Land utilization planning method considering multiple uncertainties

Abstract

The invention aims to provide a land utilization planning method considering multiple uncertainties, which comprises the following steps of: constructing a multi-target land utilization space optimization model under the multiple uncertainties, and solving the multi-target land utilization structure optimization model by utilizing an improved multi-target ant colony algorithm, obtaining land quantity structure prediction result elastic intervals of the research area in different planning periods and different land types under multiple uncertainty conditions, and then obtaining the distributionsuitability probability of each land type and setting an adaptive inertia coefficient, a neighborhood influence factor and conversion cost in combination with driving factor data and by utilizing a BP neural network; and combining the land quantity structure prediction result elastic interval of the research area with the distribution suitability probability, the adaptive inertia coefficient, theneighborhood influence factor and the conversion cost of each land class, and finally obtaining a future land utilization spatial pattern optimization result under multiple uncertain conditions. Anda new thought is provided for land utilization planning.

Description

technical field [0001] The invention relates to the field of land use planning, in particular to a land use planning method considering multiple uncertainties. Background technique [0002] Land resource is a very precious natural resource on the earth, and it is also an important resource to maintain human survival and development. With the development of society and economy, there is now an imbalance between the supply and demand of land resources in many areas. Unreasonable development and utilization will not only destroy the local environment. Ecological environment, but also will restrict economic development. Reasonable land use planning can not only promote the sustainable development of land resources, but also promote the coordinated and sustainable development of regional society, economy, and ecology, and then maximize the comprehensive benefits of regional land use economy, environment, ecology, and society. [0003] The optimal allocation of land use is an imp...

AI Technical Summary

Problems solved by technology

Regarding the optimal allocation of land use, the predecessors used some linear programming and nonlinear programming models to solve such problems, but the optimal allocation of land use is actually a complex nonlinear multi-objective optimal allocation process. At the same time, land use planning There are many uncertain factors, and most of the traditional land use structure optimization configuration models do not consider this aspect, so the traditional mathematical programming model has certain limitations in solving such problems

Some scholars use land use simulation models and quantitative structure prediction models to generate suitability maps for local types by setting conversion rules on the premise of combining analysis of social, economic and natural factors and other driving factors. Superposition is used to optimize the land use layout. This optimization method does not consider too many objectives and constraints, and is relatively subjective.

[0004] Due to its efficient optimization ability, artificial intelligence algorithms provide new ideas for the optimal allocation of land use space. Common ones include ant colony algorithm, particle swarm algorithm, simulated annealing algorithm, genetic algorithm, etc. Although these intelligent optimization algorithms are easier to implement , but there are still problems such as insufficient quality, easy to fall into local optimum, and inability to obtain a relatively continuous Pareto front, so seeking a new method for land use space optimization is of great significance to land use planning

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