Analisis Perubahan Ruang Terbuka Hijau dengan Citra Resolusi Tinggi di Kota Depok

Syahbani Putra Gunadi; Syartinilia; Andrea Emma  Pravitasari

doi:10.29244/jp2wd.2025.9.1.14-28

Syahbani Putra Gunadi Program Magister Ilmu Pengelolaan Sumberdaya Alam dan Lingkungan, Sekolah Pasca Sarjana, IPB University, Gedung Sekolah Pascasarjana Lantai II Kampus IPB Baranangsiang Bogor, 16144, Indonesia
Syartinilia Departemen Arsitektur Lanskap, Fakultas Pertanian, IPB University, Jalan Meranti, Kampus IPB Dramaga, Kelurahan Dramaga, Kabupaten Bogor, 16680, Indonesia
Andrea Emma Pravitasari Departemen Ilmu Tanah dan Sumber Daya Lahan, Fakultas Pertanian, IPB University, Jalan Meranti, Kampus IPB Dramaga, Kelurahan Dramaga, Kabupaten Bogor, 16680, Indonesia; Pusat Pengkajian Perencanaan dan Pengembangan Wilayah (P4W), IPB University, Kampus IPB Baranangsiang, Jalan Raya Pajajaran, Bogor, Jawa Barat, 16127, Indonesia

DOI: https://doi.org/10.29244/jp2wd.2025.9.1.14-28

Keywords: green open space, land cover change, maximum likelihood, supervised classification

Abstract

The massive changes in land cover in Depok City, which serves as a buffer zone for the capital city of Jakarta, have led to a decrease in Green Open Space (GOS) due to the high demand for land for development. To monitor changes in GOS land cover and obtain accurate analysis results, appropriate tools, data, and methods are required. This study employed remote sensing and GIS techniques to assess GOS changes in Depok City between 2013 and 2021. The tools used included ArcGIS 10.8, Google Earth Pro, and a set of computers. The study utilized high-resolution Spot 6 and 7 satellite imagery with analysis conducted using the supervised classification method and the maximum likelihood algorithm. The results of this study produced land cover maps with very high accuracy, where the overall accuracy and kappa coefficient were 96% and 93% in 2013, and 97% and 92% in 2021, respectively. The classification results revealed a significant decrease in GOS over the past eight years, with a reduction of 20.2% of the total area, resulting in GOS coverage of only 31.3% or 6,239 ha in 2021. Most of the GOS reduction was caused by the expansion of built-up areas, which increased by 4,857 ha. Other changes were observed in water bodies 99 ha and open land 73 ha. The GOS analysis in Depok City using the supervised classification method on high-resolution Spot imagery proved to be highly accurate compared to previous studies that used Landsat 8 OLI imagery with the NDVI method.

References

Ahmad, A., Aboobaider, B., M, Isa, M. S. M., Md Hashim, N., Rosul, M., Muhamad, S., Man, S. 2014. Temporal changes in urban green space based on normalized difference vegetation index. Appl Math Sci. 8:2743–2751. doi:10.12988/ams.2014.432230.

Aji, G. P., Ardiansyah, M., Gunawan, A. 2020. Change and Prediction of Green Open Space Land Use in Depok City. 22(2):95–100.

Andiko, J. A., Duryat, D., & Darmawan, A. (2019). Efisiensi Penggunaan Citra Multisensor untuk Pemetaan Tutupan Lahan (The Efficiency of Multisensor Images for Land Cover Mapping). Jurnal Sylva Lestari, 7(3), 342–349. https://doi.org/10.23960/jsl37342-349 .

Arisondang, V., Sudarsono, B., Prasetyo, Y. 2015. Klasifikasi Tutupan Lahan Menggunakan Metode Segmentasi Berbasis Algoritma Multiresolusi (Studi Kasus Kabupaten Purwakarta, Jawa Barat). J Geod Undip. 4(1):9–19.

Badan Pusat Statistik. 2013. Badan Pusat Statistik - Kota Depok. Https://DepokkotaBpsGoId., siap terbit. [diakses 2023 Nov 16]. https://depokkota.bps.go.id/publication/2018/01/11/e976f69e00e1c6b7309b6528/statistik-daerah-kota-depok-2013.html.

Badan Pusat Statistik. 2020. Kota Depok dalam Angka. Badan Pusat Statistik Kota Depok BPS-Statistics Of Depok Municipality.

Badan Pusat Statistik. 2021. Badan Pusat Statistik - Kota Depok. Https://DepokkotaBpsGoId., siap terbit. [diakses 2023 Jun 13]. https://depokkota.bps.go.id/publication/2021/02/26/1f4ca1f1239982119750a6b8/kota-depok-dalam-angka-2021.html.

Badan Pusat Statistik Depok. 2022. Kota Depok Dalam Angka Depok Municipality in Figures 2022. MBA, Mufti Swaghara, Haniati Y, editor. ©BPS Kota Depok/BPS-Statistics of Depok Municipality.

Briassoulis, H. 2020. Analysis of Land Use Change: Theoretical and Modeling Analysis of Land Use Change: Theoretical and Modeling Approaches Approaches. [diakses 2021 Okt 5]. https://researchrepository.wvu.edu/rri-web-book.

Chiesura, A. 2004. The role of urban parks for the sustainable city. Landsc Urban Plan. 68(1):129–138. doi:10.1016/j.landurbplan.2003.08.003.

Chowdhury, S. 2023. Comparison of Accuracy and Reliability of Random Forest , Support Vector Machine , Artificial Neural Network and Maximum Likelihood method in Land use / cover Classification of Urban S ... Environ Challenges. November:100800. doi:10.1016/j.envc.2023.100800.

Congalton, R. G. 1991. A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ. 37(1):35–46. doi:10.1016/0034-4257(91)90048-B.

Costa, H., Almeida, D., Vala, F., Marcelino, F., Caetano, M. 2018. Land cover mapping from remotely sensed and auxiliary data for harmonized official statistics. ISPRS Int J Geo-Information. 7(4). doi:10.3390/ijgi7040157

Danoedoro, P. 2015. Pengaruh Jumlah dan Metode Pengambilan Titik Sampel Penguji terhadap Tingkat Akurasi Klasifikasi Citra Digital Penginderaan Jauh. Simp Nas Sains Geoinformasi ke-4. November 2015. [diakses 2023 Agu 17]. https://www.researchgate.net/publication/302581258_PENGARUH_JUMLAH_DAN_METODE_PENGAMBILAN_TITIK_SAMPEL_PENGUJI_TERHADAP_TINGKAT_AKURASI_KLASIFIKASI_CITRA_DIGITAL_PENGINDERAAN_JAUH#fullTextFileContent.

Department of the Interior U.S. Geological Survey. 2016. Landsat 8 Data Users Handbook. Nasa. 8 June:97. [diakses 2023 Des 1]. https://www.usgs.gov/landsat-missions/landsat-8-data-users-handbook.

Dong, S., Chen, Z., Gao, B., Guo, H., Sun, D., Pan, Y. 2020. Stratified even sampling method for accuracy assessment of land use/land cover classification: a case study of Beijing, China. Int J Remote Sens. 41(16):6427–6443. doi:10.1080/01431161.2020.1739349.

Fatahillah, A., Arifin, A., Jati, D. R. 2022. Analisis Perubahan Tutupan Lahan Di Kota Pontianak dengan Metode Penginderaan Jauh. Jurnal Teknologi Lingkungan Lahan Basah. 10(2):184. doi:10.26418/jtllb.v10i2.56311.

Febrianti, N., Sulma, S. 2018. Analisis Ruang terbuka hijau di DKI Jakarta menggunakan data Spot 6 Analisis Ruang Terbuka Hijau di DKI JAKARTA. March. [diakses 2023 Nov 30]. https://www.researchgate.net/publication/323799888_Analisis_Ruang_terbuka_hijau_DI_DKI_Jakarta_menggunakan_data_SPOT_6.

Franjaya, E. E., Syartinilia, Setiawan, Y. 2018. Modelling landscape change in paddy fields using logistic regression and GIS. IOP Conf Ser Earth Environ Sci. 149(1). doi:10.1088/1755-1315/149/1/012002.

Hawryło, P., Bednarz, B., Wężyk, P., Szostak, M. 2018. Estimating defoliation of Scots pine stands using machine learning methods and vegetation indices of Sentinel-2. Eur J Remote Sens. 51(1):194–204. doi:10.1080/22797254.2017.1417745.

JSoubirane. 2013. SPOT 6 & SPOT 7 Imagery User Guide.

Landis, J. R., Koch, G. G. 1977. The Measurement of Observer Agreement for Categorical Data Published by : International Biometric Society Stable URL : http://www.jstor.org/stable/2529310. Biometrics. 33(1):159–174.

Libriyanto, O., Pravitasari, A. E., Ardiansyah, M. 2022. Dynamics and Predictions Of Land-Use Changes in Serang Raya and Their Conformity to The Spatial Plan Of Banten Province. J Geogr. 14(1):33. doi:10.24114/JG.V14I1.24441.

Malik, A. 2016. Pengolahan Citra Digital dengan ER Mapper ver 7.0. [diakses 2024 Mar 23]. https://www.researchgate.net/publication/295073376_Pengolahan_Citra_Digital_dengan_ER_Mapper_ver_70.

Mishra, S., Shrivastava, P., Dhurvey, P. 2017. Change Detection Techniques in Remote Sensing: A Review. Int J Wirel Mob Commun Ind Syst. 4(1):1–8. doi:10.21742/ijwmcis.2017.4.1.01.

Munibah, K., Sitorus, S. R. P., Rustiadi, E., Gandasasmita, K., Hartrisari, H. 2019. Model Hubungan Antara Jumlah Penduduk dengan Luas Lahan Pertanian dan Permukiman (Studi Kasus DAS Cidanau, Provinsi Banten). J Ilmu Tanah dan Lingkung. 11(1):32–40. doi:10.29244/jitl.11.1.32-40.

Nakamo, S. J., Syartinilia, Setiawan, Y. 2022. Assessment of Land Cover Changes in Litumbandyosi-Gesimasowa Game Reserve using Remote Sensing and GIS. IOP Conf Ser Earth Environ Sci. 950(1). doi:10.1088/1755-1315/950/1/012083.

Oktaviani, A., Johan, Y. 2016. Perbandingan Resolusi Spasial, Temporal Dan Radiometrik Serta Kendalanya. J Enggano. 1(2):74–79. doi:10.31186/jenggano.1.2.74-79.

Oktavilia, S., Pujiati, A., Aulia, Y. (b): Shanty Oktavilia, Fafurida, Amin Pujiati, Yozi Aulia, Firmansyah (2022). Industrialization and Land Conversion in Indonesia. Environ Ecol Res. 10(6):627–634. doi:10.13189/eer.2022.100601.

Perumal, K., Bhaskaran, R. 2010. Supervised Classification Performance of Multispectral Images. 2(2):124–129. http://arxiv.org/abs/1002.4046.

Purboyo, A. A., Ramadhan, A. H., Safitri, E., Ridwana, R., Himayah, S. 2021. Identification of Green Open Spaces Using the Normalized Difference Vegetation Index in Depok City. J Sains Inf Geogr [J Sig]. 4(1):12–21. https://journal.umgo.ac.id/index.php/GEOUMGo/index.

Rahimi, A. 2016. A methodological approach to urban landuse change modeling using infill development pattern—a case study in Tabriz, Iran. Ecol Process. 5(1):1–15. doi:10.1186/S13717-016-0044-6/TABLES/6.

Ramadhan, F., Osly, P. J. 2019. Analisis Ketersediaan Ruang Terbuka Hijau dan Kecukupannya Di Kota Depok. J Infrastruktur . 5(1):7–11. doi:10.35814/INFRASTRUKTUR.V5I1.663.

Rini, M. S. 2018. Kajian kemampuan metode neural network untuk klasifikasi penutup lahan dengan menggunakan Citra Landsat-8 OLI (kasus di Kota Yogyakarta dan sekitarnya). Geomedia Maj Ilm dan Inf Kegeografian. 16(1). doi:10.21831/GM.V16I1.20974.

Selvaraj, R., Nagarajan, S. 2022 Jan 1. Change detection techniques for a remote sensing application: An overview. Cogn Syst Signal Process Image Process., siap terbit.

Septiani, R., Citra, I. P. A., Nugraha, A. S. A. 2019. Perbandingan Metode Supervised Classification dan Unsupervised Classification terhadap Penutup Lahan di Kabupaten Buleleng. J Geogr Media Inf Pengemb dan Profesi Kegeografian. 16(2):90–96. doi:10.15294/jg.v16i2.19777.

Setyani, W., Sitorus, S. R. P., Panuju, D. R. 2017. Analisis Ruang Terbuka Hijau Dan Kecukupannya Di Kota Depok. Bul Tanah dan Lahan. 1(1):121–127. [diakses 2023 Nov 30]. https://jurnal.ipb.ac.id/index.php/btanah/article/view/17701.

Sodikin, Nurkholifah, Said, M. 2021. Spatial Modeling of Mangrove Deforestation in Mahakam River Delta Kutai District Kertanegara Province of East Kalimantan. J Empower Community Educ. 1(3):180–186.

Tian, Y., Jim, C. Y., Wang, H. 2014. Assessing the landscape and ecological quality of urban green spaces in a compact city. Landsc Urban Plan. 121 October:97–108. doi:10.1016/j.landurbplan.2013.10.001.

Turner, B. L., Lambin, E. F., Verburg, P. H. 2021. From land-use/land-cover to land system science: This article belongs to Ambio’s 50th Anniversary Collection. Theme: Agricultural land use. Ambio. 50(7):1291–1294. doi:10.1007/s13280-021-01510-4.

Ustaoglu, E., Williams, B. 2017. Determinants of Urban Expansion and Agricultural Land Conversion in 25 EU Countries. Environ Manage. 60(4):717–746. doi:10.1007/S00267-017-0908-2.

Zhu, Z., Qiu, S., Ye, S. 2022. Remote sensing of land change: A multifaceted perspective. Remote Sens Environ. 282 February. doi:10.1016/j.rse.2022.113266.