Geomorphological Changes in Sundarbans Delta Using GIS and Remote Sensing Data

2019 ◽  
pp. 40-53
Author(s):  
Krishan Kundu ◽  
Prasun Halder
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Gis And Remote Sensing ◽  
Sensing Data ◽  
Geomorphological Changes

Estimating potential soil sheet Erosion in a Brazilian semiarid county using USLE, GIS, and remote sensing data

2019 ◽  
Vol 192 (1) ◽  
Author(s):  
Cassiano José Lages Marinho Falcão ◽  
Simone Mirtes de Araújo Duarte ◽  
Aline da Silva Veloso
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Gis And Remote Sensing ◽  
Sensing Data ◽  
Brazilian Semiarid ◽  
Sheet Erosion

GIS and remote sensing data integration

1987 ◽  
Vol 2 (3) ◽  
pp. 67-73 ◽  
Author(s):  
Peter D. Archibald
Keyword(s):  
Remote Sensing ◽  
Data Integration ◽  
Remote Sensing Data ◽  
Gis And Remote Sensing ◽  
Sensing Data

scholarly journals Exploring the Relationship between LST, LULC and NDVI in Saïss Plain using Geospatial Techniques

2021 ◽  
Vol 314 ◽  
pp. 04001
Author(s):  
Manal El Garouani ◽  
Mhamed Amyay ◽  
Abderrahim Lahrach ◽  
Hassane Jarar Oulidi
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Arable Land ◽  
Remote Sensing Data ◽  
Landsat Images ◽  
Gis And Remote Sensing ◽  
Sensing Data

Land use/land cover (LULC) change has been confirmed that have a significant impact on climate through various pathways that modulate land surface temperature (LST) and precipitation. However, there are no studies illustrated this link in the Saïss plain using remote sensing data. Thus, the aim of this study is to monitor the LST relationship between LULC and vegetation index change in the Saïss plain using GIS and Remote Sensing Data. We used 18 Landsat images to study the annual and interannual variation of LST with LULC (1988, 1999, 2009 and 2019). To highlight the effect of biomass on LST distribution, the Normalized Difference Vegetation Index (NDVI) was calculated, which is a very good indicator of biomass. The mapping results showed an increase in the arboriculture and urbanized areas to detriment of arable lands and rangelands. Based on statistical analyzes, the LST varies during the phases of plant growth in all seasons and that it is diversified due to the positional influence of LULC type. The variation of land surface temperature with NDVI shows a negative correlation. This explains the increase in the surface temperature in rangelands and arable land while it decreases in irrigated crops and arboriculture.

Biotope Patterns, Phytodiversity and Forestline in the Andes, based on GIS and Remote Sensing Data

2019 ◽  
pp. 75-89
Author(s):  
Gerald Braun ◽  
Jens Mutke ◽  
Andreas Reder ◽  
Wilhelm Barthlott
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Gis And Remote Sensing ◽  
Sensing Data ◽  
The Andes
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