Remotely Sensed Data and Vegetation Coverage Change Detection - Shobairi, Seyed Omid Reza
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Since the normalized difference vegetation index (NDVI) as a graphical indicator that it was used to analyze remote sensing measurements, and it assessed whether the target being observed contains live green vegetation or not; we enabled to employ the long-term MODIS NDVI image datasets, acquired from 2000 to 2010 to monitor vegetation coverage change in a particular area in Southeast Asia. Even though, improvements in data sharing through the night-time lights datasets, and other elements likewise DEM, climatic and physiography factors helped us to be scientifically ruched mentioned plan,…mehr

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Produktbeschreibung
Since the normalized difference vegetation index (NDVI) as a graphical indicator that it was used to analyze remote sensing measurements, and it assessed whether the target being observed contains live green vegetation or not; we enabled to employ the long-term MODIS NDVI image datasets, acquired from 2000 to 2010 to monitor vegetation coverage change in a particular area in Southeast Asia. Even though, improvements in data sharing through the night-time lights datasets, and other elements likewise DEM, climatic and physiography factors helped us to be scientifically ruched mentioned plan, Although our view of them is more closer to driving factors of vegetation cover dynamic.
Autorenporträt
Seyed Omid Reza Shobairi, born on July 19th, 1986, bachelor and Master of Science in Natural Resource and Forestry, Doctor of Forest Resources Modelling in GIS and Remote Sensing from NJFU; elected as the elite researcher due to high published manuscripts indexed in Scopus. He is the Assistant Professor in Forest Ecology at USFEU, Yekaterinburg.