PENENTUAN LOKASI PERUMAHAN BERDASARKAN INTERPRETASI CITRA IKONOS DAN SISTEM INFORMASI GEOGRAFI DI KECAMATAN JETIS KABUPATEN BANTUL

The aims of the research are to determine priority areas for housing development using Ikonos satellite imagery and Geographic Information Systems (GIS) and to understand the Ikonos imagery capabilities in intercepting physical parameters that effect the determination of land for developing residenc...

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Main Authors: , HENNY INDRIANA, , Drs. Retnadi Heru Jatmiko, M.Sc.
格式: Theses and Dissertations NonPeerReviewed
出版: [Yogyakarta] : Universitas Gadjah Mada 2013
主題:
ETD
在線閱讀:https://repository.ugm.ac.id/125063/
http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=65228
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總結:The aims of the research are to determine priority areas for housing development using Ikonos satellite imagery and Geographic Information Systems (GIS) and to understand the Ikonos imagery capabilities in intercepting physical parameters that effect the determination of land for developing residences. The primary data source was obtained by interpreting the Ikonos satellite imagery and field surveys. Research method used for determining the priority areas is to base the assessment against some of the parameters used, both the physical parameters and the accessibility parameters of the land. Physical parameters used include land slope, land use, landform, soil bearing capacity, soil drainage, water table depth, while the accessibility factor used are the distance to the main street and the distance to the city center. GIS is used for the overlaying process by weighting each parameter used. The findings of the research showed the value of Ikonos image interpretation accuracy is 85,71% for the use of land, 90, 47% for the landform, and 80,95% for the the water table depth and there are 4 classes of priority areas for housing. Those are a priority I (P1) of 73,03 ha, priority II (P2) of 22,18 ha, priority III (P3) of 39,52 ha and is not prioritized (N) of 2246,35 ha. Determining the location for residential development using weighting methods on each of these parameters achieves effective result.