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Relevant bibliographies by topics / Remote sensing, geographic information system

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Academic literature on the topic 'Remote sensing, geographic information system'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Remote sensing, geographic information system"

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Ajar, Seno Budhi, Inna Prihartini, and Gentur Adi Tjahjono. "THE OBSTACLES FACTORS OF GEOGRAPHY INFORMATION SYSTEMS AND REMOTE SENSING PRACTICUM IN A HIGH SCHOOL LEVEL IN WONOGIRI DISTRICT." GeoEco 5, no. 2 (2019): 151. http://dx.doi.org/10.20961/ge.v5i2.30198.

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Practicum Geographical information systems and remote sensing have become one of the basic competencies in the realm of skills in the geography learning process at the high school level The purpose of this study is to identify problems or obstacles faced by geography teachers in carrying out geographic information systems and remote sensing practicum activities in high schools in Wonogiri Regency this is a qualitative descriptive study with the use of random sampling. Data collection uses a questionnaire about the implementation of geographic information system practice and remote sensing to the teacher. This study uses descriptive statistical analysis techniques to analyze the factors that become obstacles in the application of geographic information system practice and remote sensing in high school. The result is the obstacles factor of geographic information system and remote sensing practicum in in high schools in Wonogiri is (1). Hardware devices that have not been installed software specifically for geography information systems and remote sensing The teacher has a low ability in the geography and remote sensing information system practicum skills and does not coordinate with the teacher or laboratory assistant for Information and Communication Technology (ICT) subjects (3) Insufficient time allocation for practicum and absence of geographic information system and remote sensing practice tests as evaluations

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Allaw, Kamel, Jocelyne Adjizian Gerard, Makram Zouheir Chehayeb, and Nada Badaro Saliba. "Population estimation using geographic information system and remote sensing for unorganized areas." Geoplanning: Journal of Geomatics and Planning 7, no. 2 (2021): 75–86. http://dx.doi.org/10.14710/geoplanning.7.2.75-86.

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Population estimation using remotely sensed data has been largely discussed in the literature relative to human geography. However, the previously established models can be applied on organized areas (mainly urban areas) but they are not suitable for unorganized areas which already suffer from a lack of population data. So, the aim of this study is the establish a statistical model for population estimation based on remote sensing data and suitable for unorganized areas. To do so, the morphological characteristics have been studied and a bivariate analysis was carried out to determine factors having a strong relationship with population data as a first step. Second, factors with strongest correlations have been chosen to establish the required model. As a result, an equation has been generated which relates the population data to building volume, density of roads, number of nodes, actual urban areas, and urban trend.

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BAUMGARTNER, MICHAEL F., and GABRIELA M. APFL. "Remote sensing and geographic information systems." Hydrological Sciences Journal 41, no. 4 (1996): 593–607. http://dx.doi.org/10.1080/02626669609491527.

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Bonnefon, R., P. Dhérété, and J. Desachy. "Geographic information system updating using remote sensing images." Pattern Recognition Letters 23, no. 9 (2002): 1073–83. http://dx.doi.org/10.1016/s0167-8655(02)00054-5.

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Lytvynenko, N. "THE APPLYING OF GIS INFORMATION TECHNOLOGIES IN THE SPHERE OF THE REMOTE SENSING OF THE EARTH TO SOLVE MILITARY PROBLEMS." Visnyk Taras Shevchenko National University of Kyiv. Military-Special Sciences, no. 2 (39) (2018): 18–22. http://dx.doi.org/10.17721/1728-2217.2018.39.18-22.

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The rapid development of geographic information systems and means of remote sensing, observed in recent decades, requires the mutual integration of these areas. This article focuses on the integration of geographic information systems and technologies in the field of remote sensing to solve military problems. Keywords: remote sensing, geographic information system.

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A, JOTHIBASU, and ANBAZHAGAN S. "Drought Hazard Assessment in Ponnaiyar River Basin, India Using Remote Sensing and Geographic Information System." INTERNATIONAL JOURNAL OF EARTH SCIENCES AND ENGINEERING 10, no. 02 (2017): 247–56. http://dx.doi.org/10.21276/ijee.2017.10.0216.

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Deshmukh, Priyanka, Pawade P. Y, and Rajashree Bothale. "Remote Sensing and Geographic Information System Based Route Planning." Civil Engineering and Urban Planning: An International Journal (CiVEJ) 5, no. 1 (2018): 01–17. http://dx.doi.org/10.5121/civej.2018.5101.

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Kumar, Devendra, Arvind Dhaloiya, Ajeet Singh Nain, Mahendra Paal Sharma, and Amandeep Singh. "Prioritization of Watershed Using Remote Sensing and Geographic Information System." Sustainability 13, no. 16 (2021): 9456. http://dx.doi.org/10.3390/su13169456.

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Soil erosion is becoming a major concern at the watershed scale for the environment, natural resources, and sustainable resource management. Therefore, the estimation of soil loss through this phenomenon and the identification of critical soil erosion-prone areas are considered to be key tasks in the soil conservation programme for the design and implementation of best management practices for specific regions or areas. In the present study, revised universal soil loss equation (RUSLE) modelling is combined with remote sensing (RS) and geographical information system (GIS) techniques and used to predict soil erosion and the prioritization of watersheds in Nainital district Uttarakhand, India. For the estimation of soil loss, different factors, namely, rainfall-runoff erosivity (R) factor, soil erodability (K) factor, slope length steepness (LS) factor, cover management (C) factor, and the erosion control practices (P) factor were computed. The data on various other aspects such as land use/land cover (LU/LC), the digital elevation model (DEM), slope, contours, drainage network, soil texture, organic matter, and rainfall were integrated to prepare a database for the RUSLE equation by employing ENVI & QGIS software. The results showed that a major portion (70.26%) of Nainital district is covered with forest, followed by area under fallow and agricultural land. Annual average soil loss ranged between 20 to 80 t ha−1 yr−1 in the study area. Out of 50 watersheds in the study area, 7 watersheds were given top priority for conserving natural resources, while 11 watersheds, mostly in the east-central part of Nainital, were kept under the next priority category. Only 4 watersheds of the total were given lowest priority. Moreover, it was concluded that major portions of Nainital district were in a severely prone category of soil erosion, and therefore required immediate action plans to check soil erosion and evade the possibility of landslides.

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Chapman, D. P. "Geoinformation: Remote Sensing, Photogrammetry and Geographic Information Systems." Photogrammetric Record 18, no. 104 (2003): 330–31. http://dx.doi.org/10.1046/j.0031-868x.2003.024_02.x.

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Ablameyko, S., and B. Beregov. "Remote sensing image processing in geographic information systems." Computing & Control Engineering Journal 7, no. 5 (1996): 235–39. http://dx.doi.org/10.1049/cce:19960508.

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Dissertations / Theses on the topic "Remote sensing, geographic information system"

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Villeneuve, Julie. "Delineating wetlands using geographic information system and remote sensing technologies." Texas A&M University, 2005. http://hdl.handle.net/1969.1/3135.

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During the last century wetlands have considerably decreased. The principal cause is urbanization, especially in large urban regions such as the Houston area. In order to protect the remaining wetlands, they have to be monitored carefully. However monitoring wetland is a difficult and time-demanding task because it has to be done repetitively on large areas to be effective. This study was conducted to determine if Geographical Information System (GIS) and remote sensing technologies would allow accurate monitoring of wetland as a less time-consuming method. With this idea, a suitability model was developed to delineate wetlands in the Houston area. This model combined GIS and remote sensing technologies. The data used for this study were as high spatial resolution as possible and were generally easy to obtain. This suitability model consisted of four submodels: hydrology, soil, vegetation and multi- attribute. Each submodel generated a Wetland Suitability Index (WSI). Those WSI were summed to obtain a general WSI. The suitability model was calibrated using half of the study area. During calibration, the general model was evaluated as well as each individual index. Generally, the model showed a lack of sensitivity to changes. However, the model was slightly modified to improve the delineation of upland wet- lands by increasing the weight of the soil submodel. This model was validated using the second half of the study area. The validation results improved a bit compared to the calibration results; however they remained weak. It was demonstrated that the model does not favor riverine wetlands over upland wetlands, nor large size wetlands. The model ground truth data were evaluated and were suffciently proven to be up to date. Those results indicated that the weakness of the model must come from inac- curacy in the input data. Therefore, the study showed that while existing computing capacity supports remote delineation, spatial accuracy is still insuffcient to perform correct wetland delineation using remote sensing and GIS technologies.

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Kim, Kee-Tae. "Satellite mapping and automated feature extraction geographic information system-based change detection of the Antarctic coast /." Connect to this title online, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1072898409.

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Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xiv, 157 p.; also includes graphics. Includes bibliographical references (p. 143-148).

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Caccetta, Peter A. "Remote sensing, geographic information systems (GIS) and Bayesian knowledge-based methods for monitoring land condition." Curtin University of Technology, School of Computing, 1997. http://espace.library.curtin.edu.au:80/R/?func=dbin-jump-full&object_id=11018.

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This thesis considers various aspects of the use of remote sensing, geographical information systems and Bayesian knowledge-based expert system technologies for broad-scale monitoring of land condition in the Western Australian wheat belt.The use of remote sensing technologies for land condition monitoring in Western Australia had previously been established by other researchers, although significant limitations in the accuracy of the results remain. From a monitoring perspective, this thesis considers approaches for improving the accuracy of land condition monitoring by incorporating other data into the interpretation process.Digital elevation data provide one potentially useful source of information. The use of digital elevation data are extensively considered here. In particular, various methods for deriving variables relating to landform from digital elevation data and remotely sensed data are reviewed and new techniques derived.Given that data from a number of sources may need to be combined in order to produce accurate interpretations of land use/condition, methods for combining data are reviewed. Of the many different approaches available, a Bayesian approach is adopted.The approach adopted is based on relatively new developments in probabilistic expert systems. This thesis demonstrates how these new developments provide a unified framework for uniting traditional classification methods and methods for integrating information from other spatial data sets, including data derived from digital elevation models, remotely sensed imagery and human experts.Two applications of the techniques are primarily considered. Firstly, the techniques are applied to the task of salinity mapping/ monitoring and compared to existing techniques. Large improvements are apparent. Secondly, the techniques are applied to salinity prediction, an application not previously considered by ++<br>other researchers in this domain. The results are encouraging. Finally limitations of the approach are discussed.

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Cobbing, Benedict Louis. "The use of Landsat ETM imagery as a suitable data capture source for alien acacia species for the WFW programme." Thesis, Rhodes University, 2007. http://hdl.handle.net/10962/d1005532.

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Geographic Information System technology today allows for the rapid analysis of vast amounts of spatial and non-spatial data. The power of a GIS can only be effected with the rapid collection of accurate input data. This is particularly true in the case of the South African National Working for Water (WFW) Programme where large volumes of spatial data on alien vegetation infestations are captured throughout the country. Alien vegetation clearing contracts cannot be generated, for WFW, without this data, so that the accurate capture of such data is crucial to the success of the programme. Mapping Invasive Alien Plant (IAP) data within WFW is a perennial problem (Coetzee, pers com, 2002), because not enough mapping is being done to meet the annual requirements of the programme in the various provinces. This is re-iterated by Richardson, 2004, who states that there is a shortage of accurate data on IAP abundance in South Africa. Therefore there is a need to investigate alternate methods of data capture; such as remote sensing, whilst working within the existing WFW data capture standards. The aim of this research was to investigate the use of Landsat ETM imagery as a data capture source for mapping alien vegetation for the WFW Programme in terms of their approved mapping methods, for both automated and manual classification techniques. The automated and manual classification results were compared to control data captured by differential Global Positioning Systems (DGPS). The research tested the various methods of data capture using Landsat ETM images over a range of study sites of varying complexity: a simple grassland area, a medium complexity grassy fynbos site and a complicated indigenous forest site. An important component of the research was to develop a mapping (classification) Ranking System based upon variables identified by WFW as fundamental in data capture decision making: spatial and positional accuracy, time constraints and cost constraints for three typical alien invaded areas. The mapping Ranking System compared the results of the various mapping methods for each factor for the study sites against each other. This provided an indication of which mapping method is the most efficient or suitable for a particular area.

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Sill, Paul E. (Paul Eric). "Assessing Regional Gully Erosion Risk: A Remote Sensing and Geographic Information Systems Approach." Thesis, University of North Texas, 1995. https://digital.library.unt.edu/ark:/67531/metadc332453/.

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Gully erosion has been established as a major source of sediment pollution in the upper Trinity River watershed in north-central Texas. This fact, along with a lack of models appropriate for a large-area gully erosion analysis established a need for a gully erosion study in the upper Trinity basin. This thesis project attempted to address this need by deriving an index indicative of gully erosion risk using remote sensing and geographic information systems (GIS) methodology. In context of previous field studies, the coarse spatial resolution of the input GIS data layers presented a challenge to prediction of gully prone areas. However, the remote sensing/GIS approach was found to provide useful reconnaissance information on gully risk over large areas.

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Adjei-Darko, Priscilla. "Remote Sensing and Geographic Information Systems for Flood Risk Mapping and Near Real-time Flooding Extent Assessment in the Greater Accra Metropolitan Area." Thesis, KTH, Geoinformatik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-205191.

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Disasters, whether natural or man-made have become an issue of mounting concern all over the world. Natural disasters such as floods, earthquakes, landslides, cyclones, tsunamis and volcanic eruptions are yearly phenomena that have devastating effect on infrastructure and property and in most cases, results in the loss of human life. Floods are amongst the most prevalent natural disasters. The frequency with which floods occur, their magnitude, extent and the cost of damage are escalating all around the globe. Accra, the capital city of Ghana experiences the occurrence of flooding events annually with dire consequences. Past studies demonstrated that remote sensing and geographic information system (GIS) are very useful and effective tools in flood risk assessment and management. This thesis research seeks to demarcate flood risk areas and create a flood risk map for the Greater Accra Metropolitan Area using remote sensing and Geographic information system. Multi Criteria Analysis (MCA) is used to carry out the flood risk assessment and Sentinel-1A SAR images are used to map flood extend and to ascertain whether the resulting map from the MCA process is a close representation of the flood prone areas in the study area. The results show that the multi-criteria analysis approach could effectively combine several criteria including elevation, slope, rainfall, drainage, land cover and soil geology to produce a flood risk map. The resulting map indicates that over 50 percent of the study area is likely to experience a high level of flood. For SAR-based flood extent mapping, the results show that SAR data acquired immediately after the flooding event could better map flooding extent than the SAR data acquired 9 days after. This highlights the importance of near real-time acquisition of SAR data for mapping flooding extent and damages. All parts under the study area experience some level of flooding. The urban land cover experiences very high, and high levels of flooding and the MCA process produces a risk map that is a close depiction of flooding in the study area. Real time flood disaster monitoring, early warning and rapid damage appraisal have greatly improved due to ameliorations in the remote sensing technology and the Geographic Information Systems.

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Matoti, Andiswa. "Assessing the groundwater resources within the Table Mountain Group using remote sensing and geographic information system." Thesis, Stellenbosch : Stellenbosch University, 2003. http://hdl.handle.net/10019.1/53298.

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Thesis (MSc)--Stellenbosch University, 2003.<br>ENGLISH ABSTRACT: The Cape Town metropolitan area has limited water supply due to rapid population and urban growth. In many instances, surface water is the only source in water supply schemes. There is a need for additional water supplies to supplement the existing water sources. Groundwater systems can be used as primary or supplemental water supply sources especially in areas where there is high demand for water resources. The aim of this study is to evaluate the groundwater potential within the Table Mountain Group (TMG) with the assistance of remote sensing and Geographical Information System (GIS). Previous hydrogeological studies have found the TMG to be the second largest hydrogeological unit in South Africa with extensively fractured and multi-porous rock. The study area is 5660 km2 with TMG covering 1336 km". In this study a Landsat Enhanced Thematic Mapper Plus (ETM+) image was used to identify lineaments. The identified lineaments were overlaid with vegetation, drainage patterns, faults and fractures digitized from 1:250 000 geological maps and borehole yields to show areas with promising groundwater resources. The results did not show correlation between vegetation and lineaments. Most of the lineaments intersected drainage lines at some points, and a few were parallel to the drainage lines. Forty five percent of the digitized faults and fractures overlap with the Landsat lineament. The most dominating lineaments are oriented in a NW-SE direction. High yielding boreholes with average yield of about 12 lIs were found within the distance of 150m from the lineaments. The lineaments were further analysed to locate areas that could be suitable for groundwater exploration. These areas were identified using Landsat lineaments, boreholes and a Digital Elevation Model (DEM). The results showed that the most favourable lineaments and geological features were oriented in a 135-180° and 0-45° direction and areas with slopes of less than 40% were found to be suitable for drilling boreholes. The amount of available groundwater within the TMG was also investigated by looking at both volume of recharge and amount that could be held in storage. Rainfall data was used to estimate recharge. Groundwater recharge was calculated to be 5% of the total precipitation that falls on this area. Based on the average rainfall of 600mm per annum, the results show that TMG has an average recharge value of 30mm per annum. The total recharge for the area covered by TMG, which has an area of 1336km2 , is 160 million nr'. Geological profiles and cross sections were drawn to determine the storage capacity of the TMG, which was estimated to be 525 million m.3 According to a study done by the Department of Water Affairs and Forestry (DW AF) in 1996, the anticipated water demand in the Cape Town metropolitan area will increase from 243 million m3 in 1990 to 560 million m3 in 2020. The estimated volume of water that can be stored within the TMG can meet the current demand for the next 10 years and supplement the existing surface water sources. Groundwater vulnerability of the TMG to contamination was assessed and mapped by using the DRASTIC index. The results demonstrate that the TMG area is at low risk to contamination.<br>AFRIKAANSE OPSOMMING: 'n Vinnig groeiende bevolking en stedelike uitbreiding plaas toenemende druk op Kaapstad se water voorraad. Addisionele waterbronne sal benodig word om bestaande bronne aan te vul. Oppervlakwater is in die meeste gevalle die enigste waterbron, maar grondwater het die potensiaal om te dien as 'n primêre of aanvullende voorsieningsbron, veral in areas waar groot water tekorte bestaan. Die doel van hierdie studie is om die grondwaterpotensiaal van gesteentes van die Tafelberg Groep (TBG) te evalueer deur van afstandswaarneming en geografiese inligtingstelsels gebruik te maak. Geohidrologiese studies het getoon dat die TBG gesteentes met sy veelvuldige nate en breuksones, die tweede grootste geohidrologiese eenheid in Suid Afrika is. Die studiegebied beslaan 5660 km", waarvan 1336 km2 deur Tafelberg Sandsteen beslaan word. Vir hierdie studie is 'n "Landsat Enhanced Thematic Mapper Plus (ETM+)" beeld gebruik in die identifisering van breuksones (lineamente). Verdere analises is uitgevoer om areas geskik vir grondwater ontginning te identifiseer. Geïdentifiseerde verskuiwings op Landsat beelde is met plantegroei, dreinerings patrone en bekende verskuiwings en fraktuur sones vanaf gelogiese kaarte vergelyk in 'n poging om areas met belowende grondwaterbronne uit te wys. Bekende boorgat posisies en lewerings volumes was 'n primêre databron vir die berekening van groundwater reserves. Die studie het egter geen korrelasie tussen plantegroei en die voorkoms van lineamente gevind nie. Die riviere in die studiegebied word op verskeie plekke deur verskuiwings gekruis. Slegs 'n paar van die verskuiwings lê parallel met die dreinering. Daar is gevind dat vyf-en-veertig persent van bekende verskuiwings en fraktuursones met die geïdentifiseerd op Landsat beelde oorvleuel. Die mees prominente lineamente het 'n NW-SO oriëntasie. Boorgate met lewerings van gemiddeld 12 lis is binne 'n 150m afstand van die verskuiwings gevind. Die verskuiwings is ook geanaliseer om die mees produktiewe areas vir grondwater ontginning te identifiseer. Landsat beelde, boorgate en 'n Digitale Elevasie Model (DEM) is gebruik om moontlike boorposisies te identifiseer. Die mees produktiewe verskuiwings en geologiese verskynsels het 'n N 135-180W en NO-450 oriëntasie, terwyl areas met 'n helling < 40% vir die boor van boorgate geskik is. Berekeninge oor die hoeveelheid water wat binne die TBG gesteentes beskikbaar is, is gemaak deur die hoeveelheid aanvulling en stoorkapasiteit van die TBG gesteentes te beraam. Grondwater aanvulling, soos bereken vanaf reënval data, is 5% van die totale presipitasie van 'n gegewe area. Met 'n gemiddelde jaarlikse reënval van 600mm in die studie gebied is die TBG se jaarlikse aanvulling ongeveer 30mm. Daar word beraam dat die totale aanvulling in die 1336km2 TBG area 160-miljoen m3 per jaar is. Geologiese profiele en dwarsnitte is gemaak om die stoorvermoë van die TBG te bepaal, en is beraam op 525-miljoen rrr'. 'n 1996 navorsing studie deur die Departement van Waterwese en Bosbou toon dat waterverbruik in die Kaapse Metropolitaanse gebied sal toeneem vanaf die 1990 vlak van 243-miljoen m3 tot 560 miljoen m3 teen 2020. Die berekende volume water wat binne die TBG gestoor word, kan die water aanvraag oor die volgende 10 jaar bevredig en as aanvulling dien vir oppervlak waterbronne. Die kwesbaarheid van die TBG akwifer vir besoedeling is met behulp van die DRASTIC indeks geëvalueer en gekarteer. Die resultate toon dat die TBG 'n lae risiko vir besoedeling het.

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Charlebois, Daniel. "A planning system based on plan re-use and its application to geographical information systems and remote sensing." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/nq20994.pdf.

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Tekeli, Ahmet Emre. "Operational Hydrological Forecasting Of Snowmelt Runoff By Remote Sensing And Geographic Information Systems Integration." Phd thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12606081/index.pdf.

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Snow indicates the potential stored water volume that is an important source of water supply, which has been the most valuable and indispensable natural resource throughout the history of the world. Euphrates and Tigris, having the biggest dams of Turkey, are the two largest trans-boundary rivers that originate in Turkey and pass throughout the water deficit nations Syria, Iran, Iraq and Saudi Arabia bringing life as well as water all their way. Snowmelt runoff originating from the mountains of Eastern Turkey accounts for 60 to 70 % of total annual discharge observed in Euphrates and Tigris. For an optimum operation of the dams, maximizing energy production, mitigation of floods and satisfying water rights, hydrological models which can both simulate and forecast the river discharges of Euphrates and Tigris are needed. In this study a hydrological model, snowmelt runoff model (SRM), is used in conjunction with remote sensing and geographic information systems to forecast the river discharges in the headwaters of Euphrates River, Upper Euphrates Basin. NOAA and MODIS satellite images were used to derive the snow covered area (SCA) information required by SRM. Linear reduction methodologies based on accumulated air temperature, with constant or varying gradient, were developed to get the continuous daily SCA values from the discrete daily satellite images. Temperature and precipitation forecasts were gathered from two different numerical weather prediction models, namely European Center for Medium Range Weather Forecasts (ECMWF) and Mesoscale Model Version 5 (MM5) from Turkish State Meteorological Services. These data sets provided t+24 hour forecasts of both temperature and precipitation. Temperature, precipitation and SCA information are fed into SRM. Discharge forecasts obtained from the model outputs are compared with the observed values. The overall performance of the model was seen as promising. Possible reasons of the mismatches between the forecasted and observed values are searched. Experiences gained throughout the study are summarized and recommendations on further forecast studies are mentioned.

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Jaber, Salahuddin M. "Monitoring spatial variations in soil organic carbon using remote sensing and geographic information systems /." Available to subscribers only, 2006. http://proquest.umi.com/pqdweb?did=1208146891&sid=1&Fmt=2&clientId=1509&RQT=309&VName=PQD.

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Books on the topic "Remote sensing, geographic information system"

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K, Ghosh S., ed. Remote sensing and geographical information system. Alpha Science, 2006.

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Singh, Sarnam, and Indian Institute of Remote Sensing, eds. Biodiversity & environment: Remote sensing & geographic information system perspectives. Indian Institute of Remote Sensing, National Remote Sensing Agency, 2000.

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Bhatta, Basudeb. Remote sensing and GIS. Oxford University Press, 2008.

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Remote sensing and GIS. 2nd ed. Oxford University Press, 2011.

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Geoinformation: Remote sensing, photogrammetry and geographic information systems. Taylor & Francis, 2003.

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Remote sensing for GIS managers. ESRI Press, 2005.

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Jonathan, Williams. Geographic information from space. E. Horwood, 1990.

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Center for Environment (Lexington, Ky.), ed. State geographic information activities compendium. Council of State Governments, 1992.

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Liang, Shunlin. Advances in Land Remote Sensing: System, Modeling, Inversion and Application. Springer Science+Business Media B.V, 2008.

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A, Brebbia C., ed. Management information systems, 2004: GIS and remote sensing. WIT Press, 2004.

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Book chapters on the topic "Remote sensing, geographic information system"

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Weir, Michael J. C. "Errors in Geographic Information Systems." In Eurocourses: Remote Sensing. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-017-2879-9_19.

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Weir, Michael J. C. "Computer Systems for Geographic Information Systems." In Eurocourses: Remote Sensing. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-017-2879-9_15.

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Valenzuela, Carlos R., Hans de Brouwer, and Allard Meijerink. "Land Use Model Using a Geographic Information System." In Eurocourses: Remote Sensing. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-017-2879-9_22.

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Valenzuela, Carlos R. "Basic Principles of Geographic Information Systems." In Eurocourses: Remote Sensing. Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-017-2879-9_14.

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Lambrechts, Johannes, and Saurabh Sinha. "Geographic Information Systems and Remote Sensing." In Microsensing Networks for Sustainable Cities. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28358-6_6.

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Chan, Yupo. "Remote Sensing and Geographic Information Systems." In Location Theory and Decision Analysis. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-15663-2_6.

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Sakai, Tetsuro. "Remote Sensing and Geographic Information Systems." In Field Informatics. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29006-0_1.

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Lindgren, David T. "Remote sensing input to geographic information systems." In Land use planning and remote sensing. Springer Netherlands, 1985. http://dx.doi.org/10.1007/978-94-017-2035-9_7.

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Deshmukh, Priyanka, DSP Rao, Rajashree Botale, and P. Y. Pwade. "Remote Sensing and Geographic Information System-Based Route Planning." In Smart Technologies for Energy, Environment and Sustainable Development. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-6148-7_31.

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Pandolfi, Alessandra Maria, and Giovanna Sona. "Metropolitan Cartography, Remote Sensing and Geographic Information Systems." In Landscape Series. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-74424-3_10.

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Conference papers on the topic "Remote sensing, geographic information system"

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Bonnefon, Regis, Pierre Dherete, and Jacky Desachy. "Automatic geographic information system upgrading using remote detection images." In Europto Remote Sensing, edited by Sebastiano B. Serpico. SPIE, 2001. http://dx.doi.org/10.1117/12.413900.

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SBARDELLA, P., and R. BARICHELLO. "USING REMOTE SENSING TO UPDATE GEOGRAPHIC INFORMATION SYSTEM." In Proceedings of the First International Workshop on Multitemp 2001. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812777249_0049.

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Tingwei Huang and Yuxiang Zhou. "Remote sensing and open source geographic information system integration." In 2012 Second International Workshop on Earth Observation and Remote Sensing Applications (EORSA). IEEE, 2012. http://dx.doi.org/10.1109/eorsa.2012.6261177.

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Oladi, Jafar, and Delavar Bozorgnia. "Evaluating the ecotourism potentials of Naharkhoran area in Gorgan using remote sensing and geographic information system." In Remote Sensing, edited by Ulrich Michel and Daniel L. Civco. SPIE, 2010. http://dx.doi.org/10.1117/12.860095.

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Maleki Najafabadi, Saedeh, Alireza Soffianian, and Vahid Rahdari. "Investigation of landscape patterns of the Mouteh Wildlife Refuge using geographic information systems." In Remote Sensing, edited by Ulrich Michel and Daniel L. Civco. SPIE, 2010. http://dx.doi.org/10.1117/12.863184.

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Fahsi, Ahmed, Teferi D. Tsegaye, Tommy L. Coleman, Andrew Manu, and Z. Senwo. "Assessment of spatial and temporal soil moisture variability using Geographic Information System techniques." In Aerospace Remote Sensing '97, edited by Giovanna Cecchi, Edwin T. Engman, and Eugenio Zilioli. SPIE, 1997. http://dx.doi.org/10.1117/12.298137.

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Zhang, Huaguo, Weigen Huang, and Dongling li. "The biodiversity management of a marine protected area with a geographic information system in China." In SPIE Remote Sensing, edited by Ulrich Michel, Daniel L. Civco, Manfred Ehlers, and Hermann J. Kaufmann. SPIE, 2008. http://dx.doi.org/10.1117/12.800033.

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Zhang, Xia, Deren Li, Xinyan Zhu, and Nengcheng Chen. "Systematic plan of building Web geographic information system based on ActiveX control." In International Symposium on Remote Sensing, edited by Manfred Ehlers. SPIE, 2003. http://dx.doi.org/10.1117/12.462322.

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Rajbhandari, Narayan B., Ahmed Fahsi, Tommy L. Coleman, et al. "Landsat Thematic Mapper and Geographic Information System for sediment delivery analysis under the two modes of runoff dispersion." In Remote Sensing, edited by Giovanna Cecchi, Edwin T. Engman, and Eugenio Zilioli. SPIE, 1999. http://dx.doi.org/10.1117/12.373114.

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Xagoraris, Zafiris, and George Soulis. "The new geographic information system in ETVA VI.PE." In Fourth International Conference on Remote Sensing and Geoinformation of the Environment, edited by Kyriacos Themistocleous, Diofantos G. Hadjimitsis, Silas Michaelides, and Giorgos Papadavid. SPIE, 2016. http://dx.doi.org/10.1117/12.2240856.

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Reports on the topic "Remote sensing, geographic information system"

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Cihlar, J., L. St-Laurent, M. D'Iorio, and D. Mullins. Remote sensing/geographic information system database for monitoring Canadian landmass. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1994. http://dx.doi.org/10.4095/193932.

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Suhartono, Suhartono, Agoes Soegianto, and Achmad Amzeri. Mapping of land potentially for maize plant in Madura Island-Indonesia using remote sensing data and geographic information systems (GIS). EM International, 2020. http://dx.doi.org/10.21107/amzeri.2020.1.

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Maize productivity in Indonesia was still low (5.241 tons/ha) compared to the average of the ten largest maize producing countries in the world (6.179 tons/ha). The potential for maize on the island of Madura is approximately 360,000 hectares. The potential for maize cultivation in Madura continues to decrease in land quality due to improper land clearing and land-use change. The purpose of this research was to make a map of land suitability for maize using Remote Sensing Data and Geographic Information System (GIS). The land suitability method for maize plants used satellite imagery as a data source, supported by fieldwork and secondary data. Data analysis using Geographic Information Systems (GIS). The results of the analysis of land suitability modeling based on agroecosystem potential found that most of the Madura area was suitable for maize cultivation. Madura island had a land area of 456,622.3ha for maize cultivation, where 170.379.5 (15.4%) was very appropriate, 211.412.3 ha (46.3%) was appropriate, 160,098.6 (35.1%) was less appropriate, and 14,732.0 ha (3.2%) was not appropriate.

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Isaksson, H., and C. Andersson. Project GEOVISION: a geological information system applied to the integration of digital elevation, remote sensing and geological data. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1990. http://dx.doi.org/10.4095/128042.

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Bonilla-Mejía, Leonardo, and Erika Londoño-Ortega. Geographic Isolation and Learning in Rural Schools. Banco de la República, 2021. http://dx.doi.org/10.32468/be.1169.

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Rural schools are usually behind in terms of learning, and part of this could be related to geographical isolation. We explore this hypothesis, assessing the effect of distance between rural schools and local governments on learning in Colombia. We use spatial discontinuous regression models based on detailed administrative records from the education system and granular geographic information. Results indicate that distance to towns and Secretary of Education has significant negative effects on students’ standardized test scores. We evaluated alternative mechanisms, finding that the effect of distance is partly explained by differences in critical educational inputs, such as teachers’ education attainment and contract stability. Finally, we assess the mediating role of a program providing monetary incentives to teachers and principals in remote areas.

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Bates, C. Richards, Melanie Chocholek, Clive Fox, John Howe, and Neil Jones. Scottish Inshore Fisheries Integrated Data System (SIFIDS): Work package (3) final report development of a novel, automated mechanism for the collection of scallop stock data. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23449.

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[Extract from Executive Summary] This project, aimed at the development of a novel, automated mechanism for the collection of scallop stock data was a sub-part of the Scottish Inshore Fisheries Integrated Data Systems (SIFIDS) project. The project reviewed the state-of-the-art remote sensing (geophysical and camera-based) technologies available from industry and compared these to inexpensive, off-the -shelf equipment. Sea trials were conducted on scallop dredge sites and also hand-dived scallop sites. Data was analysed manually, and tests conducted with automated processing methods. It was concluded that geophysical acoustic technologies cannot presently detect individual scallop but the remote sensing technologies can be used for broad scale habitat mapping of scallop harvest areas. Further, the techniques allow for monitoring these areas in terms of scallop dredging impact. Camera (video and still) imagery is effective for scallop count and provide data that compares favourably with diver-based ground truth information for recording scallop density. Deployment of cameras is possible through inexpensive drop-down camera frames which it is recommended be deployed on a wide area basis for further trials. In addition, implementation of a ‘citizen science’ approach to wide area recording is suggested to increase the stock assessment across the widest possible variety of seafloor types around Scotland. Armed with such data a full, statistical analysis could be completed and data used with automated processing routines for future long-term monitoring of stock.

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Wells, Aaron, Tracy Christopherson, Gerald Frost, et al. Ecological land survey and soils inventory for Katmai National Park and Preserve, 2016–2017. National Park Service, 2021. http://dx.doi.org/10.36967/nrr-2287466.

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This study was conducted to inventory, classify, and map soils and vegetation within the ecosystems of Katmai National Park and Preserve (KATM) using an ecological land survey (ELS) approach. The ecosystem classes identified in the ELS effort were mapped across the park, using an archive of Geo-graphic Information System (GIS) and Remote Sensing (RS) datasets pertaining to land cover, topography, surficial geology, and glacial history. The description and mapping of the landform-vegetation-soil relationships identified in the ELS work provides tools to support the design and implementation of future field- and RS-based studies, facilitates further analysis and contextualization of existing data, and will help inform natural resource management decisions. We collected information on the geomorphic, topographic, hydrologic, pedologic, and vegetation characteristics of ecosystems using a dataset of 724 field plots, of which 407 were sampled by ABR, Inc.—Environmental Research and Services (ABR) staff in 2016–2017, and 317 were from existing, ancillary datasets. ABR field plots were located along transects that were selected using a gradient-direct sampling scheme (Austin and Heligers 1989) to collect data for the range of ecological conditions present within KATM, and to provide the data needed to interpret ecosystem and soils development. The field plot dataset encompassed all of the major environmental gradients and landscape histories present in KATM. Individual state-factors (e.g., soil pH, slope aspect) and other ecosystem components (e.g., geomorphic unit, vegetation species composition and structure) were measured or categorized using standard classification systems developed for Alaska. We described and analyzed the hierarchical relationships among the ecosystem components to classify 92 Plot Ecotypes (local-scale ecosystems) that best partitioned the variation in soils, vegetation, and disturbance properties observed at the field plots. From the 92 Plot Ecotypes, we developed classifications of Map Ecotypes and Disturbance Landscapes that could be mapped across the park. Additionally, using an existing surficial geology map for KATM, we developed a map of Generalized Soil Texture by aggregating similar surficial geology classes into a reduced set of classes representing the predominant soil textures in each. We then intersected the Ecotype map with the General-ized Soil Texture Map in a GIS and aggregated combinations of Map Ecotypes with similar soils to derive and map Soil Landscapes and Soil Great Groups. The classification of Great Groups captures information on the soil as a whole, as opposed to the subgroup classification which focuses on the properties of specific horizons (Soil Survey Staff 1999). Of the 724 plots included in the Ecotype analysis, sufficient soils data for classifying soil subgroups was available for 467 plots. Soils from 8 orders of soil taxonomy were encountered during the field sampling: Alfisols (<1% of the mapped area), Andisols (3%), Entisols (45%), Gelisols (<1%), Histosols (12%), Inceptisols (22%), Mollisols (<1%), and Spodosols (16%). Within these 8 Soil Orders, field plots corresponded to a total of 74 Soil Subgroups, the most common of which were Typic Cryaquents, Typic Cryorthents, Histic Cryaquepts, Vitrandic Cryorthents, and Typic Cryofluvents.

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