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Hitendra Padalia

Researcher at Indian Institute of Remote Sensing

Publications -  59
Citations -  1283

Hitendra Padalia is an academic researcher from Indian Institute of Remote Sensing. The author has contributed to research in topics: Biodiversity & Vegetation. The author has an hindex of 14, co-authored 50 publications receiving 832 citations. Previous affiliations of Hitendra Padalia include National Remote Sensing Centre & Indian Space Research Organisation.

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Development of Decadal (1985–1995–2005) Land Use and Land Cover Database for India

TL;DR: The present study utilizes the satellite images to generate national level LULC maps at decadal intervals for 1985, 1995 and 2005 using onscreen visual interpretation techniques with minimum mapping unit of 2.5 hectares to conclude that this dataset has captured the maximum cumulative patch diversity frequency, indicating the detailed representation that can be attributed to the on- screen visual interpretation technique.
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Modeling potential invasion range of alien invasive species, Hyptis suaveolens (L.) Poit. in India: Comparison of MaxEnt and GARP

TL;DR: This study model the potential invasion range of bushmint in India and investigates prediction capabilities of two popular species distribution models (SDM) viz., MaxEnt (Maximum Entropy) and GARP (Genetic Algorithm for Rule-Set Production).
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New vegetation type map of India prepared using satellite remote sensing: Comparison with global vegetation maps and utilities

Partha Sarathi Roy, +99 more
TL;DR: This vegetation type map is the most comprehensive one developed for India so far and was prepared using 23.5 m seasonal satellite remote sensing data, field samples and information relating to the biogeography, climate and soil.
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Phytosociological observations on tree species diversity of Andaman Islands, India

TL;DR: Sustainability of forest biodiversity is critical for the exi stence of tribal races and overall environmental conditions in these Andaman Islands archipelago, in the face of increasing immigrant population and deve lopmental pressure.
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Forest tree species discrimination in western Himalaya using EO-1 Hyperion

TL;DR: The potential utility of narrow spectral bands of Hyperion data in discriminating tree species in a hilly terrain is demonstrated and classification accuracy achieved with Hyperion bands was significantly higher than Landsat TM bands.