AFFOREST sDSS: a metamodel based spatial decision support system for afforestation of agricultural land

被引:31
作者
Gilliams, S
Van Orshoven, J
Muys, B
Kros, H
Heil, GW
Van Deursen, W
机构
[1] Katholieke Univ Leuven, Lab Forest Nat & Landscape Res, B-3000 Louvain, Belgium
[2] Alterra Green World Res, NL-6700 AA Wageningen, Netherlands
[3] Univ Utrecht, Dept Plant Ecol, NL-3508 TB Utrecht, Netherlands
[4] Carthago, NL-3062 VK Rotterdam, Netherlands
关键词
afforestation; decision support; GIS; goal programming; optimization;
D O I
10.1007/s11056-004-0761-z
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The concept and structure of the Spatial Decision Support System AFFOREST sDSS dealing with environmental performance (EP) of afforestation on agricultural land in northwestern Europe, is presented. EP is defined in terms of three environmental impact categories: (1) carbon sequestration (2) groundwater recharge and (3) nitrate leaching. The core of the sDSS is a raster based geographical database which allows for queries addressing 14 types of questions on where, how and how long to afforest in order to reach a desired EP or change in EP due to afforestation of the agricultural land. First the study area is differentiated according to the site conditions (based on soil texture, soil drainage, initial land use, yearly average precipitation, and yearly average N deposition. Then the EP for every site class is computed as a function of time using the VSAM metamodel. VSAM results from a conceptual simplification of an existing mechanistic point model, the forest process model SMART2. Input data for the metamodel are limited to the classified site conditions, the tree species used for afforestation, the afforestation strategy and the evaluation time. Besides limiting the data requirements, the metamodel approach allows for rapid and flexible computations on large numbers of pixel classes. Finally, depending on the type of question, the sDSS creates georeferenced outputs based on SQL-type spatial or attribute queries and more advanced multiple goal programming techniques.
引用
收藏
页码:33 / 53
页数:21
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