Pemanfaatan Citra Landsat untuk Pemantauan Perubahan Tutupan Lahan Lima Dekade pada Kawasan Perkotaan dan Aglomerasi Industri Provinsi Jawa Timur

  • Akhmad Andi Saputra, ST., MT Universitas Gresik
  • Farid Hakim Yayasan Multidimensi Indonesia Cerdas
  • Marga Mandala Universitas Jember
  • Indarto Indarto Universitas Jember
Keywords: Perubahan, Tutupan Lahan, Urban, Landsat, Klasifikasi

Abstract

Penelitian ini bertujuan untuk menganalisis perubahan tutupan lahan (LULC) di kawasan perkotaan dan aglomerasi industri di Provinsi Jawa Timur (Surabaya, Sidoarjo, Gresik, dan Mojokerto), selama lima dekade terakhir. Perubahan tersebut dianalisis dengan membandingkan empat peta yang diinterpretasikan dari serangkaian citra Landsat (1972, 1997, 2014, dan 2021). Prosedur utama penelitian terdiri atas: pengumpulan data; survei lapangan; klasifikasi citra; dan interpretasi perubahan. Klasifikasi dilakukan dengan menggunakan algoritma kemungkinan maksimum yang mencapai keseluruhan dan akurasi kappa >75%. Klasifikasi tersebut menghasilkan delapan kelas, yaitu lahan terbangun (BU), lahan pertanian heterogen (HAL), tanah gundul (BS), sawah (PF), perairan terbuka (OW), vegetasi (VG), semak belukar (SH), dan lahan basah (WL). Analisis menunjukkan terdapat peningkatan BU di wilayah tersebut sebesar 655%. Alih fungsi lahan pertanian baik PF maupun HAL mengakibatkan peningkatan luas BU yang cukup signifikan. Antara tahun 1997 dan 2014, 303 km2 PF terkonversi menjadi BU, dan antara tahun 2014 dan 2021, seluas 308 km2 lainnya juga terkonversi. Selanjutnya HAL (-79%), BS (-56%), VG (-10%), dan SH (-100%) kembali menunjukkan penurunan. Sementara terjadi peningkatan besar pada OW dan WL, masing-masing sebesar 222 dan 67%.

References

Ahmed, I. M., & Alla, E. M. A. (2019). Landuse impact on environment of Tuti Island, Sudan. Geography, Environment, Sustainability, 12(3), 27–33. https://doi.org/10.24057/2071-9388-2018-13

Basheer, S., Wang, X., Farooque, A. A., Nawaz, R. A., Liu, K., Adekanmbi, T., & Liu, S. (2022). Comparison of Land Use Land Cover Classifiers Using Different Satellite Imagery and Machine Learning Techniques. Remote Sensing, 14(19), 1–18. https://doi.org/10.3390/rs14194978

Biehl, L., & Landgrebe, D. (2002). MultiSpec—a tool for multispectral–hyperspectral image data analysis. Computers & Geosciences, 28(10), 1153–1159. https://doi.org/https://doi.org/10.1016/S0098-3004(02)00033-X

Bogoliubova, A., & Tymków, P. (2014). Accuracy Assessment of Automatic Image Processing for Land Cover Classification of St . Petersburg Protected Area. Acta Scientiarum Polonorum, Administratio Locorum, 13(1–2), 5–22.

BPS-Statistics Indonesia. (1971). Penduduk Jawa Timur. BPS-Statistics Indonesia.

BPS-Statistics of Jawa Timur Province. (1997). Jawa Timur Dalam Angka 1997 [East Java in Figures 1997]. BPS-Statistics of Jawa Timur Province.

BPS-Statistics of Jawa Timur Province. (1998). Statistik Industri Besar dan Sedang di Jawa Timur 1998. BPS-Statistics of Jawa Timur Province.

BPS-Statistics of Jawa Timur Province. (2000). Jawa Timur Dalam Angka 2000. BPS-Statistics of Jawa Timur Province.

BPS-Statistics of Jawa Timur Province. (2015). Provinsi Jawa Timur dalam Angka 2015 [Jawa Timur Province in Figures 2015]. Statistics of Jawa Timur Province.

BPS-Statistics of Jawa Timur Province. (2017). Provinsi Jawa Timur dalam Angka 2017 [Jawa Timur Province in Figures 2017]. Statistics of Jawa Timur Province.

BPS-Statistics of Jawa Timur Province. (2019). Luas Pemeliharaan Ikan Darat Menurut Kabupaten/Kota (Ha), 2014. https://jatim.bps.go.id/statictable/2017/06/19/571/luas-area-pemeliharaan-ikan-darat-menurut-kabupaten-kota-di-jawa-timur-ha-2014.html

BPS-Statistics of Jawa Timur Province. (2021). Provinsi Jawa Timur dalam Angka 2021 [Jawa Timur Province in Figures 2021]. BPS-Statistics of Jawa Timur Province.

BPS-Statistics of Jawa Timur Province. (2022). Provinsi Jawa Timur dalam Angka 2022 [Jawa Timur Province in Figures 2022]. Statistics of Jawa Timur Province.

BPS-Statistics of Jawa Timur Province. (2023). Provinsi Jawa Timur dalam Angka 2023 [Jawa Timur Province in Figures 2023]. BPS-Statistics of Jawa Timur Province.

Carrão, H., Caetano, M., & Coelho, P. S. (2007). Sample design and analysis for thematic map accuracy assessment: An approach based on domain estimation for the validation of land cover products. Proceedings, 32nd International Symposium on Remote Sensing of Environment: Sustainable Development Through Global Earth Observations, January.

Chavez, P. S. (1988). An improved dark-object subtraction technique for atmospheric scattering correction of multispectral data. Remote Sensing of Environment, 24(3), 459–479. https://doi.org/https://doi.org/10.1016/0034-4257(88)90019-3

Dastgerdi, A. S., Sargolini, M., Pierantoni, I., & Stimilli, F. (2019). Toward An Innovative Strategic Approach For Sustainable Management Of Natural Protected Areas In Italy. Geography, Environment, Sustainability. https://doi.org/10.24057/2071-9388-2019-143

Dewi, E. K., & Trisakti, B. (2017). COMPARING ATMOSPHERIC CORRECTION METHODS FOR LANDSAT OLI DATA. International Journal of Remote Sensing and Earth Sciences (IJReSES), 13(2), 105. https://doi.org/10.30536/j.ijreses.2016.v13.a2472

East Java Governor’s Decree. (2020). Keputusan Gubernur Jawa Timur Nomor 188/538/KPTS/013/2020 Tentang Upah Minimum Kabupaten/Kota di Jawa Timur Tahun 2021 [East Java Governor’s Decree Number 177/538/KPTS/013/2020 About Minimum Wages of Municipality/Regency in East Java Province].

Elias, E., Seifu, W., Tesfaye, B., & Girmay, W. (2019). Impact of land use/cover changes on lake ecosystem of Ethiopia central rift valley. Cogent Food & Agriculture, 5(1), 1595876. https://doi.org/10.1080/23311932.2019.1595876

Fonji, S. F., & Taff, G. N. (2014). Using satellite data to monitor land-use land-cover change in North-eastern Latvia. SpringerPlus, 3(1), 1–15. https://doi.org/10.1186/2193-1801-3-61

Foody, G. (2008). Harshness in image classification accuracy assessment. International Journal of Remote Sensing, 29(11), 3137–3158. https://doi.org/10.1080/01431160701442120

Foody, G. M. (2004). Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy. In Photogrammetric Engineering and Remote Sensing (Vol. 70, Issue 5, pp. 627–633). American Society for Photogrammetry and Remote Sensing. https://doi.org/10.14358/PERS.70.5.627

Hardjosoekarto, S. (1982). Permasalahan Sektor Palawija Dalam Upaya Swasembada Pangan. Analisis CSIS. https://journals.csis.or.id/index.php/analisis/article/view/622

Hassen, E. E., & Assen, M. (2018). Land use/cover dynamics and its drivers in Gelda catchment, Lake Tana watershed, Ethiopia. Environmental Systems Research, 6(1). https://doi.org/10.1186/s40068-017-0081-x

Kelly, M., Blanchard, S. D., Kersten, E., & Koy, K. (2011). Terrestrial remotely sensed imagery in support of public health: New avenues of research using object-based image analysis. Remote Sensing, 3(11), 2321–2345. https://doi.org/10.3390/rs3112321

Klimanova, O., Naumov, A., Greenfieldt, Y., Prado, R. B., & Tretyachenko, D. (2017). Recent regional trends of land use and land cover transformations in Brazil. Geography, Environment, Sustainability, 10(4), 98–116. https://doi.org/10.24057/2071-9388-2017-10-4-98-116

Klyuev, N. N. (2019). The spatial analyses of natural resources use in Russia for 1990-2017. Geography, Environment, Sustainability, 12(4), 203–211. https://doi.org/10.24057/2071-9388-2018-65

Llano, X. C. (2019). AcATaMa - QGIS plugin for Accuracy Assessment of Thematic Maps (19.11.21). https://plugins.qgis.org/plugins/AcATaMa/

Łucka, D. (2018). How to build a community. New Urbanism and its critics. Urban Development Issues, 59(1), 17–26. https://doi.org/https://doi.org/10.2478/udi-2018-0025

Mangmeechai, A. (2020). Effects of rubber plantation policy on water resources and landuse change in the Northeastern region of Thailand. Geography, Environment, Sustainability, 13(2), 73–83. https://doi.org/10.24057/2071-9388-2019-145

Mtibaa, S., & Irie, M. (2016). Land cover mapping in cropland dominated area using information on vegetation phenology and multi-seasonal Landsat 8 images. Euro-Mediterranean Journal for Environmental Integration, 1(1). https://doi.org/10.1007/s41207-016-0006-5

National Aeronautics and Space Administration [NASA] JPL. (2013). NASA Shuttle Radar Topography Mission Global 1 arc second [Data set]. NASA EOSDIS Land Processes DAAC. https://doi.org/10.5067/MEaSUREs/SRTM/SRTMGL1.003

Nguyen, L. B. (2020). Land cover change detection in northwestern Vietnam using Landsat images and Google Earth Engine. Journal of Water and Land Development, No 46, 162–169.

Phiri, D., & Morgenroth, J. (2017). Developments in Landsat land cover classification methods: A review. Remote Sensing, 9(9). https://doi.org/10.3390/rs9090967

Ptak, M., & Ławniczak, A. E. (2012). Changes in land use in the buffer zone of lake of the Mała Wełna catchment. Limnological Review, 12(1), 35–44. https://doi.org/https://doi.org/10.2478/v10194-011-0043-z

QGIS Development Team. (2022). QGIS User Guide Raster Analysis. https://docs.qgis.org/3.22/en/docs/user_manual/processing_algs/gdal/rasteranalysis.html#sieve

Suprajaka, S. (2009). IDENTIFIKASI FAKTOR-FAKTOR PENGARUH FRAGMENTASI LAHAN PERTANIAN. GEOMATIKA, 15(2). http://jurnal.big.go.id/index.php/GM/article/view/250

US. Geological Survey. (2019). Landsat Levels of Processing. https://www.usgs.gov/land-resources/nli/landsat/landsat-levels-processing

Viera, A. J., & Garrett, J. M. (2005). Understanding interobserver agreement: The kappa statistic. Family Medicine, 37(5), 360–363.

Widiatmaka, Ambarwulan, W., Setiawan, Y., & Walter, C. (2016). Assessing the suitability and availability of land for agriculture in tuban regency, East Java, Indonesia. Applied and Environmental Soil Science, 2016. https://doi.org/10.1155/2016/7302148

website, https://tanahair.indonesia.go.id/portal-web/

Published
2023-10-31