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All Journal Forum Geografi Jurnal Pengabdian, Riset, Kreativitas, Inovasi, dan Teknologi Tepat Guna (Parikesit)
Irbah, Amanda
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Agriculture, Biological Sciences & Forestry Computer Science & IT Earth & Planetary Sciences Public Health Social Sciences

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Pemetaan Lokasi Penerapan Nature-Based Solution Melalui Pendekatan Berbasis Masyarakat Sebagai Mitigasi Bencana Tanah Longsor di Kecamatan Ngebel Agus Joko Pitoyo; Irbah, Amanda; Anindya Hias Bestari; Sulistiawan Fajar Nugroho
Jurnal Pengabdian, Riset, Kreativitas, Inovasi, dan Teknologi Tepat Guna Vol 2 No 1 (2024): Mei
Publisher : Direktorat Pengabdian kepada Masyarakat

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/parikesit.v2i1.12134

Abstract

Topographically, Ngebel Sub-district, Ponorogo Regency is located in the western highland complex of Mount Wilis which is steep so that many landslides occur. This prompted an analysis of the vulnerability of landslides in Ngebel sub-district. This study formulates solutions for landslide disasters using Nature-based Solutions (NbS) or nature-based solutions in landslide-prone areas in Ngebel District by involving the community so that they can find the most suitable location for the application of NbS. NbS is a step to be able to implement mitigation in the Ngebel District area. The implementation of this service is carried out using several methods, including literature studies, secondary data collection, data processing, and counseling to the community. Information on the results of the FGD and landslide vulnerability mapping information is taken into consideration in determining alternative solutions, in the form of NbS. NbS selected for landslide disaster mitigation in Ngebel District in the form of vegetative measures and bio-engineering techniques. The selection of NbS is based on things that support the sustainability of agricultural, plantation, and livestock potential in Ngebel District so that existing solutions are able to utilize the potential and community involvement.
Machine Learning-Based Rice Field Mapping in Kulon Progo using a Fusion of Multispectral and SAR Imageries Khoirurrizqi, Yusri; Sasongko, Rohmad; Utami, Nur Laila Eka; Irbah, Amanda; Arjasakusuma, Sanjiwana
Forum Geografi Vol 37, No 2 (2023): December 2023
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v37i2.20304

Abstract

The land-conversion of rice fields can reduce rice production and negatively impact food security. Consequently, monitoring is essential to prevent the loss of productive agricultural land. This study uses a combination of Sentinel-2 MSI, Sentinel-1 SAR, along with SRTM (elevation and slope data) to monitor rice fields land-conversion. NDVI, NDBI and NDWI indices are transformed from the annual median composite Sentinel-2 MSI images used to identify different rice fields with another object. A monthly median composite of SAR images from Sentinel-1 data are used to identify cropping patterns of rice fields in the inundation phase. The classification is performed by using the Random Forest machine learning algorithm in the Google Earth Engine (GEE) platform. Random Forest classification is run using 1000 trees, with a 70:30 ratio of training and testing data from sample features extracted by visual interpretation of high resolution Google Earth imagery. In this study, Random Forest classification is effective in computing a high amount of multi-temporal and multi-sensory data to map rice-field land conversion with an accuracy rate of 96.16% (2021) and 95.95% (2017) for mapping paddy fields. From the multitemporal rice field maps in 2017—2021, a conversion of 826.66 hectares of rice-fields to non-rice fields was identified. Based on the spatial distribution, the conversion from rice-field to non-rice field is higher at the area near the roads, built area and Yogyakarta International Airport. Therefore, it is important to assess and ensure that National Strategic Projects are managed with due regard to environmental impacts and food security. 
Co-Authors Agus Joko Pitoyo Anindya Hias Bestari Khoirurrizqi, Yusri Sanjiwana Arjasakusuma, Sanjiwana Sasongko, Rohmad Sulistiawan Fajar Nugroho Utami, Nur Laila Eka