Decadal assessment of agricultural drought in the context of land use land cover change using MODIS multivariate spectral index time-series data

Autor: Thuong V. Tran, David Bruce, Cho-Ying Huang, Duy X. Tran, Soe W. Myint, Duy B. Nguyen
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: GIScience & Remote Sensing, Vol 60, Iss 1 (2023)
Druh dokumentu: article
ISSN: 1548-1603
1943-7226
15481603
DOI: 10.1080/15481603.2022.2163070
Popis: Using a multivariate drought index that incorporates important environmental variables and is suitable for a specific geographical region is essential to fully understanding the pattern and impacts of drought severity. This study applied feature scaling algorithms to MODIS time-series imagery to develop an integrated Multivariate Drought Index (iMDI). The iMDI incorporates the vegetation condition index (VCI), the temperature condition index (TCI), and the evaporative stress index (ESI). The 54,474 km2 Vietnamese Central Highlands region, which has been significantly affected by drought severity for several decades, was selected as a test site to assess the feasibility of the iMDI. Spearman correlation between the iMDI and other commonly used spectral drought indices (i.e. the Drought Severity Index (DSI–12) and the annual Vegetation Health Index (VHI–12)) and ground-based drought indices (i.e. the Standardized Precipitation Index (SPI–12) and the Reconnaissance Drought Index (RDI–12)) was employed to evaluate performance of the proposed drought index. Pixel-based linear regression together with clustering models of the iMDI time-series was applied to characterize the spatiotemporal pattern of drought from 2001 to 2020. In addition, a persistent area of LULC types (i.e. forests, croplands, and shrubland) during the 2001–2020 period was used to understand drought variation in relation to LULC. Results suggested that the iMDI outperformed the other spectral drought indices (r > 0.6; p
Databáze: Directory of Open Access Journals
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