Jurnal Geospasial, Penginderaan Jauh, dan Survei (GPS)

Analisis Sebaran Ruang Terbuka Hijau (RTH) Menggunakan Sistem Informasi Geografis Di Kota Surabaya Bagian Timur

2023-08-04T13:05:13+07:00

According to the Regulation of the Minister of Agrarian Affairs and Spatial Planning/Head of BPN Number. 14 of 2022, the test parameter used in this study is the calculation of the need for green open space based on the area of the Eastern Part of Surabaya City. The aim of the research is to determine the availability and also the need for public green open space (RTH) using the geographic information system (GIS) method in the Eastern Part of Surabaya City in 2022. A calculation is made of the need for public green open space based on the area of the Eastern Part of Surabaya City. This analysis is based on the guidelines for ATR/KBPN Ministerial Regulation Number 14 of 2022. Mapping the distribution of green open spaces (RTH) in the Eastern Part of Surabaya City uses a geographic information system (GIS). Based on the classification results, the Eastern part of Surabaya City has an area of 1,070,157.41 m2 or 1,070 km2 spread over 8 sub-districts. Public green open space in the Eastern Part of Surabaya City has not met the needs because it does not comply with the 20% of the area of the Eastern Part of Surabaya City which has been stipulated by the government in the Regulation of the Minister of Agrarian Affairs and Spatial Planning/Head of the National Land Agency Number 14 of 2022.

ANALYSIS OF PUBLIC GREEN OPEN SPACE (RTH) DISTRIBUTION USING GEOGRAPHICAL INFORMATION SYSTEM (GIS) METHOD IN SUMENEP CITY DISTRICT

2023-08-04T13:33:03+07:00

This study aims to determine the availability and also the need for public green open spaces (RTH) using the geographic information system (GIS) method in Sumenep City District in 2022, the test parameters carried out are the comparison of the area of Sumenep City District, according to the Regulations of the Minister of Agrarian Affairs and Governance Space/Head of the National Land Agency Number 14 of 2022. Calculations are made in the form of public green open space needs based on the area of the Sumenep City District. The calculation is based on the ATR/KBPN Ministerial Regulation No. 14 of 2022. Mapping to find out the distribution of public green open space (RTH) in Kota Sumenep District uses the geographic information system (GIS) method. This mapping was carried out in October – November 2022. Based on the results of the classification, the Sumenep City District has an area of 27.83 km2. .672.00 m2 or 164.2 km2 spread over 16 villages in Sumenep City District, public green open space in Sumenep City District has met the standards set by the government in the Regulation of the Minister of Agrarian Affairs and Spatial Planning/Head of the National Land Agency Number 14 of 2022, namely 20 % of the total area of a district.

IDENTIFICATION OF LANDSLIDE DISASTER PRONE SETTLEMENTS IN MADIUN REGENCY BASED ON GEOGRAPHIC INFORMATION SYSTEM

2023-08-04T15:21:02+07:00

Landslides are natural phenomena that often occur in mountainous or highland areas. Landslides can be caused by several factors, such as rainfall, slope, soil type, geology and land use. In addition, landslides can also occur due to human activities, such as deforestation, road construction, and settlements (Yulaelawati, E., 2008). Efforts to provide solutions and ease of disaster mitigation in settlements in Madiun Regency can be done by making a Landslide Hazard Map of Settlements. The map can be identified with a Geographic Information System (GIS) using the overlay method or overlay on several parameters, such as: slope, soil type, rainfall and history of landslide events. From the research that has been done, it can be concluded that the level of vulnerability to landslides in settlements in Madiun Regency is dominated by a low vulnerability level of 13398,04 ha; a medium vulnerability level of 848,78 ha; and a high level of vulnerability of 2,26 ha.

IDENTIFIKASI PERMUKIMAN RAWAN BENCANA BANJIR DI KABUPATEN MADIUN MENGGUNAKAN SIG

2023-08-04T14:02:36+07:00

Banjir luapan sungai merupakan bencana yang sering terjadi di Kabupaten Madiun khusunya di kawasan pemukiman yang dekat dengan sungai yang dipengaruhi oleh berbagai faktor. Mulai dari intensitas curah hujan yang tinggi, jenis tanahnya, hingga kondisi topografinya. Bencana tersebut menyebabkan kerugian fisik, sosial, dan ekonomi. Tujuan yang ingin dicapai dalam penelitian ini adalah mengidentifikasi kawasan pemukiman rawan bencana banjir di Kabupaten Madiun yang nantinya dapat digunakan untuk upaya melakukan mitigasi bencana. Metode yang digunakan adalah pembobotan dan skoring terhadap parameter banjir yang kemudian dioverlay. Dari hasil analisis tersebut didapatkan peta pemukiman rawan bencana banjir di Kabupaten Madiun yang menunjukkan sebaran lokasi berpotensi banjir. Dimana lokasi rawan banjir tingkat tinggi terjadi di Kecamatan Kare dengan total luasan 564,685 ha. Kemudian kerawanan tingkat sedang berada di Kecamatan Balerejo dengan total luasan 615,712 ha dan kerawanan tingkat rendah berada di Kecamatan Dagangan dengan total luasan 30.027 ha. Hasil penelitian ini diharapkan dapat menjadi acuan atau referensi pada penelitian selanjutnya, serta dapat menjadi literatur kajian untuk mengambil kebijakan terkait penanggulangan banjir yang terjadi di Kabupaten Madiun.

PEMANFAATAN METODE MSARVI UNTUK MENGHITUNG INDEKS KERAPATAN VEGETASI MENGGUNAKAN CITRA SENTINEL 2A DI DESA CIHANJUANG KECAMATAN PARONGPONG KABUPATEN BANDUNG BARAT

2023-08-04T15:15:08+07:00

In calculating this vegetation index using Sentinel 2 Imagery in conducting research in Cihanjuang Village, related to the vegetation index, in this study will use the MSARVI Method to classify classes for each region in Cihanjuang Village because it is compared with Landsat 8 OLI (Operational Land) Imagery. Imager) the resolution produced from Sentinel Imagery is higher and more precise than Landsat 8 OLI (DR Putri et al, 2018). Image processing of Sentinel 2 Level-2A is carried out on the Google Earth Engine platform to obtain the transformation of the density of the vegetation index in the village. In making the MSARVI index the correction value for vegetation from the SAVI index (L) is integrated into this model which then produces the SARVI index with the blue band normalization of the ARVI index.