Article Per Year (5 Year)
p-Index From 2020 - 2025
0.817
P-Index
This Author published in this journals
All Journal Buletin PSP The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Wikanti Asriningrum
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 7 Documents
Search

 1 
PEMODELAN KLASIFIKASI TERUMBU BERBASIS GEOMORFOLOGI DAN PEMANFAATAN SUMBERDAYA IKAN KARANG Wikanti Asriningrum; Budy Wiryawan; Domu Simbolon; Iwan Gunawan
Buletin PSP Vol. 16 No. 3 (2007): Buletin PSP
Publisher : Institut Pertanian Bogor

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Coral reef is one of important economical value natural resources which is grow better in tropical region. Indonesia as a tropical country consists of 17.508 islands and 70% territory covered by sea, in which the shallow waters around the islands, is a place for coral reef to grow. Since the biophysical characteristic information of coral reef is essential for regional marine planning, this research aims to study the satellite remote sensing data processing for geomorphologic analysis of small islands, volcanic, coral, and atoll, and reef landform in order to arrange a geomorphology-based reef classification model. Domination, uniformity, and variety analysis of coral fish is conducted to find out the relationship between small island, reef and coral fish habitat. From remote sensing data processing model, multispectral fusion results obtained are 245 channel combinations for volcanic islands, 257 for coral islands, 237 for atoll islands, and 124 for coral reefs. Spectral enhancement is autoclip and spatial enhancement is high pass sharpen 2. Multispatial fusion enhances small island morphology but not enhances for coral reefs. Geomorphology-based reefs classification model divides reef into oceanic reef and shelf reef. More detailed classification for oceanic reef is divided into fringing reef, barrier reef, and atoll. While shelf reef used in the study area is lagoonal platform reef. This classification, combined with ecological-based coral reef classification, is used to identify life reef, dead reef, and sand in the certain reef landform.
PLATFORM REEF LAGOON DETECTION FROM SENTINEL-2 IN PANGGANG ISLAND AND SEMAKDAUN ISLAND Wikanti Asriningrum; Azura Ulfa; Kholifatul Aziz; Kuncoro T. Setiawan; Dyah Pangastuti
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3804

Abstract

Processing of satellite image data for the detection of platform reef lagoons is intended as one of the geo-physical parameters of the reef landform. Panggang Island and Semakdaun Island were chosen to make the detection model because they are ideal for lagoon reef landforms and tapulang court reefs. This model is only valid in the continental shelf area and the back arc and small island tectonic type. Determination of this location is done to improve the accuracy of spectral-based data processing. Platform reefs are one of four classes of reef landforms. Sentinel-2A data with a spatial resolution of 10m, blue, green, red, and near infrared bands were selected to investigate their ability to detect lagoons. Processing of data by calculating the Optimum Index Factor (OIF) to produce a composite image and drawing transect lines to produce pixel values and spectral graphics of the lagoon. The results of data processing in the form of graphs, composite images and pixel values were built to realize a digital lagoon detection model. These results are used for lagoon growth stage analysis for the classification of three reef platform landforms, visually and digitally interpretation. This digital and visual detection system design is useful for monitoring coral reef ecosystems.
DETECTION OF WATER-BODY BOUNDARIES FROM SENTINEL-2 IMAGERY FOR FLOODPLAIN LAKES Azura Ulfa; Fajar Bahari Kusuma; A. A. Md. Ananda Putra Suardana; Wikanti Asriningrum; Andi Ibrahim; Lintang Nur Fadlillah
International Journal of Remote Sensing and Earth Sciences Vol. 19 No. 2 (2022)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2022.v19.a3827

Abstract

The impact of climate and human interaction has resulted in environmental degradation. Consistent observations of lakes in Indonesia are quite limited, especially for flood-exposure lake types. Satellite imagery data improves the ability to monitor water bodies of different scales and the efficiency of generating lake boundary information. This research aims to detect the boundaries of flood-exposure type lake water bodies from the detection model and calculate its accuracy in Semayang Melintang Lake using Sentinel-2 imagery data. The characteristics of water, soil, and vegetation objects were investigated based on the spectral values of the composite image bands from the Optimum Index Factor (OIF) calculation, to support the lake water body boundary detection model. The Object-Based Image Analysis (OBIA) method is used for water and non-water classification, by applying the machine learning algorithms random forest (RF), support vector machine (SVM), and decision tree (DT). Model validation was conducted by comparing spectral graphs and lake water body boundary model results. The accuracy test used the confusion matrix method and resulted in the highest accuracy value in the SVM algorithm with an Overall Accuracy of 95% and a kappa coefficient of 0.9. Based on the detection model, the area of Lake Semayang Melintang in 2021 is 23392.30 ha. This model can be used to estimate changes in the area of the flood-exposure lake consistently. Information on the boundaries of lake water bodies is needed to control the decline in the capacity and inundation area of flood-exposure lakes for management and monitoring plans.
ANALYSIS OF THE PENETRATION CAPABILITY OF VISIBLE SPECTRUM WITH AN ATTENUATION COEFFICIENT THROUGH THE APPARENT OPTICAL PROPERTIES APPROACH IN THE DETERMINATION OF A BATHYMETRY ANALYTICAL MODEL Kuncoro Teguh Setiawan; Gathot Winarso; Muhammad Ulin Nuha; Maryani Hartuti; Devica Natalia BR Ginting; Emi Yati; Kholifatul Aziz; Fajar Bahari Kusuma; Wikanti Asriningrum
International Journal of Remote Sensing and Earth Sciences Vol. 18 No. 2 (2021)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2021.v18.a3667

Abstract

The attenuation coefficient (Kd) can be extracted by an apparent optical properties(AOP) approach to determine marine shallow-water habitat bathymetry based on an analytical method. Such a method was employed in the Red Sea by Benny and Dawson in 1983 using Landsat MSS imagery. Therefore, we applied the Benny and Dawson algorithm to extract bathymetry in shallow marine waters off Karimunjawa Island, Jepara, Central Java, Indonesia. We used the SPOT 6 satellite, which has four multispectral bands with a spatial resolution of 6 meters. The results show that three bands of SPOT 6 data (the blue, green, and red bands) can produce bathymetric information up to 30.29, 24.63 and 18.58 meters depth respectively. The determinations of the attenuation coefficients of the three bands are 0.08069, 0.09330, and 0.39641. The overall accuracy of absolute bathymetry of the blue, green, and red bands is 61.12%, 65.73%, and 26.25% respectively, and the kappa coefficients are 0.45, 0.52, and 0.13.
ANALYSIS OF WATER PRODUCTIVITY IN THE BANDA SEA BASED ON REMOTE SENSING SATELLITE DATA Sartono Marpaung; Rizky Faristyawan; Anang Dwi Purwanto; Wikanti Asriningrum; Argo Galih Suhadha; Teguh Prayogo; Jansen Sitorus
International Journal of Remote Sensing and Earth Sciences Vol. 17 No. 1 (2020)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2020.v17.a3280

Abstract

This study examines the density of potential fishing zone (PFZ) points and chlorophyll-a concentration in the Banda Sea. The data used are those on chlorophyll-a from the Aqua MODIS satellite, PFZ points from ZAP and the monthly southern oscillation index. The methods used are single image edge detection, polygon center of mass, density function and a Hovmoller diagram. The result of the analysis show that productivity of chlorophyll-a in the Banda Sea is influenced by seasonal factors (dry season and wet season) and ENSO phenomena (El Niño and La Niña). High productivity of chlorophyll-a  occurs during in the dry season with the peak in August, while low productivity occurs in the wet season and the transition period, with the lowest levels in April and December. The variability in chlorophyll-a production is influenced by the global El Niño and La Niña phenomena; production increases during El Niño and decreases during La Niña. Tuna conservation areas have as lower productivity of chlorophyll-a and PFZ point density compared to the northern and southern parts of the Banda Sea. High density PFZ point regions are associated with regions that have higher productivity of chlorophyll-a, namely the southern part of the Banda Sea, while low density PFZ point areas are associated with regions that have a low productivity of chlorophyll-a, namely tuna conservation areas. The effect of the El Niño phenomenon in increasing chlorophyll-a concentration is stronger in the southern part of study area than in the tuna conservation area. On the other hand, the effect of La Niña phenomenon in decreasing chlorophyll-a concentration is stronger in the tuna conservation area than in the southern and northern parts of the study area.
IDENTIFICATION OF MANGROVE FORESTS USING MULTISPECTRAL SATELLITE IMAGERIES Anang Dwi Purwanto; Wikanti Asriningrum
International Journal of Remote Sensing and Earth Sciences Vol. 16 No. 1 (2019)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2019.v16.a3097

Abstract

The visual identification of mangrove forests is greatly constrained by combinations of RGB composite. This research aims to determine the best combination of RGB composite for identifying mangrove forest in Segara Anakan, Cilacap using the Optimum Index Factor (OIF) method. The OIF method uses the standard deviation value and correlation coefficient from a combination of three image bands. The image data comprise Landsat 8 imagery acquired on 30 May 2013, Sentinel 2A imagery acquired on 18 March 2018 and images from SPOT 6 acquired on 10 January 2015. The results show that the band composites of 564 (NIR+SWIR+Red) from Landsat 8 and 8a114 (Vegetation Red Edge+SWIR+Red) from Sentinel 2A are the best RGB composites for identifying mangrove forest, in addition to those of 341 (Red+NIR+Blue) from SPOT 6. The near-infrared (NIR) and short-wave infrared (SWIR) bands play an important role in determining mangrove forests. The properties of vegetation are reflected strongly at the NIR wavelength and the SWIR band is very sensitive to evaporation and the identification of wetlands.
IN-SITU MEASUREMENT OF DIFFUSE ATTENUATION COEFFICIENT AND ITS RELATIONSHIP WITH WATER CONSTITUENT AND DEPTH ESTIMATION OF SHALLOW WATERS BY REMOTE SENSING TECHNIQUE Budhi Agung Prasetyo; Vincentius Paulus Siregar; Syamsul Bahri Agus; Wikanti Asriningrum
International Journal of Remote Sensing and Earth Sciences Vol. 14 No. 1 (2017)
Publisher : BRIN

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30536/j.ijreses.2017.v14.a2682

Abstract

Diffuse attenuation coefficient, Kd(λ), has an empirical relationship with water depth, thus potentially to be used to estimate the depth of the water based on the light penetration in the water column. The aim of this research is to assess the relationship of diffuse attenuation coefficient with the water constituent and its relationship to estimate the depth of shallow waters of Air Island, Panggang Island and Karang Lebar lagoons and to compare the result of depth estimation from Kd model and derived from Landsat 8 imagery. The measurement of Kd(λ) was carried out using hyperspectral spectroradiometer TriOS-RAMSES with range 320 – 950 nm. The relationship between measurement Kd(λ) on study site with the water constituent was the occurrence of absorption by chlorophyll-a concentration at the blue and green spectral wavelength. Depth estimation using band ratio from Kd(λ) occurred at 442,96 nm and 654,59 nm, which had better relationship with the depth from in-situ measurement compared to the estimation based on Landsat 8 band ratio. Depth estimated based on Kd(λ) ratio and in-situ measurement are not significantly different statistically. Depth estimated based on Kd(λ) ratio and in-situ measurement are not significantly different statistically. However, depth estimation based on Kd(λ) ratio was inconsistent due to the bottom albedo reflection because the Kd(λ) measurement was carried out in shallow waters. Estimation of water depth based on Kd(λ) ratio had better results compared to the Landsat 8 band ratio.
Co-Authors A. A. Md. Ananda Putra Suardana Anang Dwi Purwanto Andi Ibrahim Argo Galih Suhadha Azura Ulfa Budhi Agung Prasetyo Budy Wiryawan Devica Natalia BR Ginting Domu Simbolon Dyah Pangastuti Emi Yati Fajar Bahari Kusuma Gathot Winarso Iwan Gunawan Jansen Sitorus Kholifatul Aziz Kuncoro T. Setiawan Kuncoro Teguh Setiawan Lintang Nur Fadlillah Maryani Hartuti Muhammad Ulin Nuha Rizky Faristyawan Sartono Marpaung Syamsul Bahri Agus, Syamsul Bahri Teguh Prayogo Vincentius P Siregar