Aplikasi object-based image analysis untuk identifikasi awal permukiman kumuh menggunakan Citra satelit worldview-2

https://doi.org/10.22146/mgi.32306

Prima Widayani(1*)

(1) Departemen Sains Informasi Geografi, Fakultas Geografi Universitas Gadjah Mada
(*) Corresponding Author

Abstract


Permukiman kumuh adalah perumahan yang mengalami penurunan kualitas fungsi sebagai tempat hunian.  Tidak layak huni karena ketidakteraturan bangunan, tingkat kepadatan bangunan yang tinggi, dan kualitas bangunan serta sarana dan prasarana yang tidak memenuhi syarat, (UU No.1 Tahun 2011). Permukiman kumuh banyak ditemukan di kota-kota besar termasuk di sebagian Kota Yogyakarta, karena tidak layak dari sisi keaman, kesehatan dan tidak sesuai dengan tata ruang kota, maka perlu penanganan kawasan permukiman kumuh ini. Sebagai upaya penanganan kawasan kumuh, dibutuhkan pemantauan kawasan permukiman kumuh secara berkelanjutan, sehingga perlu suatu identifikasi cepat untuk membantu pemetaan kawasan kumuh. Penelitian ini bertujuan untuk  identifikasi awal permukiman kumuh menggunakan pendekatan Object Base Image Analysis (OBIA) serta menguji kemampuan interpretasi OBIA dalam melakukan pengenalan permukiman kumuh berdasarkan ciri fisik permukiman. Data yang digunakan berupa Citra Satelit Worldview-2 tahun perekaman 2016, data kawasan kumuh Kota Yogyakarta dari program KOTAKU Yogyakarta, dan data survey lapangan. Alat yang digunakan berupa GPS, computer yang dilengkapi dengan software Ecognition, ENVI dan ArcGIS.10.2. Langkah pertama yang dilakukan sebelum menjalankan proses OBIA adalah mengenali karakteristik permukiman kumuh baik dari studi literatur, perundang-undangan maupun pengamatan lapangan. Berdasarkan studi sebelumnya dapat disusun aturan/kunci interpretasi untuk mendeteksi permukiman kumuh. Hasil identifikasi awal permukiman kumuh menggunakan OBIA dapat dilakukan berdasarkan analisis pola permukiman, kondisi jalan, tekstur, vegetasi dan jarak dengan sungai. Identifikasi permukiman kumuh di wilayah pinggiran sungai berdasarkan kondisi fisik permukiman menggunakan citra Wordview-2 mengasilkan ketelitian sebesar 82,14%.  Ketelitian ini dapat dikatakan baik sehingga kedepannya diharapkan dapat membantu identifikasi awal dalam rangka pemetaan permukiman kumuh terutama di wilayah pinggiran sungai

ABSTRACT

Slums are housing that have decreased the quality of function as dwellings. Uninhabitable due to building irregularities, high levels of building density, and the quality of buildings and facilities and infrastructure that do not meet the requirements, (Act No.1 of 2011). Slum settlements are found in large cities including in parts of Yogyakarta City, because they are not feasible in terms of security, health and are not in accordance with the urban spatial structure, it is necessary to deal with these slums. As an effort to deal with slum areas, it is necessary to monitor slum areas in a sustainable manner, so that a quick identification is needed to assist in mapping the slums. This study aims to initial identification of slums using the Object Base Image Analysis (OBIA) approach and to test the ability of OBIA's interpretation of the introduction of slums based on physical characteristics of settlements. The data used are recording Worldview-2 years Satellite Image 2016, data from Yogyakarta City slum area from Yogyakarta KOTAKU program, and field survey data. The tools used in the form of GPS, computers equipped with Ecognition, ENVI and ArcGIS software.10.2. The first step taken before carrying out the OBIA process is to recognize the characteristics of slums both from literature studies, legislation and field observations. Based on previous studies, rules / key interpretations can be prepared to detect slums. The results of the initial identification of slums using OBIA can be done based on the analysis of settlement patterns, road conditions, texture, vegetation and distance to the river. Identification of slums in the riverside area based on the physical conditions of settlements using Wordview-2 imagery resulted in accuracy of 82.14%. This accuracy can be said to be good so that in the future it is expected to be able to help initial identification in the framework of mapping slum settlements, especially in the riverside areas

 


Keywords


Permukiman kumuh; Object-Based Image Analysis; Worldview-2

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DOI: https://doi.org/10.22146/mgi.32306

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Volume 31 No 2 the Year 2017 for Volume 35 No 2 the Year 2021

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