Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia
Agriculture accounts for 29% of the Gross Domestic Product of the Nusa Tenggara Islands (NTIs). However, recurring agricultural droughts pose a major threat to the sustainability of agriculture in this region. The interplay between precipitation, solar radiation, and surface temperature as meteorolo...
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MDPI AG
2025-07-01
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| author | Gede Dedy Krisnawan Yi-Ling Chang Fuan Tsai Kuo-Hsin Tseng Tang-Huang Lin |
| author_facet | Gede Dedy Krisnawan Yi-Ling Chang Fuan Tsai Kuo-Hsin Tseng Tang-Huang Lin |
| author_sort | Gede Dedy Krisnawan |
| collection | DOAJ |
| description | Agriculture accounts for 29% of the Gross Domestic Product of the Nusa Tenggara Islands (NTIs). However, recurring agricultural droughts pose a major threat to the sustainability of agriculture in this region. The interplay between precipitation, solar radiation, and surface temperature as meteorological factors plays a key role in affecting vegetation (Soil-Adjusted Vegetation Index) and agricultural drought (Temperature Vegetation Dryness Index) in the NTIs. Based on the analyses of interplay with temporal lag, this study investigates the effect of each factor on agricultural drought and attempts to provide early warnings regarding drought in the NTIs. We collected surface information data from Moderate-Resolution Imaging Spectroradiometer (MODIS). Meanwhile, rainfall was estimated from Himawari-8 based on the INSAT Multi-Spectral Rainfall Algorithm (IMSRA). The results showed reliable performance for 8-day and monthly scales against gauges. The drought analysis results reveal that the NTIs suffer from mild-to-moderate droughts, where cropland is the most vulnerable, causing shifts in the rice cropping season. The driving factors could also explain >60% of the vegetation and surface-dryness conditions. Furthermore, our monthly and 8-day TVDI estimation models could capture spatial drought patterns consistent with MODIS, with coefficient of determination (R<sup>2</sup>) values of more than 0.64. The low error rates and the ability to capture the spatial distribution of droughts, especially in open-land vegetation, highlight the potential of these models to provide an estimation of agricultural drought. |
| format | Article |
| id | doaj-art-c19a9f7fbab3421883c70deeb33f9c37 |
| institution | DOAJ |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Remote Sensing |
| spelling | doaj-art-c19a9f7fbab3421883c70deeb33f9c372025-08-20T03:07:58ZengMDPI AGRemote Sensing2072-42922025-07-011714246010.3390/rs17142460Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, IndonesiaGede Dedy Krisnawan0Yi-Ling Chang1Fuan Tsai2Kuo-Hsin Tseng3Tang-Huang Lin4Zainuddin Abdul Madjid Meteorological Station, The Agency for Meteorology, Climatology, and Geophysics of the Republic of Indonesia (BMKG), Jl. Mandalika−Penujak, Lombok Tengah 83573, Nusa Tenggara Barat, IndonesiaCenter for Space and Remote Sensing Research, National Central University, Taoyuan City 32001, TaiwanCenter for Space and Remote Sensing Research, National Central University, Taoyuan City 32001, TaiwanCenter for Space and Remote Sensing Research, National Central University, Taoyuan City 32001, TaiwanCenter for Space and Remote Sensing Research, National Central University, Taoyuan City 32001, TaiwanAgriculture accounts for 29% of the Gross Domestic Product of the Nusa Tenggara Islands (NTIs). However, recurring agricultural droughts pose a major threat to the sustainability of agriculture in this region. The interplay between precipitation, solar radiation, and surface temperature as meteorological factors plays a key role in affecting vegetation (Soil-Adjusted Vegetation Index) and agricultural drought (Temperature Vegetation Dryness Index) in the NTIs. Based on the analyses of interplay with temporal lag, this study investigates the effect of each factor on agricultural drought and attempts to provide early warnings regarding drought in the NTIs. We collected surface information data from Moderate-Resolution Imaging Spectroradiometer (MODIS). Meanwhile, rainfall was estimated from Himawari-8 based on the INSAT Multi-Spectral Rainfall Algorithm (IMSRA). The results showed reliable performance for 8-day and monthly scales against gauges. The drought analysis results reveal that the NTIs suffer from mild-to-moderate droughts, where cropland is the most vulnerable, causing shifts in the rice cropping season. The driving factors could also explain >60% of the vegetation and surface-dryness conditions. Furthermore, our monthly and 8-day TVDI estimation models could capture spatial drought patterns consistent with MODIS, with coefficient of determination (R<sup>2</sup>) values of more than 0.64. The low error rates and the ability to capture the spatial distribution of droughts, especially in open-land vegetation, highlight the potential of these models to provide an estimation of agricultural drought.https://www.mdpi.com/2072-4292/17/14/2460agricultural droughtmeteorological factorTVDItemporal lag |
| spellingShingle | Gede Dedy Krisnawan Yi-Ling Chang Fuan Tsai Kuo-Hsin Tseng Tang-Huang Lin Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia Remote Sensing agricultural drought meteorological factor TVDI temporal lag |
| title | Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia |
| title_full | Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia |
| title_fullStr | Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia |
| title_full_unstemmed | Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia |
| title_short | Meteorological Drivers and Agricultural Drought Diagnosis Based on Surface Information and Precipitation from Satellite Observations in Nusa Tenggara Islands, Indonesia |
| title_sort | meteorological drivers and agricultural drought diagnosis based on surface information and precipitation from satellite observations in nusa tenggara islands indonesia |
| topic | agricultural drought meteorological factor TVDI temporal lag |
| url | https://www.mdpi.com/2072-4292/17/14/2460 |
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