{"title":"印度尼西亚Cisadane流域不同情景下土地利用/土地覆盖预测模型:对森林砍伐和粮食安全的影响","authors":"Wiwin Ambarwulan , Fajar Yulianto , Widiatmaka Widiatmaka , Ati Rahadiati , Suria Darma Tarigan , Irman Firmansyah , Muhrina Anggun Sari Hasibuan","doi":"10.1016/j.ejrs.2023.04.002","DOIUrl":null,"url":null,"abstract":"<div><p>Critical watersheds that exceed their carrying capacity occur in many regions of the world; their formation is facilitated by a significant driving factor known as land use/land cover (LULC) changes. This study aims to identify the LULC changes in Cisadane Watershed, Indonesia, in 2010, 2015, 2021, and simulate future LULC for 2030 and 2050. Landsat 2010 and 2015 and Sentinel 2A images from 2020 were employed for deriving LULC maps using Random Forest. This study applied a Land change modeler (LCM) under the multi-layer perception Markov chain (MLP-MC) to predict the future LULC in three scenarios. The scenarios are business as usual (BAU), protecting paddy fields (PPF), and protecting forest areas (PFA). The results showed that all the LULC maps demonstrated excellent accuracy, indicated by >83% overall accuracy. Furthermore, BAU produces the worst effect of decreasing forest and paddy field areas. PPF tends to cause forest loss, while PFA is predicted to reduce the paddy fields. There is a trade-off between maintaining food security and conserving natural resources. The study reveals the importance of efficient land use planning in the future amidst increasing resource demand due to population growth while existing land resources are limited.</p></div>","PeriodicalId":48539,"journal":{"name":"Egyptian Journal of Remote Sensing and Space Sciences","volume":null,"pages":null},"PeriodicalIF":3.7000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Modelling land use/land cover projection using different scenarios in the Cisadane Watershed, Indonesia: Implication on deforestation and food security\",\"authors\":\"Wiwin Ambarwulan , Fajar Yulianto , Widiatmaka Widiatmaka , Ati Rahadiati , Suria Darma Tarigan , Irman Firmansyah , Muhrina Anggun Sari Hasibuan\",\"doi\":\"10.1016/j.ejrs.2023.04.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Critical watersheds that exceed their carrying capacity occur in many regions of the world; their formation is facilitated by a significant driving factor known as land use/land cover (LULC) changes. This study aims to identify the LULC changes in Cisadane Watershed, Indonesia, in 2010, 2015, 2021, and simulate future LULC for 2030 and 2050. Landsat 2010 and 2015 and Sentinel 2A images from 2020 were employed for deriving LULC maps using Random Forest. This study applied a Land change modeler (LCM) under the multi-layer perception Markov chain (MLP-MC) to predict the future LULC in three scenarios. The scenarios are business as usual (BAU), protecting paddy fields (PPF), and protecting forest areas (PFA). The results showed that all the LULC maps demonstrated excellent accuracy, indicated by >83% overall accuracy. Furthermore, BAU produces the worst effect of decreasing forest and paddy field areas. PPF tends to cause forest loss, while PFA is predicted to reduce the paddy fields. There is a trade-off between maintaining food security and conserving natural resources. The study reveals the importance of efficient land use planning in the future amidst increasing resource demand due to population growth while existing land resources are limited.</p></div>\",\"PeriodicalId\":48539,\"journal\":{\"name\":\"Egyptian Journal of Remote Sensing and Space Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Egyptian Journal of Remote Sensing and Space Sciences\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1110982323000212\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Egyptian Journal of Remote Sensing and Space Sciences","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1110982323000212","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Modelling land use/land cover projection using different scenarios in the Cisadane Watershed, Indonesia: Implication on deforestation and food security
Critical watersheds that exceed their carrying capacity occur in many regions of the world; their formation is facilitated by a significant driving factor known as land use/land cover (LULC) changes. This study aims to identify the LULC changes in Cisadane Watershed, Indonesia, in 2010, 2015, 2021, and simulate future LULC for 2030 and 2050. Landsat 2010 and 2015 and Sentinel 2A images from 2020 were employed for deriving LULC maps using Random Forest. This study applied a Land change modeler (LCM) under the multi-layer perception Markov chain (MLP-MC) to predict the future LULC in three scenarios. The scenarios are business as usual (BAU), protecting paddy fields (PPF), and protecting forest areas (PFA). The results showed that all the LULC maps demonstrated excellent accuracy, indicated by >83% overall accuracy. Furthermore, BAU produces the worst effect of decreasing forest and paddy field areas. PPF tends to cause forest loss, while PFA is predicted to reduce the paddy fields. There is a trade-off between maintaining food security and conserving natural resources. The study reveals the importance of efficient land use planning in the future amidst increasing resource demand due to population growth while existing land resources are limited.
期刊介绍:
The Egyptian Journal of Remote Sensing and Space Sciences (EJRS) encompasses a comprehensive range of topics within Remote Sensing, Geographic Information Systems (GIS), planetary geology, and space technology development, including theories, applications, and modeling. EJRS aims to disseminate high-quality, peer-reviewed research focusing on the advancement of remote sensing and GIS technologies and their practical applications for effective planning, sustainable development, and environmental resource conservation. The journal particularly welcomes innovative papers with broad scientific appeal.