um conjunto de funções para calibração e validação dos modelos. As decisões de projetos envolvidas no desenvolvimento do ambiente de modelagem TerraME são descritas. A arquitetura do ambiente é detalhada e suas principais propriedades são comparadas com outras plataformas de modelagem: Swarm, STELLA, e GEONAMICA. Finalmente, o conceito de nested-CA e o ambiente TerraME são demonstrados em duas aplicações de mudança de cobertura do solo para a Amazônia brasileira.This work presents the mathematical foundations of the Nested Cellular Automata (nested-CA) model, a model of computation for multiple scale Land Use and Land Cover Change studies. The main properties of nested-CA model are described and compared to the agent-based and cellular automata models of computation. The nested- CA model has been implemented in a software environment, called TerraME (Terra Modeling Environment), which provides a high-level modeling language for model description, a set of spatiotemporal data structures for model representation and simulation, a module for spatiotemporal data management and analysis integrated to a geographic information system, and a set of functions for model calibration and validation. We describe the main design choices involved in the development of the TerraME modeling environment. Its architecture is detailed and the main properties are compared with other modeling tools: Swarm, STELLA, and GEONAMICA. Finally, the concept of nested-CA and the TerraME architecture are demonstrated in two applications of land cover change in the Brazilian Amazon.