Penelitian dan PKM Unggulan

Oil palm plantations provide the highest amount of foreign exchange earnings for the Indonesian government. However, according to the Indonesian Ministry of Agriculture, the foreign exchange has dropped to 20%. Therefore, to increase oil palm productivity, the President Republic of Indonesia issued Instruction No. 6 of 2019 regarding National Action Plan for Sustainable Oil Palm Plantation 2019–2024, one of the actions to increase national oil palm productivity is strengthening data infrastructure. Considering that the oil palm plantations in Indonesia are highly extensive and spread across almost all parts of Indonesia, cloud computing remote sensing technology is a satisfactory solution for monitoring oil palm plantations. This study aims to develop a spatial database system for monitoring oil palm plantation in Indonesia based on cloud computing remote sensing data. The methodology includes user needs and spatial data identification as Indonesian regulations, combined with focus group discussions, normalized geographic data normalization, and spatial database development using conceptual, logical, and physical models and system design and data visualization. The resulting spatial database system for monitoring oil palm plantations in Indonesia based on cloud computing remote sensing has been constructed by leveraging data saved in the cloud on ArcGIS Living Atlas of The World. The data recorded in ArcGIS Online are then linked to a visualization system created using the ArcGIS operation dashboard. The dashboard has been developed based on user needs and displays information about oil palm plantation age, administration boundaries, rainfall, terrestrial ecosystems, hot spots, and weather conditions.

In 1997, the worst forest fire in Indonesia occurred and hit mangrove forest areas including in Sembilang National Park Banyuasin Regency, South Sumatra. Therefore, the Indonesian government keeps in trying to rehabilitate the mangrove forest in Sembilang National Park. This study aimed to identify the mangrove forest changing and to predict on the future year. The situations before and after forest fire were analyzed. This study applied an integrated Markov Chain and Cellular Automata model to identify mangrove forest change in the interval years of 1989–2015 and predict it in 2028. Remote sensing technology is used based on Landsat satellite imagery (1989, 1998, 2002, and 2015). The results showed mangrove forest has decreased around 9.6% from 1989 to 1998 due to forest fire, and has increased by 8.4% between 1998 and 2002, and 2.3% in 2002–2015. Other results show that mangroves area has continued to increase from 2015 to 2028 by 27.4% to 31% (7974.8 ha). It shows that the mangrove ecosystem is periodically changing due to good management by the Indonesian government.

Oil palm phenology has many advantages in managing the sustainability of oil palm plantations. The phenology of oil palms is a key issue in harvest estimation, fruit bunch production, estimating oil palm taxes, replanting, fertilization, and detecting oil palm disease. One of the recently developed methods of oil palm phenology involves the use of remote sensing technology. We evaluated and reviewed the current state of oil palm phenology based on remote sensing and conducted an optimized systematic review of recent scientific publications, specifically focusing on scientific peer-reviewed papers published between 1990 and 2021, comprising over 100 existing journal papers on remote sensing for oil palm phenology. The review includes a description of the state of the art and the mapping of oil palm phenology based on sensors, biophysical tree parameters, and classification techniques and also describes the state of the art in the development of regression models of oil palm phenology based on wavelength, biophysical tree parameters, and the type of regression model. Finally, the review provided an opportunity to develop suitable techniques for the identification, classification, and the construction of regression models of oil palm phenology. There is a lot of potential in combining multisensor approaches, suitable classification methods, and regression models for oil palm phenology. For future studies on oil palm phenology, we recommend integrating machine learning with oil palm biophysical parameters based on multisensor remote sensing technologies.

Estimating the biophysical parameters during the phenology cycle are very important and the key parameter for indicating the productivity of oil palm plantations. In many countries, the oil palm plantation has a very large area, therefore remote sensing technology is needed to estimate biophysical parameters in large areas. The special characteristics and potential of Synthetic Aperture Radar (SAR) data in acquiring geometric and dielectric properties of biophysical parameters have led to their identification in the context of vegetation monitoring. This study, we have investigated and developed models for estimating the oil palm phenology by applying multiple linear regression (MLR). The methodology includes the biophysical parameters estimated using Sentinel-1A for extracting the canopy height model (CHM), radar vegetation index (RVI), backscattering on VV and VH, aboveground biomass, texture entropy, and texture energy. Then applied multiple linear regression (MLR) analysis for developing model and assess  its ability. The result found the best model for estimating oil palm phenology using 4 parameters.

Information about oil palm phenology is required for oil palm plantation management, but using spaceborne polarimetric radar imagery remains challenging. However, spaceborne polarimetric radar on X-, C-, and L-band is promising on structure vegetation and cloud area. This study investigates the scattering model of oil palm phenology based on spaceborne X-, C-, and L-band polarimetric Synthetic Aperture Radar (SAR) imaging. The X-, C-, and L-band polarimetric SAR are derived from spaceborne of TerraSAR-X, Sentinel-1A, and ALOS PALSAR 2. Study area is located in oil palm plantations, Asahan District, North Sumatra, Indonesia. The methodology includes data collection, preprocessing, radiometric calibration, speckle filtering, terrain correction, extraction of scattering value, and development of scattering model of oil palm phenology. The results showed different scattering characteristics for the X-, C-, and L-band polarimetric SAR of oil palm for age and found the potential of the scattering model for oil palm phenology based on the X-band on HH polarization that showed a nonlinear model with R2 = 0.65. The C-band on VH and VV polarization showed a nonlinear model with R2 = 0.56 and R2 = 0.89. The L-band on HV and HH polarization showed a logarithmic model with R2 = 0.50 and R2 = 0.51. In this case, the most potential of the scattering model of oil palm phenology based onR2is using C-band on VV polarization. However, the scattering model based on X-, C-, and L-band is potentially to be used and applied to identify the phenology of oil palm in Indonesia, which is the main parameter in yield estimation. For the future phenology model needs to improve accuracy by integrating multisensors, including different wavelengths on optical and microwave sensors and more in situ data.

Kecamatan Soreang merupakan ibu Kota Kabupaten Bandung dengan jumlah penduduk yang terus mengalami peningkatan akibat pembangunan sarana prasarana. Wilayah ini masuk ke daerah aliran Sungai Citarum. Sektor domestik merupakan penyumbang beban pencemar terbesar ke sungai ini. Wilayah ini telah memiliki instalasi pengolahan air limbah yang dibangun tahun 1991. Penelitian ini bertujuan melakukan evaluasi instalasi pengolahan air limbah yang telah dibangun, apakah kapasitasnya masih bisa menampung air limbah yang dihasilkan atau tidak. Metode yang dipergunakan yaitu observasi lapangan, pengukuran, dan komparasi dengan kriteria desain yang berlaku. Berdasarkan hasil penelitian bahwa instalasi yang telah ada hanya melayani 250 kepala keluarga. Diperlukan penambahan kapasitas unit untuk mengantisipasi pertumbuhan penduduk yang terus meningkat. Kondisi saat ini instalasi tidak beroperasi secara maksimal karena kendala pemeliharaan instalasi. Hal lain yaitu jaringan air limbah yang mengalami kerusakan, tidak tersedianya tenaga ahli yang mampu mengoperasikan instalasi. Hasil penelitian diperlukan upaya untuk mengembalikan kembali instalasi pengolahan air limbah yang ada serta menambah kapasitas yang ada. Pengolahan air limbah domestik akan mengurangi beban pencemaran ke Sungai Citarum.   Kata kunci: Kecamatan Soreang, instalasi pengolahan air limbah, pencemaran sungai.

Soreang District is the capital of Bandung Regency, with a population that continues to grow due to infrastructure development. This area falls within the Citarum River basin. The domestic sector is the largest contributor of pollutants to this river. This area already has a wastewater treatment plant, which was built in 1991. The aim of this research is to evaluate the capacity of the constructed WWTP in order to determine whether or not it is still able to copewith the wastewater produced. The methods used are field observation, measurement and comparison with current design criteria. Based on the research results, the existing plant can only serve 250 heads of families. It is necessary to increase the capacityof the plant to cater for the growing population. The current condition of the plant is sub-optimal due to plant maintenance issues. In addition, the sewerage network is damaged and there are no experts available to operate the plant. The research findings call for efforts to rehabilitate existing wastewater treatment plants and increase their capacity. Domestic wastewater treatment will reduce the pollution load of the Citarum River.   Keywords: soreang district, waste water treatment plant, river pollution

The village of Mekar Rahayu was selected as the site for the design of a wastewater treatment plant in Margaasih District. This sub-district is located in the Citarum River Basin, which does not yet have a domestic wastewater management system. Domestic wastewater is discharged into septic tanks or into drainage canals, which eventually ends up in rivers. This requires efforts to plan a domestic wastewater management system, considering that the domestic sector is the largest contributor to the pollution load in the Citarum River. The aim of this research is to determine an appropriate domestic wastewater management system to be implemented in the village of Mekar Rahayu. The research method is field observation and planning with reference to the regulations in force in Indonesia. The results of the research on local communal wastewater management systems can be applied in this region. It is planned that 2 future community wastewater treatment plants will serve 25 out of 28 community units in this sub-district. 3 communes that do not fall within the service area of the treatment plant because the settlements are small and dominated by agricultural land, so they can still use the local system. The calculation results for the total domestic wastewater generation are 118.16 litres/second. Based on the analysis of land requirements, ease of operation and other things, the selected series of domestic wastewater treatment plants are bar screen units, collection tanks, grit chambers, equilibration ponds, activated sludge, sedimentation II and disinfection.

The construction of a wastewater treatment plant (WWTP) in Sayati Village is still required in order to dispose of the village's wastewater in an appropriate manner. One potential location for wastewater disposal is the Cikahayangan River. However, the discharge of sewage into the Cikahayangan River results in water pollution, which in turn disrupts the river's natural functions. It is imperative that Sayati Village devise a WWTP that can effectively and efficiently treat wastewater, while also adapting to the existing conditions of the village over the next few years. This is crucial to prevent any adverse impacts from water pollution. The BOD/COD ratio for Sayati Village is 0.809, indicating that the wastewater is treated biologically. The unit selected from the scoring method is activated sludge. However, the land available in Sayati Village is limited, so the WWTP unit refers to the 2022 Sanimas Technical Instructions, which describe a compact WWTP for 100 families with a land availability of 3 meters in width. The domestic wastewater treatment plant (WWTP) processing unit planned for Sayati Village, Margahayu District, consists of primary, secondary, and tertiary domestic processing units. The secondary processing unit selected is an anaerobic filter, which is in accordance with the 2022 Sanimas Technical Guidelines. The units that will be planned in Sayati Village are a bar screen, a grease trap, a screw pump, a grit chamber, an equalization tank, an anaerobic filter, a disinfection unit, and a sludge processing unit.

Disposal of agricultural crop residue by open burning (CROB) is increasingly practiced in Southeast Asia (SEA) countries to get rid of huge amounts of this waste annually. The activity generates large amounts of air pollutants which cause deterioration of local air quality and potentially affect the regional climate. This paper reports the emission inventory (EI) results of CROB in 11 SEA countries in 2014. The EI covers major crops in SEA including rice, maize, soybean, potato/sweet potato, groundnut, sugarcane and cassava. The inventory species included trace gases, particulate matter, as well as semivolatile organic compounds of polycyclic aromatic hydrocarbons (PAHs), dioxins and furans (PCDDs/PCDFs), and greenhouse gases (GHGs). Activity data on field open burning in SEA was primarily collected from the local surveys. The emission factors used in the EI were those developed from the field measurements in the region whenever available. The total annual emissions from SEA in 2014, in Gg, were: 52  SO2; 379  NOx; 22,473 CO;  1,109  NMVOC; 618 NH3; 1,407  PM10; 1,288  PM2.5; 89  BC; 470  OC; 209,640 CO2;640 CH4 and 17 N2O. For toxic air pollutants, the emissions of total PAHs were estimated at 39 Gg while that of PCDD/PCDF was 83 g Toxicity EQuivalent (TEQ). Emission of benzo(a)pyrene (BaP), known as a carcinogenic pollutant, was estimated at 2 Gg in 2014. Indonesia was the top emitter of most species (22-52% depending on species) followed by Vietnam (13-26%) and Thailand (13-19%). The gridded EI results (0.1 degree resolution) prepared in this study can be readily used for regional modeling efforts.

Levels of particulate matter air pollution show an alarming situation with the frequent violation of the national ambient air quality standards. Fragmented ground-based monitoring data in Southeast Asia (SEA) especially for PM2.5, the most dangerous air pollutant, are often not sufficient to assess health impact in term of spatial and temporal distributions hence modeling was done to fill in the gaps. Weather Research Forecast (WRF) model was used to simulate 3 dimensional meteorological fields to drive regional scale chemical transport model of Chimere. Combinations of self-conducted national air pollutant emission inventory and the available on-line international dataset were used for base year of 2007. Various PM2.5 emission reduction measures were scrutinized from the available policies in SEA countries and were projected to the year of 2030 (RED2030) together with the business as usual (BAU2030) scenario. The daily observed PM2.5 concentrations obtained from the Improving Air Quality in Asian Developing Countries (AIRPET) project for four cities (i.e., Bangkok, Hanoi, Bandung, and Manila) were also used for model evaluation. WRF–Chimere results for PM2.5 showed strong seasonal influence of biomass open burning and the modeled PM2.5∕PM10 ratios estimated for four AIRPET sites ranged between 0.47 and 0.59 which were lower than observed values of 0.6–0.83. Under BAU2030, the average number of thepremature deaths per 100,000 people in the SEA domain would increase by 30 from the year of 2007 while under RED2030 the premature deaths would be avoided by 63 from RED2030. This research suggested that collective measure implementation in all countries would maximize health benefits and this can be further monetized as an economic benefit.