Analisis Pola Perubahan Lahan Terbangun Berdasarkan Kombinasi Metode Klasifikasi Menggunakan Citra Penginderaan Jauh Multitemporal di Kota Surabaya

Ramadhan, Fendra Dwi (2021) Analisis Pola Perubahan Lahan Terbangun Berdasarkan Kombinasi Metode Klasifikasi Menggunakan Citra Penginderaan Jauh Multitemporal di Kota Surabaya. Masters thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Perkembangan suatu kawasan perkotaan dapat terlihat dari perubahan fisik yang ditandai dengan bertambahnya blok wilayah berupa kumpulan piksel yang diidentifikasi sebagai wilayah yang terbangun termasuk lahan kosong serta terlihat dalam citra yang terbebas dari objek vegetasi dan objek badan air. Dalam upaya mengendalikan intensitas lahan terbangun perkotaan, dibutuhkan suatu upaya pemantauan kondisi perubahan lahan terbangun di Kota Surabaya berbasis spasial dan temporal. Dalam penelitian ini, identifikasi lahan terbangun dilakukan berdasarkan metode: klasifikasi terbimbing (maximum likelihood berbasis training area) serta kombinasi indeks spektral berbasis algoritma yang terdiri dari kombinasi A (UI–NDVI–MNDWI) dan kombinasi B (NDBI–NDVI–MNDWI). Proses segmentasi objek diterapkan berdasarkan metode Otsu thresholding. Metode analisis pola dilakukan melalui pendekatan landscape metrics, standard deviational ellipse dan perhitungan kecepatan perubahan luasan lahan terbangun. Pemodelan matematis regresi linier berganda ditentukan dengan mempertimbangkan faktor-faktor pendorong perubahan lahan terbangun yang telah ditentukan. Hasil penelitian menunjukkan bahwa kombinasi A dan kombinasi B memiliki tren yang sama yaitu pada tahun 2015 ke 2017 mengalami penurunan luasan lahan terbangun sedangkan pada tahun 2017 ke 2019 mengalami peningkatan. Uji akurasi menggunakan matriks konfusi menunjukkan bahwa semua metode yang diterapkan memiliki nilai OA (overall accuracy) diatas 80% serta nilai koefisien Kappa yang termasuk dalam kategori sedang hingga tinggi. Kota Surabaya memiliki tipe persebaran piksel lahan terbangun bersifat mengelompok, serta pola arah lahan terbangun menunjukkan kecondongan perubahan kearah sisi barat dan timur dengan konsentrasi lahan terbangun paling dominan di tengah pusat kota dan meluas di pinggiran perbatasan kota, sehingga diidentifikasi memiliki pola perkembangan kota sentrifugal konsentris dan kota berbentuk kipas. Faktor-faktor pendorong yaitu populasi (x1), jalan utama (x2), jalan non utama (x3), sungai (x4) dan CBD (x5) cukup dapat memberikan dampak terhadap penentuan wilayah lahan terbangun (y). Nilai R keseluruhan didapatkan sebesar 0,601248 yang berarti terjadi hubungan yang sedang antara seluruh faktor pendorong terhadap lahan terbangun, sedangkan nilai R2 menunjukkan presentase sumbangan pengaruh seluruh faktor pendorong terhadap lahan terbangun didapatkan sebesar 36,1499%.
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The development of an urban area can be seen from the physical changes marked by the increase in block areas in the form of a collection of pixels which are identified as built-up areas including bare land and seen in imagery that are free from vegetation objects and water bodies objects. To control the intensity of urban built-up land, an effort to monitor the conditions of changes in built-up land in the city of Surabaya is needed on a spatiotemporal basis. In this study, the identification of built-up land was performed by the following methods: supervised classification (maximum likelihood-based on training area) and a combination of algorithm-based spectral indices consisting of combination A (UI–NDVI– MNDWI) and combination B (NDBI–NDVI–MNDWI). The object segmentation process is applied based on the Otsu thresholding method. The method of pattern analysis is carried out through the landscape metrics approach, standard deviation ellipse, and the calculation of the speed of change in the area of built-up land. Multiple linear regression mathematical modeling is determined by considering the determined driving factors of built-up land changes. The results show that combination A and combination B have the same trend, namely that from 2015 to 2017 there was a decrease in built-up land, while from 2017 to 2019 it had increased. The accuracy test using a confusion matrix shows that all the methods applied have OA (overall accuracy) values above 80% and the Kappa coefficient values are included in the medium to high category. The city of Surabaya has the type of distribution of built-up land pixels that are clustered, and the pattern of the direction of the built land shows a tilt towards the west and east sides with the most dominant built-up land concentration in the middle of the city center and extends to the outskirts of the city borders, so it is identified as having a centrifugal-concentric city development pattern and fan-shaped-city. Driving factors, namely population (x1), main roads (x2), non-main roads (x3), rivers (x4) and CBD (x5) can have a sufficient impact on the determination of the built-up land area (y). The overall R-value is 0.601248, which means that there is a moderate relationship between all driving factors on the built-up land, while the R2 value shows the percentage of the contribution of the influence of all driving factors on the built-up land is 36.1499%.

Item Type:	Thesis (Masters)
Uncontrolled Keywords:	Kombinasi Metode Klasifikasi, Kota Surabaya, Lahan Terbangun, Pola Perubahan, Sentinel-2, Combination of Classification Method, Surabaya City, Built-up Land, Pattern Change, Sentinel-2
Subjects:	G Geography. Anthropology. Recreation > G Geography (General) > G70.212 ArcGIS. Geographic information systems. G Geography. Anthropology. Recreation > G Geography (General) > G70.217 Geospatial data G Geography. Anthropology. Recreation > G Geography (General) > G70.5.I4 Remote sensing G Geography. Anthropology. Recreation > GA Mathematical geography. Cartography > GA105.3 Cartography.
Divisions:	Faculty of Civil, Planning, and Geo Engineering (CIVPLAN) > Geomatics Engineering > 29101-(S2) Master Thesis
Depositing User:	Mr. Fendra Dwi Ramadhan
Date Deposited:	23 May 2021 03:58
Last Modified:	24 May 2021 03:56
URI:	http://repository.its.ac.id/id/eprint/84231

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