In this study, the spatiotemporal characteristics of salinized cultivated land in Xinjiang from 2005 to 2014 were analyzed by matrix transfer method and land use dynamics. The matrix transfer method can calculate both the changes in the salinized cultivated land and transfer ratio of different degrees of salinized cultivated land from the previous period to the latter period. Our results indicate that:1)In 2005, the area of salinized cultivated land accounted for 32.07% of the total area of cultivated land. In 2014, the area of salinized cultivated land accounted for 37.72% of the total area of cultivated land. During the study period, the total area of salinized cultivated land in Xinjiang was increasing, and most of them concentrated in the new irrigation area. With the improvement of old irrigation area, the degrees of salinization damage were obviously weakened, and the salinized cultivated land showed a stable desalination trend. 2)The salinization degree was mainly mild in Xinjiang. The proportion of moderate and severe salinized cultivated land in southern Xinjiang was higher than that in northern Xinjiang. The salinization damage of cultivated land was serious in southern Xinjiang. There were some obvious differences in the structures and quantity of salinized cultivated land in various regions. The proportions of salinized cultivated land in Bazhou and Kashgar were higher than 50%, while the proportions of cultivated land in Urumqi and Yili were less than 10%. 3)There were also significant differences in the active degree of salinized cultivated land in various regions:The comprehensive dynamic degree of Karamay is the lowest, and the CLUD value was -0.39, indicating that the area of salinized cultivated land in Karamay has decreased. The CLUD values in other regions were positive, the hot spots with high comprehensive dynamics and rapid changes were mainly concentrated in southern Xinjiang, including Kezhou, Kashgar and Bazhou. Therefore, each region must formulate a plan for improving and utilizing soil salinization according to local conditions, and it must be consistent with the overall plan.
[1] 田长彦,周宏飞,刘国庆. 21世纪新疆土壤盐渍化调控与农业持续发展研究建议[J].干旱区地理, 2000, 23(2):177-181.
[2] Wang H W,Fan Y H,Tiyip T.The research of soil salinization human impact based on remote sensing classification in oasis irrigation area[J]. Procedia Environmental Sciences, 2011, 10:2399-2405.
[3] 新疆荒地资源综合考察队. 新疆重点地区荒地资源合理利用[M]. 乌鲁木齐:新疆人民出版社, 1985.
[4] 刘纪远,匡文慧,张增祥,等. 20世纪80年代末以来中国土地利用变化的基本特征与空间格局[J].地理学报, 2014, 69(1):3-14.
[5] 刘馨,宋小宁,冷佩,等. 基于MODIS数据的黄河源区土壤干湿状况时空格局变化[J]. 中国科学院大学学报, 2019, 36(2):178-187.
[6] 孙海燕,叶含春,许丽,等.沙漠绿洲区平原水库下缘盐荒地水盐动态规律[J].干旱区研究, 2017, 34(5):967-971.
[7] Zhang Z X, Wang X, Zhao X L, et al. A 2010 update of National Land Use/Cover Database of China at 1:100000. scale using medium spatial resolution satellite images[J].Remote Sensing of Environment, 2014, 149:142-154.
[8] 陈曦.中国干旱区土地利用与土地覆被变化[M]. 北京:科学出版社, 2008:409-423.
[9] 王芳芳,吴世新,乔木,等. 基于3S技术的新疆耕地盐渍化状况调查与分析[J]. 干旱区研究, 2009, 26(3):366-371.
[10] 张寿雨,吴世新,贺可. 基于开垦年龄的新疆盐渍化耕地时空特征分析[J]. 干旱区研究, 2017, 34(5):972-979.
[11] 樊自立,马英杰,马映军. 中国西部地区耕地土壤盐渍化评估及发展趋势预测[J]. 干旱区地理, 2002, 25(2):97-102.
[12] 张英男,龙花楼,戈大专,等. 黄淮海平原耕地功能演变的时空特征及其驱动机制[J]. 地理学报, 2018, 73(3):518-534.
[13] 赵振勇,乔木,吴世新,等. 新疆耕地资源安全问题及保护策略[J]. 干旱区地理, 2010, 33(6):1019-1025.
[14] Ghassemi F, Jakeman A J, Nix H A.Salinisation of Land and Water Resources:Human Causes,Extent,Management and Case Studies[M]. UK:CAB International, 1995:26-29.
[15] Ivushkin K, Bartholomeus H, Bregt A K, et al. Soil salinity assessment through satellite thermography for different irrigated and rainfed crops[J]. International Journal of Applied Earth Observation and Geoinformation, 2018, 68:230-237.
[16] 杨小林,李义玲. 基于客观赋权法的长江流域环境风险时空动态综合评价[J]. 中国科学院大学学报,2015,32(3):349-355.
[17] 管孝艳,王少丽,高占义,等.盐渍化灌区土壤盐分的时空变异特征及其与地下水埋深的关系[J]. 生态学报, 2012, 32(4):198-206.
[18] Sidike A,Zhao S H,Wen Y M.Estimating soil salinity in Pingluo County of China using QuickBird data and soil reflectance spectra[J].International Journal of Applied Earth Observation and Geoinformation, 2014, 26:156-175.
[19] 李佳秀,陈亚宁,刘志辉. 新疆不同气候区的气温和降水变化及其对地表水资源的影响[J]. 中国科学院大学学报,2018, 35(3):370-381.
[20] Metternicht G, Zinck A. Remote Sensing of Soil Salinization:Impact on Land Management[M]. Florida:CRC Press Inc, 2008:14-20.
[21] 丁建丽,姚远,王飞.干旱区土壤盐渍化特征空间建模[J]. 生态学报, 2014, 34(16):4620-4631.
[22] 傅茜,杨德刚,张新焕,等. 伊犁河谷县域相对资源承载力时空分异[J]. 中国科学院大学学报, 2016, 33(2):170-177.
[23] 吕真真,刘广明,杨劲松.新疆玛纳斯河流域土壤盐分特征研究[J]. 土壤学报, 2013, 50(2):289-295.
[24] 任加国,郑西来,许模,等. 新疆叶尔羌河流域土壤盐渍化特征研究[J]. 土壤, 2005, 37(6):635-639.
[25] 乔木,周生斌,卢磊,等.新疆渭干河流域土壤盐渍化时空变化及成因分析[J]. 地理科学进展, 2012, 31(7):904-910.
[26] 张寿雨,吴世新,贺可,等.克拉玛依农业开发区不同开垦年限土壤盐分变化[J].土壤, 2018, 50(3):574-582.
[27] 李一琼,白俊武. 近20年苏州土地利用动态变化时空特征分析[J]. 测绘科学, 2018, 43(6):58-64.
[28] Aburas M M, Ho Y M, Ramli M F, et al. The simulation and prediction of spatio-temporal urban growth trends using cellular automata models:a review[J]. International Journal of Applied Earth Observation and Geoinformation, 2016, 52:380-389.
[29] 贺勇,胡克林,李保国,等. 区域土壤质地层次三维空间分布的地统计模拟方法比较[J]. 土壤,2010,42(3):429-437.
[30] 朱会义,李秀彬. 关于区域土地利用变化指数模型方法的讨论[J]. 地理学报,2003, 58(5):643-650.