Claim Missing Document
Check
Articles

Found 5 Documents
Search

AgriForScape Model: Optimization of Agricultural Landscape Design in Karawang District as a Pest Control Strategy with an Ecological Approach Selvianing Tiyas; Wildan Maynardy Wicaksono; Usnil Khotimah; Ali Dzulfigar; Danik Septianingrum; Rahmat Asy’ari; Muhammad Ferdiansyah; Neviaty P Zamani; Rahmat Pramulya; Yudi Setiawan
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.710

Abstract

Karawang Regency is one of the national rice barns and a major supplier of rice to Jakarta and surrounding areas. However, the productivity of this rice is threatened by the brown planthopper (Nilaparvata lugens) which causes crop failure. The reliance on chemical pesticides to control this pest results in negative impacts on the environment and endangers human health. This caused a decrease in land productivity resulting in the conversion of land use to non-agriculture. This research aims to analyze the conditions and problems of agricultural areas in Karawang Regency and design a strategy for regulating landscape structures in reducing the intensity of pest attacks in Karawang Regency. Optimizing the structure and pattern of agricultural landscapes using the AgriForScape (Agriculture-Forest-Landscape) model can be one of the effective strategies in pest control to increase land productivity by integrating agriculture and forest land covers. Land cover mapping for 2023 and 2000 was conducted using cloud computing, revealing a conversion of 14,000 hectares of rice paddy land over 23 years, leaving 99,713 hectares. AgriForScape focuses on the integration of agriculture and forest conservation to improve ecosystem balance, increase land productivity, and lower the risk of natural disasters. AgriForScape landscape management can be done with several strategies, including the addition of corridors and forest patches as habitat for natural predators of rat pests, and the addition of refugia areas as food sources and natural habitat for insect pest predators. By applying an ecological approach through optimized agricultural landscape design, this strategy aims to reduce pest attack intensity, boost rice productivity, and contribute to food security and climate change mitigation. The findings are expected to advance sustainable agriculture and offer valuable insights for local governments, farmers, and stakeholders seeking environmentally friendly land management solutions.
Data Indo InaFire: Spatial Visualization of Peatland Fire Impact and Ecosystem Restoration Monitoring in PHU Jambi using Earth Engine Apps and Sentinel-2 MSI Imagery Muhammad Ilham; Citra Putri Perdana; Verawati Ayu Lestari; Ali Dzulfigar; Hanum Resti Saputri; Danik Septianingrum; Rahmat Asy’Ari; Yudi Setiawan; Rahmat Pramulya; Neviaty Putri Zamani
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.737

Abstract

Peatlands formed from long-term accumulation of partially decomposed organic matter in wetland areas. This particular ecosystem is not only capable of sequestering significant quantities of carbon but also vulnerable to forest and land fires (karhutla). Peatland produces considerable CO₂ emissions during fire occurrences, which consequently requires spatiotemporal monitoring to sustain its ecological roles and functions. This study aims to map the severity of fires in peatland ecosystems, estimate the success of post-fire restoration, and develop an Earth Engine Apps-based monitoring platform for peatland fire monitoring. Fire severity assessment and post-fire restoration success estimation were conducted in Jambi's Peat Hydrological Unit (PHU) in 2019 using the Normalized Burn Ratio (NBR) index derived from Sentinel-2 MSI satellite imagery. Most of Jambi PHU's fire severity and restoration levels are high. The area of PHU Jambi with high fire severity was 7,822.91 hectares, while the area with high restoration success was 23,744.69 hectares. NBR monitoring in PHU Jambi can be used to detect fire severity and restore success. The visualization of forest and land fire severity was successfully displayed on the Data Indo InaFire webGIS platform, an Earth Engine Apps-based monitoring platform.
Development of Spatial Platform Based Earth Engine Apps for Mangrove Carbon Stock: Case Study in Serang Coastal Zone, Banten Province Puspitasari, Raditya Febri; Aisyah; Usnil Khotimah; Mahadika Rifka Nugraha; Ali Dzulfigar; Khairani Putri Marfi; Danik Septianingrum; Rahmat Asy'ari; Rahmat Pramulya; Neviati Putri Zamani; Yudi Setyawan
CELEBES Agricultural Vol. 4 No. 2 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v4i2.746

Abstract

Mangroves exhibited considerable potential in mitigating global climate change, as these ecosystems can sequester and store substantial amounts of carbon in the form of live and decayed plant biomass across coastal areas. This research aimed to estimate carbon stocks and assess the dynamics of carbon reserves in the silvofishery area of Serang City, Banten, utilizing geospatial technology and cloud computing. Additionally, the study sought to develop the Indo InaC Data platform to monitor CO2 uptake on silvofishery land. The methodology employed included mangrove detection through unguided classification, and carbon stock estimation was performed using regression models derived from vegetation indices, specifically the Integrated Remote Sensing and Ecological Index (IRECI) and the Transformed Vegetation Index (TRVI). The results revealed fluctuations in mangrove vegetation cover between 2016 and 2023, with a notable decrease occurring from 2016 to 2017, as the cover declined from approximately 61.91 hectares to 50.53 hectares. This decrease was followed by an increase from 2017 to 2022, during which the area rose to 78.1 hectares; however, a subsequent decrease was observed in 2023, with the area reducing to 66.82 hectares. The estimated carbon reserves in the study area for 2023 amounted to 315 tons, reflecting similar dynamics to those observed in mangrove vegetation cover. The development of the Indo InaC Data platform is anticipated to facilitate ongoing monitoring of CO2 emissions uptake, and it is expected to inform future strategies for managing silvofishery land on an annual basis.
Monitoring Land Use and Land Cover Using Remote Sensing Technology in Kubu Raya Regency, West Kalimantan Province Nur Rahmadhanti, Intan; Salsabila Nur'Aini; Herni Natasha Aulia; Muhammad Ikhwan Ramadhan; Hanum Resti Saputri; Abd Malik A Madinu; Ali Dzulfigar; Rahmat Asy'Ari; Rahmat Pramulya; Yudi Setiawan
CELEBES Agricultural Vol. 5 No. 1 (2024): CELEBES Agricultural
Publisher : Faculty of Agriculture, Tompotika Luwuk University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52045/jca.v5i1.867

Abstract

Kubu Raya Regency is one of the areas that has a peat ecosystem in it. The peat ecosystem has a role and function in mitigating climate change because it has the ability to store quite high carbon reserves. However, peat ecosystems often experience degradation and changes in land cover which can contribute carbon emissions to the atmosphere. Remote sensing is a technology that can be used to detect changes in land cover and use in Kubu Raya Regency. Therefore, this research aims to detect changes in land cover and using remote sensing technology and assess the level of accuracy of the detection results. Analysis of changes in land cover and use from 2000 - 2023 was obtained by guided classification using the Random Forest (RF) algorithm which involves various vegetation, water and built-up land indices. The research results show that there is a decrease in forest land area from 2000 to 2023 amounting to 106,542 ha. The forest area in 2000 was 524,359 ha, while in 2023 it will be 417,817 ha. The results of accuracy measurements show an overall accuracy (OA) value of 98.84% with a kappa statistic of 0.98. It is hoped that the results of these findings will provide an initial picture of the condition of the ecosystem in Kubu Raya Regency, most of which is a peat ecosystem, as a consideration in formulating peat ecosystem conservation policies.
Dynamic Change of Mangroves in Aceh Tamiang Regency using Landsat Temporal Data, 2000 to 2023 Marfi, Khairani Putri; Asy'Ari, Rahmat; Azelia Dwi Rahmawati; Ali Dzulfigar; Aulia Ulfa; Puspitasari, Raditya Febri; Yudi Setiawan; Neviaty P Zamani; Rahmat Pramulya
Media Konservasi Vol. 30 No. 2 (2025): Media Konservasi Vol 30 No 2 May 2025
Publisher : Department of Forest Resources Conservation and Ecotourism - IPB University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29244/medkon.30.2.344

Abstract

Mangroves, known for their high productivity, play vital roles in physical, ecological, and economic aspects that benefit human life. However, these ecosystems are currently threatened by climate change and human activities. To address this challenge, Indonesia aims to rehabilitate 600,000 hectares of mangroves by 2024. Effectively monitoring changes in mangrove dynamics is crucial for achieving this goal. This study focuses on understanding the dynamic change of the mangrove land cover in Aceh Tamiang from 2000 to 2023. Mangrove dynamics in Aceh Tamiang are important because it has the largest mangrove area in East Aceh, which is decreasing due to conversion to the oil palm industry. The classification using random forest (RF) algorithm by utilizing VWB-IC (Vegetation-Water-Built-up Index Combined), which area NDVI, SAVI, ARVI, GNDVI, SLAVI, and EVI as vegetation indices; MNDWI and ANDWI as water indices; and NDBI as built-up index. The employment of this combination is necessary to enhance the accuracy of classification due to the addition of more input parameters to machine learning. The image data are acquired through Landsat 5 for 2000 and 8 and 9 satellites for 2023. The observed dynamics include mangroves transitioning into fishponds (768 ha) and plantations (2,679 ha) between 2000 and 2023. The processed data indicates a decrease in the Aceh Tamiaang mangrove area from 13,270 ha in 2000 to 9,386 ha in 2023. These results can be used to determine mangrove rehabilitation policies in Aceh Tamiang, Indonesia.