Modeling land use decisions with Bayesian networks: Spatially explicit analysis of driving forces on land use change

2014 ◽  
Vol 52 ◽  
pp. 222-233 ◽  
Author(s):  
Enrico Celio ◽  
Thomas Koellner ◽  
Adrienne Grêt-Regamey
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Bayesian Networks ◽  
Driving Forces ◽  
Spatially Explicit ◽  
Land Use Decisions ◽  
Explicit Analysis

scholarly journals Assessment on the rates and potentials of soil organic carbon sequestration in agricultural lands in Japan using a process-based model and spatially explicit land-use change inventories – Part 1: Historical trend and validation based on nation-wide soil monitoring

2014 ◽  
Vol 11 (16) ◽  
pp. 4429-4442 ◽  
Author(s):  
Y. Yagasaki ◽  
Y. Shirato
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Paddy Fields ◽  
Spatially Explicit ◽  
Crop Fields ◽  
Upland Crop ◽  
Soc Stock ◽  
Stock Change ◽  
Soc Stocks

Abstract. In order to estimate a country-scale soil organic carbon (SOC) stock change in agricultural lands in Japan, while taking into account the effect of land-use changes, climate, different agricultural activities and the nature of soils, a spatially explicit model simulation system was developed using Rothamsted Carbon Model (RothC) with an integration of spatial and temporal inventories. Simulation was run from 1970 to 2008 with historical inventories. Simulated SOC stock was compared with observations in a nation-wide stationary monitoring program conducted during 1979–1998. Historical land-use change, characterized by a large decline in the area of paddy fields as well as a small but continuous decline in the area of orchards, occurred along with a relatively large increase in upland crop fields, unmanaged grasslands, and settlements (i.e. conversion of agricultural fields due to urbanization or abandoning). Results of the simulation on SOC stock change under varying land-use change indicated that land-use conversion from agricultural fields to settlements or other lands, as well as that from paddy fields to croplands have likely been an increasing source of CO2 emission, due to the reduction of organic carbon input to soils and the enhancement of SOC decomposition through transition of soil environment from anaerobic to aerobic conditions. The area-weighted mean concentrations of the simulated SOC stocks calculated for major soil groups under paddy fields and upland crop fields were comparable to those observed in the monitoring. Whereas in orchards, the simulated SOC stocks were underestimated. As the results of simulation indicated that SOC stock change under managed grasslands and settlements has been likely a major sink and source of CO2 emission at country-scale, respectively, validation of SOC stock change under these land-use types, which could not have been accomplished due to limited availability or a lack of measurement, remains a forthcoming challenge.

scholarly journals Deriving spatially explicit water uses from land use change modelling results in four river basins across Europe

2018 ◽  
Vol 628-629 ◽  
pp. 1079-1097 ◽  
Author(s):  
Verena Huber García ◽  
Swen Meyer ◽  
Kasper Kok ◽  
Peter Verweij ◽  
Ralf Ludwig
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
River Basins ◽  
Spatially Explicit ◽  
Explicit Water ◽  
Water Uses

scholarly journals Land Use Change from Biofuels Derived from Forest Residue: A Case of Washington State

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Daniel Brent ◽  
Sergey Rabotyagov
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
The United States ◽  
Washington State ◽  
Spatially Explicit ◽  
Biofuel Policy ◽  
Indirect Land Use Change ◽  
Forest Residue ◽  
Net Returns ◽  
Processing Plants

Biofuel policy in the United States is transitioning away from corn towards second-generation biofuels in part because of the debate over environmental damages from indirect land use change. We combine a spatially explicit parcel level model for land use change in Washington State with simulations for biofuel policy aimed at utilizing forest residue as feedstock. Using a spatially explicit model provides greater precision in measuring net returns to forestland and development and indicates which areas will be most impacted by biofuel policy. The effect of policy is simulated via scenarios of increasing net returns to forestry and of siting feedstock-processing plants. Our results suggest that forestland will increase from such a policy, leading to a net reduction in atmospheric carbon from indirect land use change. This is in contrast to the experience of corn ethanol where the change in carbon emissions is potentially positive and large in magnitude.

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