Pemetaan Kekeringan Menggunakan VTCI dan TVDI Satelit MODIS (Studi Kasus: Jawa Timur)

Kusuma, Anandya Chiara Eky (2026) Pemetaan Kekeringan Menggunakan VTCI dan TVDI Satelit MODIS (Studi Kasus: Jawa Timur). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Pemanasan iklim global yang berlangsung secara terus-menerus memicu peningkatan frekuensi dan intensitas kejadian kekeringan, termasuk di wilayah agraris seperti Jawa Timur. Penelitian ini memetakan tingkat kekeringan pertanian di Provinsi Jawa Timur periode 2019-2024 menggunakan data time series MODIS, melalui indeks Temperature Vegetation Dryness Index (TVDI) dan Vegetation Temperature Condition Index (VTCI) yang diturunkan dari ruang fitur Land Surface Temperature (LST) dan Normalized Difference Vegetation Index (NDVI). Ruang fitur dibangun dari komposit median multitahun setelah land cover masking dan DEM masking, menghasilkan persamaan dry edge LST = −19,538NDVI + 47,28 dan wet edge LST = −2,628NDVI + 29,69. Hasil menunjukkan pola kekeringan yang berfluktuasi antar-tahun, dengan kondisi terbasah pada tahun 2022 (VTCI rata-rata 0,525; TVDI rata-rata 0,553) dan kondisi terkering pada tahun 2023 (VTCI rata-rata 0,372; TVDI rata-rata 0,683). Pada tingkat kabupaten/kota, Kabupaten Bojonegoro secara konsisten menunjukkan tingkat kekeringan tertinggi, diikuti Pamekasan, Ngawi, Sampang, dan Sidoarjo. Analisis korelasi Spearman antara VTCI/TVDI dengan data curah hujan CHIRPS menunjukkan hubungan yang signifikan secara statistik (p = 0,010) namun sangat lemah (r = 0,170 untuk VTCI dan −0,170 untuk TVDI), yang mengindikasikan bahwa fluktuasi kedua indeks lebih dipengaruhi oleh variabilitas iklim antar-tahun (ENSO) dan keterlambatan respons hidrologis (time-lag) dibandingkan curah hujan sesaat. Hasil penelitian ini memberikan informasi spasial dan temporal yang dapat mendukung perencanaan mitigasi kekeringan pertanian di Provinsi Jawa Timur.
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Continuous global climate warming has significantly triggered an increase in the frequency and intensity of drought events, particularly in agrarian regions such as East Java. This study maps agricultural drought levels in East Java Province during the 2019-2024 period using MODIS time series data, through the Temperature Vegetation Dryness Index (TVDI) and Vegetation Temperature Condition Index (VTCI), both derived from a Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) feature space. The feature space was constructed from a multi-year median composite following land cover masking and DEM masking, resulting in a dry edge equation of LST = −19.538NDVI + 47.28 and a wet edge equation of LST = −2.628NDVI + 29.69. The results show a fluctuating drought pattern across years, with the wettest condition occurring in 2022 (mean VTCI = 0.525; mean TVDI = 0.553) and the driest condition occurring in 2023 (mean VTCI = 0.372; mean TVDI = 0.683). At the district level, Bojonegoro Regency consistently exhibited the highest drought levels, followed by Pamekasan, Ngawi, Sampang, and Sidoarjo. Spearman correlation analysis between VTCI/TVDI and CHIRPS rainfall data revealed a statistically significant (p = 0.010) but very weak relationship (r = 0.170 for VTCI and −0.170 for TVDI), indicating that the fluctuation of both indices is more strongly influenced by interannual climate variability (ENSO) and hydrological time-lag effects than by instantaneous rainfall. These findings provide spatial and temporal information that can support agricultural drought mitigation planning in East Java Province.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Kekeringan, Penginderaan Jauh, Time Series, MODIS, TVDI, VTCI. ============================================================= Drought, Remote Sensing, Time Series, MODIS, TVDI, VTCI.
Subjects:	Q Science Q Science > QA Mathematics > QA276 Mathematical statistics. Time-series analysis. Failure time data analysis. Survival analysis (Biometry) Q Science > QK Botany > QK754.7.D75 Droughts. Drought tolerance S Agriculture > S Agriculture (General)
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Anandya Chiara Eky Kusuma
Date Deposited:	31 Jul 2026 08:27
Last Modified:	31 Jul 2026 08:27
URI:	http://repository.its.ac.id/id/eprint/140845

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