Pemetaan Perubahan Lahan Sawah Kabupaten Sukabumi Menggunakan Google Earth Engine

Widia Siska; Widiatmaka Widiatmaka; Yudi Setiawan; Setyono Hari Adi

doi:10.14710/tataloka.24.1.74-83

DOI: https://doi.org/10.14710/tataloka.24.1.74-83

Pemetaan Perubahan Lahan Sawah Kabupaten Sukabumi Menggunakan Google Earth Engine

*Widia Siska - Institut Pertanian Bogor, Indonesia

Widiatmaka Widiatmaka - Institut Pertanian Bogor, Indonesia

Yudi Setiawan - Institut Pertanian Bogor, Indonesia

Setyono Hari Adi - Balai Penelitian Agroklimat dan Hidrologi, Indonesia

BibTex Citation Data :

@article{tataloka10714,
    author = {Widia Siska and Widiatmaka Widiatmaka and Yudi Setiawan and Setyono Adi},
    title = {Pemetaan Perubahan Lahan Sawah Kabupaten Sukabumi Menggunakan Google Earth Engine},
    journal = {TATALOKA},
  volume = {24},
    number = {1},
    year = {2022},
    keywords = {Google Earth Engine, Kabupaten Sukabumi, Sawah},
    abstract = { Google Earth Engine  (GEE) merupakan layanan pemrosesan geospasial yang telah banyak digunakan di berbagai bidang pemetaan. Tujuan penelitian ini adalah  identifikasi perubahan lahan sawah Kabupaten Sukabumi menggunakan  GEE . Data citra landsat 5 dan landsat 8 yang digunakan di GEE merupakan data citra yang telah di  pre-process  dan terkoreksi. Klasifikasi penggunaan/tutupan lahan dibedakan menjadi 6 kelas yaitu sawah, badan air, pemukiman, bervegetasi, hutan dan tanah terbuka. Sampel acak penggunaan lahan dibuat sebanyak 394 titik di GEE menggunakan  poin  dan  rectangular . Klasifikasi penggunaan lahan dianilisis menggunakan metode  Random Forest  (RF). Penilaian akurasi dihitung menggunakan  confusion Matrix,  sedangkan   validasi lapang dilakukan dengan menggunakan metode  stratified random sampling .    Uji akurasi analisis tutupan lahan tahun 2020 dengan  confusion Matrix  menghasilkan nilai  Overall Accuracy (OA)  0,94 dan nilai  kappa   0,91; tahun 2015 dengan nilai OA 0,93 dan nilai  Kappa  0,91; sedangkan tahun 2010 memiliki nilai  OA  0.96 dan nilai  Kappa  0.94. Hasil analisis ini menunjukkan bahwa luas lahan sawah Kabupaten Sukabumi mengalami penyusutan seluas 10,317.27  ha dalam kurun waktu sepuluh tahun (2010-2020). Klasifikasi penggunaan lahan menggunakan GEE dapat menghasilkan peta dengan akurasi tinggi dengan OA >85%, serta dapat mempersingkat waktu analisis.},
   issn = {2356-0266},   pages = {74--83}  doi = {10.14710/tataloka.24.1.74-83},
    url = {https://ejournal2.undip.ac.id/index.php/tataloka/article/view/10714}
}

Citation Format:

Abstract

Google Earth Engine (GEE) merupakan layanan pemrosesan geospasial yang telah banyak digunakan di berbagai bidang pemetaan. Tujuan penelitian ini adalah identifikasi perubahan lahan sawah Kabupaten Sukabumi menggunakan GEE. Data citra landsat 5 dan landsat 8 yang digunakan di GEE merupakan data citra yang telah di pre-process dan terkoreksi. Klasifikasi penggunaan/tutupan lahan dibedakan menjadi 6 kelas yaitu sawah, badan air, pemukiman, bervegetasi, hutan dan tanah terbuka. Sampel acak penggunaan lahan dibuat sebanyak 394 titik di GEE menggunakan poin dan rectangular. Klasifikasi penggunaan lahan dianilisis menggunakan metode Random Forest (RF). Penilaian akurasi dihitung menggunakan confusion Matrix, sedangkan validasi lapang dilakukan dengan menggunakan metode stratified random sampling. Uji akurasi analisis tutupan lahan tahun 2020 dengan confusion Matrix menghasilkan nilai Overall Accuracy (OA) 0,94 dan nilai kappa 0,91; tahun 2015 dengan nilai OA 0,93 dan nilai Kappa 0,91; sedangkan tahun 2010 memiliki nilai OA 0.96 dan nilai Kappa 0.94. Hasil analisis ini menunjukkan bahwa luas lahan sawah Kabupaten Sukabumi mengalami penyusutan seluas 10,317.27 ha dalam kurun waktu sepuluh tahun (2010-2020). Klasifikasi penggunaan lahan menggunakan GEE dapat menghasilkan peta dengan akurasi tinggi dengan OA >85%, serta dapat mempersingkat waktu analisis.

Fulltext View|Download

Keywords: Google Earth Engine, Kabupaten Sukabumi, Sawah

Funding: IPB

Article Metrics:

Article Info

Section: Articles

Language : EN

In Vol 24, No 1 (2022): Volume 24 No. 1, February 2022

Recent articles

Urban Tourism Concepts in the Design of Kampung Tua in Batam Potensi Pengembangan TOD di Kota Medan: Studi Kasus di Stasiun Medan Identification of Sprawl Development Typologies around Toll Road Gates in Java, Indonesia More recent articles

Becker, W. R., Ló, T. B., Johann, J. A., & Mercante, E. (2021). Statistical features for land use and land cover classification in Google Earth Engine. Remote Sensing Applications: Society and Environment, 21, 100459
BPS Jawa Barat. (2019). Provinsi Jawa Barat dalam Angka 2019. Badan Pusat Statistik Provinsi Jawa Barat
BPS Kabupaten Sukabumi. (2020). Jumlah Penduduk Rasio Jenis Kelamin dan Kepadatan Penduduk Menurut Jenis Kelamin di Kabupaten Sukabumi. Retrieved March 2, 2020, from https://sukabumikab.bps.go.id/statictable/2020/01/27/116/jumlah-penduduk-rasio-jenis-kelamin-dan-kepadatan-penduduk-menurut-jenis-kelamin-di-kabupaten-sukabumi-1930-2018.html)
Congalton, R. ., & Green, K. (2009). Assessing in Accuracy of Remote Sensed Data. Volume 2. New York (ID): CRC Press
Dong, J., Xiao, X., Menarguez, M. A., Zhang, G., Qin, Y., Thau, D., … Moore, B. (2016). Mapping paddy rice planting area in Northeastern Asia with Landsat 8 images, phenology-based algorithm and Google Earth Engine. Remote Sensing of Environment, 185, 1–13. https://doi.org/10.1016/j.rse.2016.02.016
Housman, I., Tanpipat, V., Biswas, T., Clark, A., Stephen, P., Maus, P., & Megown, K. (2015). Monitoring forest change in southeast Asia: case studies for USAID Lowering Emissions in Asia’s Forests. US Department of Agriculture, Forest Service, Remote Sensing Applications Center: Salt Lake City, Utah, 1-16
Irawan, B. (2015). Dinamika Produksi Padi Sawah Dan Padi Gogo: Implikasinya Terhadap Kebijakan Peningkatan Produksi Padi. In E. Pasandaran, M. Rachmat, Hermanto, M. Ariani, Sumedi, K. Suradisastra, & Haryono (Eds.), Memperkuat Kemampuan Swasembada Pangan (pp. 68–88). Jakarta (ID): IAARD PRESS
Kepmen ATR/BPN. (2018). Ketetapan Menteri Agraria dan Tata Ruang/Kepala Badan Pertanahan Nasional Nomor 399/Kep-23.3/X/2018 tentang Penetapan Luas Baku Sawah Nasional Tahun 2018
Lillesand, T. M., & Keifer, R. W. (1994). Remote Sensing and Image Interpretation. Third Edition. John Willey and Sons, Inc, United States of America
Nduru, R. E., Situmorang, M., & Tarigan, G. (2014). Analisa faktor-faktor yang Mempengaruhi Hasil Produksi Padi di Deli Serdang. Jurnal Saintia Matematika, 2(1)(1), 71–83
Oliphant, A. J., Thenkabail, P. S., Teluguntla, P., Xiong, J., Gumma, M. K., Congalton, R. G., & Yadav, K. (2019). Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using a random forest classifier on the Google Earth Engine Cloud. International Journal of Applied Earth Observation and Geoinformation, 81(May), 110–124. https://doi.org/10.1016/j.jag.2018.11.014
Phalke, A. R., Özdoğan, M., Thenkabail, P. S., Erickson, T., Gorelick, N., Yadav, K., & Congalton, R. G. (2020). Mapping croplands of Europe, Middle East, Russia, and Central Asia using Landsat, Random Forest, and Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 167(June), 104–122. https://doi.org/10.1016/j.isprsjprs.2020.06.022
Pusdatin. (2019). Statistik lahan pertanian tahun 2014-2018. Pusat Data dan Sistem Informasi Pertanian. Sekretariat Jenderal Kementerian Pertanian
Rodriguez-Galiano, V. F., Ghimire, B., Rogan, J., Chica-Olmo, M., & Rigol-Sanchez, J. P. (2012). An assessment of the effectiveness of a random forest classifier for land-cover classification. ISPRS Journal of Photogrammetry and Remote Sensing, 67, 93–104
Shaharum, N. S. N., Shafri, H. Z. M., Ghani, W. A. W. A. K., Samsatli, S., Al-Habshi, M. M. A., & Yusuf, B. (2020). Oil palm mapping over Peninsular Malaysia using Google Earth Engine and machine learning algorithms. Remote Sensing Applications: Society and Environment, 17, 100287. https://doi.org/10.1016/j.rsase.2020.100287
Singha, M., Dong, J., Sarmah, S., You, N., Zhou, Y., Zhang, G., … Xiao, X. (2020). Identifying floods and flood-affected paddy rice fields in Bangladesh based on Sentinel-1 imagery and Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 166, 278–293. https://doi.org/10.1016/j.isprsjprs.2020.06.011
Sutanto. (2016). Metode Penelitian Penginderaan Jauh. Yogyakarta (ID): Ombak
Waske, B., & Braun, M. (2009). Classifier ensembles for land cover mapping using multitemporal SAR imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 64(5), 450–457. https://doi.org/10.1016/j.isprsjprs.2009.01.003
Zulfajri, Danoedoro, P., & Murti, S. H. (2021). Klasifikasi tutupan lahan data Landsat-8 OLI menggunakan metode Random Forest. Jurnal Penginderaan Jauh Indonesia, 03(01), 1–7
Zurqani, H. A., Post, C. J., Mikhailova, E. A., Schlautman, M. A., & Sharp, J. L. (2018). Geospatial analysis of land use change in the Savannah River Basin using Google Earth Engine. International Journal of Applied Earth Observation and Geoinformation, 69, 175–185. https://doi.org/10.1016/j.jag.2017.12.006

Last update:

No citation recorded.

Last update:

No citation recorded.

As an article writer, the author has the right to use their articles for various purposes, including use by institutions that employ authors or institutions that provide funding for research. Author rights are granted without special permission.

Author who publishes a paper at Tataloka has the broad right to use their work for teaching and scientific purposes without the need to ask permission, including: used for (i) teaching in the author's class or institution, (ii) presentation at meetings or conferences and distributing copies to participants ; (iii) training conducted by the author or author's institution; (iv) distribution to colleagues for research use; (v) use in the compilation of subsequent authors' works; (vi) inclusion in a thesis or dissertation; (vi) reuse of part of the article in another work (with citation); (vii) preparation of derivative works (with citation); (viii) voluntary posting on open websites operated by authors or author institutions for scientific purposes.

Authors and readers can copy and redistribute material in any media or format, and mix, modify, and build material for any purpose but they must provide appropriate credit (provide article citation or content), providing links to the license, and indicate if there are changes.

The authors submitting a manuscript do so on the understanding that if accepted for publication, copyright of the article shall be assigned to Jurnal Tataloka . Copyright encompasses rights to reproduce and deliver the article in all form and media, including reprints, photographs, microfilms and any other similar reproductions, as well as translations.

Reproduce any part of this journal, its storage in the database or its transmission by all forms or media is permitted does not need for written permission from Tataloka . However, it should be cited as an honor in academic manners

Tataloka and the Department of Urban and Regional Planning of Diponegoro University and the Editor make every effort to ensure that there are no data, opinions, or false or misleading statements published in Tataloka. However, the content of the article is the sole and exclusive responsibility of each author.

The Copyright Transfer Form can be downloaded here: [Copyright Transfer Form - Indonesian] [Copyright Transfer Form - English]. The copyright form should be signed originally and send to the Editor in the form of printed letters, scanned documents sent via email or fax.