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基于CLUE-S模型的煤礦城市土地利用變化模擬
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國(guó)家自然科學(xué)基金項(xiàng)目(41501226、31700369)、安徽省高校自然科學(xué)研究項(xiàng)目(KJ2015A034)和安徽理工大學(xué)人才引進(jìn)項(xiàng)目(ZY020)


Simulation of Land Use Change in Typical Coal Mining City Based on CLUE-S Model
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    以淮南市為研究區(qū),選擇1985、1995、2005、2016年土地利用數(shù)據(jù),在分析土地利用動(dòng)態(tài)變化特征的基礎(chǔ)上,利用CLUE-S模型模擬預(yù)測(cè)了未來(lái)土地利用格局。結(jié)果表明:1985—2016年,研究區(qū)耕地面積減少11.62%;建設(shè)用地和水體面積百分比分別增加7.98個(gè)百分點(diǎn)和4.29個(gè)百分點(diǎn)。2005—2016年是各地類變化最強(qiáng)烈的階段,其綜合土地利用動(dòng)態(tài)度最大,為13.46%。建設(shè)用地變化速率最快,其土地利用動(dòng)態(tài)度為5.19%。土地轉(zhuǎn)移主要發(fā)生在耕地、水體和建設(shè)用地之間,以耕地向建設(shè)用地和水體的轉(zhuǎn)換為主。耕地轉(zhuǎn)為建設(shè)用地的面積達(dá)207.61km2,新增水體集中分布在潘謝礦區(qū)。加入空間自相關(guān)性和土壤質(zhì)量因子后,耕地和建設(shè)用地的Logistics回歸效果顯著改善,ROC分別增加0.201和0.133。年均降水量是影響耕地變化的主要驅(qū)動(dòng)因子,與耕地分布概率呈負(fù)相關(guān);而建設(shè)用地變化主要驅(qū)動(dòng)因子為GDP。土地利用模擬的Kappa系數(shù)為0.74,CLUE-S模型在研究區(qū)域具有較好的模擬能力。運(yùn)用CLUE-S模型預(yù)測(cè)了研究區(qū)2028、2034、2040年土地利用空間分布,未來(lái)土地利用空間分布格局總體上沒(méi)有明顯變化,各用地類型面積變化相對(duì)穩(wěn)定。

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    Huainan in Anhui Province was selected as study area. The dynamic change characteristics of land use was explored by using land use data of 1985, 1995, 2005 and 2016. And then the future land use patterns were simulated and predicted based on CLUE-S model. The results showed that from 1985 to 2016, the cultivated land area in the study area was decreased by 11.62%;the area percentage of construction land and water body was increased by 7.98 percentage points and 4.29 percentage points, respectively. From 2005 to 2016, the comprehensive dynamic degree was the largest, and it was the stage where the change of each land use type was the strongest, which was 13.46%. The change rate of construction land was the fastest, with land use dynamic index of 5.19%. Land use types mainly changed between cultivated land, water area and construction land. Cultivated land converted to construction land and water area were the dominant land use change types. The area of cultivated land converted to construction land reached 207.61km2, and the newly added water body was mainly distributed in the Panxie mining area. After adding soil quality factor and spatial autocorrelation, the Logistics regression effect of cultivated land and construction land was significantly improved, and the ROC was increased by 0.201 and 0.133, respectively. The main driving factor of cultivated land change was mean annual precipitation, which was negatively correlated with the cultivated land distribution probability;and the main driving force of construction land was GDP. Kappa index of land use simulation was 0.74, indicating that CLUE-S model had good capabilities of land use simulation in study area. On this basis, the CLUE-S model was used to predict the spatial distribution of land use in study area in 2028, 2034 and 2040. There was no significant change in the spatial distribution of land use in the future, and the area change of each land use was relatively stable.

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趙明松,徐少杰,鄧良,劉斌寅,王世航,吳運(yùn)金.基于CLUE-S模型的煤礦城市土地利用變化模擬[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2022,53(5):158-168. ZHAO Mingsong, XU Shaojie, DENG Liang, LIU Binyin, WANG Shihang, WU Yunjin. Simulation of Land Use Change in Typical Coal Mining City Based on CLUE-S Model[J]. Transactions of the Chinese Society for Agricultural Machinery,2022,53(5):158-168.

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  • 收稿日期:2021-07-07
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  • 在線發(fā)布日期: 2022-05-10
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