不确定条件下土地资源空间优化的弹性空间划定.

The management of uncertainties during resource utilization could perceive the underlying uncertainties in advance, thus conversely improving resources and environmental policy design to avoid risk, so nowadays much attention is paid to the research of uncertainties during resource and environmental management. Land use as a kind of important socio-economic activity also suffers from serious uncertainties, and especially the spatial characteristics make that more complicated. Up to now, many literatures have studied the uncertain quantities optimization of land resource, i.e., uncertain land use structure optimization, however that is not enough. Due to different preferences of land use on spatial units, land use planning demands spatial optimization based on the result of land use structure to guide human activities spatially, the uncertainties continue to propagate on space, and finally the flexible space of land resource spatial optimization is formed, which has important implications for formulating land use policy. This paper studies how to designate the flexible space for land resource spatial optimization under uncertain conditions. Firstly the uncertainties during land use optimization were analyzed systematically from views of population, economic, policy and nature variations, while excluding the uncertainties of spatial parameters, and at the same time the numerical expression of uncertainties was defined as uncertain indices to be dealt with. Secondly based on the comprehensive consideration of existing uncertain variables, the interval number was selected to represent the uncertain indices, which were brought into an interval programming model to obtain the flexible size of land use structure optimization, corresponding to the interval size of maximum objective value, in which only economic benefit was set as pursuit, and ecological and social demands were embodied into the constraints. Since the interval sizes of different land use areas were obtained, it was necessary to allocate them spatially to form the flexible space. Thus thirdly, a spatial optimization method was established, in which fitness and spatial distribution such as compactness and contiguity were considered during allocating land use types to spatial units, because it was considered that the final suitability of certain unit to some land use was affected by the conditions of its neighboring units. For each land use type, corresponding metric was selected to evaluate its fitness to spatial units, and we also regulated the influential rule of core cell to its neighbors on fitness. Combining the 2 sides, this method automatically identified which cell could be changed, until the area of changed cell reached the set threshold. Therefore in this way, the lower and upper limit area of each land use type were allocated on space, generating 2 optimization boundary scenarios, the overlapped part of that was defined as optimized boundary, while different part was supposed as flexible space of spatial optimization for that land use type. Lastly Yangzhou, an eastern China city, was taken as a case to illustrate the application of the flexible space designation approach, also providing reference for management policy making of Yangzhou. We could find that: the emergence of flexible space is due to uncertainties, and flexible space is designated to accommodate uncertainties; flexible space designation can perceive and deal with underlying uncertainties in advance, thus improving the effectiveness of land use policy. This research can provide theoretical basis and technical support for flexible space designation of current Chinese general land use planning. [ABSTRACT FROM AUTHOR]