摘要
【目的】研究新疆石河子垦区绿洲人工化进程中土地利用时空演变规律以及驱动机制。【方法】以1990年、2000年、2010年和2020年的TM/ETM影像为基础数据,运用RS和GIS技术分析近30年垦区土地利用时空变化特征,利用CA-Markov模型和土地利用重心迁移模型,模拟预测2030年和2040年研究区的土地利用/覆被格局。【结果】(1)1990-2020年石河子垦区土地利用/覆被格局以未利用地为主,占总面积的41.18%以上,呈小幅波动变化状态;(2)林地的重心迁移最显著,由北向南迁移了0.6°,耕地动态度变化最活跃,30年间平均每年增加2.72%,林地次之;(3)Kappa系数的一致性检验结果均高于80.36%。【结论】CA-Markov模型可信度较高,适合石河子垦区土地利用/覆被变化及空间格局预测。
【Objective】To explore the spatio-temporal evolution law of land use and driving mechanism in the process of artificialization oasis in Shihezi Reclamation Area,【Methods】Based on the data of TM images in 1990,2000,2010 and 2020,the distribution land use pattern in THE past 30 years was analyzed by RS and GIS,the CA-Markov model and the land use gravity center model were used to simulate and predict the land use/cover pattern in 2030 and 2040.【Results】(1)From 1990 to 2020,the land use/cover pattern of Shihezi Reclamation Area was dominated by unused land,the main change trends were the expansion of farmland and building,and the decrease of forest and grassland;(2)The center of gravity of forest has migrated most significantly,moving from north to south by 0.6°,farmland had the most dynamic changes,with an average annual increase of 2.72%during the past 30 years,followed by forest land;(3)The Kappa coefficient were both higher than 80.36%.【Conclusion】Indicating that the model had high reliability and was suitable for the prediction of land use/cover change and spatial pattern in Shihezi Reclamation Area.The simulation showed the farmland and building would continue to increase.
作者
李长晓
范文波
张建新
乔长录
杨海梅
王雅琴
LI Changxiao;FAN Wenbo;ZHANG Jianxin;QIAO Changlu;YANG Haimei;WANG Yaqin(College of Water&Architectural Engineering,Shihezi University,Shihezi Xinjiang 832000,China;Key Laboratory of Modern Water-Saving Irrigation of Xinjiang Production&Construction Corps,Shihezi University,Shihezi Xinjiang 832000,China;Xinjiang Academy of Agr-Reclamation Sciences,Shihezi Xinjiang 832000,China)
出处
《新疆农业科学》
CAS
CSCD
北大核心
2022年第10期2585-2594,共10页
Xinjiang Agricultural Sciences
基金
国家自然科学基金(51569028)
国家自然科学基金(51769030)
国家自然科学基金(41761064)。