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Letteratura scientifica selezionata sul tema "Land cover"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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Articoli di riviste sul tema "Land cover"

Azevedo, Thiago, and Lindon Fonseca Matias. "Urban Land Use and Land Cover Mapping." Agua y Territorio / Water and Landscape, no. 23 (September 7, 2023): e7251. http://dx.doi.org/10.17561/at.23.7251.

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The Brazilian urbanization process produced a complex urban space, with a variety of urban land use and cover as a result. The study of these forms through a classification system is essential, but most current systems don’t capture this complexity, condensing it. Urban forms are difficult to distinguish and classify, resulting in the need for a system with a high degree of detail, for a more accurate urban planning. The objective of this work is to propose a classification system for urban land use and cover, which can demonstrate the multiplicities through remote sensing, using data from CBE

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Agone, Vikram, and Arvind Suryawanshi. "Assessing Land Use and Land Cover Changes in Waghur Basin: A Remote Sensing and Machine Learning Approach for Sustainable Land Management." JOURNAL OF RESEARCH AND DEVELOPMENT 15, no. 19 (2023): 5–15. https://doi.org/10.5281/zenodo.12570062.

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This research focuses on the importance of studying land use and land cover changes in densely populated countries, with a specific focus on the Waghur Basin in India. It emphasizes the significance of remote sensing techniques for detecting and analyzing these changes. The study uses remote sensing data and machine learning algorithms to classify and analyze land use and land cover patterns in the Waghur Basin from 1990 to 2022. The results reveal significant changes in land utilization, including an increase in agricultural land and a decrease in forest and bare land areas. These changes hav

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Strode, Georgianna, Victor Mesev, Benjamin Thornton, Marjorie Jerez, Thomas Tricarico, and Tyler McAlear. "Geovisualization of land use and land cover using bivariate maps and Sankey flow diagrams." Proceedings of the ICA 1 (May 16, 2018): 1–5. http://dx.doi.org/10.5194/ica-proc-1-106-2018.

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The terms ‘land use’ and ‘land cover’ typically describe categories that convey information about the landscape. Despite the major difference of land use implying some degree of anthropogenic disturbance, the two terms are commonly used interchangeably, especially when anthropogenic disturbance is ambiguous, say managed forestland or abandoned agricultural fields. Cartographically, land use and land cover are also sometimes represented interchangeably within common legends, giving with the impression that the landscape is a seamless continuum of land use parcels spatially adjacent to land cove

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Kumar, R. Shiva, and Afsana Tabassum. "Changes of Land Use Land Cover in Bandipur National Park." Geo-Eye 10, no. 1 (2021): 22–26. https://doi.org/10.53989/bu.ge.v10i1.4.

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This study mainly focusses on changes of land use land cover (LULC) in Bandipur National Park in 2001, 2011and 2019. Methodology have been used for LULC analysis, downloaded satellite imageries of Landsat 8 (OLI) for 2019, Landsat (ETM+) for 2001, and Landsat 4-5 (TM) for 2011. with the help of Geoinformatics tools clipped the area with 5 km buffer in context to our study area and processed it with supervised classification of water, dense forest, open forest, urban, agriculture, current fallow to get LULC map for the study area. In three decades, areawise changes noticed in LULC analysis reve

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Morales, Narkis S., and Ignacio C. Fernández. "Land-Cover Classification Using MaxEnt: Can We Trust in Model Quality Metrics for Estimating Classification Accuracy?" Entropy 22, no. 3 (2020): 342. http://dx.doi.org/10.3390/e22030342.

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MaxEnt is a popular maximum entropy-based algorithm originally developed for modelling species distribution, but increasingly used for land-cover classification. In this article, we used MaxEnt as a single-class land-cover classification and explored if recommended procedures for generating high-quality species distribution models also apply for generating high-accuracy land-cover classification. We used remote sensing imagery and randomly selected ground-true points for four types of land covers (built, grass, deciduous, evergreen) to generate 1980 classification maps using MaxEnt. We calcula

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Oliveira, J. C., R. A. C. Lamparelli, G. K. D. A. Figueiredo, et al. "PASTURE LAND COVER CHANGE IN SÃO PAULO STATE, BRAZIL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W12-2020 (November 6, 2020): 321–26. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w12-2020-321-2020.

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Abstract. Pastures are complex land covers with a variety of land use systems. This land cover occupies large areas in the globe and is mainly used for livestock production. Brazil is one of the largest livestock producers and has extensive pasture areas. We analyzed the pasture land cover change of the São Paulo State between the years 2000 to 2015. São Paulo was chosen as study case due to its large industrial and agricultural importance and its expressive land cover changes over past decades. It was analyzed land covers databases generated by the Brazilian Annual Land Use and Land Cover Map

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Parsa, I. Made. "supabase Please extract the text as it is Here is the extracted text from the image: DENOSING OF HIGH RESOLUTION REMOTE SENSING DATA USING STATIONARY WAVELET TRANSFORM Danang Surya Candra Peneliti Bidang Jianta, Pusdata, LAPAN e-mail: thedananx@yahoo." Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital 10, no. 2 (2013): 113–21. https://doi.org/10.30536/inderaja.v10i2.3279.

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Land cover change, from bare land, water and to vegetation, or vice versa can be used as the basis for paddy fields mapping using the theory of probability, that is probability a land cover can be regarded as an paddy fields if a sequence of land cover changes of water, vegetation and bare land or vice versa on multitemporal images have been detected. The data being used were Landsat multitemporal imagery, while the methods being used in this analysis is the transformation of vegetation index and converted to land covers (bare land, water and vegetation). Detection of three types of land cover

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TOWNSHEND, J. R. G. "Land cover." International Journal of Remote Sensing 13, no. 6-7 (1992): 1319–28. http://dx.doi.org/10.1080/01431169208904193.

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Remlalruata. "STUDIES ON LAND USE AND LAND COVER CHANGE IN AIZAWL DISTRICT, MIZORAM." International Journal of Recent Research in Social Sciences and Humanities (IJRRSSH) 10, no. 2 (2023): 107–16. https://doi.org/10.5281/zenodo.8042670.

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<strong>Abstract:</strong> The Assessment of land use and land cover change is important for the development of a policy by the government. Land cover change is still a very interesting and hot topic in todays world even in Mizoram. For supporting decision-making processes, identifying LULCC and comprehending the underlying forces are crucial. We examined and analyze the changing variation of land use and land cover during the period of 2000 to 2020 using Three Landsat Thematic Mapper (TM) 4-5 C1 level-1 satellite imagery for 2000, 2010 and Landsat 8 OLI/TIRS C1 level-1 imagery for 2020. Accur

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Shumila, Petronillah Mutenyi, Mutavi Irene Nzisa, and Denis Mutama Masika. "Effects of Land Use Land Cover Changes on Vegetation Cover Types in Khwisero Sub County, Kakamega County, Kenya." Indiana Journal of Humanities and Social Sciences 5, no. 7 (2024): 11–28. https://doi.org/10.5281/zenodo.12740878.

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Land use land cover changes have to a great extent changed the world's landscapes rebuilding environments and what they provide to humans during the time spent supporting the rising population across the globe. However, the LULCCs affect land quality in terms of loss of vegetation cover types and altering soil quality to great extent. Misango Hills natural forest and other forms of vegetation cover types in Khwisero Sub County have been changed over completely to farming and built up regions. Cross sectional descriptive and longitudinal research designs were used. Purposive sampling was used t

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Più fonti

Tesi sul tema "Land cover"

Comber, Alexis. "Automated land cover change detection." Thesis, University of Aberdeen, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.248628.

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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 modellin

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Leach, Nicholas Persak. "Hydrologic response of land use and land cover changes." Thesis, University of Iowa, 2015. https://ir.uiowa.edu/etd/1870.

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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

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Skelsey, Chris. "A system for monitoring land cover." Thesis, University of Aberdeen, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.361785.

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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

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Zollet, Simona <1986&gt. "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.

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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

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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.

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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.

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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, mul

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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.

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Rosa, Isabel Maria Duarte. "Modelling land cover change in tropical rainforests." Thesis, Imperial College London, 2013. http://hdl.handle.net/10044/1/40148.

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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 governmen

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Makido, Yasuyo Kato. "Land cover mapping at sub-pixel scales." Diss., Connect to online resource - MSU authorized users, 2006.

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陳章偉 and 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.

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Più fonti

Libri sul tema "Land cover"

Harrison, Mukunda, and Kenya. Dept. of Resource Surveys and Remote Sensing., eds. Land cover/land use in Kiambu District. Dept. of Resource Surveys and Remote Sensing, Ministry of Environment and Natural Resources, 2008.

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Lambin, Eric F., and Helmut Geist, eds. Land-Use and Land-Cover Change. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/3-540-32202-7.

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Mölders, Nicole. Land-Use and Land-Cover Changes. Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-1527-1.

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Meiner, Andrus. Eesti maakate: CORINE Land Cover projekti täitmine Eestis = Land cover of Estonia : implementation of CORINE Land Cover project in Estonia. EV Keskkonnaministeeriumi Info- ja Tehnokeskus, 1999.

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National Workshop for India (2005 Indian Institue of Technology). National Workshop for India: 15-19 February 2005 : workshop report. Food and Agriculture Organization of the United Nations, 2006.

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1959-, Taniguchi Makoto, and Western Pacific Geophysics Meeting (1996 : Brisbane, Qld.), eds. Subsurface hydrological responses to land cover and land use changes. Kluwer Academic Publishers, 1997.

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author, Jiang Luguang, and Zhang Jinghua author, eds. Lancang Jiang liu yu yu da Xianggelila di qu tu di li yong yu tu di fu bei bian hua kao cha yan jiu. Ke xue chu ban she, 2017.

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Gaur, Mahesh K. Impact of changing pattern of landuse/land cover on the desert eco-system of Rajasthan: A study based on remote sensing technique of Pokaran Tehsil, Jaisalmer district. Mahesh Kumar Gaur, 2001.

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author, Kabir Uddin, Shrestha Basanta Raj author, International Centre for Integrated Mountain Development, and HKKH Partnership Project, eds. Land cover mapping in the HKKH region: Cases from three mountain protected areas. Published on behalf of the HKKH Partnership Project by International Centre for Integrated Mountain Development, 2009.

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Geological Survey (U.S.), ed. Land cover characterization program. U.S. Dept. of the Interior, U.S. Geological Survey, 1997.

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Più fonti

Capitoli di libri sul tema "Land cover"

Mölders, Nicole. "Impact of Land-Cover and Land-Cover Changes." In Land-Use and Land-Cover Changes. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1527-1_3.

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Büttner, György. "CORINE Land Cover and Land Cover Change Products." In Land Use and Land Cover Mapping in Europe. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-7969-3_5.

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Maude, Alaric. "Land cover change." In Thinking Geographically. Routledge, 2023. http://dx.doi.org/10.4324/9781003376668-11.

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Chu, Duo. "Land-Cover Change." In Remote Sensing of Land Use and Land Cover in Mountain Region. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7580-4_7.

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Chu, Duo. "Land-Cover Classification." In Remote Sensing of Land Use and Land Cover in Mountain Region. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7580-4_9.

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Feranec, Ján, and Tomáš Soukup. "Land Cover and Land Use." In Recent Landform Evolution. Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2448-8_4.

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Probeck, Markus, Anja Colgan, Tatjana Krimly, Marcelo Zárate, and Karl Schneider. "Land Use and Land Cover." In Regional Assessment of Global Change Impacts. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-16751-0_9.

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Wang, Jing’ai, Shunlin Liang, and Peijun Shi. "Land Cover and Land Use." In World Regional Geography Book Series. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04158-7_6.

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Paudel, Basanta, and Basanta Raj Adhikari. "Land Use and Land Cover." In The Soils of Nepal. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80999-7_5.

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Saikia, Anup. "Land-Use Land-Cover Change." In Over-Exploitation of Forests. Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-01408-1_5.

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Atti di convegni sul tema "Land cover"

Yelistratova, Lesya, Alexander Apostolov, Artur Khodorovskyi, and Maksym Tymchyshyn. "LAND COVER DEGRADATION CHALLENGES IN UKRAINE: NATURAL DRIVERS AND PROCESSES." In 24th SGEM International Multidisciplinary Scientific GeoConference 2024. STEF92 Technology, 2024. https://doi.org/10.5593/sgem2024/2.1/s10.32.

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Land cover degradation poses global challenges, both economically and scientifically, with significant implications for Ukraine's sustainable development. Understanding the need for effective strategies to prevent soil degradation, address degraded lands, and reduce associated risks is crucial at both global and regional scales. Early identification and degradation monitoring require establishing natural predictors (drivers) to preserve ecosystems and biodiversity for future sustainable development. An objective assessment of land cover degradation and its predictors involves integrating remot

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Eapen, Naived George, and Jossy George. "Ensemble Representation Learning for Land Use Land Cover Classification." In 2024 IEEE 4th International Conference on ICT in Business Industry & Government (ICTBIG). IEEE, 2024. https://doi.org/10.1109/ictbig64922.2024.10911832.

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Ragunthar, T., Himanth Kumar Reddy, and Thanneru Dwithej Pavan. "Sematic Segmentation of Land Cover Dataset." In 2025 International Conference on Multi-Agent Systems for Collaborative Intelligence (ICMSCI). IEEE, 2025. https://doi.org/10.1109/icmsci62561.2025.10894303.

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Mustafić, Sead, Karlheinz Gutjahr, Petra Miletich, and Roland Perko. "Artificial Intelligence for Land Use and Land Cover Mapping in Austria." In IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2024. http://dx.doi.org/10.1109/igarss53475.2024.10642647.

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Fukue, Kiyonari, Haruhisa Shimoda, and Toshibumi Sakata. "Spatial land cover classification based on land cover elements." In Europto Remote Sensing, edited by Sebastiano B. Serpico. SPIE, 2001. http://dx.doi.org/10.1117/12.413901.

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Hongri Zhang, Xingyuan Xiao, Ying Li, and Min Wang. "Study on land use/land cover change." In 2011 International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE). IEEE, 2011. http://dx.doi.org/10.1109/rsete.2011.5965806.

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Boriah, Shyam, Vipin Kumar, Michael Steinbach, Christopher Potter, and Steven Klooster. "Land cover change detection." In the 14th ACM SIGKDD international conference. ACM Press, 2008. http://dx.doi.org/10.1145/1401890.1401993.

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Reis, Mariane S., Sidnei J. S. Sant'Anna, Luciano V. Dutra, Maria Isabel S. Escada, and Eliana Pantaleao. "The use of land cover change likelihood for improving land cover classification." In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. http://dx.doi.org/10.1109/igarss.2017.8127683.

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Wang, Yi-Chen, and Chen-Chieh Feng. "Visualizing research of land use land cover change." In Geoinformatics 2008 and Joint conference on GIS and Built Environment: The Built Environment and its Dynamics, edited by Lin Liu, Xia Li, Kai Liu, Xinchang Zhang, and Xinhao Wang. SPIE, 2008. http://dx.doi.org/10.1117/12.812709.

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Hou, Ankai, Abrado Blankson Samuel, Mujie Li, et al. "Land Use and Land Cover Change of Ghana." In IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2020. http://dx.doi.org/10.1109/igarss39084.2020.9323303.

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Rapporti di organizzazioni sul tema "Land cover"

Wang, S. Land use/cover. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2016. http://dx.doi.org/10.4095/298873.

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Latifovic, R. Canada's land cover. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2019. http://dx.doi.org/10.4095/313355.

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Latifovic, R. Canada's land cover. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2019. http://dx.doi.org/10.4095/315659.

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Hansen, Leslie. Los Alamos Land Cover. Office of Scientific and Technical Information (OSTI), 2022. http://dx.doi.org/10.2172/1855122.

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Latifovic, R., Z. L. Zhu, J. Cihlar, C. Giri, and I. Olthof. Land Cover Mapping of North and Central America - Global Land Cover 2000. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2004. http://dx.doi.org/10.4095/219994.

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Bauer, Marvin, Brian Loeffelholz, and Doug Shinneman. Border Lakes land-cover classification. U.S. Department of Agriculture, Forest Service, Northern Research Station, 2009. http://dx.doi.org/10.2737/nrs-rmap-1.

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Mücher, C. A., P. J. F. M. Verweij, H. Kramer, D. Thomas, and R. J. H. G. Henkens. Land Cover Classification 2020 and analysis historical land cover changes since 1900 on Aruba. Wageningen Environmental Research, 2024. http://dx.doi.org/10.18174/679738.

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Caster, Joshua J., Joel B. Sankey, and Nathaniel D. Branksy. Land Cover Change Within Wetland Complexes at Dixie Meadows, Churchill County, Nevada: 2015 – 2023. U.S. Fish and Wildlife Service, 2025. https://doi.org/10.3996/3632813421.

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Dixie Meadows, Nevada, is a system of geothermal springs and seeps that feed a complex of marshes and wetland meadows that are located within lands managed by the Bureau of Land Management (BLM) and the Department of Defense (DOD). A previous U.S. Geological Survey report documented variability in satellite imagery-based land cover classifications for seven wetland complexes at near monthly time intervals between October 2015 and January 2022. This report presents additional data, extending analysis to November 2023. Land cover classifications between October 2015 and November 2023 demonstrate

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Gould, William A., Sebastian Martinuzzi, and Olga M. Ramos Gonzalez. Developed land cover of Puerto Rico. U.S. Department of Agriculture, Forest Service, International Institute of Tropical Forestry, 2008. http://dx.doi.org/10.2737/iitf-rmap-10.

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Chomani, Kaifi. Evaluation of Different Classification Algorithms for Land Use Land Cover Mapping. ResearchHub Technologies, Inc., 2025. https://doi.org/10.55277/researchhub.2vexo15g.1.

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