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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

Land use/land cover in view of earth observation: data sources, input dimensions, and classifiers—a review of the state of the art

TL;DR: Land use/land cover (LULC) is a fundamental concept of the Earth's system intimately connected to many phases of the human and physical environment as mentioned in this paper, and Earth observation (EO) technology provides an in...
Journal ArticleDOI

Spatial distribution of mangrove forest species and biomass assessment using field inventory and earth observation hyperspectral data

TL;DR: In this article, the authors used spectral angle mapper to identify species, provide spatial distribution of the species and estimate the biomass in the mangrove forest, Bhitarkanika India.
Journal ArticleDOI

Prediction of spatial soil organic carbon distribution using Sentinel-2A and field inventory data in Sariska Tiger Reserve

TL;DR: In this paper, the authors assessed distribution of soil organic carbon (SOC) using field and satellite data in Sariska Tiger Reserve located in the Aravalli Hill Range, India.
Journal ArticleDOI

The refined spatiotemporal representation of soil organic matter based on remote images fusion of Sentinel-2 and Sentinel-3

TL;DR: The spatiotemporal dynamics of SOM highlighted the necessity of modeling with fused remote sensing images, and more effective modeling could be expected with the continued increase in SOM in future.
Journal ArticleDOI

Synergetic use of in situ and hyperspectral data for mapping species diversity and above ground biomass in Shoolpaneshwar Wildlife Sanctuary, Gujarat

TL;DR: In this paper, the authors used quadrat sampling in Shoolpaneshwar Wildlife Sanctuary (SWS), Gujarat, which was used to compute Shannon-Weiner Diversity Index (H′), above ground biomass (AGB) was calculated measuring the Height and Diameter at Breast Height (DBH) of different trees in the sampling plots.
References
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Settlement Risk Zone Recognition Using High Resolution Satellite Data in Jharia Coal Field, Dhanbad, India

TL;DR: Kumar et al. as mentioned in this paper showed the settlement risk zone recognition using high-resolution satellite data in Jharia coal field, Dhanbad, India, which is the most exploited coal field because of available metallurgical grade coal reserves.
Journal ArticleDOI

Digital analysis techniques for forestry applications

TL;DR: A wide variety of computer processing procedures have been developed to utilize this satellite multispectral scanner (MSS) data in various disciplines, including forestry as mentioned in this paper, and many studies have evaluated these data analysis systems and techniques in order to determine their utility for forestry applications.
Proceedings ArticleDOI

A review of remote sensing methods for biodiversity assessment and bioindicator extraction

TL;DR: In this paper, the authors review several recent methods based on remote sensing observations, derived either from satellite or airborne sensors, in an effort to approach biodiversity assessment from different perspectives, ranging from ecosystem fragmentation and habitat mapping to monitoring of species distribution and invasion of alien species.
Proceedings ArticleDOI

How to Better Protect Biodiversity in Land Management

TL;DR: In this article, the combination between biodiversity protection and land use is explored, with the introduction of engineering measures, political measures and other measures in biodiversity protection respectively, and some further improvements.
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