Modeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques

2013 ◽  
Vol 28 (7) ◽  
pp. 632-656 ◽  
Author(s):  
M. Surabuddin Mondal ◽  
Nayan Sharma ◽  
Martin Kappas ◽  
P.K. Garg
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Temporal Dynamics ◽  
Brahmaputra River ◽  
Spatio Temporal

scholarly journals Contribution à l’étude de la vulnérabilité des terres de cultures de la région de Thiès (Sénégal) à l’aide de la télédétection et des systèmes d’information géographique (SIG)

2019 ◽  
pp. 6731-6746 ◽  
Author(s):  
Amadou SALL ◽  
Assize TOURE ◽  
Alioune KANE ◽  
Awa Niang Fall
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Temporal Dynamics ◽  
Remote Sensing And Gis ◽  
Cultivated Land ◽  
Landsat Images ◽  
Systèmes D’Information Géographique ◽  
Spatio Temporal ◽  
Systèmes D’Information

L’objectif de cette étude est d’établir à partir de la télédétection et des SIG, la dynamique spatio-temporelle des terres de cultures et d’explorer les futurs possibles de l’occupation du sol dans trois communes rurales de la région de Thiès (Fandène, Notto Diobass et Taiba Ndiaye). Une classification multidate des images landsat (1988, 2002 et 2014) a permis de quantifier les changements d’occupation des terres. Les résultats montrent que les zones de culture de Fandène sont passées entre 1988 et 2014 de 62% à 52% de la superficie totale de la commune. A l’opposée la commune de Taiba Ndiaye connait une expansion des zones de culture entre ces deux dates. Les changements enregistrés à Notto sont négligeables. Les simulations, faites sur la base des probabilités pour que la valeur d’une cellule i reste inchangée ou prenne la valeur d’une autre cellule j à l’horizon 2035, révèlent que les terres de culture de Fandène ont 69% de probabilité d’évoluer vers d’autres classes d’occupation du sol. ABSTRACT The objective of this study is to quantify from remote sensing and GIS the spatio temporal dynamics of cultivated land and explore possible futures of land use in three rural municipalities of Thies (Fandene, Notto Diobass, and Taiba Ndiaye). A multidate classification Landsat images (1988, 2002 et 2014) was used to quantify change in land cover. The results show that between 1988 and 2014 Fandene cropping areas have passed from 62% to 52% of the total area. At the opposite the commune of Taiba Ndiaye has known an expansion of cropping areas between these two dates. Minor changes are noted in Notto district. Simulations carried out on the basis of probabilities for a unit i to stay in the same cell or to be converted to another unit j in 2035, reveals that the probability for a cultivated land unit to be transformed into a another land cover category is high in Fandene (69 %).

scholarly journals Monitoring Land Use/Land Cover Changes in a River Basin due to Urbanization using Remote Sensing and GIS Approach

2014 ◽  
Vol XL-8 ◽  
pp. 949-953
Author(s):  
S. Shukla ◽  
M. V. Khire ◽  
S. S. Gedam
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Remote Sensing And Gis ◽  
Land Use Land Cover ◽  
Agricultural Lands ◽  
Sensing Technology ◽  
Liss Iii ◽  
Spatio Temporal

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 urbanization using modern geospatial techniques such as remote sensing and GIS. In this study, the Upper Bhima river basin is divided into three adjacent sub-basins: Mula-Mutha sub-basin (ubanized), Bhima sub-basin (semi-urbanized) and Ghod sub-basin (unurbanized). Time series LU/LC maps were prepared for the study area for a period of 1980, 2002 and 2009 using satellite datasets viz. Landsat MSS (October, 1980), Landsat ETM+ (October, 2002) and IRS LISS III (October 2008 and November 2009). All the satellite images were classified into five LU/LC classes viz. built-up lands, agricultural lands, waterbodies, forests and wastelands using supervised classification approach. Post classification change detection method was used to understand the LU/LC changes in the study area. Results reveal that built up lands, waterbodies and agricultural lands are increasing in all the three sub-basins of the study area at the cost of decreasing forests and wastelands. But the change is more drastic in urbanized Mula-Mutha sub-basin compared to the other two sub-basins.

scholarly journals A Spatio-temporal Study of Land Use Land Cover Change Detection Using GIS and Remote Sensing Techniques

2021 ◽  
Vol 12 (1) ◽  
pp. 026-031
Author(s):  
Snehalata Chaware ◽  
◽  
Nitin Patil ◽  
Gajanan Satpute ◽  
M. R. Meshram ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Land Use Planning ◽  
Water Body ◽  
Temporal Dynamics ◽  
Kappa Coefficient ◽  
Population Pressure ◽  
Land Use Land Cover ◽  
Spatio Temporal

Land resources in India are under severe pressure and it is widely believed that marginal lands are being brought under cultivation. The extent of such changes needs to be known for better land use planning decisions. The present study illustrates the spatio-temporal dynamics of land use land cover of Nagjhari watershed in Bhatkuli block of Amravati, Maharashtra. Multi-temporal high resolution of Sentinel and Landsat satellite data were used to identify the significant positive and negative Land use land cover changes over a decade of 2007 to 2017. From 2007 to 2017, the ‘habitation’ class increased by 34% due to increasing population pressure. There was a decrease in ‘wasteland’ by 10.3%, while the area under ‘agriculture’ decreased by approximately 4.7% because of the increased area under ‘habitation’ and ‘water body’ at Nagjhari watershed. The biggest change occurred in land use class ‘water body’ increased sharply from 2013-17 by 62.7 per cent due to consequence of state policy of watershed development that was implemented after 2014. The forest class recorded maximum loss (18.3%) due to increasing population maximum land converted into habitation. The study shows overall classification accuracy as 85.46% and kappa coefficient (K) of 0.85. Kappa coefficient indicated that land use land cover assessment from remote sensing data show the best accuracy. These finding will help in deciding land use policy for future and its impact on land management of the watershed.

scholarly journals Land use/ Land cover Change Detection in Auranga River Basin, Jharkhand

2020 ◽  
Vol 66 (1) ◽  
pp. 51-58
Author(s):  
Chnadrakesh Maurya ◽  
◽  
V. N. Sharma ◽  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Supervised Classification ◽  
Land Resource ◽  
Land Use Land Cover ◽  
Ancillary Data ◽  
Classification Technique ◽  
Spatio Temporal ◽  
Cover Pattern

Land use is a man-made dynamic process in which human uses land resource to fulfil their various economic, social and cultural needs and at the same time it also provides a base for development. The proper management needed for sustainable development of land can improve the eco-system and its productivity in a particular geographical region. The present study focuses on spatio-temporal changes in land use and land cover pattern in Auranga river basin of Jharkhand using geospatial approach. Supervised classification technique was applied in this study to detect land use/ land cover changes. The main objective of the study is to analyse temporal change of land use/ land cover pattern during 1996, 2007 and 2018 using various dataset as well as other ancillary data. The result reveales both increase and decrease of the different land use/ land cover classes from 1996 to 2018.

Spatio-Temporal Change of Land Use and Land Cover in Chao River Basin Based on GIS

2013 ◽  
Vol 353-356 ◽  
pp. 3498-3501
Author(s):  
Zi Jun Li ◽  
Can Juan Gong
Keyword(s):  
Land Use ◽  
Land Cover ◽  
River Basin ◽  
Temporal Change ◽  
Arable Land ◽  
Water Source ◽  
Gis Technology ◽  
Spatio Temporal ◽  
Resources Conservation ◽  
Ecological Construction

Spatio-temporal change of land use and land cover from 1985 to 2005 in Chao River Basin, the important water source to Miyun Reservoir, was analyzed based on GIS technology. The results showed that woodland was the main land cover type in the basin, and then the arable land and grassland. During 1985-2005, the area of woodland increased, while the area of grassland greatly reduced. Changes of land use and land cover were more violent from 1985 to 1995 than that from 1995 to 2005. There were obvious regional differences in land use change in the basin. The conversion from grassland to woodland was the dominant process of LUCC in the basin, and this was relevant to the national ecological construction policies on water resources conservation.

scholarly journals Time Series Land Cover Mapping and Change Detection Analysis Using Geographic Information System and Remote Sensing, North and West of Africa

Proceedings ◽  
2019 ◽  
Vol 39 (1) ◽  
pp. 3
Author(s):  
Malak Henchiri ◽  
Wilson Kalisa ◽  
Zhang Sha ◽  
Jiahua Zhang
Keyword(s):  
Land Use ◽  
Time Series ◽  
Land Cover ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Temporal Dynamics ◽  
Land Resources ◽  
Detection Analysis ◽  
Spatio Temporal ◽  
Very High

Land use planners require a time series land resources information and changing pattern for future management. Therefore, it is essential to assess changes in land cover. This study was to quantify the spatio-temporal dynamics of land use change over North and West Africa between 1985 and 2015 using the Normalized Difference Vegetation Index (NDVI) from the Very High Resolution Radiometer (AVHRR). The total investigated area was determined by 17,328,557.16 km2. The class of Urban and Built-up, Barren or sparsely vegetated, Savannas and Deciduous Broadleaf Forests increases considerably during the last three decades. In contrast, the class of Open Shrublands, Woody Savannas and water decrease notably during the three decades. The class of croplands decreases from 1985 to 1995 and increased from 1995 to 2015. The class of grasslands recorded a first increase from 1985 to 1995, and then decreased from 1995 to 2015. The class of permanent wetlands first decrease from 1985 to 1995, then increase from 1995 to 2005, followed by a decreasing trend during the last decade. The class of evergreen broadleaf forests decreased in the first two decades, from 1985 to 2005, and increased over the last decade.

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