Simulation And Analysis Of Land-use Evolution In Ludian District Based On CLUE-S Model

With the rapid development of economy in recent years, a large amount of people flock to the city. As the acceleration of the urbanization process, the city has been expanding itself sharply and the land turns out to be laid-wasted. Eco-cost rises heavily because of the unreasonable structure of Land-Use and Cover Change(LUCC) brought heavy cost of ecology, so research of LUCC, which becomes important things to study. The study of the LUCC focuses on all the driving factors that affected the Land-use and Coverage Change, which is the basis of building the empirical model of the dynamic change of the land-use and deducing the variation trend of the land-use in the future.This paper took three key towns in Ludian Country as study area and adopted land-use datas in 1999, 2004, 2009 as basis to:(1) Predict annual demand area of six land-use types between 2004 and 2009 by Markov model;(2) Extract distance factors of road, river, resident etc. In addition, the factor of slope could be extracted on the basis of DEM and the population density factor could be obtained on the basis of a variety of statistics information. Based on these factors and land use map in 2009, we could calculate the correlation degree of each factor and various land use types by Logistic regression analysis. The regression results could be fitted by ROC curves to evaluate. Predication of land-use change in 2014 could be done in CLUE-S model with the datas above, and the simulation results would be compared with achievements interpreted by Worldview image in 2014. Finally, The pattern of Land-use in 2024 was predicted, and the result of prediction was analyzed to make recommendations to key town of Ludian about sustainable development.We can draw the following conclusions with analyzing the results:(1) Accounting for 97% of the total area, farmland, woodland and residential area were three major land-use types in study area. Residential areas, woodland, unused land, transportation land area increased between 1999 and 2014, and arable land decreased. Water system area had a significant reduction between 1999 and 2004 and a stable increase between 2004 and 2014.(2) Based on eight natural, socio-economic factors selected in this paper, the regression coefficients(β) of each factor could be obtained by Logistic regression analysis. The regression results could be fitted to evaluate by ROC curve. The evaluation results indicated that fitting results of forest, land transportation, water system, residential land were good, and ROC values were 0.857,0.955,0.943,0.955 respectively.(3) As the basis of land-use map in 2009, annual land-use demand from 2004 to 2009, driving factors, region restriction file, conversion setting, β coefficients, land-use pattern of study area in 2014 could be simulated by CLUE-S model. The simulation accuracy could be validated by Kappa index. Quantity Kappa Index, Location Kappa Index, Standard Kappa Index, Random Kappa Index is 93.92%,85.12%,78.95%,87.99% respectively, which indicated that the simulation result was accurate.(4) The pattern of Land-use in 2024 was predicted, and the result of prediction was analyzed to make recommendations.Ludian County suffered a major earthquake in 2014, and the pattern of LUCC had been severely damaged. Mastering LUCC states of disaster area can provide decisive basis for reconstruction work.