COMPARISON OF MULTISERVICE REMOTE SENSING DATA FOR VEGETATION INDEX ANALYSIS

With advancements in satellite sensors, multi-source observation systems have become widely utilized. However, significant disparities exist among quantitative remote sensing products due to variations in observational methods and retrieval algorithms. This study investigates the quantitative relationships between the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and a vegetation index derived using the universal decomposition method for data from Landsat 2+ and Landsat 3 sensors

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-25
DOI
https://doi.org/10.5281/zenodo.14555003
Primary Topic
Remote Sensing in Agriculture
Type
article
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article

COMPARISON OF MULTISERVICE REMOTE SENSING DATA FOR VEGETATION INDEX ANALYSIS

Zenodo (CERN European Organization for Nuclear Research)
Remote Sensing in Agriculture
article

COMPARISON OF MULTISERVICE REMOTE SENSING DATA FOR VEGETATION INDEX ANALYSIS

article en

Abstract

With advancements in satellite sensors, multi-source observation systems have become widely utilized. However, significant disparities exist among quantitative remote sensing products due to variations in observational methods and retrieval algorithms. This study investigates the quantitative relationships between the Normalized Difference Vegetation Index (NDVI), Soil-Adjusted Vegetation Index (SAVI), and a vegetation index derived using the universal decomposition method for data from Landsat 2+ and Landsat 3 sensors

Zenodo (CERN European Organization for Nuclear Research)
Tashkent University of Information Technology (UZ)
Life in Land
Openalex Percentile: Top 55%
Remote Sensing in Agriculture
DOIOpen Access PDFOpenAlex
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COMPARISON OF MULTISERVICE REMOTE SENSING DATA FOR VEGETATION INDEX ANALYSIS · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS