Article Per Year (5 Year)
p-Index From 2021 - 2026
2.217
P-Index
This Author published in this journals
All Journal Sumatra Journal of Disaster, Geography and Geography Education Sustainability (STPP) Theory, Practice and Policy International remote sensing application journal Future Space: Studies in Geo-Education
Putri, Sri Kandi
Unknown Affiliation
Agriculture, Biological Sciences & Forestry Astronomy Computer Science & IT Earth & Planetary Sciences Education Energy Environmental Science Social Sciences

Published : 16 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 4 Documents
Search
Journal : International remote sensing application journal

 1 
UTILIZATION OF REMOTE SENSING DATA IN IDENTIFYING COASTLINE CHANGES WITH THE BILKO ALGORITHM METHOD IN 2014, 2018, AND 2022 Basri, Zafini; Arif, Dian Adhetya; Putri, Sri Kandi; Fitriawan, Dedy
International Remote Sensing Applied Journal Vol 4 No 2 (2023): International Remote Sensing Application Journal (December Edition 2023)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v4i2.46

Abstract

The beach is a form of geology composed of sand located in coastal areas and the position of the coastline is dynamic. Identification of shoreline changes is important information that can be obtained from Remote Sensing Data and Geographic Information Systems (GIS) which has advantages and speed in the results of the process. This research was carried out in the Pasir Baru Beach area, Nagari Pilubang, Sungai Limau District using Landsat 8 OLI Satellite Images in 2014, 2018, and 2022 with the aim of determining changes in coastlines in the 2014-2018 and 2018-2022 ranges and knowing the extent of coastline changes in the 2014-2018 and 2018-2022 ranges. The method used to extract the coastline is obtained from the extraction results from the Landsat 8 OLI Satellite Image using the BILKO algorithm method, for the calculation of distance and rate of change of coastlines using a digital coastline analysis system (DSAS) with two statistical methods, namely Net Shoreline Movement (NSM) and End Point Rate (EPR) and for calculating the area of coastline change using the Calculate Geometry menu using attribute information in the software ArcGIS 10.5 in square meters (m2). Based on the results of the study that the coastal process that occurred in the research area from 2014-2022 was an erosion or abrasion event. The amount of erosion increased from 2018 to 2022 with an average erosion rate of 2.11 m / year, while the average abrasion distance was 7.49 m / year which was characterized by the formation of abrasion gawir and the fall of new trunk trees around the beach due to soil erosion. Meanwhile, the average rate for sedimentation or accretion events in 2018-2022 is 0.04 m/year while the average distance of change due to accretion events is 0.15 m/year. With a total area of erosion or abrasion events in 2018-2022 of 48,220.4 m, with an average annual area change of 12,055 m. Meanwhile, the total area of sedimentation or accretion events in 2018-2022 amounted to 449.3 m with an average annual area change of 112.3 m.
LAND COVER CLASSIFICATION WITH OBIA METHOD (OBJECT BASED IMAGE ANALYSIS) IN PADANGWEST DISTRICT, PADANG CITY Salsabila, Rania; Putri, Sri Kandi; Syahar, Fitriana; Fitriawan, Dedy
International Remote Sensing Applied Journal Vol 4 No 2 (2023): International Remote Sensing Application Journal (December Edition 2023)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v4i2.50

Abstract

High population growth has an impact on the development of a region. Therefore, the need for the latest information regarding land cover obtained through data processing using remote sensing techniques. This land cover monitoring utilizes object-based SPOT 7 satellite imagery data (OBIA) in West Padang District, Padang City. This research was conducted with the aim of knowing the level of accuracy of the OBIA method in land cover classification on SPOT 7 Imagery. The OBIA method consists of two stages, namely segmentation and classification with the Train Maximum Likelihood Classifier algorithm. In this study, there were 10 land cover classifications and resulted in an overall accuracy of 95% and a kappa accuracy of 94%.
DETECTION OF LAND USE CHANGES USING LANDSAT 8 COMPOSITE BAND 4,3,2 AND BAND 7,6,4 COMPOSITE IMAGES IN 2019 AND 2022 USING THE METHODPOST- CLASSIFICATION COMPARISSON PADANG CITY REGION saputra, eko bima; putri, sri kandi; ernawati, ernawati; febriandi, febriandi
International Remote Sensing Applied Journal Vol. 5 No. 1 (2024): International Remote Sensing Application Journal (June Edition 2024)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v5i1.53

Abstract

This study aims to 1) determine the area of land use in the city of Padang in 2019 and 2022 using the 4,3,2 (True Color) composite. 2) to determine the area of land use in Padang City in 2019 and 2022 using composite 7,6,4 (False Colour). 3) to find out changes in land use in the City of Padang in 2019 and 2022 using the Post- Classification Comparisson method. Processing is done using Landsat 8 satellite imagery downloaded from the USGS website. Before performing image interpretation, radiometric correction, atmospheric correction and geometric correction are carried out as well as band composite and satellite image cropping with the boundaries of the study area, namely the administrative boundaries of the City of Padang. The interpretation process is carried out using the Maximum Likelihood method using digital image processing applications and Geographic Information Systems (GIS). Change detection analysis method through Post-Classification Comparisson. Accuracy sampling was carried out systematically random sampling with the confusion matrix accuracy test technique. The results of the study in the Padang City area which has an area of 694.96 km2, Land use changes using Composite Band 4,3,2 Mixed Forests experienced a reduction of around 157.58Ha. Open land increased by around 48.85 Ha, rice fields decreased by 397.84 Ha. built-up area increased by around 94.12 Ha. Shrubs and shrubs, an increase of about 412.45 Ha. Changes in land use using Composite Band 7,6,4 Mixed Forest experienced a reduction of around 155.32 Ha. Open land increased by around 48.70 Ha. paddy fields decreased by 399.03 Ha. built-up area increased by around 94.83 Ha. Shrubs and shrubs increased by around 410.82 Ha of rivers in 2019 and in 2022 there will be no change with an area of 437.33 Ha.
USE OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS FOR FOREST RESOURCE BALANCE MAPPING IN LEMBAH GUMANTI DISTRICT, SOLOK DISTRICT sausaen, laura ovia; Syarief, Azhari; Iswandi U, Iswandi U; Putri, Sri Kandi
International Remote Sensing Applied Journal Vol. 5 No. 1 (2024): International Remote Sensing Application Journal (June Edition 2024)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v5i1.56

Abstract

The forest resources balance sheet prepared for the implementation of law no. 41 of 1999 ratified article 13 paragraph (4), in the technical process of implementation it always refers to the decision of the Minister of Forestry no. 6444/kpts-ll/1999 regarding instructions for preparing forest resource balance sheets. The forest resource balance sheet is information that describes forest resource reserves, loss and use of forest resources so that at a certain time the trend of surplus or deficit compared to the previous period can be seen. Law. 41 of 1999, article 13 paragraph 4. Remote sensing offers great potential for the development of methods for calculating the balance of forest resources and changes in the forest sector and geographic information systems (SIG) which are used to provide digital form and analysis of the earth's geographic surface so as to form precise and accurate spatial information. This research uses quantitative analysis. This research aims to determine changes in forestry stocks in the Gumanti Valley district, and knowledge about forest balance in the Gumanti Valley region. The results of research based on data show that around -12,708 ha of land in the form of secondary forest has experienced a reduction or deficit in area. Apart from that, other land that has experienced a reduction in area is primary forest. Meanwhile, the land that has experienced the most significant increase in area is in the form of fields covering an area of ​​+13,239 ha from 2017 to 2023.
Co-Authors Afifah, Nabilla Agustiyara Aisyah, Juliana Ameiliya, Nandha Anggita, Sekha Aprizon Putra Arifian, Naf'an Azhari Syarief Basri, Zafini Deded Chandra Dedy Fitriawan Dian Adhetya Arif dion, nofrion Ernawati Ernawati Febriandi Febriandi, Febriandi Helfia Edial Islamisari, Wilda Iswandi Iswandi Iswandi U Jasiro, Affandri Jaya, Wikan Lailatur Rahmi Lionar, Uun Mayasari, Dinda Mentari Dian Pertiwi Nova, Sari Noveraliza, Yessy Ratna Wilis Rery Novio Salsabila, Rania saputra, eko bima Sari Nova sausaen, laura ovia Septria, Adit Shatri, Alni Sri Mariya Syahar, fitriana Wita, Tria Maya