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All Journal ULIN: Jurnal Hutan Tropis Jurnal Hutan Tropika The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Rizqi I’anatus Sholihah
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Environmental Science

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COMPARISON OF MACHINE LEARNING MODELS FOR LAND COVER CLASSIFICATION Bambang H. Trisasongko; Dyah R. Panuju; Nur Etika Karyati; Rizqi I’anatus Sholihah
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 1 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3786

Abstract

Land cover data remain one of crucial information for public use. Â With rapid human-associated land alteration, this information needs to be frequently updated. Remotely-sensed data provide the best option to construct land cover maps with numerous methods available in the literature. While disagreement exists to select the robust one, further exploration should be made to extend the understanding on the behavior of machine learners, in particular, for classification problems. This article discusses performance of pixel-based machine learning algorithms, frequently used in research or implementation. Five popular algorithms were evaluated to distinguish five rural land cover classes, i.e. built-ups, crops, mixed garden, oil palm plantations and rubber estates, from Sentinel-2 data. This research found that the benchmark, classification and regression tree, was unable to differentiate woody vegetation, although the overall accuracy was sufficiently moderate. This suggested that overall accuracy cannot be seen as the only measure for assessing the quality of the thematic output. Meanwhile, support vector machines and random forest competed to yield the highest accuracy and class detection capability, although the latter was in favor with 98% accuracy level. A newly developed model, like extreme gradient boosting, achieved a similar level of accuracy. This research implies that modern machine learning approaches would be invaluable for land cover classification; hence, access to these modeling toolkits is substantial.
Analisis Spasial Hubungan Sebaran Hotspot, Perubahan Stok Karbon, dan Karakteristik Lahan (Kawasan Hutan dan Ketebalan Gambut) di KHG Kahayan Sebangau, Kalimantan Tengah Tahun 2018-2022: Spatial Analysis of Hotspots, Carbon Stock Changes and Land Properties in Peatland Hydrology Unitary (KHG) Kahayan-Sebangau, Central Kalimantan in 2018 – 2022 Atmaja, Krisologus Genesa Ruby; Rahman, Basuki; Santosa, Lenalda Febriany; Sholihah, Rizqi I’anatus; Wulandari, Verlina Intan
JURNAL HUTAN TROPIKA Vol 20 No 2 (2025): Volume 20 Nomor 2 Tahun 2025
Publisher : Jurusan Kehutanan, Fakultas Pertanian Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36873/jht.v20i2.23073

Abstract

Peatland fires have been a long-standing topic of discussion in combating greenhouse gas effects, especially in Indonesia, which has the largest tropical peatlands in the world. However, peatland fires have their own complexities, one of which is that hotspots do not always reflect the amount of carbon emissions. This study was conducted in the Kahayan-Sebangau Peatland Hydrological Unitary (KHG) by integrating several spatial data sets: MODIS hotspot distribution data from 2019 to 2022, peat thickness data, forest area status data, land cover data from 2018 and 2022 with carbon content values based on the 2015 national guidelines of the Ministry of Environment and Forestry (KLHK). Carbon emissions were estimated from changes in land cover and carbon reserves per hectare. The results show that Production Forests (HP) contribute >40% of total hotspots and >80% of carbon emissions, while Conversion Production Forests (HPK) have the highest hotspot density at 1.08 hotspots/km2 and the highest carbon emissions are found in the deep peat thickness class. This study found that the status of forest areas and peat thickness greatly determine the amount of carbon emissions from a fire, as indicated by the distribution of hotspots.
Pemantauan Dinamika Land Surface Temperature dan Indeks Spektral (NDVI) Menggunakan Landsat ETM+ dan OLI/TIRS di Lanskap Jember Selatan: Monitoring Land Surface Temperature and Spectral Indices (NDVI) Dynamics Using Landsat ETM+ and OLI/TIRS in the Southern Jember Landscape Sholihah, Rizqi I'anatus; Putra, Rizki Auliansyah; Santosa, Lenalda Febriany; Atmadja, Krisologus Genesa Ruby; Wulandari, Verlina Intan; Rahman, Basuki; Islami, Muflihatul Maghfiroh; Kusneti, Monica
JURNAL HUTAN TROPIKA Vol 20 No 2 (2025): Volume 20 Nomor 2 Tahun 2025
Publisher : Jurusan Kehutanan, Fakultas Pertanian Universitas Palangka Raya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36873/jht.v20i2.24103

Abstract

Landscape transformation driven by rapid urbanization is a primary determinant of microclimate change in peri-urban regions. This study aims to analyze the spatiotemporal dynamics of land surface temperature (LST) and its relationship with vegetation density (Normalized Difference Vegetation Index/NDVI) in the Southern Jember landscape. Utilizing Landsat 7 ETM+ and Landsat 8 OLI/TIRS imagery from 2001, 2013, and 2025, this research evaluates the impact of land cover changes on the regional thermal regime and vegetation index variability. The results reveal a fundamental landscape transition, where the dominance of paddy fields shrank drastically from 66.400 ha (2001) to 13.800 ha (2025), replaced by a massive expansion of settlements reaching 82,900 ha. This shift triggered a significant surface urban heat island (SUHI) phenomenon. Settlement areas recorded an extreme maximum LST of 38,1°C in 2025, a sharp increase compared to the initial study period. Spectral analysis confirms that the rise in LST has a negative correlation with NDVI. This evidence suggests that the loss of vegetation biomass and the increase in impervious surfaces due to uncontrolled urbanization are the primary drivers of environmental warming in South Jember. These findings underscore the urgency of climate-mitigation-based spatial planning strategies for regional sustainability.
Identifikasi Faktor Keberadaan Spesies Burung Langka di Desa Artain Kalimantan Selatan Rahman, Basuki; Fithria, Abdi; Wulandari, Verlina Intan; Atmadja, Krisologus Genesa Ruby; Sholihah, Rizqi I'anatus; Santosa, Lenalda Febriany
ULIN: Jurnal Hutan Tropis Vol 10, No 1 (2026)
Publisher : Fakultas Kehutanan Universitas Mulawarman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32522/ujht.v10i1.22609

Abstract

Pengamatan menunjukkan pola persebaran yang tidak merata, dengan keberadaan spesies sangat ditentukan oleh karakteristik habitat dan ketersediaan sumber pakan. Spesies sensitif seperti Rangkong badak (Buceros rhinoceros) dan Cica-daun besar (Chloropsis sonnerati) hanya dijumpai di hutan primer yang menyediakan pohon tinggi dan minim aktivitas manusia. Sebaliknya, Elang-ular bido (Spilornis cheela) tercatat di habitat hutan primer dan sekunder yang masih mendukung ketersediaan mangsa. Beberapa spesies seperti Kipasan belang (Rhipidura javanica) dan Sepah raja (Aethopyga siparaja) menunjukkan toleransi yang lebih baik terhadap aktivitas manusia selama habitat masih menyediakan kebutuhan spesifik mereka. Penelitian ini menyimpulkan bahwa strategi konservasi perlu mempertimbangkan karakteristik spesifik setiap spesies, dengan kombinasi perlindungan habitat kunci dan pengelolaan terhadap habitat dengan aktivitas manusia yang tinggi. Penelitian ini bertujuan untuk menganalisis faktor-faktor penentu persebaran burung langka tersebut guna menjadi bahan kajian terhadap kepentingan konservasi.
Co-Authors Abdi Fithria Atmadja, Krisologus Genesa Bambang Hendro Trisasongko Dyah R. Panuju Islami, Muflihatul Maghfiroh Kusneti, Monica Nur Etika Karyati Rahman, Basuki Rizki Auliansyah Putra, Rizki Auliansyah Santosa, Lenalda Febriany Wulandari, Verlina Intan