Indonesian Journal of Remote Sensing and Applications

ANALYSIS OF LAND USE CHANGES DUE TO LANDSLIDES IN PANTI DISTRICT USING LANDSAT 8 IMAGERY

ZUBAIDAH — 2023-06-05

The Panti District area which is located in the highlands often experiences landslides, on the other hand the population growth of the Panti District has also experienced an increase in population. This of course can provide potential land damage, disruption of ecosystem balance, and loss of land cover vegetation. This study aims to determine changes in land use due to landslides in the Panti District. This study uses a quantitative descriptive research method with data collection techniques sourced from secondary data. While the analysis technique uses the supervised maximum likelihood classification method and accuracy test. This accuracy test is carried out to determine the accuracy of the classified image with data in the field. The results of the Landsat 8 imagery accuracy test in Panti District in 2018 and 2022 using Google Earth obtained the same results, namely 86.66% of the 30 sample points. Meanwhile, the classification is determined into 4 classes, namely, forest, sawan, settlements, and gardens. Where from the results of the classification and accuracy test, it was obtained data that land use in the Panti District between 2018 and 2022 there was an almost complete change in land use on all of its land with the use of paddy fields having the most changes, namelyincrease to 8,421 Ha in 2022 which causes degradation and deforestation of forest lands, thus triggering an increase in landslide disasters. Therefore, it is necessary to reduce development near steep slopes and minimize development near areas with less stable slopes, as well as reduce the conversion of forest land to rice fields

Vegetation Density Change Due to Landslides in Sadu Village, Soreang Subdistrict, Bandung Regency

Abhiseka D. Imanjaya — 2023-06-05

Landslides that have occurred in Sadu Village, Soreang Subdistric, Bandung Regency, West Java resulted change density of vegetation low on the last 3 years, that is on year 2019-2022. Analysis change land use employ Landsat 8-Oli imagery done for identify wide change land use occurring in the region cases study based on multitemporal data as well as land area data obtained. This research aims for analyze change in vegetation density to change land use in Sadu Village on 2019-2022 seen from extraction image landsat 8-OIL. As for this research using method supervised maximum likelihood classification. Test accuracy image in this study used for look accuracy classified image and field data. The results that is, research Accuracy Test Landsat image classification land use obtain results by 90 % (2019) and 86.6 % (2022) and study related to the results of changes in land use in 2019 and 2022 which showed that there was a change in vegetation to non-vegetation in the form of built-up land of 16 Ha, then the results of changes in vegetation density in the results for 2019 and 2022 show that the density of quite dense vegetation has increased by 78 Ha and the dense vegetation category has decreased by 88 Ha. It shows that exists change use occurring land on three year final form land area forest to agricultural land and built-up land, apart from that there was an avalanche disaster which reduced the denser vegetation area because it was eroded by the avalanche.

Keywords : Landsat Imagery, Land Use, Vegetation Density

Integration of Normalized Difference Vegetation Index (NDVI) and Soil-Adjusted Vegetation Index (SAVI) to Identify Vegetation Covers on an Oil-Producing Landscape in Kedewan, Bojonegoro Regency

Saffina Eka Rahma Wati — 2023-06-05

East Java Province is one of the most populous provinces in Indonesia with the second most populous position in Indonesia, the number of regencies and cities in East Java is 28 regions. Meanwhile, Bojonegoro Regency is the tenth most populous area in East Java. Population growth every year, of course, greatly impacts land use in Bojonegoro Regency, including one of its sub-districts, namely the Kadewan Sub-district. The increasing land use that occurs in Kedewan District is not only caused by increasingly dense population growth. However, this is caused by the fact that Kedewan District has an energy source in the form of oil, whose land is used for mining. If mining expands, it cannot be ruled out that vegetation, which is the main source producing oxygen for humans, will decrease. Therefore, it is important to re-analyze the vegetation index in the region. The method used in this study is a quantitative approach located in Kedewan Sub-district, Bojonegoro Regency. Data collection using mothed observation techniques (non-participant observation) and document study techniques. The results of the study showed that NDVI and SAVI calculations had been carried out, and it was found that the overall density conditions in Kedewan District were classified as having a moderate level of vegetation density. Apart from that, from the calculations and analysis that have been done, the SAVI method is superior to using the NDVI method.

References

Ariani, D., Y. Prasetyo, dan B. Sasmito. 2020. Estimasi tingkat produktivitas padi berdasarkan algoritma ndvi, evi dan savi menggunakan citra sentinel-2 multitemporal (studi kasus: kabupaten pekalongan, jawa tengah). Jurnal Geodesi Undip. 9(1):207–216. https://ejournal3.undip.ac.id/index.php/geodesi/article/view/26165

Arimbawa, I. K. 2010. Kajian Berbagai Macam Citra Satelit Terhadap Skala Peta (Planimetris). Geoid. 5(1):055–058.

Asma, N. (2018). Analisa Perubahan Lahan Tambak Menggunakan Metode Maximum Likelihood (Studi Kasus: Kota Banda Aceh). Tugas Akhir Universitas Syiah Kuala. Banda Aceh, 59.

Hidayati, N. 2010. Sistem penginderaan jauh satelit ldcm (landsat-8). Kajian Pemanfaatan Satelit Masa Depan. 11(2):47–58.

Imburi, C. S. 2020. Perbandingan algoritma pada metode klasifikasi supervised berbasis citra alos avnir-2 untuk pemetaan mangrove. Jurnal Kehutanan Papuasia. 6(1):1–9. https://doi.org/10.46703/jurnalpapuasia.Vol6.Iss1.177

Kalinda, I. O. P., B. Sasmito, dan A. Sukmono. 2018. Analisis Pengaruh Koreksi Atmosfer Terhadap Deteksi Land Surface Temperature Menggunakan Citra Landsat 8 Di Kota Semarang. Jurnal Geodesi Undip. 7(3):66–76. https://ejournal3.undip.ac.id/index.php/geodesi/article/view/21217

Kristanto, Y., T. Agustin, dan F. Rizki Muhammad. 2017. Pendugaan Karakteristik Awan Berdasarkan Data Spektral Citra Satelit Resolusi Spasial Menengah Landsat 8 Oli/Tirs (Studi Kasus: Provinsi Dki Jakarta). Jurnal Meteorologi Klimatologi Dan Geofisika. 4(2):42–51. https://jurnal.stmkg.ac.id/index.php/jmkg/article/view/46

Nuraini, N. F., I. W. G. A. Karang, dan I. N. G. Putra. 2022. Estimasi Stok Karbon Di Atas Permukaan Menggunakan Citra Sentinel-1a Di Hutan Mangrove Karang Sewu, Bali. Journal of Marine Research and Technology. 5(1):21. https://doi.org/10.24843/JMRT.2022.v05.i01.p05

Que, V. K. S., S. Y. J. Prasetyo, dan C. Fibriani. 2019. Analisis Perbedaan Indeks Vegetasi Normalized Difference Vegtation Index (Ndvi) Dan Normalized Burn Ratio (Nbr) Kabupaten Pelalawan Menggunakan Citra Satelit Landsat 8. Indonesian Journal OF Computing AND Modeling. 1(1):1–7. https://ejournal.uksw.edu/icm/article/view/2534

Purnia, D. S., & Alawiyah, T. (2020). Metode Penelitian: Strategi Menyusun Tugas Akhir. Yogyakarta: Graha Ilmu.

Saputra, J., M. Kamal, dan P. Wicaksono. 2018. Pengaruh Resolusi Spasial Citra Terhadap Hasil Pemetaan Kandungan Hara Nitrogen Perkebunan Karet. Jurnal Penelitian Karet. (July):13–24. https://doi.org/10.22302/ppk.jpk.v36i1.545

Simarmata, N., K. Wikantika, T. A. Tarigan, M. Aldyansyah, R. K. Tohir, A. Fauziah, dan Y. Purnama. 2021. Analisis transformasi indeks ndvi, ndwi dan savi untuk identifikasi kerapatan vegetasi mangrove menggunakan citra sentinel di pesisir timur provinsi lampung. JURNAL GEOGRAFI Geografi Dan Pengajarannya. 19(2):69–79. https://doi.org/10.26740/jggp.v19n2.p69-79

Sinaga, S. H., A. Suprayogi, dan Haniah. 2018. Analisis ketersediaan ruang terbuka hijau dengan metode normalized difference vegetation index dan soil adjusted vegetation index menggunakan citra satelit sentinel-2a (studi kasus : kabupaten demak). Jurnal Geodesi Undip. 7(1):202–211. https://ejournal3.undip.ac.id/index.php/geodesi/article/view/19329

Widiyatmoko, W., S. Sudibyakto, dan E. Nurjani. 2018. Analisis Kerentanan Tanaman Terhadap Ancaman Kekeringan Pertanian Menggunakan Pendekatan Multi-Temporal Di Das Progo Hulu. Geomedia: Majalah Ilmiah Dan Informasi Kegeografian. 15(2). https://doi.org/10.21831/gm.v15i2.19553

Wijaya, S. F. A., K. Koredianto, dan S. Saidah. 2022. Analisis Perbandingan K-Nearest Neighbor Dan Support Vector Machine Pada Klasifikasi Jenis Sapi Dengan Metode Gray Level Coocurrence Matrix. Jurnal Ilmu Komputer Dan Informatika. 2(2):93–102. https://doi.org/10.54082/jiki.27

Wulansari, H. (2017). Uji Akurasi Klasifikasi Penggunaan Lahan Dengan Menggunakan Metode Defuzzifikasi Maximum Likelihood Berbasis Citra Alos Avnir-2. BHUMI: Jurnal Agraria Dan Pertanahan, 3(1), 98-110. https://doi.org/10.31292/jb.v3i1.233

ANALYSIS OF VEGETATION DENSITY IN FLOOD DISASTER USINGLANDSAT 8 IMAGERY IN JEMBER URBAN AREA 2010-2019 AND 2020-2022

Muhammad Jiddan Amrullah — 2023-06-05

Vegetation has an important in human life. Studies related to vegetation can include its
density or distribution in the area. To analyze the vegetation density in an area by using
Remote Sensing System technology. This study aims to analyze vegetation density in flood
disaster using Landsat 8 imagery in the urban area of Jember in 2010-2019 and 2020-2022.
The research method used is a quantitative research method. This type of research was chosen
because there will be data that needs to be processed using remote sensing techniques, which
are also related to numbers. The research object to be studied is vegetation density using
Landsat 8-OLI imagery and field survey data. The data collection technique in this study uses
the observation method to compare the results of imagery processing on the Envi 4.5
application with direct conditions in the field, then field documentation is carried out. Then
the vegetation index method used is the NDVI method (Normalized Difference Vegetation
Index). The results of the research it is known that several sub-districts in the center of
Jember Regency, such as Patrang, Sumbersari, and Kaliwates sub-districts, have land cover
for vegetation that varies from medium to dense vegetation.

Analysis of Differences In Vegetation Development In 2009 and 2022 In Semboro Sub-District, Jember Regency

Agum Taufan — 2023-06-05

One type of spatial information that can be extracted based on remote sensing satellite data is land cover information. This information is created and used for various types of purposes, so that many different versions are found according to the intended use. This study aims to identify the vegetation density index in the Sukokulon rubber plantation area in 2009 and 2022. This research was conducted using a descriptive approach in which the researcher explained the results of field identification. Data analysis techniques were carried out by means of descriptive analysis by describing the situation based on observations made and secondary data on Landsat 7 and Landsat 9 images to determine differences in vegetation density, as well as by analysis through literature studies. Vegetation density in 2009–2022, shows an increase in the value of vegetation density in the Semboro District area, but in the northern region it is still with high vegetation density.