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MAPPING OF PELAGIC FISHING POTENTIALS USING SINGLE IMAGE EDGE DETECTION (SIED) AND TEMPERATURE GRADIENT ANALYSIS (TGA) IN THE WATERS OF PADANG CITY Rahmad Triadi Akbar; Sri Kandi Putri
International Remote Sensing Applied Journal Vol 1 No 2 (2020): international remote sensing application journal (December Edition)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (856.282 KB) | DOI: 10.24036/irsaj.v1i2.15

Abstract

Padang City waters are one of the waters that have very promising potential for fishermen. This study aims to obtain potential areas for catching large pelagic fish which are analyzed using fashionable image data of chlorophyll a and SST. This research was carried out in November 2021. This research covered the period June, July and August, on June 9 potential zones for large pelagic fish were scattered, based on the distribution of potential large pelagic fish zones a distance of beat tween 1,000 meters to 5,000 resulted in 5 zones of potenzones for large pelagic fish and a distance of 1,000 meters to 10,000 or sea II produces 4 zones indicating the potential for large pelagic fish. In July the potential zone for large pelagic fish increased by 14 potential zones for large pelagic fish from a distance of 5. As a result, the distribution of sea surface temperature increases every month and the distribution of chlorophyll tends to crease. Based on the results of the interpolation of the potential for large pelagic fish, August is a month that has the potential for large pelagic fish catching zones, in the distribution of potential fish zones in the waters of Padang City, the average sea depth is between 10 meters and 50 meters. Based on tests of the accuracy of the distribution of fishing vessels in the waters of the City of Padang, only 5,000 meters from the shoreline, this has resulted in fewer fisherfewerbeing able to explore the potential spread across the waters of the City of Padang because there are no ships with engines with tonnage or wide cruising to be able to explore existing the potential.
UTILIZING LANDSAT 8 IMAGERY FOR MAPPING OF BURNED AREAS USING THE NORMALIZE DIFFERENCE VEGETATION INDEX (NDVI) AND NORMALIZE BURN RATIO (NBR) METHODS Rizka Fadil; Dian Adhetya Arief; Sri Kandi Putri
International Remote Sensing Applied Journal Vol 1 No 2 (2020): international remote sensing application journal (December Edition)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (713.159 KB) | DOI: 10.24036/irsaj.v1i2.17

Abstract

This study aims (1) to map changes in the area of ​​forest land in the western part of Bengkalis Regency in 2016 and 2021, (2) to determine the distribution of the area of ​​forest burned in the western part of Bengkalis Regency, (3) to determine the severity of forest fires in the District of Bengkalis West Bengkalis.This study used the NDVI (Normalized Difference Vegetation Index) method by Huete et. Al by compositing band 5 (NIR) and band 4 (Red) on Landsat 8 imagery which was processed using ArcGIS software before and after a forest fire. As well as the NBR (Normalized Burn Ratio) and dNBR (Difference Normalized Burn Ratio) methods by Eidenshink et al by compositing band 5 (NIR) and band 7 (SWIR) on Landsat 8 images processed using QGIS software. For sampling using random sampling method and accuracy test using overall accuracy, user's accuracy, producer's accuracy, and kappa analysis. The results of this study are (1) the area of ​​forest land in Bengkalis Regency continues to decrease every year, in 2016 the area of ​​forest land903,920 ha and 2021 the total forest area is463,441 ha. (2)The area of ​​forest land burned due to forest fires in Bengkalis Regency, which burned the least was 267.43 ha, while it was 1468.93 ha and the most extensive was 2186.53 ha.(3) Based on one forest fire distribution map, it is divided into 7 fire severity classes, namely high post-fire regrowth, low post-fire regrowth, no burning, low, medium-high and very high and the most dominant forest fire level is low-high.
Mapping of Limestone Potential Using Landsat 8 Satellite Imageryin Some Areasof Timpeh Sabrina Roselini; Dian Adhetya Arif; Sri Kandi Putri
International Remote Sensing Applied Journal Vol 3 No 2 (2022): International remote sensing application journal (Dec Edition 2022)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (628.524 KB) | DOI: 10.24036/irsaj.v3i2.36

Abstract

Limestone potential is important information that can be obtained from remote sensing data which has advantages and speed in processing results. Remote sensing is a technology that can overcome the problemof measuring data for fast and accurate information. This research was carried out in some areas of the Timpeh sub-district,andDharmasraya districtusing Landsat 8-OLI imagery with the aimof1) identifying the potential of limestone using the Band Ratio method. 2) How to apply remote sensing in mapping the potential of limestoneusing Landsat 8 Oli imagery. This research was carried out in several stages, namely Pre Processing which included radiometric correction and atmospheric correction, image cropping according to the research area, and processing whichincluded making geological maps, making landform maps, making maps of river flow patterns and vegetationindex maps and limestone identification using the RGB band ratio method (5/4;6/3;4/2). The results of field identification in potential limestone areas, where the RGB (Red Green Blue)composite of the band ratio 5/4;6/3;4/2 shows that the presence of limestone is characterized by the appearanceof greenish-brown colored objects. The average pixel value for limestone with a band ratio of 5/4 is 2.475, for a6/3 ratio is 1.275 and for a 4/3 ratio is 0.788. In this study, the potential area of limestone in the research areawasfound,whichwas approximately 2352,14564 ha.
IDENTIFICATION OF EROSION RATE USING UNIVERSAL SOIL LOSS EQUATION (USLE) METHOD IN KOTO TANGAH DISTRICT PADANG CITY IN 2024: Inggris Raju Mahendrik; Sri Kandi Putri
International Remote Sensing Applied Journal Vol. 6 No. 1 (2025): International Remote Sensing Application Journal (June Edition 2025)
Publisher : Remote Sensing Technology Study Program

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

Abstract

This study aims to analyze the erosion rate in Koto Tangah District, which is an area with varied topography and high rainfall. The area of ​​this area reaches 232.25 square kilometers, this area faces an increased risk of erosion due to human activities such as land clearing for agriculture and settlements. This study aims to: (1) calculate the erosion rate using the USLE method, and (2) map the distribution of areas with the potential for erosion in 2024. The formulation of the problem is focused on identifying the magnitude of the erosion rate and the distribution pattern of areas prone to erosion in Koto Tangah District. The research method uses the Universal Soil Loss Equation (USLE) approach integrated with the Geographic Information System (GIS). The data used include: rainfall data from CHIRPS 2024, soil type data from the Digital Soil Map of the World (DSMW) 2007, slope data from DEM, and land use data from the interpretation of Landsat imagery on October 8, 2024 using the Maximum Likelihood Classification method. The results of the analysis are expected to provide important information for the government and the community in disaster mitigation efforts and natural resource management. The study shows variations in erosion rates from <15 tons/ha/year to >480 tons/ha/year, with steep mountainous areas (>45%) showing the highest erosion rates. The discussion reveals that the interaction of slope factors, soil type, and land cover are the main determinants of the magnitude of erosion. Through a better understanding of erosion conditions in Koto Tangah, it is hoped that proactive steps can be taken to reduce the negative impacts of soil erosion and increase environmental resilience.