AgResearch
Browse
- No file added yet -

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

Download (14.48 MB)
journal contribution
posted on 2023-07-09, 23:55 authored by Thuong Tran, David Bruce, Cho-Ying Huang, Duy TranDuy Tran, Soe W. Myint, Duy B. Nguyen

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 < 0.005). The analysis revealed an increase in drought risk in some provinces of the Central Highlands including Gia Lai, Kon Tum, and Dak Lak. It was also found that changes in LULC patterns could minimize (reforestation) or exacerbate (deforestation) the impacts of drought. Our study suggests that applying a multivariate drought index enables a better understanding of drought patterns at the local scale. This provides valuable information for the development of appropriate land and environmental management practices that can affect and mitigate climate change effects.

History

Rights statement

© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Publication date

2023-01-03

Project number

  • Non revenue

Language

  • English

Does this contain Māori information or data?

  • No

Publisher

Taylor & Francis Group

Journal title

GIScience & Remote Sensing

ISSN

1548-1603

Volume/issue number

60(1)

Page numbers

2163070