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Journal ArticleDOI

Efficient Recognition of Forest Species Biodiversity by Inventory-Based Geospatial Approach Using LISS IV Sensor

TLDR
In this paper, the authors used field-based surveys along with remote sensing technologies using a regression model to estimate and recognize different species diversity in Sariska Tiger Reserve, where a positive correlation was found in the infrared band even negative correlation has been found in other bands.
Abstract
Tropical forest is one of the great biodiversity repositories of the world ecosystem. Biodiversity is depleting very fast due to conversion of forest region into agricultural or other land use. Here comes the role of biodiversity assessment and evaluation of spatial data of species to prioritize the conservation purposes. Traditionally, ground-based plots were used to assess different biodiversity. Later on, remote sensing approaches were also incorporated along with field-based studies to quantify the results accurately. Assessment of biodiversity constitutes estimation of various indices that were obtained using ground-based plot or survey. With the advancement of the remote sensing technology, spatial information about tree species was collected using field sample and satellite data and field sample plots within the Sariska Tiger Reserve. Different diversity indices were calculated like α, β, diversity, and others, i.e., Pilot's index (J), Shannon-Wiener index (SR), Margalef index (E w ), and Whittaker's index (H'). The multistage statistical techniques, which integrate high spatial resolution and spectral characteristics of satellite data (LISS IV), will help in providing precise information about tree species. Regression analysis provides better results to identify forest species among different bands. A positive correlation has been found in the infrared band even negative correlation has been found in other bands. This paper incorporates field-based surveys along with remote sensing technologies using a regression model (r 2 = 0.636) to estimate and recognize different species diversity in Sariska Tiger Reserve.

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Citations
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Journal ArticleDOI

Optimal band characterization in reformation of hyperspectral indices for species diversity estimation

TL;DR: In this paper , the authors provided modified hyperspectral indices through detection of optimum bands for estimating species diversity within Shoolpaneshwar Wildlife Sanctuary (SWS) in India.
Proceedings ArticleDOI

Understanding the dynamics of Gautala Autramghat forest: A digital image classification approach

TL;DR: This study highlights the potential of LISSIII sensor temporal data of the year 2003 and 2015 for monitoring the precious natural resource Gautala Autramghat Wildlife Sanctuary.
Book ChapterDOI

Assessment of Forest Species Diversity in Sariska Tiger Reserve, Rajasthan, India

TL;DR: In this article, the authors made an attempt to assess tree species diversity in Sariska Tiger Reserve (STR), Rajasthan, India, using Sentinel-2A data.
Journal ArticleDOI

Responses of Vegetation and Soil to Artificial Restoration Measures in Abandoned Gold Mining Areas in Altai Mountain, Northwest China

TL;DR: Zhang et al. as discussed by the authors proposed a field observation to evaluate the short-term efforts of the artificial restoration measures taken by the Two-River Source Nature Reserve Administration from 2010 to 2015 in an abandoned gold mining area in Altai Mountain, Northwest China.
References
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Book

Ecological Diversity and its Measurement

TL;DR: In this paper, the authors define definitions of diversity and apply them to the problem of measuring species diversity, choosing an index and interpreting diversity measures, and applying them to structural and structural diversity.
Journal ArticleDOI

An Ordination of the Upland Forest Communities of Southern Wisconsin

TL;DR: It is shown that nature of unit variation is a naajor problenl in systematies, and that whether this variation is diserete, continuous, or in some other form, there is a need for appliGation of (uantitative and statistical methods.
Journal ArticleDOI

Evolution and measurement of species diversity

Robert H. Whittaker
- 01 May 1972 - 
Journal ArticleDOI

Global land cover mapping from MODIS: algorithms and early results

TL;DR: This product provides maps of global land cover at 1-km spatial resolution using several classification systems, principally that of the IGBP, and a supervised classification methodology is used that exploits a global database of training sites interpreted from high-resolution imagery in association with ancillary data.
Journal ArticleDOI

Global land cover classification at 1 km spatial resolution using a classification tree approach

TL;DR: In this paper, a 1km spatial resolution land cover classification using data for 1992-1993 from the Advanced Very High Resolution Radiometer (AVHRR) is presented. But the approach taken involved a hierarchy of pair-wise class trees where a logic based on vegetation form was applied until all classes were depicted.
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