Analisis Identifikasi Jaringan Drainase Permukaan Menggunakan Metode Penghalusan DEM LiDAR Feature-Preserving Dan Edge-Preserving Smoothing (Studi Kasus: Sungai Kedungbener, Kecamatan Kebumen)

Bawasir, Arizal (2021) Analisis Identifikasi Jaringan Drainase Permukaan Menggunakan Metode Penghalusan DEM LiDAR Feature-Preserving Dan Edge-Preserving Smoothing (Studi Kasus: Sungai Kedungbener, Kecamatan Kebumen). Undergraduate thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Informasi akurat terkait konektivitas hidrologi akan diperlukan dalam aliran permukaan daratan yang terkena dampak bencana alam. Seperti halnya pada wilayah Kecamatan Kebumen yang merupakan daerah dengan tingkat kerawanan banjir tinggi, termasuk di daerah sekitar Sungai Kedungbener. DEM resolusi tinggi yang dihasilkan dari data LiDAR dapat memetakan kondisi permukaan secara akurat. Tetapi pada saat yang sama, permukaan topografi DEM LiDAR sangat kompleks, yang mana berkontribusi pada tampilan kasar DEM LiDAR.
Metode penghalusan feature-preserving dan edge-preserving secara umum dapat menghasilkan smoothed DEM LiDAR yang optimal pada nilai parameter tertentu dalam algoritmanya. DEM LiDAR optimal untuk kedua metode penghalusan ditentukan berdasarkan konsistensi efek penghalusannya menggunakan asesmen Circular Variance of Aspect (CVA) pada tiap-tiap parameter algoritma. DEM optimal didapatkan pada parameter kernel size 25-31 piksel; normal difference threshold 20o-25o; iterasi 10 kali (metode feature-preserving) dan sigma spasial 1,7-2,3 piksel; sigma range 2,0-10,0 piksel (metode edge-preserving). Hasil smoothing optimal pada dua metode penghalusan, selanjutnya disebut sebagai Feature-preserving Smoothed DEM (FPDEM-S) dan Edge-preserving Smoothed DEM (EPDEM-S).
Jaringan drainase yang dihasilkan dari FPDEM-S dan EPDEM-S dapat mengidentifikasi hingga fitur drainase kecil di sekitar sawah dan pemukiman. Dari hasil validasi fitur drainase besar terhadap vektor sungai RBI skala 1:25.000, fitur drainase pada vektor RBI teridentifikasi sebanyak 10 dari 11 fitur drainase besar pada jaringan drainase FPDEM-S maupun EPDEM-S. FPDEM-S dan EPDEM-S memiliki karakteristik morfometri aliran dan watershed yang hampir sama, dengan rasio panjang aliran pada FPDEM-S memiliki konsistensi 7% lebih baik. Kedua jaringan drainase menghasilkan karakteristik watershed yang serupa, memiliki densitas drainase tinggi, serta bentuk watershed oval mendekati sirkular.
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required in land surface flows affected by natural disasters. As is the case in the Kebumen District which is an area with a high level of flood vulnerability, including in the area around the Kedungbener River. High-resolution DEMs generated from LiDAR data could have accurate surface conditions. But at the same time, the topographic surfaces are highly complex, which contributes to the rough appearance of many LiDAR DEMs.
The feature-preserving and edge-preserving smoothing methods in general can produce an optimal smoothed LiDAR DEM at certain parameter values in the algorithms. The optimal LiDAR DEM for both smoothing methods was determined based on the consistency of the smoothing effect using a Circular Variance of Aspect (CVA) assessment for each parameter. Optimal DEM is obtained at kernel size parameters of 25-31 pixels; normal difference threshold of 20o-25o; iteration 10 times (feature preservation method) and sigma spatial 1.7-2.3 pixels; sigma range of intensity 2.0-10.0 (edge-preserving method). Optimal smoothing results in two smoothing methods, hereinafter referred to as FPDEM-S (Feature-preserving Smoothed DEM) and EPDEM-S (Edge-preserving Smoothed DEM)
The drainage networks generated from FPDEM-S and EPDEM-S can identify up to small drainage features around rice fields and settlements. From the results of the validation of large/main drainage features on the RBI river vector (scale of 1:25,000), drainage features in the RBI vector identified as many as 10 of the 11 large drainage features in the FPDEM-S and EPDEM-S drainage networks. FPDEM-S and EPDEM-S drainage networks have almost the same stream and watershed morphometric characteristics, with the stream length ratio in FPDEM-S has 7% better consistency. The two drainage networks produce similar watershed characteristics, have high drainage density, and have an oval nearly circular shape.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	LiDAR DEM, Feature-preserving smoothing, Edge-preserving smoothing, CVA, drainage features, watershed, stream, morphometry.
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.212 ArcGIS. Geographic information systems. G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography > GA139 Digital Elevation Model (computer program) T Technology > T Technology (General) > T57.5 Data Processing T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29202-(S1) Undergraduate Thesis
Depositing User:	Arizal Bawasir
Date Deposited:	14 Aug 2021 13:19
Last Modified:	14 Aug 2021 13:19
URI:	http://repository.its.ac.id/id/eprint/86434

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