Survey and Mapping of Vegetation Density through Remote Sensing and Satellite Imagery
Call For Paper: Vol. 4 No.2 March 2026
Basuki
University of Jember
Muhammad Rizal Romadhon
University of Jember
Retno Purnama Sari
University of Jember
Bimo Arvi Aji Isnanto
University of Jember
ABSTRACT
The development of technology in the current era of globalization is taking place very fast and information technology is needed, among others, as an informant for the situation on the earth's surface. GIS technology can be used to identify vegetation density in an area. The data analysis method used was the NDVI and SAVI vegetation index transformation methods for vegetation density identification. This research was conducted in Ambulu District, Jember Regency, East Java Province. Using satellite images from Landsat 8 OLI imagery which is then explained with descriptive analysis. The identification results showed that for the use of NDVI and SAVI methods, the similarity in the number of classes was 3 classes with low, medium and high categories. It has 3 similarities in classes but there are differences in the area of land in each of these vegetation indexes.
Keyword : Vegetation Density, NDVI, SAVI, GIS Technology
REFERENCES
Ahmed, F., Ali, I., & Kousar, S. (2022). The environmental impact of industrialization and foreign direct investment: Empirical evidence from the Asia-Pacific region. Environmental Science and Pollution Research, 29(1), 29778–29792.
Badan Pusat Statistik (BPS). (2024). Pertumbuhan ekonomi Kabupaten Jember 2024.
Basuki, A. R., Destiawan, H. A., & Sari, V. K. (2025). Land characterization and management in the marine-volcanic area of Mount Semeru, Indonesia: A case study of sugarcane commodities. Journal of Degraded and Mining Lands Management, 12(3), 7765–7778.
Basuki, B., Mandala, M., Bowo, C., & Fitriani, V. (2022). Evaluation of the suitability of sugarcane plants in Mount Argopura’s volcanic land using a geographic information system. Jurnal Ilmiah Rekayasa Pertanian dan Biosistem, 10(1), 145–160.
Dai, L., Ruiyu, F., Xiaowei, G., Yangong, D., Fawei, Z., & Guangmin, C. (2022). Soil moisture variations in response to precipitation across different vegetation types on the northeastern Qinghai-Tibet Plateau. Plant Science, 13(1), 1–11.
Danoedoro, P. (2016). Pengolahan citra digital: Teori dan aplikasinya dalam penginderaan jauh. Yogyakarta: Fakultas Geografi, Universitas Gadjah Mada.
Erkossa, T., Fanuel, L., Wuletawu, A., & Lulseged, T. (2022). Evolution of soil fertility research and development in Ethiopia: From reconnaissance to data-mining approaches. Experimental Agriculture, 58(1), 1–13.
Hardianto, A., Pegita, U. D., Taufiq, F., Novia, F. S. S., & Nadifa, S. R. (2021). Pemanfaatan citra Landsat 8 dalam mengidentifikasi nilai indeks kerapatan vegetasi (NDVI) tahun 2013 dan 2019 (Area studi: Kota Bandar Lampung). JSRG, 2(1), 8–15.
Hardianto, L. O., Muh, G. J., Nurgiantoro, & Noor, H. K. (2021). Perbandingan metode indeks vegetasi NDVI, SAVI dan EVI terkoneksi atmosfer iCOR. JAGAT, 5(1), 53–62.
Hatulesila, J. W., Gun, M., & Irwanto. (2019). Analisis nilai indeks kehijauan (NDVI) pada pola ruang Kota Ambon, Provinsi Maluku. JHPPK, 1(1), 55–67.
Huang, S., Lina, T., Joseph, P. H., Yang, W., & Guafan, S. (2021). A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing. Forestry Research, 32(1), 1–6.
Jogiyanto, H. (2018). Metoda pengumpulan dan teknik analisis data. Yogyakarta: Penerbit Andi.
Lufilah, S. N., Makalew, A. D., & Sulistyantara, B. (2017). Pemanfaatan citra Landsat 8 untuk analisis indeks vegetasi di DKI Jakarta. Jurnal Lanskap Indonesia, 9(1), 73–80.
Marwoto, & Ginting, R. (2009). Penyusunan data dan karakteristik daerah tangkapan air Danau Sentani, Kabupaten Jayapura serta perubahan penutupan lahannya menggunakan data penginderaan jauh. Berita Inderaja, 8, 57. Bidang Penyajian Data, Pusat Data Penginderaan Jauh, Lembaga Penerbangan dan Antariksa Nasional.
Muhaimin, A. R., Ramadhani, W. S., & Rahmat, A. (2021). Analisis perubahan penggunaan lahan di Kecamatan Tanjung Karang Timur, Kota Bandar Lampung dengan menggunakan metode NDVI: Analysis of land use change in Tanjung Karang Timur Subdistrict, Bandar Lampung City using the NDVI method. Open Science and Technology, 1(1), 1–7.
Mukiibi, A., Machakaire, A. T. B., Franke, A. C., & Steyn, J. M. (2025). A systematic review of vegetation indices for potato growth monitoring and tuber yield prediction from remote sensing. Potato Research, 68(1), 409–448.
Stamford, J. D., Silvere, V. C., Iain, C., & Tracy, L. (2023). Development of an accurate low-cost NDVI imaging system for assessing plant health. Plant Methods, 1(1), 1–19.
Trigunasih, N. M., I. W. N., & Moh, S. (2023). Measurement of soil chemical properties for mapping soil fertility status. International Journal of Design & Nature and Ecodynamics, 18(6), 1381–1390.
Mutmainna, N. D., Achmad, M., & Suhardi, S. (2017). Pendugaan lengas tanah Inceptisol pada tanaman hortikultura menggunakan citra Landsat 8. Jurnal Agritechno, 1(1), 135–151.
Prakoso, R. B., Mayasari, E. D., & Hastuti, E. W. D. (2022). Analisis kestabilan lereng menggunakan penginderaan jauh daerah Gununglarang, Kabupaten Majalengka, Jawa Barat. Journal of Geology Sriwijaya, 1(1), 1–11.
Putri, D. R., Abdi, S., & Bambang, 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), 85–96.
Segah, H. (1999). Kajian akurasi citra Landsat-TM yang didukung citra NOAA AVHRR dalam mendeteksi perubahan penutupan lahan areal Proyek Pengembangan Lahan Gambut (PLG) Sejuta Hektar di Provinsi Kalimantan Tengah.
Setiawati, T. C., Nurcholis, M., Basuki, B., Budiman, S. A., & Yudiantoro, D. F. (2024). Elemental composition and mineralogical characteristics of volcanic ash and soil affected by the eruption of Mount Semeru, East Java. Journal of Degraded and Mining Lands Management, 11(3), 5741–5753.
Wikantiyoso, R., Aditya, G. S., & Tonny, S. (2021). Detection of potential green open space area using Landsat 8 satellite imagery. Arteks, 6(1), 149–154.
Yudistira, R., Meha, A. I., & Prasetyo, S. Y. J. (2019). Perubahan konversi lahan menggunakan NDVI, EVI, SAVI dan PCA pada citra Landsat 8 (studi kasus: Kota Salatiga). Indonesian Journal of Computing and Modeling, 2(1), 25–30
Published
31-09-2025
Issue
Pages
45-57
License
Copyright (c) 2023 JSA:Journal of Soilscpae and Agriculture
How to Cite
Basuki, B., Romadhon, M. R., Sari, R. P., & Isnanto, B. A. A. (2025). Survey and Mapping of Vegetation Density through Remote Sensing and Satellite Imagery. Journal of Soilscape and Agriculture, 4(1), 36–44. https://doi.org/10.19184/jsa.v4i1.6187