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Madhura Niphadkar

Researcher at Manipal University

Publications -  13
Citations -  435

Madhura Niphadkar is an academic researcher from Manipal University. The author has contributed to research in topics: Moderate-resolution imaging spectroradiometer & Chaparral. The author has an hindex of 9, co-authored 12 publications receiving 350 citations. Previous affiliations of Madhura Niphadkar include San Diego State University.

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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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MODIS‐derived visible atmospherically resistant index for monitoring chaparral moisture content

TL;DR: In this paper, the authors compared the visible atmospherically resistant index (VARI) and normalized difference water index (NDWI) for monitoring live fuel moisture content (FMC) of chaparral shrublands.
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Remote sensing of invasive plants: incorporating functional traits into the picture

TL;DR: This review summarizes research utilizing plant functional traits in RS mapping of invasive species from the years 2000 to 2014 and summarizes plant traits that can be related to spatial and spectral properties, and used to discriminate invasive alien plants from native vegetation.
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Satellite Earth observation data to identify anthropogenic pressures in selected protected areas

TL;DR: This paper builds on the DPSIR framework, providing a terminology to relate the concepts of state, pressures, and drivers with the application of EO analysis, and provides detailed examples for two protected areas, demonstrating the use ofEO data for detection of land cover/habitat change, coupled with expert interpretation to relate such change to specific anthropogenic pressures.
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Comparing Pixel and Object-Based Approaches to Map an Understorey Invasive Shrub in Tropical Mixed Forests.

TL;DR: Improved ability of the object-based approach to delineate structurally distinct objects with characteristic spectral and spatial characteristics of their own, as well as with reference to their surroundings, allows for much flexibility in identifying invasive understorey shrubs among the complex vegetation of the tropical forest than that provided by the parametric classifier.