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All Journal OLDI (Oseanologi dan Limnologi di Indonesia) Forest and Society Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital
Nanin Anggraini, Nanin
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Social Sciences

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DETEKSI TINGGI VEGETASI DI DELTA MAHAKAM DENGAN PENGINDERAAN JAUH Anggraini, Nanin; Julzarika, Atriyon
OLDI (Oseanologi dan Limnologi di Indonesia) Vol 4, No 3 (2019)
Publisher : Indonesian Institute of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/oldi.2019.v4i3.212

Abstract

Tinggi pohon (vegetasi) adalah jarak tegak antara puncak pohon terhadap permukaan tanah. Tinggi vegetasi menjadi salah satu parameter bagi pertumbuhan vegetasi. Ada berbagai metode untuk mengukur tinggi vegetasi, salah satunya dengan menggunakan teknologi penginderaan jauh. Penelitian ini bertujuan untuk pemetaan tinggi vegetasi di Delta Mahakam dengan model tinggi dari penginderaan jauh. Model tinggi yang digunakan adalah Model Permukaan Digital (MPD) dan Model Terrain Digital (MTD). MPD dibuat dari gabungan hasil interferometri citra satelit ALOS PALSAR dengan citra X SAR, Shuttle Radar Topography Mission (SRTM), dan tinggi geodetik dari satelit Icesat/GLAS. Penggabungan ini menggunakan metode integrasi Model Elevasi Digital (MED). Bidang geoid yang digunakan adalah EGM 2008. Langkah selanjutnya adalah koreksi terhadap kesalahan tinggi pada MPD. Koreksi terrain dilakukan untuk mengubah MPD menjadi MTD. Tinggi vegetasi diperoleh dari pengurangan MPD menjadi MTD. Uji akurasi vertikal mengacu ke toleransi 1,96?  (95 %) sebesar minimal 80 cm. Pada MPD, diperoleh nilai akurasi vertikal sebesar 60,4 cm sehingga MPD ini bisa digunakan pada pemetaan 1:10.000. Sedangkan pada MTD diperoleh nilai uji akurasi vertikal  sebesar 37 cm sehingga dapat juga digunakan untuk pemetaan skala 1:10.000. Berdasarkan hasil perhitungan MPD dan MTD, tinggi vegetasi di Delta Mahakam bervariasi antara 0 - 64 m.
Estimation and Mapping Above-Ground Mangrove Carbon Stock Using Sentinel-2 Data Derived Vegetation Indices in Benoa Bay of Bali Province, Indonesia Suardana, A. A. Md. Ananda Putra; Anggraini, Nanin; Nandika, Muhammad Rizki; Aziz, Kholifatul; As-syakur, Abd. Rahman; Ulfa, Azura; Wijaya, Agung Dwi; Prasetio, Wiji; Winarso, Gathot; Dewanti, Ratih
Forest and Society Vol. 7 No. 1 (2023): APRIL
Publisher : Forestry Faculty, Universitas Hasanuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24259/fs.v7i1.22062

Abstract

Carbon dioxide (CO2) is one of the greenhouse gases that causes global warming with the highest concentration in the atmosphere. Mangrove forests can absorb CO2 three times higher than terrestrial forests and tropical rainforests. Moreover, mangrove forests can be a source of Indonesian income in the form of a blue economy, therefore an accurate method is needed to investigates mangrove carbon stock. Utilization of remote sensing data with the results of the above-ground carbon (AGC) detection model of mangrove forests based on multispectral imaging and vegetation index, can be a solution to get fast, cheap, and accurate information related to AGC estimation. This study aimed to investigates the best model for estimating the AGC of mangroves using Sentinel-2 imagery in Benoa Bay, Bali Province. The random forest (RF) method was used to classified the difference between mangrove and non-mangrove with the treatment of several parameters. Furthermore, a semi-empirical approach was used to assessed and map the AGC of mangroves. Allometric equations were used to calculated and produced AGC per species. Moreover, the model was built with linear regression equations for one variable x, and multiple regression equations for more than one x variable. Root Mean Square Error (RMSE) was used to assess the validation of the model results. The results of the mangrove forests area detected in the research location around 1134.92 ha, with an Overall Accuracy (OA) of 0.984 and a kappa coefficient of 0.961. This study highlights that the best model was the combination of IRECI and TRVI vegetation indices (RMSE: 11.09 Mg/ha) for a model based on red edge bands. Meanwhile, the best results from the model that does not use the red edge band were the combination of TRVI and DVI vegetation indices (RMSE: 13.63 Mg/ha). The use of red edge and NIR bands is highly recommended in building the AGC model of mangrove forests because they can increase the accuracy value. Thus, the results of this study are highly recommended in estimating the AGC of mangrove forests, because it has been proven to be able to increase the accuracy value of previous studies using optical images.
MONITORING OF DROUGHT-VULNERABLE AREA IN JAVA ISLAND, INDONESIA USING SATELLITE REMOTE-SENSING DATA Roswintiarti, Orbita; Sofan, Parwati; Anggraini, Nanin
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 8 No. 1 (2011)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v8i1.3248

Abstract

The impact of climatic variability and climate change is of great importance in Indonesia. Monitoring this impact, furthermore, is essential to the preparedness of the regions in dealing with drought-vulnerable conditions. In this study, satellite remote sensing data were used for monitoring drought in Java island, Indonesia. Monthly rainfall data from Tropical Rainfall Measuring Mission (TRMM) data were used to derive the Standardized Precipitation Index (SPI). The Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua satellites was used for calculating the Enhanced Vegetative Index (EVI) and Land Surface Temperature (LST). EVI and LST were then converted to the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI), which are useful indices for the estimation of vegetation moisture and thermal conditions, respectively. Vegetation Health Index (VHI) was calculated using the VCI and TCI to represent the overall vegetation health. The analysis was carried out during the El Niño/Southern Oscillation (ENSO) of June to August 2009. From the SPI analysis, it is found that since June 2009 the conditions of mild drought (-1.0 < SPI < 0) have developed in almost all parts of Java island due to rainfall deficiency. The VCI maps show that the vegetative stress (VCI < 36) as a result of the vegetation moisture condition has gradually developed in the East Java province in June 2009. Meanwhile, from the TCI maps it is found that the vegetative stress (TCI < 36) due to the thermal condition of vegetation was built up in the West Java province in June 2009. Hence, the overall vegetative health in Java island obtained from the VHI maps shows that the moderate vegetative drought (VHI < 36) started to develop in July 2009.
PEMANFAATAN DATA SATELIT UNTUK ANALISIS POTENSI GENANGAN DAN DAMPAK KERUSAKAN AKIBAT KENAIKAN MUKA AIR LAUT Anggraini, Nanin; Trisakti, Bambang; Soesilo, Tri Edhi Budhi
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 9 No. 2 (2012)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v9i2.3266

Abstract

Increasing of ocean water volume caused sea level rise (SLR) that threatens the existence of small islands and coastal areas, such as North Jakarta. Besides the SLR, North Jakarta is also threatened by land subsidence. This study aims to predict the height of SLR in 2030 and to analyze the impact of SLR on the coastal areas of North Jakarta. The total height of SLR in 2030 was predicted using tidal data, land subsidence data, and SLR prediction by B2 scenario from the Intergovernmental Panel on Climate Change (IPCC). Potential inundation area due to SLR was estimated using Digital Elevation Model Shuttle Radar Topography Mission (DEM SRTM) X-C band with spatial resolution 30 m. The damage was analyzed by doing the overlay between the inundation areas with the land use information extracted from QuickBird data. The result shows that the SLR predictions in 2030 are 2.88 m caused by the tide, 2.28 m caused by the land subsidence, and 1.29 m caused by the B2 scenario IPCC. The total height of SLR prediction is 6.45 m. The potential damages of land use are dominated by urban area (1045 ha) and industrial area (563 ha). The most inundated areas are located in Penjaringan sub-district for urban (523 ha) and in Cilincing sub-district for industrial area (311 ha).
ANALISIS PERUBAHAN GARIS PANTAI UJUNG PANGKAH DENGAN MENGGUNAKAN METODE EDGE DETECTION DAN NORMALIZED DIFFERENCE WATER INDEX Anggraini, Nanin; Marpaung, Sartono; Hartuti, Maryani
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 14 No. 2 (2017)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.pjpdcd.1017.v14.a2545

Abstract

Besides to the effects from tidal, coastline position changed due to abrasion and accretion. Therefore, it is necessary to detect the position of coastline, one of them by utilizing Landsat data by using edge detection and NDWI filter. Edge detection is a mathematical method that aims to identify a point on a digital image based on the brightness level. Edge detection is used because it is very good to present the appearance of a very varied object on the image so it can be distinguished easily. NDWI is able to separate land and water clearly, making it easier for coastline analysis. This study aimed to detect coastline changes in Ujung Pangkah of Gresik Regency caused by accretion and abrasion using edge detection and NDWI filters on temporal Landsat data (2000 and 2015). The data used in this research was Landsat 7 in 2000 and Landsat 8 in 2015. The results showed that the coastline of Ujung Pangkah Gresik underwent many changes due to accretion and abrasion. The accretion area reached 11,35 km² and abrasion 5,19 km² within 15 year period.
ESTIMASI BATIMETRI DARI DATA SPOT 7 STUDI KASUS PERAIRAN GILI MATRA NUSA TENGGARA BARAT Setiawan, Kuncoro Teguh; Manessa, Masita Dwi Mandini; Winarso, Gathot; Anggraini, Nanin; Giarrastowo, Gigih; Asriningrum, Wikanti; Herianto, Herianto; Rosid, Syamsu; Supardjo, A. Harsono
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 15 No. 2 (2018)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v15i2.3342

Abstract

Indonesia is an archipelagic state consists of five large islands and thousands of small islands surrounded by shallow marine waters. For this reason, complete and accurate bathymetric information is needed. Large scale bathymetry data in Indonesian waters is still limited, including in the shallow sea waters of Gili Matra, NTB Province. To overcome these problems, remote sensing technology is used. The aim of the study was to analyze the effect of shallow marine habitat base objects on estimating bathymetry from SPOT 7 satellite images. Many methods can be used to produce estimated bathymetry with this technology. The analysis used in this study is multiple linear regression (MLR). The data used is SPOT 7 satellite imagery in the shallow sea waters of Gili Matra, West Nusa Tenggara Province. The estimation of bathymetry was carried out using insitu depth data with two modifications. The first modification did not pay attention to the basic habitat object types and the second modification paid attention to the coral habitat, seagrass, macroalgae and substrate objects. The results of this study provide the value of determination R2 which increased from 72.1% to 78.6% and decreased the RMSE value from 3.3 meters to 2.9 meters.
ANALISIS SPASIAL KESESUAIAN BUDIDAYA KERAPU BERBASIS DATA PENGINDERAAN JAUH (STUDI KASUS: PULAU AMBON MALUKU) Anggraini, Nanin; Adawiah, Syifa Wismayati; Ginting, Devica Natalia Br; Marpaung, Sartono
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.v16i2.3358

Abstract

Indonesian waters have abundant marine aquaculture potential. This activity need to be maximized with remote sensing technology approach to determining locations that have the potential aquaculture areas. The research location is Ambon Island, Maluku Province. The method used for suitability site is Weighted Overlay Technique from biophysical parameters such as total suspended solids (TSS), sea surface temperature (SST), chlorophyll, and bathymetry. In addition, mangrove and coral reef data are used as a limiting factor for the suitability site. Based on the results of processing data, classes were quite suitable dominated in Piru Bay, Banguala Bay, and Ambon Bay; the appropriate classes were detected in Ambon Dalam Bay, and very suitable classes were detected in Piru Bay and Ambon Bay. The results of field measurement verification showed that the temperature of the image data with the insitu data correlated with the value of R2 0.74 and TSS image with insitu data shown R2 of 0.63.
PEMANFAATAN METODE SEMI-ANALITIK UNTUK PENENTUAN BATIMETRI MENGGUNAKAN CITRA SATELIT RESOLUSI TINGGI Setiawan, Kuncoro T.; Winarso, Gathot; Ginting, Devica N. BR.; Manessa, M.D.M.; Surahman, Surahman; Anggraini, Nanin; Hartuti, Maryani; Asriningrum, Wikanti; Parwati, Ety
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 18 No. 1 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v18i1.3361

Abstract

Semi-Analytical methods for detecting bathymetry using medium resolution satellite image data is the development of methods for determining satellite-based bathymetry. This method takes into account the principle of the propagation of light waves in water and the intensity of incident light which decreases according to the increase in depth traversed. The satellite image used is SPOT 7. The image is the latest generation of SPOT satellites which have 4 multispectral channels with a spatial resolution of 6 meters. Therefore, this high-resolution image is expected to produce bathymetry in shallow marine waters more accurately. Semi-analytical methods used to detect bathymetry are Benny and Dawson's methods. This method uses a comparison of the reflectance value between deep water and shallow water by taking into account the approach of the water column attenuation coefficient and the elevation angle of the satellite. The purpose of this study is to detect bathymetry in shallow sea waters. The study area is Karimunjawa Island coastal waters, Jepara, Central Java. The data used is the SPOT 7 acquisition image dated 18 May 2017 has been analysed, in situ depth data as well as tide data. The results showed that off the three SPOT 7 channels, the depth range of 0 - 11.45 meters for the blue channel band, 0 - 10.49 meters for the green channel and 0 - 9.72 meters for the channel red. The accuracy of the bathymetry detection results from the green channel shows quite good results to a depth of less than 5 meters. Green channel parameters of the Benny Dawson algorithm used are 0.3274 for Ld, 0.8932 for Lo, attenuation coefficient of 0.823 and Cosec E '0.6311272.
KESESUAIAN WILAYAH BUDI DAYA IKAN KERAPU BERDASARKAN CITRA SATELIT LANDSAT-8 OPERATIONAL LAND IMAGER (OLI)/THERMAL INFRARED SENSOR (TIRS) (STUDI KASUS PERAIRAN KECAMATAN GEROKGAK, KABUPATEN BULELENG, PROVINSI BALI) Azizah, Febiana Nur; Afgatiani, Pingkan Mayestika; Adawiah, Syifa Wismayanti; Anggraini, Nanin; Ginting, Devica Natalia Br; Patwati, Ety; Asriningrum, Wikanti
Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital Vol. 18 No. 1 (2021)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/inderaja.v18i1.3364

Abstract

he waters in Gerokgak District are one of the aquatic region in Indonesia that have potential as regional land for the development of aquaculture, one of which is grouper cultivation. To increase the potential of grouper cultivation, it is necessary to know the right location of grouper cultivation. This study applies a method using an overlay between oceanographic parameters, namely sea surface temperature (SST), salinity, chlorophyll, and Total Suspended Solid (TSS). In addition, this study also uses a remote sensing approach by utilizing Landsat-8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) satellite imagery data. The results of this study indicate that the waters in the Teluk Penerusan, Gerokgak District, Bali have waters that are suitable for grouper cultivation. Based analysis result between the values of sea surface temperature and chlorophyll with in situ values, it shows good accuracy with values of R2 = 0,661; 0,686 for chlorophyll in situ, and 0,658 for TSS with in situ.
Co-Authors Abd. Rahman As-syakur Adawiah, Syifa Wismayanti Afgatiani, Pingkan Mayestika Atriyon Julzarika Aziz, Kholifatul Azizah, Febiana Nur Azura Ulfa, Azura Bambang Trisakti Ety Parwati Gathot Winarso, Gathot Giarrastowo, Gigih Ginting, Devica N. BR. Ginting, Devica Natalia Br Herianto Herianto Kuncoro Teguh Setiawan, Kuncoro Teguh Manessa, M.D.M. Maryani Hartuti, Maryani MASITA DWI MANDINI MANESSA, MASITA DWI MANDINI Nandika, Muhammad Rizki Orbita Roswintiarti, Orbita Parwati Sofan, Parwati Patwati, Ety Prasetio, Wiji Ratih Dewanti -Hariyadi Sartono Marpaung, Sartono Setiawan, Kuncoro T. Soesilo, Tri Edhi Budhi Suardana, A. A. Md. Ananda Putra Supardjo, A. Harsono Surahman Surahman Syamsu Rosid Syifa Wismayati Adawiah, Syifa Wismayati Wijaya, Agung Dwi Wikanti Asriningrum, Wikanti