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All Journal Jurnal Mahasiswa Jurusan Teknik Sipil Rekayasa Sipil AGRIVITA, Journal of Agricultural Science
Pudyono .
Jurusan Teknik Sipil Fakultas Teknik Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Civil Engineering, Building, Construction & Architecture

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Journal : AGRIVITA, Journal of Agricultural Science

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THE USE OF SATELLITE REMOTE SENSING DATA AND GEOGRAPHIC INFORMATION SYSTEMS ON CRITICAL LAND ANALYSIS Suharyanto, Agus; Suhartanto, Ery; Pudyono, Pudyono
AGRIVITA, Journal of Agricultural Science Vol 35, No 2 (2013)
Publisher : Faculty of Agriculture University of Brawijaya and Indonesian Agronomic Assossiation

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

Abstract

Critical land classification can be analyzed using combination between Top Soil Thickness - Land erosion method, and BRLT methods. Both methods are needed soil erosion data as one of input data. The soil erosion data can be analyzed using USLE and MUSLE methods. The combination of two critical land analyses methods with input soil erosion data from two analyses methods will be produced four combinations of critical land classification. In this research, four of the critical land classification and two soil erosion classification will be analyzed using GIS. The best method to classify critical land will be investigated in this research. The best classified critical land is the classified critical land data is nearest with the field condition.Percentage of vegetation cover (PVC) is one of the most important input data in the critical land classification analysis using BRLKT method. This data have 50% weight. PVC condition is classified into five categories i.e. very good, good, fair, poor, and very poor. Each category have score 5, 4, 3, 2, 1 respectively. To analyze this PVC classification, NDVI generated from satellite remote sensing data is used in this research. From the four methods of land critical classification analyses used in this research, critical land classified using BRLKT method with input soil erosion analyzed using method is produced the critical land classification nearest with the critical land condition in the field.Keywords: Critical land, Land erosion, GIS, Satellite Remote Sensing Data, NDVI
THE USE OF SATELLITE REMOTE SENSING DATA AND GEOGRAPHIC INFORMATION SYSTEMS ON CRITICAL LAND ANALYSIS Agus Suharyanto; Ery Suhartanto; Pudyono Pudyono
AGRIVITA, Journal of Agricultural Science Vol 35, No 2 (2013)
Publisher : Faculty of Agriculture University of Brawijaya in collaboration with PERAGI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17503/agrivita.v35i2.182

Abstract

Critical land classification can be analyzed using combination between Top Soil Thickness - Land erosion method, and BRLT methods. Both methods are needed soil erosion data as one of input data. The soil erosion data can be analyzed using USLE and MUSLE methods. The combination of two critical land analyses methods with input soil erosion data from two analyses methods will be produced four combinations of critical land classification. In this research, four of the critical land classification and two soil erosion classification will be analyzed using GIS. The best method to classify critical land will be investigated in this research. The best classified critical land is the classified critical land data is nearest with the field condition.Percentage of vegetation cover (PVC) is one of the most important input data in the critical land classification analysis using BRLKT method. This data have 50% weight. PVC condition is classified into five categories i.e. very good, good, fair, poor, and very poor. Each category have score 5, 4, 3, 2, 1 respectively. To analyze this PVC classification, NDVI generated from satellite remote sensing data is used in this research. From the four methods of land critical classification analyses used in this research, critical land classified using BRLKT method with input soil erosion analyzed using method is produced the critical land classification nearest with the critical land condition in the field.Keywords: Critical land, Land erosion, GIS, Satellite Remote Sensing Data, NDVI
Co-Authors Abdurrahman, Gani Agus Suharyanto Agus Suharyanto Agus Suharyanto Alwafi Pujiraharjo Alwafi Pujiraharjo Arief Rachmansyah Arief Rachmansyah Da Costa Rao, Fredy Benedictus Dewa Hari Wicaksono Dwi Ratna Nur F. Ery Suhartanto Ery Suhartanto Fatimatuzahro Fatimatuzahro Gustianto, Garindra IGN Adipa Indradi Wijatmiko Khoirul Azhar M Hamzah Hasyim M. Hamzah Hasyim M. Ruslin A., M. Ruslin M. Ruslin Anwar M. Ruslin Anwar Prastumi Prastumi Sahiruddin M. Saifoe El Unas Sunik Sunik Suroso Suroso Usri Amrullah Wiharsa, Ida Aditya Yatnanta Padma Devia Yulvi Zaika Zarkasi, Hamim