Garuda - Garba Rujukan Digital

Article Per Year (5 Year)

p-Index From 2021 - 2026

0.778

P-Index

This Author published in this journals

All Journal JPG (Jurnal Pendidikan Geografi) International remote sensing application journal

Sri Kandi Putri

Jurusan Geografi, Fakultas Ilmu Sosial, UniversitasNegeri Padang

Author-ID : 5570004

Astronomy Computer Science & IT Earth & Planetary Sciences Education

Published : 4 Documents Claim Missing Document

Claim Missing Document

Articles

Title

UTILIZATION OF REMOTE SENSING IMAGES IN MAPPING SUSPENDED SOLID IN LAKE MANINJAU WEST SUMATRA PROVINCE Ilham Ridho; Dian Adhetya Arief; Sri Kandi Putri
International Remote Sensing Applied Journal Vol 2 No 1 (2021): international remote sensing application journal (June Edition 2021)
Publisher : Remote Sensing Technology Study Program

Remote sensing is generally defined as the technical art of obtaining information or data regarding the physical condition of an object or object, target, target or area and phenomenon without touching or direct contact with the object or target (Soenarmo, 2009). With remote sensing data, this research can easily see how the condition of the lake water. Based on these factors, efforts are needed to monitor the distribution of TSS in Lake Maninjau considering the importance of water potential to support various needs. In this study the classification was divided into 5 for the first class with concentration values of tss- 0 – 15 mg/L, 15 – 25 mg/L, 25 – 35 mg/L, TSS 35 – 80 mg/L, TSS > 80 mg/L. The result of in situ data processing is the lowest value is 8.2 mg/L and the highest is 72.2 mg/L. The Syarif Budhiman algorithm has the lowest at 8.14 mg/L and the highest at 40.04 mg/L. The lowest Parwati algorithm is 3.32 mg/L and the highest is 32.86 mg/L. The Guzman - Santaella algorithm has the lowest at 3.15 mg/L and the highest at 164.38 mg/L. The TSS concentrations in the alleged party and budhiman algorithms tend to have the same pattern as the TSS concentrations in the field, but there are several points with significant differences. The validation test shows that the Budhiman Algorithm (2004) has the smallest NMAE value between in situ data and image processing with a value of 14.4%.

UTILIZATION OF IMAGE SENTINEL-1 SAR FOR IDENTIFICATION OF FLOOD DISTRIBUTION AREA In PANGKALAN KOTO BARU SUMATERA DISTRICT Mardalena Mardalena; Sri Kandi Putri
International Remote Sensing Applied Journal Vol 2 No 2 (2021): international remote sensing application journal (Dec Edition 2021)
Publisher : Remote Sensing Technology Study Program

This research was conducted to determine the flood distribution area in Pangkalan Koto Baru District. Using the Normalized Difference Sigma Index (NDSI) method. By using this remote sensing method, it is possible to identify the flood distribution areas in Pangkalan Koto Baru District on March 15 2017. In this study, the identification of flood distribution areas using Sentinel-1 satellite imagery data. The sentinel-1 image data needed is before the flood (20 February 2017) and at the time of the flood (15 March 2017). Furthermore, Sentinel-1 Image processing begins with a subset, some radiometric corrections and geometric corrections. The Normalized Difference Sigma Index (NDSI) method is used to identify the flood distribution which is then vectorized. The results of the study have taken that based on the results of flood analysis using the GIS technique the area identified as flooding in this study is 41561.172 Ha. In Nagari Tanjuang Pauah it is ± 2454.301 Ha, Nagari Tanjuang Balik is ± 2076.138 Ha, Nagari Pangkalan is ± 14765.141 Ha, Nagari Mangilang is ± 917.724 Ha, Nagari Koto Alam is ± 8361.579 Ha, and Nagari Gunuang Manggilang is ± 917.724 Ha.

COMPARISON OF ASTER GDEM IMAGES AND SRTM IMAGES FOR RIVER WATERSHED AND GEOMORPHOLOGY STUDY Naf’an Arifian; Kemal Rahman Denis; 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

This study uses two DEM images, namely ASTER GDEM and DEM SRTM to map the distribution of rivers and geomorphology located in The District of Pesisir Selatan. In this study a comparison of the two images was carried out with the same level of resolution of 30 meters to see the accuracy of the images used in the study of watersheds and geomorphology. The method used in this research is processing image data then identifying the river for each image used. Further carrying out a confusion matrix which is used to check or improve data from a quantitative approach. The results of the study in terms of comparison of ASTER and SRTM images for watershed identification show that SRTM imagery is more accurate in identifying watersheds compared to ASTER imagery. After taking samples with the number of sample points taken, namely 36 samples on each, and then testing for spatial accuracy, the results show that the SRTM imagery had an accuracy rate of 88% where out of 36 sample points only 5 were wrong or not on the river. Whereas in the ASTER image of 36 sample points, there were only 6 which were right on the river, show that the level of image accuracy is only 14% for river identification. The study also shows that after the research process and accuracy test, for geomorphologic identification on the two DEM images, namely DEM SRTM and ASTER GDEM, it found that both images have the same level of accuracy, therefore both images are equally good at identifying geomorphology.

Co-Authors Dian Adhetya Arief Dian Adhetya Arif Ilham Ridho Indah Fultriasantri Kemal Rahman Denis Mardalena Mardalena Naf’an Arifian

Title Search

Found 3 Documents Search Journal : International remote sensing application journal

Abstract

Abstract

Abstract

Title

Found 3 Documents
Search
Journal : International remote sensing application journal