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Journal articles on the topic 'Land cover (LU/LC)'

Author: Grafiati

Published: 5 June 2025

Last updated: 1 August 2025

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1

Sertel, Elif, Raziye Topaloğlu, Betül Şallı, Irmak Yay Algan, and Gül Aksu. "Comparison of Landscape Metrics for Three Different Level Land Cover/Land Use Maps." ISPRS International Journal of Geo-Information 7, no. 10 (2018): 408. http://dx.doi.org/10.3390/ijgi7100408.

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This research aims to investigate how different landscape metrics are affected by the enhancement of the thematic classes in land cover/land use (LC/LU) maps. For this aim, three different LC/LU maps based on three different levels of CORINE (Coordination of Information on The Environment) nomenclature were created for the selected study area using GEOBIA (Geographic Object Based Image Analysis) techniques. First, second and third level LC/LU maps of the study area have five, thirteen and twenty-seven hierarchical thematic classes, respectively. High-resolution Spot 7 images with 1.5 m spatial

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López, N., A. Márquez Romance, and E. Guevara Pérez. "Change dynamics of land-use and land-cover for tropical wetland management." Water Practice and Technology 15, no. 3 (2020): 632–44. http://dx.doi.org/10.2166/wpt.2020.049.

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Abstract In hydrographic basins with wetlands, changes in land use (LU) and land cover (LC) impact the conservation of natural resources, leading to dynamics analysis for integral management. A method is proposed offering greater accuracy in determining the LU and LC bi-temporal and spatial change dynamics in tropical wetlands. LU and LC monitoring is based on Landsat images from 1986 to 2017. ‘Pre-classification’ and ‘post-classification’ methods are applied. In the former, reflectance image differencing and principal component N° 1 image differencing are analyzed to estimate the rate of chan

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3

Giuliani, Gregory, Denisa Rodila, Nathan Külling, Ramona Maggini, and Anthony Lehmann. "Downscaling Switzerland Land Use/Land Cover Data Using Nearest Neighbors and an Expert System." Land 11, no. 5 (2022): 615. http://dx.doi.org/10.3390/land11050615.

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High spatial and thematic resolution of Land Use/Cover (LU/LC) maps are central for accurate watershed analyses, improved species, and habitat distribution modeling as well as ecosystem services assessment, robust assessments of LU/LC changes, and calculation of indices. Downscaled LU/LC maps for Switzerland were obtained for three time periods by blending two inputs: the Swiss topographic base map at a 1:25,000 scale and the national LU/LC statistics obtained from aerial photointerpretation on a 100 m regular lattice of points. The spatial resolution of the resulting LU/LC map was improved by

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4

K, Ramesh, Asha R, and Jamuna E. "Assessment of land use/land cover change detection of Mettupalayam Taluk, Coimbatore district, Tamil Nadu, India, using RS and GIS." GSC Biological and Pharmaceutical Sciences 22, no. 1 (2023): 241–46. https://doi.org/10.5281/zenodo.7661343.

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Understanding changes in land use land cover is essential managing and monitoring natural resources and development, particularly where urbanization is expanding. In present study, describes land use/land cover (LU/LC) mapping and change detection analysis of Mettupalayam taluk of Coimbatore district in Tamil Nadu. Estimation in ArcGIS for LU/LC classification from LANSAT images, is the best method for classifier for the different features were used to classify the satellite images are used to classify the land use/land cover change s for the given period. The results indicated that land cover

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5

Getu Engida, Tewodros, Tewodros Assefa Nigussie, Abreham Berta Aneseyee, and John Barnabas. "Land Use/Land Cover Change Impact on Hydrological Process in the Upper Baro Basin, Ethiopia." Applied and Environmental Soil Science 2021 (July 29, 2021): 1–15. http://dx.doi.org/10.1155/2021/6617541.

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Understanding the hydrological process associated with Land Use/Land Cover (LU/LC) change is vital for decision-makers in improving human wellbeing. LU/LC change significantly affects the hydrology of the landscape, caused by anthropogenic activities. The scope of this study is to investigate the impact of LU/LC change on the hydrological process of Upper Baro Basin for the years 1987, 2002, and 2017. The Soil Water Assessment Tool (SWAT) model was used for the simulation of the streamflow. The required data for the SWAT model are soils obtained from the Food and Agriculture Organization; Digi

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Shekar N C, Sanjay, and Hemalatha H N. "Land use and Land Cover Characteristics using Bhuvan and MODIS Satellite Data." International Journal of Recent Technology and Engineering 9, no. 5 (2021): 289–94. http://dx.doi.org/10.35940/ijrte.f5322.019521.

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Understanding vegetation characteristics is essential for watershed modeling, like in the prediction of streamflow and evapotranspiration (AET) estimation. So, the present study was taken to analyze the Land use/Land cover characteristics in a Sub-humid tropical river basin which is originating in the forested part of Western Ghats mountain ranges using the Moderate Resolution Imaging Spectroradiometer (MODIS) and Bhuvan satellite data as inputs for the algorithm. All the fourteen LU/LC characteristics present in the Hemavathi basin (5427 km2 ) were analyzed in the basin using satellite data w

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Dr., Sanjay Shekar N. C., and Hemalatha H. N. Dr. "Land use and Land Cover Characteristics using Bhuvan and MODIS Satellite Data." International Journal of Recent Technology and Engineering (IJRTE) 9, no. 5 (2021): 289–94. https://doi.org/10.35940/ijrte.F5322.019521.

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<strong>Abstract:</strong> Understanding vegetation characteristics is essential for watershed modeling, like in the prediction of streamflow and evapotranspiration (AET) estimation. So, the present study was taken to analyze the Land use/Land cover characteristics in a Sub-humid tropical river basin which is originating in the forested part of Western Ghats mountain ranges using the Moderate Resolution Imaging Spectroradiometer (MODIS) and Bhuvan satellite data as inputs for the algorithm. All the fourteen LU/LC characteristics present in the Hemavathi basin (5427 km2 ) were analyzed in the b

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Syed, Rouhullah Ali, Junaid N. Khan, Rohitashw Kumar, Farooq Ahmad Lone, Shakeel Ahmad Mir, and Imran Khan. "Analysis of changes in land use and land cover in Central Kashmir of the Great Himalayas using geospatial technologies." Environment Conservation Journal 24, no. 1 (2023): 183–88. http://dx.doi.org/10.36953/ecj.12542350.

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Remote sensing data may identify changes in land use and land cover (LU/LC). Land cover changes include changing from one land cover category to another and changing conditions within a category. LU/LC change is an essential aspect of current environmental management techniques. It is vital for land conservation, sustainable development, and water resource management. The study's goal is to investigate changes in land use and land cover in Central Kashmir of the Great Himalayas. This study used LISS III 23.5 m resolution images between 2000 and 2017 to detect land cover change. Changes were id

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G.S, Dwarakish, Jagadeesha Ballambettu Pai, and Jubina C.K. "INFLUENCE OF LAND USE LAND COVER CHANGE ON RUNOFF CHARACTERISTICS OF NETRAVATHI RIVER CATCHMENT, KARNATAKA, INDIA." Water Conservation & Management 8, no. 1 (2023): 66–78. https://doi.org/10.26480/wcm.01.2024.66.78.

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The effect of LU/LC on the streamflow characteristics of the Netravathi river basin, Karnataka, India, is studied using Soil and Water Assessment Tool (SWAT) model. Landsat images, soil map from FAO, ASTER DEM (30m grid) and streamflow data, forms the database for the present work. The most significant changes from 1981 to 2015, in the LU/LC includes agricultural land (31.86%), built-up area (67.9%), forest cover (-20.01%), coconut plantation (55.12%), other vegetation (-18.55%) and others (-11.82%). The verification of performance of model was carried out by the coefficient of determination v

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Shukla, S., M. V. Khire, and S. S. Gedam. "Monitoring Land Use/Land Cover Changes in a River Basin due to Urbanization using Remote Sensing and GIS Approach." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 949–53. http://dx.doi.org/10.5194/isprsarchives-xl-8-949-2014.

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Faster pace of urbanization, industrialization, unplanned infrastructure developments and extensive agriculture result in the rapid changes in the Land Use/Land Cover (LU/LC) of the sub-tropical river basins. Study of LU/LC transformations in a river basin is crucial for vulnerability assessment and proper management of the natural resources of a river basin. Remote sensing technology is very promising in mapping the LU/LC distribution of a large region on different spatio-temporal scales. The present study is intended to understand the LU/LC changes in the Upper Bhima river basin due to urban

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Raj, Gogana Prasanna, Asmita Deb, Dr Venkateswarlu Gogana, and Amar Viplow Beera. "Evolution of Land Use and Land Cover Change in Panjim, Goa: A Comparative Analysis from 1990 to 2024." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 008 (2024): 1–15. http://dx.doi.org/10.55041/ijsrem37223.

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This research paper investigates the dynamics of land use and land cover (LU/LC) change in Panjim, Goa, India, from 1990 to 2024. Using satellite Data and GIS techniques, the study analyzes the spatial and temporal transformations of land cover categories, including forest, agriculture, urban areas, and water bodies. The primary objective is to understand the drivers of LU/LC change and assess their implications for sustainable urban development and environmental conservation. The findings reveal significant urban expansion, encroachment on agricultural lands, and reduction in forest cover. Th

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12

Mansourmoghaddam, Mohammad, Iman Rousta, Pedro Cabral, et al. "Investigation and Prediction of the Land Use/Land Cover (LU/LC) and Land Surface Temperature (LST) Changes for Mashhad City in Iran during 1990–2030." Atmosphere 14, no. 4 (2023): 741. http://dx.doi.org/10.3390/atmos14040741.

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Studies on how cities are affected by urban heat islands (UHI) are critical nowadays for a better understanding of the connected effects and for providing helpful insights for sustainable city development planning. In this study, Landsat-5 Thematic Mapper (TM), Landsat-7 Enhanced Thematic Mapper+ (ETM+), and Landsat-8 Operational Land Imager (OLI) images were used to assess the dynamics of the spatiotemporal pattern of land use/land cover (LU/LC) and land surface temperature (LST) in the metropolitan city of Mashhad, Iran in the period between 1990 and 2019. The Markov chain model (MCM) was us

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K Ramesh, R Asha, and E Jamuna. "Assessment of land use/land cover change detection of Mettupalayam Taluk, Coimbatore district, Tamil Nadu, India, using RS and GIS." GSC Biological and Pharmaceutical Sciences 22, no. 1 (2023): 241–46. http://dx.doi.org/10.30574/gscbps.2023.22.1.0023.

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Understanding changes in land use land cover is essential managing and monitoring natural resources and development, particularly where urbanization is expanding. In present study, describes land use/land cover (LU/LC) mapping and change detection analysis of Mettupalayam taluk of Coimbatore district in Tamil Nadu. Estimation in ArcGIS for LU/LC classification from LANSAT images, is the best method for classifier for the different features were used to classify the satellite images are used to classify the land use/land cover change s for the given period. The results indicated that land cover

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14

Jangid, Amita, Mukesh Kumar Gupta, and Vishal Shrivastava. "Techniques and Challenges of the Machine Learning Method for Land Use/Land Cover (LU/LC) Classification in Remote Sensing Using the Google Earth Engine." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 7 (2023): 85–92. http://dx.doi.org/10.17762/ijritcc.v11i7.7833.

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In order to accurately observe the globe, land use and land cover are crucial. Due to the proliferation of several global modifications associated with the existence of the planet, land use/land cover (LU/LC) classification is now regarded as a topic of highest significance in the natural environment and an important field to be researched by researchers. Google Earth provides satellite image dataset which contains high-resolution images; these images are used to analyze the land area. In order to address the dearth of review articles throughout the land use/land cover classification phase, we

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15

Tiwari, Jagriti, S. K. Sharma, and R. J. Patil. "Land use and Land cover Mapping Based on Normalized Difference Vegetation Index using Remote Sensing and Geographical Information System in Banjar River Watershed of Narmada Basin." Current World Environment 12, no. 3 (2017): 678–84. http://dx.doi.org/10.12944/cwe.12.3.19.

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The spatial analysis of land use and land cover (LULC) dynamics is necessary for sustainable utilization and management of the land resources of an area. Remote sensing along with Geographical Information System emerged as an effective technique for mapping the LU/LC categories of an area in an efficient and cost-effective manner. The present study was conducted in Banjar river watershed located in Balaghat and Mandla district of Madhya Pradesh, India. The Normalized Difference Vegetation Index (NDVI) approach was adopted for LU/LC classification of study area. The Landsat-8 satellite data of

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16

Gupta, Garima, R. S. Yadav, and Deepak Maurya. "Decomposition and Nitrogen Dynamics of Tree Pruned Biomass Under Albizia Procera Based Agroforestry System in Semi Arid Region of Bundelkhand, India." Current World Environment 12, no. 3 (2017): 725–33. http://dx.doi.org/10.12944/cwe.12.3.24.

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The spatial analysis of land use and land cover (LULC) dynamics is necessary for sustainable utilization and management of the land resources of an area. Remote sensing along with Geographical Information System emerged as an effective technique for mapping the LU/LC categories of an area in an efficient and cost-effective manner. The present study was conducted in Banjar river watershed located in Balaghat and Mandla district of Madhya Pradesh, India. The Normalized Difference Vegetation Index (NDVI) approach was adopted for LU/LC classification of study area. The Landsat-8 satellite data of

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17

Tuzcu Kokal, A., İ. İsmailoğlu, and N. Musaoğlu. "COMPARISON OF LANDSAT-9 AND PRISMA SATELLITE DATA FOR LAND USE / LAND COVER CLASSIFICATION." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-M-2-2022 (July 25, 2022): 197–201. http://dx.doi.org/10.5194/isprs-archives-xlvi-m-2-2022-197-2022.

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Abstract. Land use and land cover (LU/LC) detection has great significance in management of natural resources and protection of environment. Hence, monitoring LU/LC with the state-of-the-art approaches has gained importance during the recent years and free access satellite images have become valuable data source. The aim of this study is to compare classification abilities of Landsat-9 and PRISMA satellite images while applying Support Vector Machine (SVM) algorithm to distinguish different LU/LC classes. For this purpose, the study area was chosen to be of heterogeneous character that include

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18

Tadese, Semegnew, Teshome Soromessa, and Tesefaye Bekele. "Analysis of the Current and Future Prediction of Land Use/Land Cover Change Using Remote Sensing and the CA-Markov Model in Majang Forest Biosphere Reserves of Gambella, Southwestern Ethiopia." Scientific World Journal 2021 (February 23, 2021): 1–18. http://dx.doi.org/10.1155/2021/6685045.

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This study aimed to evaluate land use/land cover changes (1987–2017), prediction (2032–2047), and identify the drivers of Majang Forest Biosphere Reserves. Landsat image (TM, ETM+, and OLI-TIRS) and socioeconomy data were used for the LU/LC analysis and its drivers of change. The supervised classification was also employed to classify LU/LC. The CA-Markov model was used to predict future LU/LC change using IDRISI software. Data were collected from 240 households from eight kebeles in two districts to identify LU/LC change drivers. Five LU/LC classes were identified: forestland, farmland, grass

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D’Ambrosio, Lara, Massimiliano Cannata, and Daniele Strigaro. "Assessing built-up surface dynamics in the Ticino River Basin using multi-source LU/LC datasets: A preliminary comparative study within the INTERREG WINCA4TI project." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W13-2025 (July 11, 2025): 95–101. https://doi.org/10.5194/isprs-archives-xlviii-4-w13-2025-95-2025.

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Abstract. This study developed within the INTERREG VI-A Italy–Switzerland project WINCA4TI (Water Interactions with Nature, Climate, and Agriculture for the Ticino Hydrographic Basin), investigates land use and land cover (LU/LC) changes focusing on builtup surface evolution in the Swiss portion of the Ticino watershed. LU/LC data are essential for tracking environmental change, modeling nutrient flows, and guiding sustainable land management. We analyzed and compared three key LU/LC datasets available for Switzerland: the national Arealstatistik, the European CORINE Land Cover (CLC), and the

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Jovanović, S., T. Predić, and G. Bratić. "ANALYSIS OF FREE AND OPEN LAND COVER MAPS FOR AGRICULTURAL LAND USE PLANNING AT LOCAL LEVEL." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (August 5, 2022): 237–43. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-237-2022.

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Abstract. According to the Law on Agricultural Land of the Republic of Srpska, municipalities and cities are obliged to prepare a planning document “Groundwork for Agricultural Land Protection, Use and Restructuring (The groundwork)”. Information related to the current state of land cover and land cover use are essential for the groundwork. Such layer was created for the municipality Laktaši in Bosnia and Herzegovina by digitization of land cover features from orthophoto imagery. Even if digitization provides highly reliable data, it is also time-consuming activity, and therefore the evaluatio

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Khairul Amri Kamarudin, Mohd, Kabir Abdulkadir Gidado, Mohd Ekhwan Toriman, et al. "Classification of Land Use/Land Cover Changes Using GIS and Remote Sensing Technique in Lake Kenyir Basin, Terengganu, Malaysia." International Journal of Engineering & Technology 7, no. 3.14 (2018): 12. http://dx.doi.org/10.14419/ijet.v7i3.14.16854.

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Geographical information system (GIS) techniques and Remote Sensing (RS) data are fundamental in the study of land use (LU) and land cover (LC) changes and classification. The aim of this study is to map and classify the LU and LC change of Lake Kenyir Basin within 40 years’ period (1976 to 2016). Multi-temporal Landsat images used are MSS 1976, 1989, ETM+ 2001 and OLI 8 2016. Supervised Classification on Maximum Likelihood Algorithm method was used in ArcGIS 10.3. The result shows three classes of LU and LC via vegetation, water body and built up area. Vegetation, which is the dominant LC fou

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Yousefi, Saleh, Somayeh Mirzaee, Hussein Almohamad, et al. "Image Classification and Land Cover Mapping Using Sentinel-2 Imagery: Optimization of SVM Parameters." Land 11, no. 7 (2022): 993. http://dx.doi.org/10.3390/land11070993.

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Land use/cover (LU/LC) classification provides proxies of the natural and social processes related to urban development, providing stakeholders with crucial information. Remotely sensed images combined with supervised classification are common to define land use, but high-performance classifiers remain difficult to achieve, due to the presence of model hyperparameters. Conventional approaches rely on manual adjustment, which is time consuming and often unsatisfying. Therefore, the goal of this study has been to optimize the parameters of the support vector machine (SVM) algorithm for the gener

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Sanga, Faraja, Emma T. Liwenga, and Evaristo Haulle. "Land-use Dynamics in Lupila Ward of Makete District in Southern Highlands of Tanzania." Journal of Land and Rural Studies 10, no. 1 (2021): 124–44. http://dx.doi.org/10.1177/23210249211051117.

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This article examines Land-Use (LU) dynamics in Lupila ward of Makete District in Southern Highlands of Tanzania. Specifically, the purpose of this study is to track LU change in Lupila ward from 1984 to 2014. Geographical information system (GIS) was employed to track LU/Land-Cover (LU/LC) change from 1984 to 2014. The questionnaire, Focus Group Discussions (FGDs), in-depth interview and field observations were used to supplement GIS. The data were collected from 87 respondents through questionnaire, FGDs and in-depth interview. Five LU/LC classes were identified, which are agriculture with s

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Chourushi, Shibani, Pradeep P. Lodha, and Indra Prakash. "A COMPARATIVE STUDY OF THREE DECADAL LU/LC MAPS OF SABARMATI RIVER BASIN." COMPUSOFT: An International Journal of Advanced Computer Technology 08, no. 08 (2019): 3312–16. https://doi.org/10.5281/zenodo.14832857.

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India is a country of heterogeneous land uses/ land covers. And each LU/LC plays an essential part in maintaining and conserving our natural environment. Land use is created by human beings for the betterment of human beings which includes built-up areas, agricultural areas, industrial areas, recreational areas, etc whereas land cover is the natural environmental cover present on the earth surface such as vegetation cover, forests, water bodies, wetlands etc. The main objective of the paper is to compare the three LU/LC (1985-1995-2005) maps using remote sensing and ArcGIS software to detect c

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Basavarajappa, H.T* Pushpavathi K.N Manjunatha M.C. "GEOINFORMATICS APPLICATION ON LAND USE/ LAND COVER CLASSIFICATION ANALYSIS IN KOLLEGALA TALUK OF CHAMARAJANAGARA DISTRICT, KARNATAKA, INDIA." Global Journal of Engineering Science and Research Management 3, no. 6 (2016): 112–22. https://doi.org/10.5281/zenodo.56719.

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Land resources planning and its development is an important issue in the present era. Major changes in any part of earth’s surfaces will significantly influences the environmental factors such as atmosphere, soil, topography, vegetation, underlying geology, hydrology, plant & animal population. The present aim is to classify the Land Use/ Land Cover (LU/LC) categories based on NRSC’ standards (1995) to increase land productivity, restoration of soil degradation, reclamation of wastelands and increase the environmental qualities. An attempt have been made to evaluate the level-I

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MuraliKrishna, I., and V. S. Sahithi. "ASSESSING THE RELATION BETWEEN LAND USE / LAND COVER CHANGES AND ENVIRONMENTAL PARAMETERS FOR CHENNAI CITY, TAMIL NADU: A REMOTE SENSING AND GIS APPROACH." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-1/W2-2023 (December 13, 2023): 471–82. http://dx.doi.org/10.5194/isprs-archives-xlviii-1-w2-2023-471-2023.

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Abstract. Land use land cover changes in coastal regions are prone to many factors like rapid urbanization and industrialization, tourism, and tideline changes etc. Chennai city, a coastal city of TamilNadu, India has witnessed tremendous changes in land use land cover over the past two decades due to rapid urbanization and industrialization. Remote sensing and GIS technologies can efficiently help in analyzing these changes. In this study, changes in land use land cover patterns of Chennai city from 2005 to 2016 were assessed using IRS P6 LISS III remotely sensed satellite images. Post classi

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Adegbola, P. A., J. R. Adewumi, and O. A. Obiora-Okeke. "Application of Markov Chain Model and ArcGIS in Land Use Projection of Ala River Catchment, Akure, Nigeria." Nigerian Journal of Technological Development 18, no. 1 (2021): 30–38. http://dx.doi.org/10.4314/njtd.v18i1.5.

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Increase land use change is one of the consequences of rapid population growth of cities in developing countries with its negative consequences on the environment. This study generates previous and present land use of Ala watershed and project the future land use using Markov chain model and ArcGIS software (version 10.2.1). Landsat 7, Enhanced Thematic mapper plus (ETM+) image and Landsat 8 operational land imager (OLI) with path 190 and row 2 used to generate land use (LU) and land cover (LC) images for the years 2000, 2010 and 2019. Six LU/LC classes were considered as follows: developed ar

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Joseph, Sabu, Rahul R, and Sukanya S. "Land Use/Land Cover (LU/LC) Changes and its impact on Soil Organic Carbon Stock in Killiar River Basin, Kerala, India: A Geospatial Approach." Current World Environment 16, no. 3 (2021): 662–64. http://dx.doi.org/10.12944/cwe.16.3.2.

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The changes in the pattern of land use and land cover (LU/LC) have remarkable consequences on ecosystem functioning and natural resources dynamics. The present study analyzes the spatial pattern of LU/LC change detection along the Killiar River Basin (KRB), a major tributary of Karamana river in Thiruvananthapuram district, Kerala (India), over a period of 64 years (1957-2021) through Remote Sensing and GIS approach. The rationale of the study is to identify and classify LU/LC changes in KRB using the Survey of India (SOI) toposheet (1:50,000) of 1957, LISS-III imagery of 2005, Landsat 8 OLI &

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Turchi, Agnese, Federico Di Traglia, Tania Luti, Davide Olori, Iacopo Zetti, and Riccardo Fanti. "Environmental Aftermath of the 2019 Stromboli Eruption." Remote Sensing 12, no. 6 (2020): 994. http://dx.doi.org/10.3390/rs12060994.

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This study focuses on the July-August 2019 eruption-induced wildfires at the Stromboli island (Italy). The analysis of land cover (LC) and land use (LU) changes has been crucial to describe the environmental impacts concerning endemic vegetation loss, damages to agricultural heritage, and transformations to landscape patterns. Moreover, a survey was useful to collect eyewitness accounts aimed to define the LU and to obtain detailed information about eruption-induced damages. Detection of burnt areas was based on PLÉIADES-1 and Sentinel-2 satellite imagery, and field surveys. Normalized Burn Ra

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Ünsal, Ömer. "Land Use Change in Türkiye and Determination of Priority Areas for Urban Heat Island Studies." Coğrafi Bilimler Dergisi 23, no. 1 (2025): 1–21. https://doi.org/10.33688/aucbd.1597846.

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Urban Heat Island (UHI) effect of climate change and unplanned urbanisation in developing countries like Türkiye is frequently investigated. Where to prioritise UHI studies is an important problem. In this study, CORINE Land Use/Land Cover (LU/LC), Meteorological Station (MS), urban LU/LC and provincial boundary data were analysed using GIS to provide a basis for the planning of UHI studies in Türkiye. In addition to the change in the LU/LC at the provincial level in Türkiye, the proportion of urbanised area within a 10 kilometer radius of the MS and the proportion of dense urban LU/LC types w

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Sheykhmousa, Mohammadreza, Norman Kerle, Monika Kuffer, and Saman Ghaffarian. "Post-Disaster Recovery Assessment with Machine Learning-Derived Land Cover and Land Use Information." Remote Sensing 11, no. 10 (2019): 1174. http://dx.doi.org/10.3390/rs11101174.

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Post-disaster recovery (PDR) is a complex, long-lasting, resource intensive, and poorly understood process. PDR goes beyond physical reconstruction (physical recovery) and includes relevant processes such as economic and social (functional recovery) processes. Knowing the size and location of the places that positively or negatively recovered is important to effectively support policymakers to help readjust planning and resource allocation to rebuild better. Disasters and the subsequent recovery are mainly expressed through unique land cover and land use changes (LCLUCs). Although LCLUCs have

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Das, Rajeshree. "Urban Expansion and Climate Change: Spatio-Temporal Analysis of Land Use and Land Cover Changes in Ranchi City, India." Disaster Advances 18, no. 7 (2025): 31–38. https://doi.org/10.25303/187da031038.

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This study investigates the spatio-temporal changes in land use and land cover (LU/LC) in Ranchi City from 1999 to 2024 and evaluates their impact on the climate. Satellite imagery from LISS III Resourcesat 1 (NRSC) and LANDSAT 7 (USGS) for the years 1999, 2004, 2009, 2014 and 2024 were utilized. A supervised image classification approach using maximum likelihood classification (MLC) was employed to generate LU/LC maps. To assess the accuracy of these classifications, 400 sample verification points were selected through purposive random sampling. The results indicate a consistent increase in b

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Sridhar, P., K. Anil, J. N. S. S. Raju, and K. V. Ramana. "Land Use and Land Cover Classification using Support Vector Machine Technique: A Case Study of Kaddam Watershed." Disaster Advances 18, no. 6 (2025): 1–6. https://doi.org/10.25303/186da0106.

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Land use and land cover (LU/LC) maps, along with their temporal dynamics, are essential for flood prediction, seasonal water quality monitoring, environmental sustainability planning and ecological assessments. Accurate classification of satellite image datasets presents a challenging task due to the complexity of land use patterns and the need for precise methods. To address these challenges, this study utilized multi-temporal satellite image datasets to perform LU/LC classification and analyze temporal changes within the Kaddam watershed. The Support Vector Machine (SVM) classification techn

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Suheri, Asep, Cecep Kusmana, and Moh Yanuar J. Purwanto. "Implementasi Rencana Induk Pengembangan Kawasan Sentul City Terhadap Limpasan Puncak dan Konstribusi Banjir." TATALOKA 23, no. 1 (2021): 39–56. http://dx.doi.org/10.14710/tataloka.23.1.39-56.

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The purpose of this study is to create a peak runoff model in urban SC areas based on existing land use/land cover (LU / LC) and a master plan. To calculate peak runoff (PRO) using the rational method. To find out the current LU / LC through existing SPOT-6 image analysis in 2017, using supervised classification method with an estimation of gamma distribution parameters with the maximum likelihood method using QGIS 2.8 software, SAGA GIS, and Arc -GIS 10.4.1. Based on the results of image analysis obtained twelve types of LU, which can be grouped into three types of LC, namely 33% of developed

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Kumar, P., S. Ravindranath, and K. G. Raj. "OBJECT ORIENTED CLASSIFICATION AND FEATURE EXTRACTION FOR PARTS OF EAST DELHI USING HYBRID APPROACH." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5 (November 19, 2018): 749–54. http://dx.doi.org/10.5194/isprs-archives-xlii-5-749-2018.

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<p><strong>Abstract.</strong> Rapid urbanization of Indian cities requires a focused attention with respect to preparation of Master Plans of cities. Urban land use/land cover from very high resolution satellite data sets is an important input for the preparation of the master plans of the cities along with extraction of transportation network, infrastructure details etc. Conventional classifiers, which are pixel based do not yield reasonably accurate urban land use/land cover classification of very high resolution satellite data (usually merged images of Panchromatic &am

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Rousta, Iman, Md Sarif, Rajan Gupta, et al. "Spatiotemporal Analysis of Land Use/Land Cover and Its Effects on Surface Urban Heat Island Using Landsat Data: A Case Study of Metropolitan City Tehran (1988–2018)." Sustainability 10, no. 12 (2018): 4433. http://dx.doi.org/10.3390/su10124433.

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This article summarized the spatiotemporal pattern of land use/land cover (LU/LC) and urban heat island (UHI) dynamics in the Metropolitan city of Tehran between 1988 and 2018. The study showed dynamics of each LU/LC class and their role in influencing the UHI. The impervious surface area expanded by 286.04 (48.27% of total land) and vegetated land was depleted by 42.06 km2 (7.10% of total land) during the period of 1988–2018. The mean land surface temperature (LST) has enlarged by approximately 2–3 °C at the city center and 5–7 °C at the periphery between 1988 and 2018 based on the urban–rura

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Połedniková, Zuzana, Adriana Holušová, Lukáš Vaverka, and Tomáš Galia. "Effects of policy changes in the last 80 years on LU/LC and ecosystem services: A case study of the Odra River floodplain (Czech Republic)." Moravian Geographical Reports 33, no. 2 (2025): 91–105. https://doi.org/10.2478/mgr-2025-0007.

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Abstract Riverscapes are degraded and threatened by human activities. We investigated the spatiotemporal dynamics and trends of land use/land cover (LU/LC) and ecosystem services (ES) in the floodplain of the Odra River in the Czech Republic over the last 80 years. Our focus was on: (i) the effects of changing political regimes and environmental policies on changes in LU/LC and ES (agricultural potential, natural flooding, and water provision and quality), and (ii) the effects of the establishment of a protected landscape area (Poodří PLA) on ES over the last 30 years. To assess LU/LC changes,

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Nasradeen, A. H. GADALLAH, HANO Abdelnasir, and YAGOUB Yousif. "Characterizing Forest Cover Changes Based on Satellite Images cum Forest Dependents' Data." Agriculture and Forestry Journal 4, no. 2 (2020): 63–70. https://doi.org/10.5281/zenodo.4310945.

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While the reliable and consistent information on forests dynamic as well as communities living in their vicinities are fundamental to sustain their socioeconomic and environmental benefits, these information are lacking in Wad Al-Bashir Forest (WF) area that located in Sennar State of Sudan. Thus, this study assessed the land use/land cover (LU/LC) changes cum forests’ dependents needs (FDNs) as well as forestland-related-activities (FRAs) using geospatial techniques alongside key informant interview (KII) cum structured questionnaire, respectively. For assessing the LU/LC, Landsat image

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Degerli, Burcu, and Mehmet Çetin. "Using the Remote Sensing Method to Simulate the Land Change in the Year 2030." Turkish Journal of Agriculture - Food Science and Technology 10, no. 12 (2022): 2453–66. http://dx.doi.org/10.24925/turjaf.v10i12.2453-2466.5555.

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This is study is based with the support of RS-GIS technology on the land use of Samsun Center, as well as the coastal districts of Ilkadım,Atakum,Bafra Plain, through the processing and interpretation of satellite images in the summer months of 2000,2010,2020. Spatial and temporal variability properties of LU/LC were determined using MLC algorithm, controlled classification approach. The predictive values of the LU/LC change that will occur in 2030, calculated with the MLP‑ANN model based on Machine Learning algorithms and mapped with the QGIS 3.16 program. To determine the accuracy coefficien

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ALPHAN, Hakan, and Laden GÜVENSOY. "DETECTING COASTAL URBANIZATION AND LAND USE CHANGE IN SOUTHERN TURKEY." JOURNAL OF ENVIRONMENTAL ENGINEERING AND LANDSCAPE MANAGEMENT 24, no. 2 (2016): 97–107. http://dx.doi.org/10.3846/16486897.2015.1113976.

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One of the most important needs in contemporary landscape planning is quantitative land use/land cover (LU/LC) change information. The reason a strong emphasis is placed on landscape change information is that it serves as an ecological and geographical basis for preparing and implementing development plans in a more sustainable manner. Multi-temporal analysis of LU/LC changes on the Eastern Mediterranean coast of Turkey revealed that there is a marked preference for these areas primarily for building development. This paper demonstrates a methodology that relies on quantitative analysis techn

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Nivedita Priyadarshini, K., M. Kumar, S. A. Rahaman, and S. Nitheshnirmal. "A COMPARATIVE STUDY OF ADVANCED LAND USE/LAND COVER CLASSIFICATION ALGORITHMS USING SENTINEL-2 DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5 (November 19, 2018): 665–70. http://dx.doi.org/10.5194/isprs-archives-xlii-5-665-2018.

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<p><strong>Abstract.</strong> Land Use/ Land Cover (LU/LC) is a major driving phenomenon of distributed ecosystems and its functioning. Interpretation of remote sensor data acquired from satellites requires enhancement through classification in order to attain better results. Classification of satellite products provides detailed information about the existing landscape that can also be analyzed on temporal basis. Image processing techniques acts as a platform for analysis of raw data using supervised and unsupervised classification algorithms. Classification comprises two br

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Der Sarkissian, Rita, Mario J. Al Sayah, Chadi Abdallah, Jean-Marc Zaninetti, and Rachid Nedjai. "Land Use Planning to Reduce Flood Risk: Opportunities, Challenges and Uncertainties in Developing Countries." Sensors 22, no. 18 (2022): 6957. http://dx.doi.org/10.3390/s22186957.

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Land use planning for flood risk reduction has been significantly addressed in literature. However, a clear methodology for flood mitigation oriented land-use planning and its implementation, particularly in developing countries like Lebanon, is still missing. Knowledge on land use planning is still in its earliest stages in Lebanon. A lack of hazard-informed land use planning coupled to random land cover pattern evolution characterize the country. In response, this study focuses on the opportunities, challenges and uncertainties resulting from the integration of land use planning into efficie

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Haitham, Maram, Mustafa Tariq Mustafa, and Alhassan H. Ismail. "Accuracy Assessment of Land Use/Land Cover Indices for Al-Rusafa in Baghdad Governorate by Remote Sensing Technology and GIS." IOP Conference Series: Earth and Environmental Science 1300, no. 1 (2024): 012009. http://dx.doi.org/10.1088/1755-1315/1300/1/012009.

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Abstract The management and planning of natural and artificial resources depend on accurately monitoring land cover changes. Land cover change mapping and monitoring used to require expensive field surveys. Remote sensing is cheaper and more practical for mapping land use and cover changes. The Tigris River divides the Iraqi capital, Baghdad, into two parts: Karkh and Rusafa. Al-Rusafa was selected as a study area for current research, which has had rapid population and urban growth in recent decades. The current research applies the support vector machine technique to supervised LU/LC maps’ c

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Leinenkugel, Patrick, Ramona Deck, Juliane Huth, Marco Ottinger, and Benjamin Mack. "The Potential of Open Geodata for Automated Large-Scale Land Use and Land Cover Classification." Remote Sensing 11, no. 19 (2019): 2249. http://dx.doi.org/10.3390/rs11192249.

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This study examines the potential of open geodata sets and multitemporal Landsat satellite data as the basis for the automated generation of land use and land cover (LU/LC) information at large scales. In total, six openly available pan-European geodata sets, i.e., CORINE, Natura 2000, Riparian Zones, Urban Atlas, OpenStreetMap, and LUCAS in combination with about 1500 Landsat-7/8 scenes were used to generate land use and land cover information for three large-scale focus regions in Europe using the TimeTools processing framework. This fully automated preprocessing chain integrates data acquis

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Vinayan, Midhuna, B. Gurugnanam, and S. Bairavi. "Land use/Land cover Change Detection Study in Vythiri Taluk, Wayanad District, Kerala using Geospatial Technology." Disaster Advances 15, no. 4 (2022): 26–33. http://dx.doi.org/10.25303/1504da026033.

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Mapping and monitoring the land use/land cover (LU/LC) changes in the Vythiri taluk of Wayanad district are essential for sustainable improvement and management. Remote sensing and GIS technology are used to track the changes in land use/ land cover of Vythiri taluk of Wayanad district for the year 2015–2021. Images from Landsat-8 data were used to generate LU/LC maps. The maximum likelihood supervised classification approach was used to produce the signature class of the important land use/ land cover category. Six major land use/ land cover classes were noticed viz. agricultural land, barren

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M.R. Goutham, Suneel Kumar Duvvuri, Srinivasa Rao Narra, and Uma Mahesh Goudu. "Comparative Study on Various Supervised Learning Algorithms for Land Use and Land Cover Classification in Part of East Godavari District, Andhra Pradesh, India." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 4 (2025): 84–93. https://doi.org/10.32628/cseit2511148.

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Accurate Land Use and Land Cover (LU/LC) classification is essential for sustainable resource management, urban development, and environmental conservation. The integration of remote sensing data with supervised machine learning algorithms has significantly enhanced classification accuracy and efficiency. This study evaluates the performance of five widely used supervised learning algorithms namely 1) Classification and Regression Tree (CART), 2) Gradient Boost Tree (GB), 3) K-Nearest Neighbours (KNN), 4) Support Vector Machine (SVM) and 5) Random Forest (RF) for LU/LC mapping in study area of

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Rahaman, S. A., S. Aruchamy, K. Balasubramani, and R. Jegankumar. "LAND USE/LAND COVER CHANGES IN SEMI-ARID MOUNTAIN LANDSCAPE IN SOUTHERN INDIA: A GEOINFORMATICS BASED MARKOV CHAIN APPROACH." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 231–37. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-231-2017.

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Nowadays land use/ land cover in mountain landscape is in critical condition; it leads to high risky and uncertain environments. These areas are facing multiple stresses including degradation of land resources; vagaries of climate and depletion of water resources continuously affect land use practices and livelihoods. To understand the Land use/Land cover (Lu/Lc) changes in a semi-arid mountain landscape, Kallar watershed of Bhavani basin, in southern India has been chosen. Most of the hilly part in the study area covers with forest, plantation, orchards and vegetables and which are highly aff

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Falťan, Vladimír, František Petrovič, Ján Oťaheľ, et al. "Comparison of CORINE Land Cover Data with National Statistics and the Possibility to Record This Data on a Local Scale—Case Studies from Slovakia." Remote Sensing 12, no. 15 (2020): 2484. http://dx.doi.org/10.3390/rs12152484.

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Monitoring of land cover (LC) provides important information of actual land use (LU) and landscape dynamics. LC research results depend on the size of the area, purpose and applied methodology. CORINE Land Cover (CLC) data is one of the most important sources of LU data from a European perspective. Our research compares official CLC data (third hierarchical level of nomenclature at a scale of 1:100,000) and national statistics (NS) of LU in Slovakia between 2000 and 2018 at national, county, and local levels. The most significant differences occurred in arable land and permanent grassland, whi

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Marić, Ivan, and Luka Smajo. "Spatio-Temporal Landuse/Landcover (LU/LC) Changes of Significant Landscape „Barćeve Špilje“." Geodetski glasnik, no. 54 (December 31, 2023): 5–31. http://dx.doi.org/10.58817/2233-1786.2023.57.54.5.

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Changes in the land use/land cover (LU/LC) model caused by different anthropogenic and natural factors are an important object of numerous scientific research. In this paper, an analysis of the spatio-temporal changes (LUCCs) for the area of Significant landscape (SL) of the „Baraćeve špilje“ in the period from 1960 to 2021 was performed. Using aerial photographs and a hybrid classification method, LU/LC models and spatio-temporal changes (STCs) analysis were performed. The research showed that the abandonment of agriculture and the slow disappearance of anthropogenic influence led to the disa

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Getaneh, Zeleke Assefa, Sebsebe Demissew, and Zerihun Woldu. "Spatiotemporal dynamics of land use land cover change and its drivers in the western part of Lake Abaya, Ethiopia." PeerJ 12 (September 18, 2024): e17892. http://dx.doi.org/10.7717/peerj.17892.

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Understanding the dynamics of land use/land cover (LU/LC) changes and what drives these changes is essential for creating effective strategies for sustainable land management. It also helps to monitor the impact on ecosystems and biodiversity, which is crucial for policy-making. This study focused on assessing the trends, rates, and extent of LU/LC change and its causes in the western part of Lake Abaya in Ethiopia. To achieve this, we used a supervised classification method with a maximum-likelihood algorithm to map different land use land cover types. Additionally, we gathered information th

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