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All Journal Pendidikan Geografi Jurnal Riset Fisika Edukasi dan Sains Sumatra Journal of Disaster, Geography and Geography Education Jurnal Geografi Georafflesia : Artikel Ilmiah Pendidikan Geografi Jurnal Geografi JURNAL PENDIDIKAN TAMBUSAI Abdi: Jurnal Pengabdian dan Pemberdayaan Masyarakat Jurnal Administrasi Pemerintahan Desa YASIN: Jurnal Pendidikan dan Sosial Budaya ANWARUL: Jurnal Pendidikan dan Dakwah MASALIQ: Jurnal Pendidikan dan Sains ARZUSIN: Jurnal Manajemen dan Pendidikan Dasar Al-DYAS : Jurnal Inovasi dan Pengabdian kepada Masyarakat International remote sensing application journal Jurnal Geosains West Science JURNAL BUANA
Azhari Syarief
Lecturer Study Program D3 Remote Sensing Technology
Religion Humanities Astronomy Computer Science & IT Earth & Planetary Sciences Education Environmental Science Health Professions Medicine & Pharmacology Physics Public Health Social Sciences Other

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Journal : International remote sensing application journal

 1 
DETERMINATION OF COMMUNITY STRUCTURE AND INDEX MANGROVE HEALTH INDEX (MHI) IN DELI SERDANG DISTRICT, PROVINCE NORTH SUMATRA dea lusiyanti; Yudi Antomi; Triyatno Triyatno; Azhari Syarief
International Remote Sensing Applied Journal Vol 4 No 1 (2023): International Remote Sensing Application Journal (June Edition 2023)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v4i1.40

Abstract

This research aims to 1) Know the structure of the mangrove community in Deli Serdang Regency, 2) To find out the differences in the classification of the health level of the mangrove communities in Deli Serdang Regency using Sentinel 2A and Landsat 8OLI imagery in 2022. In determining the structure of the mangrove community carried out by making plot plots to measure trunk circumference and types of mangroves found in Deli Serdang Regency, while to find out differences in the classification of mangrove health levels it was done by comparing the vegetation density values ​​in the field and the canopy density values ​​based on the NDVI vegetation index from Sentinel 2A and Landsat 8OLI imagery. year 2022. The results of this study are, 1) The dominant mangrove species in Deli Serdang Regency are the Avicennia marina, Avicennia alba and Excoecaria agallocha types, with a low level of species diversity. 2) Sentinel 2A imagery is better to use than Landsat 8OLI imagery in determining the Mangrove Health Index (MHI).
UTILIZATION OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS FOR SHRIMP POND IDENTIFICATION USING OBIA METHOD IN BATANG ANAI DISTRICT Diva Valensia; Febriandi Febriandi; Azhari Syarief; Triyatno Triyatno
International Remote Sensing Applied Journal Vol 4 No 1 (2023): International Remote Sensing Application Journal (June Edition 2023)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v4i1.41

Abstract

This study aims to identify shrimp pond objects using Sentinel images in 2017 and 2022 and determine the area of ponds from 2017 to 2022 in Batang Anai District to monitor shrimp pond cultivation, where the amount of production each year always increases. The method used in this study is OBIA (Object Based Image Analysis). Based on the results of image interpretation of the Obia Citra Sentinel-2 method in 2017, it shows that the area of shrimp ponds in Batang Anai District, especially Nagari Katapiang, is only 1.82 ha. Meanwhile, the results of the interpretation of the Obia method image in 2022 show that the area of shrimp ponds in Batang Anai District is 102.75 ha. The Object Base Image Analysis (Obia) method used in Sentinel-2 images in 2017 and 2022 produces segmentation that shapes existing objects into a class that has the same characteristics. Shrimp ponds are segmented with a grayish dark hue, regular shape, boxed pattern, have a smooth texture, water site and associate with rivers. and located on the beach bordering the sea. The identification of obia method ponds in 2017 and 2022 has changed quite drastically in the last 5 years, namely the addition of pond areas of around 100.91 ha. Identification of ponds using the obia method produces segmentation which makes objects look the same into one object.
ESTIMATION OF MANGROVE FOREST CARBON STOCK USING THE VEGETATION INDEX METHOD IN PADANG PARIAMAN DISTRICT Insanul Putri; Yudi Antomi; Febriandi Febriandi; Azhari Syarief
International Remote Sensing Applied Journal Vol 4 No 1 (2023): International Remote Sensing Application Journal (June Edition 2023)
Publisher : Remote Sensing Technology Study Program

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/irsaj.v4i1.43

Abstract

Padang Pariaman Regency is categorized as a coastal district because it has a coastline of 42.11 km. Padang Pariaman Regency has resources, one of which is mangrove forests. Mangrove forests are scattered in several sub-districts in Padang Pariaman Regency. This study aims to determine the estimated carbon stock value of mangrove forests in Padang Pariaman District using the Geographic Information System and Landsat 8 imagery, and to determine the accuracy of the carbon stock estimation results from the Landsat 8 imagery vegetation index. The method used in this study isNormalized Difference Vegetation Index (NDVI). Based on the estimation results of the above surface biomass values ​​obtained from the calculation of the correlation and regression equations in band 6 Landsat 8 imagery shows that the estimation results of the above surface biomass of mangrove forests in Padang Pariaman District obtain a maximum value of 644.85 tons/ha and a minimum value of 487, 92 tons/ha to obtain an estimated carbon stock value of 46% of the biomass value and an estimated maximum carbon stock value of 296.63 tons/ha and a minimum of 224.44 tons/ha.
FLOOD IDENTIFICATION BY UTILIZING REMOTE SENSING AND SPATIAL ANALYSIS TECHNIQUES IN PADANG CITY Islami, Refki Addea; Ernawati, Ernawati; Edial, Helfia; Syarief, Azhari
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.v5i1.55

Abstract

Natural disasters floods are the most common disasters found almost everywhere, floods can cause damage and can even take lives. The city of Padang is often hit by flood disasters which result in damage and loss for those affected. This research aims to 1) To find out the results of identifying flood-prone areas by utilizing remote sensing and spatial analysis techniques in Padang City; 2) To determine the level of flood vulnerability by utilizing remote sensing and spatial analysis techniques in Padang City. This research uses an overlay method which combines several parameters. Parameters for identifying areas that have the potential for flooding in this research include slope, rainfall, land use, elevation, soil type, and river buffer. Each of these parameters is given a different scoring value and weight, then an overlay analysis is carried out and a flood hazard map will be produced as a result of the combination of parameters used. After obtaining the results from the overlay analysis of all parameters, the map of potential flood areas will be divided into 3 vulnerability classes, namely low, medium and high vulnerability classes. The results of the research are that the low vulnerability class has an area of ​​33854.4 ha with a percentage of 49% of the total area of ​​Padang City, the medium vulnerability class has an area of ​​26337.6 with a percentage of 38.2% of the total area, and the high vulnerability class has an area of ​​8823.3 ha with a percentage of 12.8% of the total area.
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.
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.
Co-Authors Aidhia Rahmi Akbar, Ramatul Alghiffari, Figo Alhadi, Zikri April Lidiya, Putri Aprizon Putra Bayu Wijayanto Bayu Wijayanto dea lusiyanti Dedi Hermon Dedy Fitriawan Dewantara, Bagus Putra Dio alex sandra Diva Valensia Endah Purwaningsih erna, ernawati Fadhillah, Abdul Khaliq Fauzan, Healdy Febriandi Febriandi fihansnur, henisya Fitri, Aynul Gilang Samudra Helfia Edial Hidayat, Rizki Insanul Putri Irmayanti, Silvia Irsal, Mursyid Islami, Refki Addea Isman, Mentari Ashari Iswandi U Lailatur Rahmi Malfira Salsabila, Rasyfa Marantika, Dewi Nurfadilah Nurfadilah Pahlevi, Arbiansyah Reza Prasetio, Hamyah Putri, Shalsabila Lachenda Putri, Sri Kandi Rachmawati, Fena Rahma, Anisa Lailatul Ramadhan, Risky Ramadhana, Yolla Ratna Wilis Riandini, Ory Rido Koja Salsabila, Fatihah Saputra, Dani sausaen, laura ovia Sri Mariya syahadani, meilani Triyatno Triyatno Triyatno Triyatno Triyatno Triyatno Wartin, Angeli Wulandari, Dina Yasranda, Ilham Yudi Antomi Zuhdi, Iqbal