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All Journal IAES International Journal of Artificial Intelligence (IJ-AI) Jurnal Azimut International remote sensing application journal
Dedy Fitriawan
Program Studi Geografi, Universitas Tamansiswa Padang
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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.
IDENTIFICATION OF LAND USE CHANGES USING THE OBJECT BASED IMAGE ANALYSIS (OBIA) METHOD IN BUNGUS TELUK KABUNG DISTRICT Wahyuni, Sri Agustia; Fitriawan, Dedy; Triyatno, Triyatno; Arif, Dian Adhetya
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.v4i2.48

Abstract

Object-based image analysis (OBIA) is an image classification that considers not only the spectral aspects of objects, but also their spatial aspects. This classification is guided by objects that have distribution patterns from object samples which are used as references for their accuracy. However, this object-based classification process must be taken into account when looking at color and calculating it so that there is no error in classification. In this research, the OBIA method was used to identify changes in land use in the Bungus Teluk Kabung District in 2012, 2017 and 2022. By using the OBIA method, identification results were obtained in areas where land use changes occurred between 2012 and 2017, which were identified as having changed from open land to built-up land. with an area of 355.84ha, plantations 22.62ha and rice fields 20.97ha. From 2017 to 2022, it was identified that there was a change in land use from dry land forests to 6.30ha of built-up land. The change in open land to built-up land was 7.47ha. Plantations experienced changes to 6.21ha of built-up land and 9.27ha of rice fields. Meanwhile, bushes/shrubs experienced changes in plantations of 2.47ha.
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%.
THE USE OF SENTINEL-2A IMAGERY FOR MAPPING THE CONVERSION OF AGRICULTURAL LAND INTO DEVELOPED LAND USING THE OBIA METHOD IN BATANG ANAI DISTRICT 2017 AND 2022 syahadani, meilani; Syarief, Azhari; Ramadhan, Risky; Fitriawan, Dedy
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.v5i1.57

Abstract

Indonesia is a developing country with a population growth rate of 1.38%. Due to the relatively strong population growth every year, this greatly affects land change. Therefore, the phenomenon of land use change emerged. In general, the rate of population growth correlates with the rate of land use change, which results in increased satisfaction of land-use needs such as settlements and public facilities. This study aims to determine the Change in Land Cover resulting from the Change of Agricultural Land Function into developed land and where the direction of changing agricultural land to developed land in Batang Anai District. This study uses a quantitative approach by utilizing Remote Sensing using Object-Based Classification (OBIA). Based on the interpretation results on Sentinel-2A images in 2017 and 2022, 8 land cover classes were found with an Overall Accuracy of 91% and a Kappa Index of 89.80%. Agricultural land in Batang Anai District has undergone land conversion into built-up land of 304.2 Ha or 8.70% of the agricultural land area in Batang Anai District with a total of 3499.16 Ha so that the remaining agricultural land area in 2022 is 3194.96 Ha. As a result of the land use change, there was a development of built-up land which was converted into housing development, public facilities and the Padang-Pekanbaru toll road leading from South to North.
MAPPING OF LAND USE CHANGES AND ALIGNMENT OF SPATIAL PATTERN PLANS IN PADANG CITY Delta, Yusran Rizky Ananda; Ismail, Muhammad; Syahar, Fitriana; Fitriawan, Dedy
International Remote Sensing Applied Journal Vol. 5 No. 2 (2024): International Remote Sensing Application Journal (December Edition 2024)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v5i2.64

Abstract

Changes in land use in accordance with spatial pattern plans are a challenge for the government as the population in an area increases, resulting in increased land requirements. This greatly influences the spatial pattern plans that have been planned previously. These land use changes can be obtained from Remote Sensing data which has the advantage and ease of obtaining land use information. This research uses Sentinel-2A satellite image data for 2017 and 2023. The objectives of this research are (1) To determine the ability of Sentinel-2A imagery to interpret land use (2) To determine changes in land use in 2017 and 2023 (3) To find out the alignment of land use identification with the Padang City spatial pattern plan. The method used in this research is a quantitative method with an approach spatial (spatial approach). The method used for land use classification is the manual digitization method (on screen) and land use area calculation using the Geometry Calculator tool in ArcGIS 10.6.1 software. The research results show the ability of Sentinel-2A imagery to produce 15 land uses, namely highland forest, residential/mixed buildings, rivers, cultivated open land, rice fields, dry land seasonal crops, bushes and thickets, mining, runways, ports, buildings industry and trade, grass, mangrove forests, savannas and stretches of coastal sand. In a period of 5 years there were 13 land uses that experienced changes, namely highland forests, residential/mixed buildings, open cultivated land, bushes and shrubs, mining, industrial/commerce buildings, dry land seasonal crops, rice fields, mangrove forests, stretches of beach sand and grass. The harmony between the land use of Padang City and the Padang City Spatial Pattern Plan is dominated by harmony, but there are also those which are not in harmony, namely highland forests, residential/mixed buildings, rice fields, dry land annual crops and mining.
USE OF MEDIUM RESOLUTION IMAGERY FOR PREDICTION MAPPING OF LAND COVER CHANGES IN SOLOK DISTRICT Sari, Yolanda Indah Permata; Fitriawan, Dedy; Antomi, Yudi; Arif, Dian Adhetya
International Remote Sensing Applied Journal Vol. 5 No. 2 (2024): International Remote Sensing Application Journal (December Edition 2024)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v5i2.65

Abstract

This research aims to determine changes in land cover from 2017-2022 in Solok Regency, to find out predictions of changes in land cover until 2032 in Solok Regency, to find out the results of land cover accuracy tests in Solok Regency. This research uses the Supervised (Maximum Likelihood) method to identify changes in land cover in Solok Regency in 2017 and 2022. This research was carried out in several stages, namely the preprocessing stage including radiometric and atmospheric correction, image cropping according to the research area. The processing stage uses the Supervised (Maximum Likelihood) method to determine the classification, then creating a land cover change identification matrix, creating sample points in the field, accuracy testing, and finally making predictions using the Cellular Automata model to predict land cover in 2032. Identification results in areas there was a change in land cover from 2012 to 2017 to 2022, land cover that changed, namely primary forest in 2012 to 2017 experienced a change in 2022 to 206,362.04ha, built-up land also experienced an area change of 3,162.37ha, followed by open land experiencing changes 283.98ha, mixed plantation land experienced a change of 78,176.71ha, wetland farming experienced a change of 12,751.07ha and dry land farming experienced a change of 20,707.08ha in 2022. Then the results of land cover predictions in 2032 are forest land area primary area in Solok Regency changed to 207,382.99ha, while the area of ​​water bodies changed to 6,889.05ha, then built-up land experienced a change of 3,288.13ha, then open land cover changed to 77,912.95ha, then mixed plantation cover changed to 13,248.51 , in wetland agriculture it changed to 13,248.51ha and dryland agriculture to 19,164.11ha.
Co-Authors Abdul Hamid Azhari Syarief Basri, Zafini Bin Mohamad, Kamaruddin Malik Cik Feresa Mohd Foozy, Cik Feresa Delta, Yusran Rizky Ananda Dian Adhetya Arif Hary Tri Senov Hasugian, Joni Heny Mariati Maslan, Andi Muhammad Ismail Novelisa Suryani Nurfadilah Nurfadilah Osronita Osronita Putri, Sri Kandi Rahma Dinda Ramadhan, Risky Rengga Permana Rengga Permana Putra Roberto Roberto Salsabila, Rania Sari, Yolanda Indah Permata syahadani, meilani Syahar, fitriana Triyatno Triyatno Wahyuni, Sri Agustia Yudi Antomi