Ewa Gromny , Małgorzata Jenerowicz-Sanikowska , Jörg Haarpaintner , Sebastian Aleksandrowicz , Edyta Woźniak , Lluís Pesquer Mayos , Magdalena Chułek , Karolina Sobczak-Szelc , Anna Wawrzaszek , Szymon Sala , Astrid Espegren , Daniel Starczewski , Zofia Pawlak
{"title":"遥感洞察土地覆被动态和社会经济驱动因素:坦桑尼亚 Mtendeli 难民营案例(2016-2022 年)","authors":"Ewa Gromny , Małgorzata Jenerowicz-Sanikowska , Jörg Haarpaintner , Sebastian Aleksandrowicz , Edyta Woźniak , Lluís Pesquer Mayos , Magdalena Chułek , Karolina Sobczak-Szelc , Anna Wawrzaszek , Szymon Sala , Astrid Espegren , Daniel Starczewski , Zofia Pawlak","doi":"10.1016/j.rsase.2024.101334","DOIUrl":null,"url":null,"abstract":"<div><p>The purpose of this article is to present the scope and the dynamics of the environmental changes unfolded in the vicinity of Mtendeli refugee camp. It presents a new method, which combines geospatial analysis of high-resolution Earth observation data (Sentinel-1&2) with ground-based observations and input from local experts. Time series classifications of annual land use/land cover in the surroundings of the camp is developed from remote data. Subsequently main transitions and trends are quantitatively achieved. This is a first study which, not only treats the land transition process in a comprehensive manner, but also tracks the changes and their main drivers on an annual scale over the lifetime of the camp (2016–2021) and the post-closure situation in 2022. Most importantly, thanks to the involvement of social studies, it unfolds the socio-economical drivers of those changes. Drawing upon a random forest algorithm and available databases, we achieve overall classification accuracies of 83.5% (2020) and 82.0% (2022). Our findings indicate an ongoing expansion of cropland between 2016 and 2021, to the detriment of natural vegetation classes. The impact of environmental restoration programs implemented in the former camp area is visible by 2022. The proposed method can be used to identify areas of environmental risk and thus support decisions linked with sustainable development and land management.</p></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"36 ","pages":"Article 101334"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2352938524001988/pdfft?md5=489236b2bf08863cf5a44ab1e38b7197&pid=1-s2.0-S2352938524001988-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Remote sensing insights into land cover dynamics and socio-economic Drivers: The case of Mtendeli refugee camp, Tanzania (2016–2022)\",\"authors\":\"Ewa Gromny , Małgorzata Jenerowicz-Sanikowska , Jörg Haarpaintner , Sebastian Aleksandrowicz , Edyta Woźniak , Lluís Pesquer Mayos , Magdalena Chułek , Karolina Sobczak-Szelc , Anna Wawrzaszek , Szymon Sala , Astrid Espegren , Daniel Starczewski , Zofia Pawlak\",\"doi\":\"10.1016/j.rsase.2024.101334\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The purpose of this article is to present the scope and the dynamics of the environmental changes unfolded in the vicinity of Mtendeli refugee camp. It presents a new method, which combines geospatial analysis of high-resolution Earth observation data (Sentinel-1&2) with ground-based observations and input from local experts. Time series classifications of annual land use/land cover in the surroundings of the camp is developed from remote data. Subsequently main transitions and trends are quantitatively achieved. This is a first study which, not only treats the land transition process in a comprehensive manner, but also tracks the changes and their main drivers on an annual scale over the lifetime of the camp (2016–2021) and the post-closure situation in 2022. Most importantly, thanks to the involvement of social studies, it unfolds the socio-economical drivers of those changes. Drawing upon a random forest algorithm and available databases, we achieve overall classification accuracies of 83.5% (2020) and 82.0% (2022). 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Remote sensing insights into land cover dynamics and socio-economic Drivers: The case of Mtendeli refugee camp, Tanzania (2016–2022)
The purpose of this article is to present the scope and the dynamics of the environmental changes unfolded in the vicinity of Mtendeli refugee camp. It presents a new method, which combines geospatial analysis of high-resolution Earth observation data (Sentinel-1&2) with ground-based observations and input from local experts. Time series classifications of annual land use/land cover in the surroundings of the camp is developed from remote data. Subsequently main transitions and trends are quantitatively achieved. This is a first study which, not only treats the land transition process in a comprehensive manner, but also tracks the changes and their main drivers on an annual scale over the lifetime of the camp (2016–2021) and the post-closure situation in 2022. Most importantly, thanks to the involvement of social studies, it unfolds the socio-economical drivers of those changes. Drawing upon a random forest algorithm and available databases, we achieve overall classification accuracies of 83.5% (2020) and 82.0% (2022). Our findings indicate an ongoing expansion of cropland between 2016 and 2021, to the detriment of natural vegetation classes. The impact of environmental restoration programs implemented in the former camp area is visible by 2022. The proposed method can be used to identify areas of environmental risk and thus support decisions linked with sustainable development and land management.
期刊介绍:
The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems