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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

Forest biomass estimation using remote sensing and field inventory: a case study of Tripura, India

TL;DR: The results indicate that the methodology adopted in this study can help in selecting best fit model for analyzing relationship between AGB and NDVI/LAI and for estimating biomass using allometric equation at various spatial scales.
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Biodiversity Assessment Based On Artificial Intelligence And Neural Network Algorithms

TL;DR: It is argued that the implementation of biodiversity assessments will lead to high-quality models and inferences used in the final assessment, and the expansion of Artificial Intelligence and Neural Network Algorithms standards and guidelines encourages a wider community to participate in ongoing improvement.
Journal ArticleDOI

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

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

Estimating soil organic and aboveground woody carbon stock in a protected dry Miombo ecosystem, Zimbabwe: Landsat 8 OLI data applications

TL;DR: In this paper, the relationship between aboveground woody carbon pool and the soil carbon pool, using both ground-based and remote sensing methods, was modeled using both correlation and regression analysis.
Journal ArticleDOI

Calculating forest species diversity with information-theory based indices using sentinel-2A sensor’s of Mahavir Swami Wildlife Sanctuary

TL;DR: In this paper , the authors made an attempt to identify the concentration of species among tree diversity in Mahavir Swami Wildlife Sanctuary, Bundelkhand, India and found that Shannon-Weiner diversity index (H/) was the best index for assessing species richness while Simpson's diversity (D) index was more suited for determining species diversity.
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.
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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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