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Kesesuaian dan Arahan Penggunaan Lahan Berdasarkan Rencana Pola Ruang Wilayah di Hulu Daerah Aliran Sungai Kelara Arsyad, Usman; Soma, Andang Suryana; Wahyuni, Wahyuni; Arief, Tita Rahayu
Jurnal Hutan dan Masyarakat VOLUME 9 NOMOR 2, DESEMBER 2017
Publisher : Fakultas Kehutanan, Universitas Hasanuddin

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Abstract

This study aimed to analyze the compatibility between the land cover spatial pattern plan and determine the direction of land use in the event of a discrepancy. This research was conducted on the Kelara Upstream Watershed located in gowa and jeneponto using land cover maps generated from landsat imagery interpretation 8. Then overlay to map the spatial pattern plan. Then determined the order of land use is done when there is a discrepancy between the results of the overlay with maps of land cover spatial pattern plan. The result showed that 41,05% of the total area of the Kelara Upstream Watershed of 28.185,68 ha a land use form of a orchards. After overlay discovered discrepancy land cover maps with maps of spatial pattern plan. Based on a map spatial pattern plan that should in reality the field is man made forest, orchards, dryland agriculture and rice field. According to these condition the specified order of land use that is Hkm (Community Forest) with agroforestry and Agroforestry Systems. Rice field In the Protected and Production forest order to intensification land use and plantations forest, orchards and dry land agriculture order to Community Forest with agroforestry systems . In the area of cultivation the land use rice field, orchards and dryland agriculture order to agroforestry systems.
THE PERFORMANCE OF LAND USE CHANGE CAUSATIVE FACTOR ON LANDSLIDE SUSCEPTIBILITY MAP IN UPPER UJUNG-LOE WATERSHEDS SOUTH SULAWESI, INDONESIA Soma, Andang Suryana; Kubota, Tetsuya
Geoplanning: Journal of Geomatics and Planning Vol 4, No 2 (2017): (October 2017)
Publisher : Department of Urban and Regional Planning, Diponegoro University

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Abstract

The study aims to develop and apply land use change (LUC) performance on landslide susceptibility map using frequency ratio (FR), and Logistic regression (LR) method in a geographic information system. In the study area, Upper Ujung-loe Watersheds area of Indonesia, landslides were detected using field survey and air photography from time series data image of Google Earth Pro from 2012 to 2016 and LUC from 2004 to 2011. Landslide susceptibility map (LSM) was constructed using FR and LR with nine causative factors. The result indicated that LUC affect the production of LSM. Validation of landslide susceptibility was carried out in this study at both with and without LUC causative factors. First, performances of each landslide model were tested using AUC curve for success and predictive rate. The highest value of predictive rate at with LUC in both FR and LR method were 83.4 % and 85.2 %, respectively. In the second stage, the ratio of landslides falling on high to a very high class of susceptibility was obtained, which indicates the level of accuracy of the method.LR method with LUC had the highest accuracy of 80.24 %. Taken together, the results suggested that changing the vegetation to another landscape causes slopes unstable and increases probability to landslide occurrence.
ANALISIS TINGKAT KERAWANAN TANAH LONGSOR MENGGUNAKAN METODE FREKUENSI RASIO DI DAERAH ALIRAN SUNGAI BIALO Fadilah, Nurul; Arsyad, Usman; Soma, Andang Suryana
PERENNIAL Vol 15, No 1 (2019)
Publisher : Forestry Faculty of Universitas Hasanuddin

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Abstract

Landslide is a movement of soil with slope direction and moves it on a slide. This study aimed to predict the landslide susceptibility map by using a frequency ratio. It used seven causative factors, such as slope, curvature, land use, lithology, distance to a river, distance to lineament, and rainfall. The result showed the AUC of success rate and predicted rate produced high accuracy with 0.907 and 0.904, respectively.  According to the frequency ratio, the slope was the most influential than the other causative factors with 7.15. The landslide susceptibility divided into five classes, i.e. very low, low, moderate, high, and very high.  Landslide susceptibility with very high and high was 19%.  Moreover, classes susceptibility of very low, low, and moderate were 71%. The presentation of very high and high susceptibility is low, but it was located on an upper stream, and it will be a danger if to the downstream.