基于地理信息数据与人工智能算法的土地资源优化  

Optimization of land resources based on geographical information data and artificial intelligence algorithms

作　　者：刘细林 任上峰 LIU Xilin;REN Shangfeng(Leqing Surveying and Mapping Institute,Leqing,Zhejiang 325600,China;Wenzhou Ouhai Surveying and Mapping Engineering Institute,Wenzhou,Zhejiang 325005,China)

机构地区：[1]乐清市测绘院,浙江乐清325600 [2]温州市瓯海测绘工程院,浙江温州325005

出　　处：《北京测绘》2025年第4期516-521,共6页Beijing Surveying and Mapping

基　　金：浙江省自然资源科技项目(2023-33)。

摘　　要：土地资源规划是实现可持续发展的重要步骤,通过土地利用结构优化可以有效提高资源利用效率。针对如何结合地理信息数据对土地资源规划进行优化的问题,本文提出通过地理信息数据与人工智能算法进行土地资源优化的方法。研究选取某市复杂多样的地形资源作为研究对象,通过对高程数据以及平面数据的综合分析,建立关于土地资源规划优化的目标,并设置对应的约束条件。通过粒子群算法以及差分进化算法对土地资源的结构数量以及空间格局进行优化。经过实际的数据分析验证,通过地理信息数据与人工智能算法进行土地资源优化方式预测的总体精度平均为91.6%,能够为土地资源优化提供更好的技术支持。Land resource planning is a crucial step in achieving sustainable development.By optimizing land use structures,resource utilization efficiency can be significantly improved.This paper proposed a method for optimizing land resources through the integration of geographical information data and artificial intelligence algorithms.The study selected the complex and diverse terrain resources of a certain city as the research object.Through the comprehensive analysis of elevation and planar data,optimization objectives for land resource planning were established,along with corresponding constraints.Particle swarm optimization and differential evolution algorithms were applied to optimize the quantity and spatial patterns of land resources.Data analysis verification shows that the overall accuracy of the predictions made using geographical information data and artificial intelligence algorithms for land resource optimization is an average of 91.6%,providing better technical support for land resource optimization.

关 键 词：地理信息数据 粒子群算法 差分进化算法 土地资源优化 空间格局 

分 类 号：P208[天文地球—地图制图学与地理信息工程]