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Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes

Bibliographic Data

ID8019397
AuthorsDébora J Dutra (0000-0003-3748-5622), Marcos A T Elmiro (0000-0001-7680-3131, Universidade Federal de Minas Gerais), Carlos Wagner Gonçalves Andrade Coelho (0000-0002-8166-8082, Federal Center for Technological Education of Minas Gerais), Marcelo Antonio Nero (0000-0003-2124-5018, Universidade Federal de Minas Gerais), Plinio Da Costa Temba (0000-0002-4673-2915, Universidade Federal de Minas Gerais)
Year2021
Volume33
Publication date2021-06-10
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSociedade & natureza (JOURNAL)
Journal identifiersISSN: 0103-1570 • E-ISSN: 1982-4513
PublisherEDUFU (PUBLISHER • BR)
DOI10.14393/sn-v33-2021-59505
OpenAlexW3186436873
LanguageEN
References cited2

The development of several time series analysis programs using satellite images has provided many applications based on resources from geostatistics field. Currently, the use of statistical tests applied to vegetation indexes has enabled the analysis of different natural phenomena, such as drought events in watershed areas. The objective of this article is to provide a comparative analysis between NDVI and EVI vegetation index data made available by MOD13Q1 project of MODIS sensor for drought mapping using vegetation condition index (VCI) in the Serra Azul stream sub-basin, MG. The methodology adopted the Cox-Stuart statistical test for seasonality analysis and Pearson's linear correlation to verify the influence of different indexes on delimitation of drought in a watershed. The results indicated the NDVI vegetation index as more efficient than EVI in spatial characterization of studied watershed region, mainly in identification of seasonality. The VCI proved to be highly feasible for monitoring drought in study period between 2013 and 2018, allowing the effective delimitation of drought conditions in the Serra Azul stream sub-basin. In addition, the effectiveness of MODIS sensor data in characterizing drought events that affected the study area was proven

Climate change · Enhanced vegetation index · Geography · Geostatistics · Hydrology (agriculture · Normalized Difference Vegetation Index · Physical geography · Remote sensing · Seasonality · Spatial variability · Statistics · Vegetation (pathology · Vegetation Index · Watershed · Computer Science · Environmental and biological studies · Environmental Science · Geology · Leaf Properties and Growth Measurement · Mathematics · Remote Sensing in Agriculture

  • Overview of the radiometric and biophysical performance of the Modis vegetation indices

    Open Access•Alfredo Huete, Kamel Didan et al.•Remote Sensing of Environment•2002

  • Comparative analysis of methods applied in vegetation cover delimitation using Landsat 8 images

    Open Access•Débora J Dutra, Marcos A T Elmiro et al.•Sociedade & natureza•2020

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