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Rapid detection of land cover change in tropical savanna environment using conditional change vector analysis on remote sensing data in Moyo watershed, Sumbawa Regency, West Nusa Tenggara Province, Indonesia Nugroho, Gatot; Chulafak, Galdita Aruba; Yulianto, Fajar
Journal of Degraded and Mining Lands Management Vol. 8 No. 3 (2021)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2021.083.2731

Abstract

In environmental management, land cover change is a crucial aspect. The area of tropical savanna environments is vulnerable to land degradation. This study aimed to rapidly detect land cover changes in a tropical savanna environment based on remote sensing data. Conditional change detection was performed using the Change Vector Analysis (CVA) with input parameters such as the Enhanced Vegetation Index (EVI) and Normalized Difference Soil Index (NDSI). The results showed that during the period 2015 to 2019, changes were detected in the Moyo watershed every year. From 2015 to 2016, the Moyo River Basin was dominated by changes with a change magnitude of less than 0.088, which was 63% of the Moyo River Basin area. From 2016 to 2017, the changes were dominated by the change magnitude value of 0.063, which was 58.6% of the Moyo River Basin area. From 2017 to 2018, changes were dominated by the change magnitude value of 0.084 of 55.26% of the Moyo watershed area. From 2018 to 2019, the change was dominated by the change magnitude value of 0.057, which was 47.57% of the Moyo watershed area. The direction of land cover change was dominated by Q2 in 2016, Q4 in 2017 and 2018, and Q2 and Q4 in 2019. These changes generally occurred in the Moyo watershed middle and downstream parts, which are grasslands. The use of the Conditional Change Vector Analysis (CCVA) approach in a tropical savanna environment can detect changes and the direction of change with an accuracy of about 70%.
Spatial and temporal distribution of estimated surface runoff caused by land use/land cover changes in the upstream Citarum watershed, West Java, Indonesia Yulianto, Fajar; Khomarudin, Muhammad Rokhis; Hermawan, Eddy; Nugroho, Nunung Puji; Chulafak, Galdita Aruba; Nugroho, Gatot; Nugroho, Udhi Catur; Suwarsono, Suwarsono; Fitriana, Hana Listi; Priyanto, Eko
Journal of Degraded and Mining Lands Management Vol. 9 No. 2 (2022)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2022.092.3293

Abstract

In Indonesia, flooding is one of the natural hazards that often occurs during the rainy season. Surface runoff coefficient values are an essential indicator of the supply of regional water resources. The smaller the surface runoff value, the greater the water storage in the ground, and the smaller surface was running water. This study analyses the spatial and temporal distribution of the estimated surface runoff caused by land use/land cover changes in the upstream Citarum watershed. The study area is located in the upstream Citarum watershed, West Java, Indonesia. The site has a long history of flooding and various complex environmental problems. The geographic Information System method was used as a tool in analyzing the spatially and temporally. The research result shows that there has been a change in land cover in several periods of the year in the Citarum upstream watershed. The occurrence of the LULC phenomenon positively affects the surface runoff coefficient. The increasing area of Built land and plantation in the Citarum upstream watershed will further increase the surface runoff coefficient and, in the end, will potentially increase the surface runoff and contribute to flooding in the Bandung basin. This study results can be used to provide input in determining the direction and policies for watershed management, taking into account the varying characteristics of each subwatershed.
The use of multi-sensor satellite imagery to analyze flood events and land cover changes using change detection and machine learning techniques in the Barito watershed Priyatna, Muhammad; Wijaya, Sastra Kusuma; Khomarudin, Muhammad Rokhis; Yulianto, Fajar; Nugroho, Gatot; Afgatiani, Pingkan Mayestika; Rarasati, Anisa; Hussein, Muhammad Arfin
Journal of Degraded and Mining Lands Management Vol. 10 No. 2 (2023)
Publisher : Brawijaya University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15243/jdmlm.2023.102.4073

Abstract

Indonesia is one of the countries in the world that is frequently affected by floods. Flood disasters can have various negative impacts and therefore need to be analyzed to determine prevention and mitigation measures. This study examined land cover change, flood detection, and flood distribution using multitemporal Sentinel-1 and Landsat-8 satellite imagery in the Barito watershed. A combination of change detection and the application of the Otsu algorithm was used to detect floodplains from Sentinel-1 imagery. Land use/land cover (LULC) changes are detected using a combination of change detection and machine learning in the form of a random forest algorithm. The overlay technique was used to analyze the distribution of floodplains. In this study, the floodplain in the study area was mapped to 109,623 ha. The change detection method detects a decrease in the areas of primary forest, secondary forest, fields, rice fields, shrubs and ponds, respectively, by 13,020 ha, 116,235 ha, 259 ha, 146,696 ha, 47,308 ha, and 9,601 ha. Settlements, bare land, plantations and water bodies increase by 14,879 ha, 64,830 ha, 218,916 ha, and 34,768 ha, respectively. Flooding was mainly found in the classes of rice fields, water bodies and primary forests.