The Experts below are selected from a list of 306264 Experts worldwide ranked by ideXlab platform
Volker C Radeloff - One of the best experts on this subject based on the ideXlab platform.
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mapping Agricultural Land abandonment from spatial and temporal segmentation of Landsat time series
Remote Sensing of Environment, 2018Co-Authors: He Yin, Alexander V. Prishchepov, Tobias Kuemmerle, Benjamin Bleyhl, Johanna Buchner, Volker C RadeloffAbstract:Abstract Agricultural Land abandonment is a common Land-use change, making the accurate mapping of both location and timing when Agricultural Land abandonment occurred important to understand its environmental and social outcomes. However, it is challenging to distinguish Agricultural abandonment from transitional classes such as fallow Land at high spatial resolutions due to the complexity of change process. To date, no robust approach exists to detect when Agricultural Land abandonment occurred based on 30-m Landsat images. Our goal here was to develop a new approach to detect the extent and the exact timing of Agricultural Land abandonment using spatial and temporal segments derived from Landsat time series. We tested our approach for one Landsat footprint in the Caucasus, covering parts of Russia and Georgia, where Agricultural Land abandonment is widespread. First, we generated Agricultural Land image objects from multi-date Landsat imagery using a multi-resolution segmentation approach. Second, we estimated the probability for each object that Agricultural Land was used each year based on Landsat temporal-spectral metrics and a random forest model. Third, we applied temporal segmentation of the resulting Agricultural Land probability time series to identify change classes and detect when abandonment occurred. We found that our approach was able to accurately separate Agricultural abandonment from active Agricultural Lands, fallow Land, and re-cultivation. Our spatial and temporal segmentation approach captured the changes at the object level well (overall mapping accuracy = 97 ± 1%), and performed substantially better than pixel-level change detection (overall accuracy = 82 ± 3%). We found strong spatial and temporal variations in Agricultural Land abandonment rates in our study area, likely a consequence of regional wars after the collapse of the Soviet Union. In summary, the combination of spatial and temporal segmentation approaches of time-series is a robust method to track Agricultural Land abandonment and may be relevant for other Land-use changes as well.
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determinants of Agricultural Land abandonment in post soviet european russia
Land Use Policy, 2013Co-Authors: Alexander V. Prishchepov, Daniel Muller, Maxim Dubinin, Matthias Baumann, Volker C RadeloffAbstract:a b s t r a c t The breakdown of socialism caused massive socio-economic and institutional changes that led to substan- tial Agricultural Land abandonment. The goal of our study was to identify the determinants of Agricultural Land abandonment in post-Soviet Russia during the first decade of transition from a state-controlled economy to a market-driven economy (1990-2000). We analyzed the determinants of Agricultural Land abandonment for approximately 150,550 km 2 of Land area in the provinces (oblasts) of Kaluga, Rjazan, Smolensk, Tula and Vladimir in European Russia. Based on the economic assumptions of profit max- imization, we integrated maps of abandoned Agricultural Land from five ∼185 km × 185 km Landsat TM/ETM+ footprints with socio-economic, environmental and geographic variables, and we estimated logistic regressions at the pixel level to identify the determinants of Agricultural Land abandonment. Our results showed that a higher likelihood of Agricultural Land abandonment was significantly associated with lower average grain yields in the late 1980s and with higher distances from the nearest settlements, municipality centers, and settlements with more than 500 citizens. Hierarchical partitioning showed that the average grain yields in the late 1980s had the greatest power to explain Agricultural Land abandon- ment in our models, followed by the locational attributes of the Agricultural Land. We hypothesize that the termination of 90% of state subsidies for agriculture from 1990 to 2000 was an important underlying cause for the decrease of cultivation in economically and environmentally marginal agriculture areas. Thus, whereas the spatial patterns corresponded to the Land rent theory of von Thunen, it was primarily the macro-scale driving forces that fostered Agricultural abandonment. Our study highlighted the value of spatially explicit statistical models for studying the determinants of Land-use and Land-cover change in large areas.
Alexander V. Prishchepov - One of the best experts on this subject based on the ideXlab platform.
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Agricultural Land Abandonment
Environmental Science, 2020Co-Authors: Alexander V. PrishchepovAbstract:Agricultural Land abandonment is increasingly a global Land-cover change phenomenon that has strong implications for the environment (e.g., biodiversity, carbon sequestration, novel ecosystems, wildfires) and societal well-being (livelihood, Agricultural Landscapes). Agricultural Land abandonment is often referred to as the cessation of farming and giving away Land for natural succession, such as grasses, shrubs, and trees on former Agricultural Lands, but may also result in Land degradation. Agricultural Land abandonment can be a more complex Land-change transition, including the cessation of Agricultural activity in favor of Land uses other than Agricultural ones, such as forestry, construction of dwellings, game reserves, and tourism. Studies have shown that Agricultural Land abandonment often is driven by rational decision-making and profit maximization, including weighing up opportunity costs and alternative livelihood strategies. However, the conditions of institutions, which are supposed to govern Land use, and the personal characteristics of those involved in Agricultural activities, are playing a vital role in the decision of abandonment. It should also be noted that the decision on abandonment or maintenance of farming can be quite complex and driven by non-economic factors, such as personal predisposition to farming, education, ethnicity, religion, age, and availability of successors. The progress of studying Land abandonment and existing research gaps are highlighted in the text.
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mapping Agricultural Land abandonment from spatial and temporal segmentation of Landsat time series
Remote Sensing of Environment, 2018Co-Authors: He Yin, Alexander V. Prishchepov, Tobias Kuemmerle, Benjamin Bleyhl, Johanna Buchner, Volker C RadeloffAbstract:Abstract Agricultural Land abandonment is a common Land-use change, making the accurate mapping of both location and timing when Agricultural Land abandonment occurred important to understand its environmental and social outcomes. However, it is challenging to distinguish Agricultural abandonment from transitional classes such as fallow Land at high spatial resolutions due to the complexity of change process. To date, no robust approach exists to detect when Agricultural Land abandonment occurred based on 30-m Landsat images. Our goal here was to develop a new approach to detect the extent and the exact timing of Agricultural Land abandonment using spatial and temporal segments derived from Landsat time series. We tested our approach for one Landsat footprint in the Caucasus, covering parts of Russia and Georgia, where Agricultural Land abandonment is widespread. First, we generated Agricultural Land image objects from multi-date Landsat imagery using a multi-resolution segmentation approach. Second, we estimated the probability for each object that Agricultural Land was used each year based on Landsat temporal-spectral metrics and a random forest model. Third, we applied temporal segmentation of the resulting Agricultural Land probability time series to identify change classes and detect when abandonment occurred. We found that our approach was able to accurately separate Agricultural abandonment from active Agricultural Lands, fallow Land, and re-cultivation. Our spatial and temporal segmentation approach captured the changes at the object level well (overall mapping accuracy = 97 ± 1%), and performed substantially better than pixel-level change detection (overall accuracy = 82 ± 3%). We found strong spatial and temporal variations in Agricultural Land abandonment rates in our study area, likely a consequence of regional wars after the collapse of the Soviet Union. In summary, the combination of spatial and temporal segmentation approaches of time-series is a robust method to track Agricultural Land abandonment and may be relevant for other Land-use changes as well.
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determinants of Agricultural Land abandonment in post soviet european russia
Land Use Policy, 2013Co-Authors: Alexander V. Prishchepov, Daniel Muller, Maxim Dubinin, Matthias Baumann, Volker C RadeloffAbstract:a b s t r a c t The breakdown of socialism caused massive socio-economic and institutional changes that led to substan- tial Agricultural Land abandonment. The goal of our study was to identify the determinants of Agricultural Land abandonment in post-Soviet Russia during the first decade of transition from a state-controlled economy to a market-driven economy (1990-2000). We analyzed the determinants of Agricultural Land abandonment for approximately 150,550 km 2 of Land area in the provinces (oblasts) of Kaluga, Rjazan, Smolensk, Tula and Vladimir in European Russia. Based on the economic assumptions of profit max- imization, we integrated maps of abandoned Agricultural Land from five ∼185 km × 185 km Landsat TM/ETM+ footprints with socio-economic, environmental and geographic variables, and we estimated logistic regressions at the pixel level to identify the determinants of Agricultural Land abandonment. Our results showed that a higher likelihood of Agricultural Land abandonment was significantly associated with lower average grain yields in the late 1980s and with higher distances from the nearest settlements, municipality centers, and settlements with more than 500 citizens. Hierarchical partitioning showed that the average grain yields in the late 1980s had the greatest power to explain Agricultural Land abandon- ment in our models, followed by the locational attributes of the Agricultural Land. We hypothesize that the termination of 90% of state subsidies for agriculture from 1990 to 2000 was an important underlying cause for the decrease of cultivation in economically and environmentally marginal agriculture areas. Thus, whereas the spatial patterns corresponded to the Land rent theory of von Thunen, it was primarily the macro-scale driving forces that fostered Agricultural abandonment. Our study highlighted the value of spatially explicit statistical models for studying the determinants of Land-use and Land-cover change in large areas.
Xianghui Wang - One of the best experts on this subject based on the ideXlab platform.
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A Sustainability Assessment Framework for Agricultural Land Remediation in China
Land Degradation & Development, 2017Co-Authors: Deyi Hou, Zhenyu Ding, Guanlin Guo, Xingrun Wang, David O'connor, Xianghui WangAbstract:China has an extensive Agricultural Land degradation issue due to pollution, with 19·4% of its Agricultural Land being contaminated. The government has released an ambitious Soil Pollution Prevention and Remediation Action Plan, aiming to remediate millions of hectares of contaminated Agricultural Land within the next several years. Amongst the many challenges facing the Action Plan, there is a need to assess the sustainability of these actions, especially in arid and semi-arid regions where rehabilitation of degraded Land is particularly challenging. There is a growing body of literature addressing the sustainability of remediation at industrial sites, but the remediation of Agricultural Land involves different sustainability concerns and, therefore, different indicators. To help address this issue, we propose a framework, which encompasses four impact categories, 11 subcategories, and 32 indicators, to assess the sustainability of Agricultural Land remediation. The proposed sustainability assessment framework was applied to five cases of Agricultural Land remediation, and the implications to policy makers and practitioners are discussed. An in-depth life cycle assessment was also conducted for the remediation of Agricultural Land in an arid region of northern China. This study suggests that Agricultural Land remediation projects in China need to pay more attention to social aspects of sustainability and provide further scientific evidence to prove Agricultural sustainability. It is imperative to conduct scientific research and develop policy instruments to progress life cycle sustainability in Agricultural Land remediation. Copyright © 2017 John Wiley & Sons, Ltd.
Karen C. Seto - One of the best experts on this subject based on the ideXlab platform.
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urbanization and Agricultural Land loss in india comparing satellite estimates with census data
Journal of Environmental Management, 2015Co-Authors: Bhartendu Pandey, Karen C. SetoAbstract:We examine the impacts of urbanization on Agricultural Land loss in India from 2001 to 2010. We combined a hierarchical classification approach with econometric time series analysis to reconstruct Land-cover change histories using time series MODIS 250 m VI images composited at 16-day intervals and night time lights (NTL) data. We compared estimates of Agricultural Land loss using satellite data with Agricultural census data. Our analysis highlights six key results. First, Agricultural Land loss is occurring around smaller cities more than around bigger cities. Second, from 2001 to 2010, each state lost less than 1% of its total geographical area due to agriculture to urban expansion. Third, the northeastern states experienced the least amount of Agricultural Land loss. Fourth, Agricultural Land loss is largely in states and districts which have a larger number of operational or approved SEZs. Fifth, urban conversion of Agricultural Land is concentrated in a few districts and states with high rates of economic growth. Sixth, Agricultural Land loss is predominantly in states with higher Agricultural Land suitability compared to other states. Although the total area of Agricultural Land lost to urban expansion has been relatively low, our results show that since 2006, the amount of Agricultural Land converted has been increasing steadily. Given that the preponderance of India's urban population growth has yet to occur, the results suggest an increase in the conversion of Agricultural Land going into the future.
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The impact of urban expansion on Agricultural Land use intensity in China
Land Use Policy, 2013Co-Authors: Li Jiang, Xiangzheng Deng, Karen C. SetoAbstract:Abstract China's urbanization has resulted in significant changes in both Agricultural Land and Agricultural Land use. However, there is limited understanding about the relationship between the two primary changes occurring to China's Agricultural Land – the urban expansion on Agricultural Land and Agricultural Land use intensity. The goal of this paper is to understand this relationship in China using panel econometric methods. Our results show that urban expansion is associated with a decline in Agricultural Land use intensity. The area of cultivated Land per capita, a measurement about Land scarcity, is negatively correlated with Agricultural Land use intensity. We also find that GDP in the industrial sector negatively affects Agricultural Land use intensity. GDP per capita and Agricultural investments both positively contribute to the intensification of Agricultural Land use. Our results, together with the links between urbanization, Agricultural Land, and Agricultural production imply that Agricultural Land expansion is highly likely with continued urban expansion and that pressures on the country's natural Land resources will remain high in the future.
Deyi Hou - One of the best experts on this subject based on the ideXlab platform.
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A Sustainability Assessment Framework for Agricultural Land Remediation in China
Land Degradation & Development, 2017Co-Authors: Deyi Hou, Zhenyu Ding, Guanlin Guo, Xingrun Wang, David O'connor, Xianghui WangAbstract:China has an extensive Agricultural Land degradation issue due to pollution, with 19·4% of its Agricultural Land being contaminated. The government has released an ambitious Soil Pollution Prevention and Remediation Action Plan, aiming to remediate millions of hectares of contaminated Agricultural Land within the next several years. Amongst the many challenges facing the Action Plan, there is a need to assess the sustainability of these actions, especially in arid and semi-arid regions where rehabilitation of degraded Land is particularly challenging. There is a growing body of literature addressing the sustainability of remediation at industrial sites, but the remediation of Agricultural Land involves different sustainability concerns and, therefore, different indicators. To help address this issue, we propose a framework, which encompasses four impact categories, 11 subcategories, and 32 indicators, to assess the sustainability of Agricultural Land remediation. The proposed sustainability assessment framework was applied to five cases of Agricultural Land remediation, and the implications to policy makers and practitioners are discussed. An in-depth life cycle assessment was also conducted for the remediation of Agricultural Land in an arid region of northern China. This study suggests that Agricultural Land remediation projects in China need to pay more attention to social aspects of sustainability and provide further scientific evidence to prove Agricultural sustainability. It is imperative to conduct scientific research and develop policy instruments to progress life cycle sustainability in Agricultural Land remediation. Copyright © 2017 John Wiley & Sons, Ltd.
