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Pusat Penelitian Lingkungan Hidup, Universitas Udayana
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Validasi Mangrove Health Index Berbasis Sentinel-2 di Bali dan Jawa Timur, Indonesia Abd. Rahman As-syakur; I Gede Agus Novanda; I Putu Sugiana; I Gusti Ayu Istri Pradnyandari Dewi; Anak Agung Eka Andiani; Putu Echa Priyaning Aryunisha; Adhisti Riskianisya; I Made Sara Wijana
Jurnal Kelautan Tropis Vol 29, No 1 (2026): JURNAL KELAUTAN TROPIS
Publisher : Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/jkt.v29i1.30565

Abstract

Hutan mangrove memegang peranan yang penting dalam perlindungan pesisir dan penyerapan karbon, namun ancaman degradasinya terus meningkat. Teknologi penginderaan jauh menawarkan solusi pemantauan efisien melalui Indeks Kesehatan Mangrove atau Mangrove Health Index (MHI) berbasis citra Sentinel-2 (MHI-S2). Penelitian ini mengevaluasi akurasi model empiris MHI-S2 dibandingkan dengan pengukuran MHI lapangan (MHI-L), pada ekosistem mangrove di Bali dan Jawa Timur. Data dikumpulkan dari 194 plot pada 6 lokasi berbeda di Bali dan Jawa Timur dengan pengamatan yang mencakup parameter tutupan tajuk, diameter batang, dan kerapatan pancang/sapling, yang kemudian disandingkan dengan MHI-S2 pada periode waktu berdekatan. Evaluasi kinerja menggunakan koefisien korelasi Pearson (r dan R²), metrik galat/error (RMSE, MAE, bias), koefisien korelasi konkordansi Lin (Lin’s CCC), serta analisis Bland–Altman. Hasil menunjukkan hubungan moderat antara MHI-S2 dan MHI-L (r = 0,71; R² = 0,50). Meski demikian, ditemukan bias positif yang cukup tinggi yaitu sebesar 20,6 yang mengindikasikan kecenderungan overestimasi oleh model MHI-S2. Rendahnya nilai Lin’s CCC (0,36) dan lebarnya rentang batas kesepakatan 95% hasil analisis Bland–Altman (–17 hingga +59) menegaskan akurasi yang terbatas pada skala plot. Temuan ini mengimplikasikan bahwa model MHI-S2 yang tersedia saat ini belum sepenuhnya andal untuk estimasi nilai absolut MHI-L. Oleh karena itu, diperlukan pengembangan model empiris lanjutan serta validasi lapangan yang lebih intensif untuk meningkatkan presisi pemantauan berbasis satelit, demi mendukung keberhasilan manajemen konservasi mangrove.
Analisis Variabilitas Curah Hujan, Suhu Udara, Dan Suhu Permukaan Tanah Selama Periode 2000-2022 Di Pulau Bali Dengan Memanfaatkan Data Penginderaan Jauh I Gede Agus Novanda; Wahyudin; Anak Agung Eka Andiani; Gusti Ayu Istri Pradnyandari Dewi
Jurnal Geografi, Edukasi dan Lingkungan (JGEL) Vol. 10 No. 2 (2026): Edisi Bulan Juli
Publisher : Pendidikan Geografi Universitas Muhammadiyah Prof. Dr. Hamka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22236/jgel.v10i2.20738

Abstract

Information regarding the characteristics and variability of climate in Bali Island remains relatively limited, despite its importance for supporting development planning, natural resource management, and disaster risk mitigation. This study aims to analyze the characteristics of rainfall, air temperature, and land surface temperature (LST) in Bali Island during the period 2000–2022 using remote sensing data. The datasets employed include CHIRPS for rainfall, ERA5-Land for air temperature, and MODIS MOD11A2 V6.1 for land surface temperature. Spatial and temporal analyses were conducted to identify climate patterns, variability, and the relationships among climate variables. The results show that the highest average rainfall occurred in January, reaching 318.38 mm/month, with an average of 19 rainy days per month, while rainfall intensity tended to be higher in May and October, corresponding to the transitional seasons. The average air temperature exhibited two annual peaks, occurring in April (24.77°C) and November (24.99°C), while the lowest temperature was recorded in August (23.38°C). Meanwhile, the highest average land surface temperature was observed in 2015 (28.7°C), whereas the lowest was recorded in 2022 (25.8°C). Spatially, the mountainous regions of central and northern Bali generally experienced higher rainfall and lower temperatures than other areas. The findings demonstrate that remote sensing data are effective for identifying regional climate characteristics and variability. The results are expected to provide valuable information for climate-based development planning, natural resource management, and climate change adaptation efforts in Bali Island.
Co-Authors Abd. Rahman As-syakur Adhisti Riskianisya Gusti Ayu Istri Pradnyandari Dewi I Gede Agus Novanda I Gede Agus Novanda I Gusti Ayu Istri Pradnyandari Dewi I Made Sara Wijana Putu Echa Priyaning Aryunisha Sugiana, I Putu Wahyudin