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All Journal International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Tatik Kartika, Tatik
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering

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MONITORING MODEL OF LAND COVER CHANGE FOR THE INDICATION OF DEVEGETATION AND REVEGETATION USING SENTINEL-2 Arifin, Samsul; Kartika, Tatik
International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 17, No 2 (2020)
Publisher : National Institute of Aeronautics and Space of Indonesia (LAPAN)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2020.v17.a3385

Abstract

IInformation on land cover change is very important for various purposes, including the monitoring of changes for environmental sustainability. The objective of this study is to create a monitoring model of land cover change for the indication of devegetation and revegetation usingdata fromSentinel-2 from 2017 to 2018 of the Brantas watershed.This is one of the priority watersheds in Indonesia, so it is necessary to observe changes in its environment, including land cover change. Such change can be detected using remote sensing data. The method used is a hybrid between Normalized Difference Vegetation Index(NDVI) and Normalized Burn Ratio (NBR) which aims to detect land changes with a focus on devegetationand revegetation by determining the threshold value for vegetation index (ΔNDVI) and open land index (ΔNBR).The study found that the best thresholds to detect revegetation were ΔNDVI > 0.0309 and ΔNBR < 0.0176 and to detect devegetation ΔNDVI < -0.0206 and ΔNBR > 0.0314.It is concluded that Sentinel-2 data can be used to monitor land changes indicating devegetation and revegetation with established NDVI and NBR threshold conditions.
ANALISIS HUBUNGAN PENUTUP/PENGGUNAAN LAHAN DENGAN TOTAL SUSPENDED MATTER (TSM) KAWASAN PERAIRAN SEGARA ANAKAN MENGGUNAKAN DATA INDERAJA Parwati, Ety; Trisakti, Bambang; Carolita, Ita; Kartika, Tatik; Harini, Sri; Dewanti, Ratih
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 3 No. 1 (2006)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v3i1.3183

Abstract

Segara Anakan and its surrounding which is located in Cilacap Regency Central of Java, is the study area for this research. This region, like other estuaries, has a unique ecosystem which is protected and surrounded by the mangrove forest that can cause very dynamic development. In the upland, there are three big rivers flow; Citanduy, Cibeureum, and Cimeng. The main issue in this region is that the lagoon to become narrowing because of rapid sedimentation process. Landsat MSS, TM, and ETM of the years 1978, 1995, 1998, and 2003 are remote sensing data used in this research. An analysis in term of correlation between landuse/landcover changes and sedimentation was carried out by looking at their changes in the upper land especially along the rivers that have big contribution to the sedimentation in the lagoon. The result shows that there is high relation between landuse/landcover changes in the upper land and sedimentation around the lagoon.
KAJIAN KOREKSI TERRAIN PADA CITRA LANDSAT THEMATIC MAPPER (TM) Trisakti, Bambang; Kartasasmita, Mahdi; Kustiyo, Kustiyo; Kartika, Tatik
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 6 No. 1 (2009)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v6i1.3239

Abstract

Terrain correction is used to minimize the shadow effect due to variation of earth’s topography. So, the process is very useful to correct the distortion of the pixel value at the mountainous area in the satellite image. The aim of this paper is to study the terrain correction process and its implementation for Landsat TM. The algorithm of the terrain correction was built by determining the pixel normal angle which is defined as an angle between the sun and surface normal directions. The calculation of the terrain correction needs the information of sun zenith angle, sun elevation angle (obtained from header data), pixel slope, and pixel aspect derived from digital elevation model (DEM). The C coefficient from each band was determined by calculating the gradient and the intercept of the correlation between the Cos pixel normal angle and the pixel reflectance in each band. Then, the Landsat TM image was corrected by the algorithm using the pixel normal angle and C coefficient. C Coefficients used in this research were obtained from our calculation and from Indonesia National Carbon Accounting System (INCAS). The result shows that without the C coefficient, pixels value increases very high when the pixel normal angle approximates 90°. The C coefficient prevents that condition, so the implementation of the C coefficient obtained from INCAS in the algorithm can produce the image which has the same topography appearance. Further, each band of the corrected image has a good correlation with the corrected band from the INCAS result. The implementation of the C coefficient from our calculation still needs some evaluation, especially for the method to determine the training sample for calculating the C coefficient.
EVALUASI REHABILITASI LAHAN KRITIS BERDASARKAN TREND NDVI LANDSAT-8 (Studi Kasus: DAS Serayu Hulu) Kartika, Tatik; Dirgahayu, Dede; Sari, Inggit Lolita; Parsa, I Made; Carolita, Ita
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 16 No. 2 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v16i2.3353

Abstract

The use of remote sensing in vegetation monitoring has been widely applied, including vegetation density monitoring. However, the use to evaluate rehabilitation program on critical land is still limited. Evaluation of forest cover and land rehabilitation activities become important due to the increase of critical land. The current method to evaluate the land condition is conducted by ground check at the rehabilitation site held at the end of the year after the initial implementation of the rehabilitation program until the third year. This method requires a lot of time, labour, and money. Based on the standard regulation to evaluate the rehabilitation program, the program is successful if 90% the new vegetation planted can grows until the third year. Therefore, this research uses an effective and efficient method for evaluating land rehabilitation programs using remote sensing data by understanding vegetation conditions and their densities using multi-temporal analysis for large areas. A multi-temporal Landsat-8 images from 2015-2018 will be used to analyze the Normalized Difference Vegetation Index (NDVI) trend in the time-based sequence method using spatial analysis. The results show that the non-forest area in Serayu Hulu Watershed consist of non-critical land, moderate critical land, critical land, and severe ciritical land. According to the ground check and NDVI trend analysis, the rehabilitation in non-critical land of the non-forest area was generally unsuccessful due to the area rehabilitation plant were harvested before the rehabilitation evaluation time ended. On the otherhand, on critical land; moderate critical land; and severe critical land of the non-forest area, the success of rehabilitation program was indicated by the achievement of the NDVI threshold value at 0.4660; 0.4947. 0.4916, respectively.
APLIKASI MODEL GEOBIOFISIK NDVI UNTUK IDENTIFIKASI HUTAN PADA DATA SATELIT LAPAN-A3 Arifin, Samsul; Carolita, Ita; Kartika, Tatik
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 16 No. 2 (2019)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v16i2.3356

Abstract

The LAPAN-A3 / IPB satellite is a micro satellite created by the nation's children in order to build the nation's independence in the field of Space. This satellite has 4 bands including 3 visible waves and 1 near infrared. Given that it is a new satellite, it is necessary to do a study and research on the ability of sensor characteristics to identify natural resources, one of which is forests. In this study besides using LAPAN-A3 satellite data, Landsat-8 data is also used as comparative data for testing the similarity of forest object classification results. Determination of extraction of geobiophysical parameters of forest identification using the Normalized Difference Vegetation Index (NDVI) model with a threshold value for forest identification. The results of the study with LAPAN-A3 satellite data show that the threshold range for forest identification is above 0.65 on the vegetation index scale -1 (minus one) to +1 (plus one). The results of the study after comparing NDVI values with Landsat-8 data have a 60% similarity.
Co-Authors Bambang Trisakti Dede Dirgahayu Ety Parwati I Made Parsa Inggit Lolita Sari, Inggit Lolita Ita Carolita, Ita Kustiyo Kustiyo, Kustiyo Mahdi Kartasasmita Ratih Dewanti -Hariyadi Samsul Arifin Sri Harini