Drought Monitoring Using Remote Sensing Data in Nusa Tenggara Timur Province, Indonesia in Between 2018 and 2023

This study utilized remote sensing data to monitor the relationship between land cover and drought exposure in Nusa Tenggara Timur (NTT) Province.NTT is a province in Indonesia, located in the Nusa Tenggara archipelago, characterized by low to medium rainfall, which contributes to frequent drought events.In 2018 and 2019, the province was impacted by El Nio, resulting in approximately 865,900 and 1,154,714 affected and displaced individuals, respectively.Due to the limited availability of time-series data, observations from the Landsat-8 OLI/ TIRS mission, spanning from 2018 to 2023, were utilized.The normalized difference vegetation index (NDVI) was employed to assess land conditions, while the vegetation health index (VHI), calculated from the Temperature Condition Index (TCI) and vegetation condition index (VCI), was used to estimate drought severity.To validate the dry season period in the study area, ERA5 climate reanalysis data from 1990 to 2020 was used.This study provides new insights into drought monitoring in NTT Province, Indonesia, by analyzing temporal variations in vegetation.The results indicated that seasonal dynamics, climatic variability, seasonal farming practices, and land fires are major contributors to severe drought conditions in NTT.Notably, this research highlighted a finding absent from previous studies: seasonal farming and land fires are the primary drivers of elevated drought levels in the province.The study is significant, as it elucidated the impacts of drought on development, agriculture, and water resources.Through remote sensing data, it revealed spatial drought distribution patterns during the study period in NTT.This research could provide information about land-use and environmental planning in tropical regions.

Authors

Publication Details

Journal
Ecological Engineering & Environmental Technology
Published
2024-09-23
DOI
https://doi.org/10.12912/27197050/192472
Citations
1
Primary Topic
Data Mining and Machine Learning Applications
Type
article
Field-Weighted Citation Impact
0.78
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article

Drought Monitoring Using Remote Sensing Data in Nusa Tenggara Timur Province, Indonesia in Between 2018 and 2023

I Wayan Nuarsa, I Made Sudarma, I Made Oka Guna Antara, Tati Budi Kusmiyarti et al.
1 citations
Ecological Engineering & Environmental Technology
Data Mining and Machine Learning Applications
0.78
article

Drought Monitoring Using Remote Sensing Data in Nusa Tenggara Timur Province, Indonesia in Between 2018 and 2023

I Wayan Nuarsa, I Made Sudarma, I Made Oka Guna Antara, Tati Budi Kusmiyarti, I Wayan Sandi Adnyana
article en
1 citations

Abstract

This study utilized remote sensing data to monitor the relationship between land cover and drought exposure in Nusa Tenggara Timur (NTT) Province.NTT is a province in Indonesia, located in the Nusa Tenggara archipelago, characterized by low to medium rainfall, which contributes to frequent drought events.In 2018 and 2019, the province was impacted by El Nio, resulting in approximately 865,900 and 1,154,714 affected and displaced individuals, respectively.Due to the limited availability of time-series data, observations from the Landsat-8 OLI/ TIRS mission, spanning from 2018 to 2023, were utilized.The normalized difference vegetation index (NDVI) was employed to assess land conditions, while the vegetation health index (VHI), calculated from the Temperature Condition Index (TCI) and vegetation condition index (VCI), was used to estimate drought severity.To validate the dry season period in the study area, ERA5 climate reanalysis data from 1990 to 2020 was used.This study provides new insights into drought monitoring in NTT Province, Indonesia, by analyzing temporal variations in vegetation.The results indicated that seasonal dynamics, climatic variability, seasonal farming practices, and land fires are major contributors to severe drought conditions in NTT.Notably, this research highlighted a finding absent from previous studies: seasonal farming and land fires are the primary drivers of elevated drought levels in the province.The study is significant, as it elucidated the impacts of drought on development, agriculture, and water resources.Through remote sensing data, it revealed spatial drought distribution patterns during the study period in NTT.This research could provide information about land-use and environmental planning in tropical regions.

Ecological Engineering & Environmental TechnologyVol. 25(11)
Climate action
Openalex Percentile: Top 21%
Data Mining and Machine Learning Applications
0.78
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