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Journal : Agromet

Identification of Peatland Burned Area based on Multiple Spectral Indices and Adaptive Thresholding in Central Kalimantan Pratikasiwi, Hilda Ayu; Taufik, Muh.; Santikayasa, I Putu; Domiri, Dede Dirgahayu
Agromet Vol. 38 No. 2 (2024): DECEMBER 2024
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.38.2.68-77

Abstract

Nowadays, spectral index has become popular as a tool to identify fire-burned areas. However, the use of a single index may not be universally applicable to region with diverse landscape and vegetation as peatlands. Here, we propose to develop a procedure that integrates multiple spectral indices with an adaptive thresholding method to enhance the performance of burned area detection. We combined the Normalized Difference Vegetation Index (NDVI) and the Normalized Burn Ratio (NBR) using MODIS imagery from 2002 to 2022 to calculate (Confirmed Burned Pixel) by filtering dNDVI and dNBR. The mean and standard deviation of serve as inputs for image thresholding. We tested our approach in Sebangau peatland, Central Kalimantan, where fires occur annually. The results showed that the model performed well with overall accuracy > of 91%, indicating that the model is effective and reliable for identifying burned areas. The findings also revealed that the frequency of fire is below 2 times/year, with the southeastern is the most fire prone regions. Further, our findings provide an alternative approach for identifying burned areas in locations with diverse vegetation cover and different geographical regions.
Pemodelan Dinamika CO2 Pada Tanaman Kelapa Sawit Kii, Meriana Ina; June, Tania; Santikayasa, I Putu
Agromet Vol. 34 No. 1 (2020): JUNE 2020
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (554.343 KB) | DOI: 10.29244/j.agromet.34.1.42-54

Abstract

Oil palm plantation has a high potency to absorb carbon. Limited observed data and expensive instrumentations to measure the absorbed carbon have caused an inaccurate estimation of carbon storage from oil palm. The objectives of this research were to develop a CO2 absorption model, and to calculate the carbon cycle based on climate factors and plant age. CO2 absorption was derived from gross primary production (GPP) and net primary production (NPP), which were ​​based on solar radiation. From NPP we derived net ecosystem exchange (NEE) by calculating the difference between NPP and soil respiration. Our results showed that age of oil palm has influenced the CO2 absorption from 9.8 (1 year) to 117 tons ha-1 year-1 (19 years), with average of 86.5 tons ha-1 year-1 (over 25-year life cycle). We validated our NPP model with biomass that indicated a very good performance of the model with R2 0.95 and RMSE 1.81. Meanwhile, the performance of NEE model was slightly lower (R2 0.71 and 0.72, for wet and dry conditions), but the model had a similar pattern with the measured NEE. Based on the model performance, the findings imply that the model is useful to estimate CO2 absorption, where there is no eddy covariance measurement. This research suggests that carbon modeling will contribute to global terrestrial carbon modeling.
Assessing the Influence of Climate Services and Climate Change Adaptation Strategies on Smallholder Agriculture: A Systematic Literature Review Marjuki, Marjuki; Koesmaryono, Yonny; Santikayasa, I Putu; Sopaheluwakan, Ardhasena
Agromet Vol. 39 No. 2 (2025): DECEMBER 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.2.75-85

Abstract

Climate services and climate change adaptation practices are increasingly recognized as essential for supporting smallholder farmers. Despite numerous studies on climate impacts and adaptation strategies, limited systematic evidence exists on how climate services and adaptation interventions influence farming practices across regions. This study addresses the gap through a systematic literature review of Scopus-indexed publications over the past decade. Using the PRISMA approach, 1981 articles were screened, with 31 meeting the eligibility criteria. Of these, 23 focused on adaptation interventions and 8 on climate services. Geographically, 30 studies were concentrated in tropical regions Africa (n =16) and in Asia (n=14), while one study was outside the tropics. Findings show that climate information strongly supports the adoption of adaptation strategies (>60%), especially in technological interventions such as Climate-Smart Agriculture, ecosystem management, irrigation, and climate risk reduction. In terms of service delivery, basic climate service provision demonstrated greater effectiveness (80%) compared to advisory-based agricultural services (40%). Socio-demographic factors, particularly education and age, consistently influenced farmers’ decision-making in adopting both climate services and adaptation practices. Overall, this review highlights the need for more integrated approaches that explicitly connect climate services with adaptation interventions. Strengthening these linkages is especially critical in tropical regions, where smallholder farmers remain highly vulnerable to climate variability and long-term climate change risks.
ECMWF SEAS5 Seasonal Rainfall Assessment: A Study Case in Papua Andika, Steven; Santikayasa, I Putu; Donaldi Sukma, Permana
Agromet Vol. 39 No. 2 (2025): DECEMBER 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.2.%p

Abstract

Papua, Indonesia’s easternmost island, is prone to seasonal hydrometeorological disasters, necessitating high-quality climate forecasts for effective risk management. This study evaluates the performance of the European Centre for Medium-Range Weather Forecasts (ECMWF) Seasonal Forecast System 5 (SEAS5) in predicting seasonal (3-monthly) rainfall across Papua from 1982 to 2016, using the blended Climate Hazards group InfraRed Precipitation with in-situ rainfall data (CHIRP+Pos) as the observational reference. SEAS5 forecasts at 1 to 3 month lead times were assessed across seasons which defined as July-August-September (JAS), August-September-October (ASO), September-October-November (SON), and December-January-February (DJF), and El Niño-Southern Oscillation (ENSO) phases (El Niño, La Niña, Neutral), using Pearson correlation coefficient (Corr), root mean square error (RMSE), and Kling-Gupta Efficiency (KGE) metrics. Results show stronger SEAS5 skill in JAS–SON (Corr up to 0.939) compared to DJF-JFM (Corr as low as -0.208), with a robust ENSO-rainfall relationship in JJA-SON. SEAS5 performed best during El Niño, particularly in lowlands and exhibited greater variability skill during La Niña and Neutral phases. Benchmarking against a linear regression baseline showed SEAS5’s superior Corr in 76.2% of grids but higher RMSE in 60.6%. Despite limitations in mountainous regions and at longer lead times, SEAS5 offers reliable forecasts for lowland areas during JAS-SON under El Niño, supporting operational applications like drought preparedness and agricultural planning in the regions.
Spatiotemporal Patterns of Meteorological Drought in the National Food Barn Region: A Case Study of South Sulawesi Province Andini, Nastiti; Santikayasa, I Putu; Setiawan, Amsari Mudzakir
Agromet Vol. 39 No. 2 (2025): DECEMBER 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.2.120-130

Abstract

Hydrometeorological disasters, particularly droughts, pose a significant threat to food crop productivity. South Sulawesi, one of Indonesia’s major rice-producing regions outside Java, is highly vulnerable to drought impacts. This study analyzes the spatiotemporal patterns of meteorological drought in South Sulawesi during 1981–2020 using the Standardized Precipitation Index (SPI) and applies run theory to characterize drought events. Monthly rainfall data were obtained from the Climate Hazards Center InfraRed Precipitation (CHIRP) dataset and complemented with ground-based observations from the BMKG rainfall observation network. Principal Component Analysis (PCA) with varimax rotation was employed to identify dominant spatial patterns of meteorological drought variability. The results identify three principal regions explaining more than 65% of the total variance: Region 1 (R1; 56%) in northern South Sulawesi, Region 2 (R2; 10%) in the central to eastern areas, and Region 3 (R3; 10%) in the western region. R1 exhibits the highest drought frequency and intensity but relatively short durations, whereas R3 shows the lowest frequency but the longest durations and largest magnitudes. A positive correlation between drought duration and magnitude is observed across all regions, along with a significant drying trend in the southern part of R2. Overall, these findings provide important insights into the spatial and temporal variability of meteorological drought in South Sulawesi and offer a scientific basis for strengthening drought risk management and regional food security strategies.
Transboundary Trajectory Patterns of PM2.5 in The Lower Troposphere of Jakarta Region Istiqomah, Sifa; Santikayasa, I Putu; Turyanti, Ana
Agromet Vol. 39 No. 2 (2025): DECEMBER 2025
Publisher : PERHIMPI (Indonesian Association of Agricultural Meteorology)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/j.agromet.39.2.107-119

Abstract

PM2.5 is a key indicator of air quality and poses serious environmental and health concern, especially in Jakarta where air quality frequently exceeds recommended standards. But researches mainly focus on surface-level pollutant, underscoring transboundary emission. This study aims to analyze the transboundary trajectory patterns of PM2.5 pollutants, and to estimate the contribution of emissions to air quality in the Jakarta for 2024. Meteorological data and PM2.5 concentrations from five air quality monitoring stations were analyzed during non-rainfall periods. Potential emission sources analysis was simulated using HYSPLIT Concentration Weighted Trajectory (CWT). Our results show PM2.5 concentrations during the wet season were ~40% lower than dry season, with an average concentration of 27.11 μg/m3 and were strongly influenced by monsoonal wind patterns in both seasons. During the west monsoon, pollutant transport was predominantly from the southwest to northeast, whereas during the east monsoon it shifted from the northwest to northeast. The trajectory patterns exhibited no substantial differences across all layers (15, 50, 100, and 200 m), although seasonal atmospheric stability influenced pollutant dispersion. In the wet season, PM2.5 primarily originated from western regions of Jakarta, while in the dry season sources were predominantly from the east, which is consistent with prevailing monsoonal winds. Several monitoring stations also indicated potential contributions from North Jakarta due to curved airflow patterns. These findings highlight the dominant role of monsoonal wind in controlling PM2.5 concentrations and transboundary transport in Jakarta within the lower troposphere.