APLIKASI CITRA SENTINEL-2 UNTUK PEMETAAN TUTUPAN DAN PERUNTUKAN LAHAN PADA TINGKAT DESA

Authors

  • indarto indarto Universitas Jember
  • Marga Mandala Universitas Jember
  • Fery Febrian Arifin Universitas Jember
  • Farid Lukman Hakim Universitas Jember

DOI:

https://doi.org/10.24114/jg.v12i02.16970

Abstract

Sentine-2 menjanjikan citra yang gratis, pada ketelitian spasial sedang dan ketelitian spektral tinggi. Data citra ini mungkin dapat digunakan sebagai dasar pemetaan tutupan lahan (land cover) dan pruntukan lahan (land use) sampai dengan level Desa. Artikel ini bertujuan untuk membandingkan dan mengevaluasi peta tematik yang dihasilkan dari: (1) Klasifikasi dari citra Sentinel-2A, (b) digitasi manual dari Google Earth Image, (c) dan peta RBI (Rupa Bumi Indonesia). Citra Sentinel-2A, citra google earth dan peta RBI digital  digunakan sebagai input utama. Pengolahan citra Sentinel-2A mencakup: atmosferic correction, image composite, klasifikasi terbimbing, koleksi training area,  dan  uji-akurasi. Selanjutnya, ke tiga jenis peta tematik yang dihasilkan digunakan untuk membandingkan luasan per jenis tutupan lahan  yang dipetakan dan interpretasi perubahan peruntukan lahan yang terjadi. Selanjutnya, wilayah empat desa digunakan sebagai sampel pengukuran. Penelitian menghasilkan peta tematik tutupan dan peruntukan lahan pada level Desa. Perbandingan peta tematik menunjukkan bahwa citra Sentinel mampu untuk menangkap fitur tutupan lahan yang utama (yaitu: Lahan-sub-optimal kering, lahan irigasi, lahan non-irigasi, area terbangun, hutan-perkebunan, dan badan air) pada level desa. Lebih lanjut peta yang dihasilkan dari citra Sentinel dapat digunakan untuk memperbaharui, perencanaan dan evaluasi kegiatan pembangunan di Desa. Kata Kunci: Sentinel-2A, Pemetaan, Tutupan Lahan, peruntukan lahan, desa.Sentinel-2 provide a free of cost imagery in medium spatial and high spectral resolutions. These data promise a rapid, low-cost and easy to apply imagery for the end-user.  These free data may produce a rationale thematic land cover and land use (LCLU) map at the village level. This paper aims to compare and to evaluate the thematics maps created by (a) Sentinel-2, (b) digitalisation from Google Earth and (c) RBI (Rupa Bumi Indonesia) Digital Map. Sentinel-2 image, google earth image, and RBI digital map used as the primary input. The treatment of sentinel 2A imagery consists of atmospheric correction, image composite, supervised classification, collecting training areas, and accuracy assessment.  The three types of maps use to compare area extent mapped for each type of land cover (LC), and the interpretation of land-use change occurred. Four villages used as samples of measurement. The research produces thematic LCLU maps at the village level. Comparison of maps shows that Sentinel capable of capturing major LC (i.e., Dry-marginal land, non-irrigated area, irrigated area, pavement areas, forest - plantation, and water body) at the village level.  Moreover, Sentinel-2A produce more detail of land cover type. Finally, the maps derived from Sentinel data provide data for up-dating, planning and evaluation of village development.Keywords :  Sentinel-2A, mapping, land cover, land use, village.

References

Abdi, A. M. (2019) ˜Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data™, GIScience & Remote Sensing. Taylor & Francis, pp. 1“20. doi: 10.1080/15481603.2019.1650447.

BIG (2019) Indonesia Geospatial Portal. Available at: http://tanahair.indonesia.go.id/portal-web (Accessed: 15 December 2019).

Bolton, D. K. et al. (2020) ˜Continental-scale land surface phenology from harmonized Landsat 8 and Sentinel-2 imagery™, Remote Sensing of Environment. Elsevier Inc., 240. doi: 10.1016/j.rse.2020.111685.

BPS, S. (2019) Kabupaten Situbondo dalam angka tahun 2019 (Regency Situbondo in number). Situbondo. Available at: https://situbondokab.bps.go.id/publication/2019/12/26/ee20f467bae2040464413b80/statistik-daerah-kabupaten-situbondo-2019.html (Accessed: 25 May 2020).

Campbell, J. B. and Wynne, R. H. (2011) Introduction to remote sensing. Guilford Press.

Clerici, N., Valbuena Calderón, C. A. and Posada, J. M. (2017) ˜Fusion of sentinel-1a and sentinel-2A data for land cover mapping: A case study in the lower Magdalena region, Colombia™, Journal of Maps. doi: 10.1080/17445647.2017.1372316.

Congedo, L. (2016) Semi-Automatic Classiï¬cation Plugin Documentation. doi: 10.13140/RG.2.2.29474.02242/1.

Efroymson, R. A. et al. (2016) ˜A causal analysis framework for land-use change and the potential role of bioenergy policy™, Land Use Policy. Elsevier Ltd, 59, pp. 516“527. doi: 10.1016/j.landusepol.2016.09.009.

Eremiášová, R. and Skokanová, H. (2009) ˜Land Use Changes (Recorded in Old Maps) and Delimitation of the Most Stable Areas from the Perspective of Land Use in the KaÅ¡perské Hory Region™, Journal of Landscape Ecology. Berlin: Sciendo, 2(1), pp. 20“34. doi: https://doi.org/10.2478/v10285-012-0012-5.

Esa (2013) SENTINEL-2 User Handbook Sentinel-2 User Handbook SENTINEL-2 User Handbook Title Sentinel-2 User Handbook Issue 1 Revision 1 SENTINEL-2 User Handbook.

EUROSTAT (2001) Manual of concepts on land cover and land use information systems. Available at: http://europa.eu.int (Accessed: 17 May 2020).

Foody, G. (2008) ˜Harshness in image classification accuracy assessment™, International Journal of Remote Sensing. Taylor and Francis Ltd., 29(11), pp. 3137“3158. doi: 10.1080/01431160701442120.

Foody, G. M. (2002) ˜Status of land cover classification accuracy assessment™, Remote Sensing of Environment. Elsevier Inc., pp. 185“201. doi: 10.1016/S0034-4257(01)00295-4.

Foody, G. M. (2004) ˜Thematic map comparison: Evaluating the statistical significance of differences in classification accuracy™, Photogrammetric Engineering and Remote Sensing. American Society for Photogrammetry and Remote Sensing, pp. 627“633. doi: 10.14358/PERS.70.5.627.

Hakim, Y. F., Riqqi, A. and Harto, A. B. (2014) ˜Kontrol Kualitas Dalam Alur Produksi Kartografi Peta RBI di Badan Informasi Geospasial™, GEOMATIKA, 20(1).

Hariyono, M. I. (no date) ˜Kajian Perubahan Penutup Lahan Peta Rupabumi pada Skala yang Berbeda™.

Khorram, S. et al. (2013) ˜Digital Image Acquisition: Preprocessing and Data Reduction BT - Handbook of Satellite Applications™, in Pelton, J. N., Madry, S., and Camacho-Lara, S. (eds). New York, NY: Springer New York, pp. 809“837. doi: 10.1007/978-1-4419-7671-0_46.

Lambin, E. F. et al. (2001) ˜The causes of land-use and land-cover change: Moving beyond the myths™, Global Environmental Change. Elsevier Ltd, pp. 261“269. doi: 10.1016/S0959-3780(01)00007-3.

Landgrebe, D. (2015) MultiSpec Tutorial: Supervised Classification-Select Training Fields. Available at: https://engineering.purdue.edu/~biehl/MultiSpec/documentation.html (Accessed: 26 November 2019).

LAPAN (2015) ˜LAPAN Pedoman Pengolahan Data Penginderaan Jauh Landsat 8 untuk MPT™. Available at: file:///F:/BISMILLAH/Ris/000_Buku_Pedoman_TSM_final.pdf.

Li, G. et al. (2012) ˜A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region™, ISPRS Journal of Photogrammetry and Remote Sensing, 70, pp. 26“38. doi: 10.1016/j.isprsjprs.2012.03.010.

Lillesand, T. M., Kiefer, R. W. and Chipman, J. W. (2008) Remote Sensing and Image Interpretation. 6th edn. New Jersey.

Lopes, M. et al. (2020) ˜Combining optical and radar satellite image time series to map natural vegetation: savannas as an example™, Remote Sensing in Ecology and Conservation. Wiley-Blackwell. doi: 10.1002/rse2.139.

Martínez, S. and Mollicone, D. (2012) ˜From Land Cover to Land Use: A Methodology to Assess Land Use from Remote Sensing Data™, Remote Sensing. MDPI AG, 4(4), pp. 1024“1045. doi: 10.3390/rs4041024.

Moran, E. F. (2010) ˜Land Cover Classification in a Complex Urban-Rural Landscape with Quickbird Imagery™, Photogrammetric engineering and remote sensing. NIH Public Access, 76(10), p. 1159.

Mulyani, A., Priyono, A. and Agus, F. (2013) ˜Semiarid Soils of Eastern Indonesia: Soil Classification and Land Uses™, in, pp. 449“466. doi: 10.1007/978-94-007-5332-7_24.

Mulyani, A. and Sarwani, M. (2013) ˜Karakteristik dan Potensi Lahan Sub Optimal untuk Pengembangan Pertanian di Indonesia | Mulyani | Jurnal Sumberdaya Lahan™, Jurnal Sumberdaya Lahan, 7(1), pp. 47“55. Available at: http://ejurnal.litbang.pertanian.go.id/index.php/jsl/article/view/6429 (Accessed: 26 November 2019).

Parece, T. E. and Campbell, J. B. (2015) ˜Land use/land cover monitoring and geospatial technologies: An overview™, in Handbook of Environmental Chemistry. Springer Verlag, pp. 1“32. doi: 10.1007/978-3-319-14212-8_1.

Ptak, M. and Åawniczak, A. E. (2012) ˜Changes in land use in the buffer zone of lake of the MaÅ‚a WeÅ‚na catchment™, Limnological Review. Berlin: Sciendo, 12(1), pp. 35“44. doi: https://doi.org/10.2478/v10194-011-0043-z.

Putri Abdi. Sudarsono, Bambang., D. R. S. (2018) ˜Analisis Kombinasi Citra Sentinel-1a Dan Citra Sentinel-2a Untuk Klasifikasi Tutupan Lahan (Studi Kasus: Kabupaten Demak, Jawa Tengah)™, Jurnal Geodesi Undip, 7(2), pp. 85“96. doi: 10.1016/j.cirp.2008.03.009.

Riadi, B. and Makmuriyanto, A. (2014) ˜Kajian Percepatan Penetapan dan Penegasan Batas Kecamatan/Distrik, Desa/Kelurahan Secara Kartometris™, Majalah Ilmiah Globe, 16(2).

Riadi, B. and Rachma, T. R. N. (2017) ˜Kajian Prototipe Peta Desa Menggunakan Citra Satelit Resolusi Tinggi™, Majalah Ilmiah Globe, 19(2), pp. 147“156.

Richards, J. A. (2013) Remote Sensing Digital Image Analysis. 5th edn. Heidelberg: Springer-Verlag. Available at: file:///D:/KULIAH/SKRIPSI/05_Jurnal Penunjang/Remote_Sensing_Digital_Image_Analysis_www.GISman.ir.pdf.

Rujoiu-Mare, M.-R. et al. (2017) ˜Land cover classification in Romanian Carpathians and Subcarpathians using multi-date Sentinel-2 remote sensing imagery™, European Journal of Remote Sensing. Taylor & Francis, 50(1), pp. 496“508. doi: 10.1080/22797254.2017.1365570.

Song, X. P. et al. (2018) ˜Global land change from 1982 to 2016™, Nature. Nature Publishing Group, 560(7720), pp. 639“643. doi: 10.1038/s41586-018-0411-9.

Sudarman, S., Sadikin, H. and Prijatna, K. (2020) ˜Desain Alternatif Lembar Peta Rupabumi Indonesia (RBI) Skala Besar™, GEOMATIKA, 26(1), pp. 35“44.

Susetyo, D. B. (2015) ˜Generalisasi kartografis pada peta Rupabumi Indonesia (RBI) skala 1: 25.000 menjadi 1: 50.000™, Proceeding of Simposium Sains Geoinformasi, pp. 217“225.

Tavares, P. A. et al. (2019) ˜Integration of sentinel-1 and sentinel-2 for classification and LULC mapping in the urban area of Belém, eastern Brazilian Amazon™, Sensors (Switzerland). MDPI AG, 19(5). doi: 10.3390/s19051140.

USGS (2019) ˜EarthExplorer - Home™, U.S. Geological Survey. Available at: https://earthexplorer.usgs.gov/ (Accessed: 15 December 2019).

USGS, U. S. G. (2019) ˜Landsat 8 (L8) Data Users Hanbook Version 4.0™, Department of the Interior, U.S. Geological Survey, 4(April), p. 106. Available at: https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/atoms/files/LSDS-1574_L8_Data_Users_Handbook_v4.0.pdf.

Wężyk, P. et al. (2016) ˜Using Geobia and Data Fusion Approach for Land use and Land Cover Mapping™, Quaestiones Geographicae. Berlin: Sciendo, 35(1), pp. 93“104. doi: https://doi.org/10.1515/quageo-2016-0009.

Downloads

Published

2020-08-01

How to Cite

indarto, indarto, Mandala, M., Febrian Arifin, F., & Lukman Hakim, F. (2020). APLIKASI CITRA SENTINEL-2 UNTUK PEMETAAN TUTUPAN DAN PERUNTUKAN LAHAN PADA TINGKAT DESA. JURNAL GEOGRAFI, 12(2), 189–201. https://doi.org/10.24114/jg.v12i02.16970