Titlebook: SIMPLE-G; A Gridded Economic A Iman Haqiqi,Thomas W. Hertel Book‘‘‘‘‘‘‘‘ 2025 The Editor(s) (if applicable) and The Author(s) 2025 Interdis

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书目名称SIMPLE-G影响因子(影响力)




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书目名称SIMPLE-G网络公开度




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书目名称SIMPLE-G被引频次




书目名称SIMPLE-G被引频次学科排名




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书目名称SIMPLE-G读者反馈学科排名

使尴尬

Introduction level of individual grid cells as well as in a global context. This will help to guide model parameterization, calibration, and validation. The eight diverse applications offered in this book provide a starting point for others to modify and extend this framework to address a wide range of sustainability challenges facing the world today.

有杂色

FLACK

Benchmark Data: Integrating Biophysical and Economic Information in a Consistent Geospatial Datasetimulations, and national censuses). These data are then processed and made consistent to produce gridded data that can be used within the model. This consistent, multiscale dataset allows researchers to better understand and predict the impact of certain changes on the human and environmental systems.

避开

Model Validation: Comparing Gridded and Regional Simulations to Observationsmodel using various methods. We use benchmark replication, backcasting, sensitivity analysis, and uncertainty quantification. These methods help ensure that the model can replicate a base reference condition accurately, model structural processes correctly, identify important parameters, and determine sources of uncertainty in the results.

镇压

Book‘‘‘‘‘‘‘‘ 2025physical sciences to enable multi-scale analysis of a range of sustainability challenges confronting the world’s land and water resources at both local and global scales. It focuses specifically on the interface between the environment and food systems, utilizing economic theory to structure the ove

传染

SIMPLE-G Model Specification: Mathematical Equations in a Multiscale Market Equilibrium Modells depends on the details about agricultural inputs, the assumptions about market connections and input mobility, the choice of functional forms, and the spatial heterogeneity required by the research question.

Amylase

Behavioral Parameters: Capturing Geospatial Heterogeneity in Economic Decisions and Responses agricultural production under various scenarios. While this chapter concentrates on the US dataset, the methods introduced here can be applied to other regions. Overall, this dataset empowers researchers to tackle fundamental environmental and societal challenges through advanced geospatial understanding and modeling.

Foolproof

NOVA