Green Cover Assessment of Delhi National Capital Territory of India

This study conducts a comprehensive assessment of the green cover in the Delhi National Capital Territory (NCT) of India through advanced remote sensing techniques, utilizing the Normalized Difference Vegetation Index (NDVI) derived from high-resolution Sentinel-2 satellite imagery. The methodology involved the preprocessing of multispectral satellite data to accurately compute NDVI values, enabling detailed mapping and quantification of vegetation density across the region. To ensure the robustness of the analysis, the NDVI-derived vegetation metrics were cross-validated against data from the India State of Forest Report 2021 (ISFR), an authoritative source provided by a Government of India agency. The temporal analysis revealed a significant increase in green cover from 2019 to 2022, followed by a marginal decline in subsequent years, highlighting the dynamic nature of urban green spaces. The integration of remote sensing technology and geospatial analysis in this research underscores the potential of quantitative methods in environmental monitoring, offering critical insights into urban ecosystem management and policy formulation.

Authors

Institutions

Publication Details

Published
2024-10-04
DOI
https://doi.org/10.1109/mac61551.2024.10837040
Citations
1
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
0.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Green Cover Assessment of Delhi National Capital Territory of India

Prakash Singh, Ravi Kumar Arya, Pranav Raj
1 citations
Remote Sensing in Agriculture
0.46
article

Green Cover Assessment of Delhi National Capital Territory of India

Prakash Singh, Ravi Kumar Arya, Pranav Raj
article en
1 citations

Abstract

This study conducts a comprehensive assessment of the green cover in the Delhi National Capital Territory (NCT) of India through advanced remote sensing techniques, utilizing the Normalized Difference Vegetation Index (NDVI) derived from high-resolution Sentinel-2 satellite imagery. The methodology involved the preprocessing of multispectral satellite data to accurately compute NDVI values, enabling detailed mapping and quantification of vegetation density across the region. To ensure the robustness of the analysis, the NDVI-derived vegetation metrics were cross-validated against data from the India State of Forest Report 2021 (ISFR), an authoritative source provided by a Government of India agency. The temporal analysis revealed a significant increase in green cover from 2019 to 2022, followed by a marginal decline in subsequent years, highlighting the dynamic nature of urban green spaces. The integration of remote sensing technology and geospatial analysis in this research underscores the potential of quantitative methods in environmental monitoring, offering critical insights into urban ecosystem management and policy formulation.

Changchun University of Science and Technology (CN), Zhongshan Hospital (CN), National Institute of Technology Delhi (IN)
Openalex Percentile: Top 27%
Remote Sensing in Agriculture
0.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.