2000-2020年南疆地区棉花种植空间格局及其变化特征分析

南疆地区是中国棉花的重要产区。综合全面了解南疆地区棉花种植空间格局及其变化特征对各级政府部门制定相关决策、保障国家粮棉供给、促进中国棉纺织工业加速发展具有重要意义。该研究以MODIS EVI数据为基础,应用TIMESAT软件平台集成的Double-Logistic滤波对棉花生长曲线进行重构,根据曲线特点提取阈值,进而提取南疆地区棉花种植信息,分析其种植空间格局及其变化特征。结果表明：1）南疆地区棉花主要分布在天山山脉南侧,形成以阿克苏地区为核心,喀什东北部及巴州北部为边缘的"核心-边缘"结构;2）近20 a南疆地区棉花种植面积增加103.17万hm2,年均棉花面积增长5.16万hm2,主要来源于耕地（76.85%）与草地（11.91%）;3）棉花分布在空间上呈"东北-西南"走向,棉花种植重心近20 a总移动距离91.5 km,年移动速率4.58 km/a,基本稳定保持在阿克苏市境内;4）南疆地区棉花种植面积冷点主要分布在克州以及和田地区,2005年后逐渐向西南侧集聚;热点分布格局年际变化显著,2005年前主要分布在阿克苏地区,2005年后逐渐向南疆地区东北侧延伸,主要集中在阿克苏地区以及巴州地区北部。研究成果可为制定区域国土管理制度和涉棉企业科学决策提供参考,对调整和优化棉花结构布局具有积极作用。

Analysis of the spatial distribution and variation characteristics of cotton planting in southern Xinjiang from 2000 to 2020

Abstract: Southern Xinjiang is one of the most important cotton-producing areas in China. It is necessary to fully understand the spatial distribution of cotton and variation characteristics for national grain and cotton supply, particularly on the development of the cotton textile industry in China. Therefore, this study followed the research idea of "reconstructing growth curve - extracting planting information - analyzing changing characteristics". Firstly, TIMESAT software was used to generate the enhanced vegetation index (EVI) growth curve of cotton in Southern Xinjiang. Subsequently, a Double-Logistic filter was selected to rebuild the growth curve. Secondly, the specific characteristics of the cotton growth curve were analyzed further to obtain the cotton growth threshold. Thirdly, a Band Math tool in ENVI5.3 was selected to extract the cotton planting areas. The spatial distribution accuracy of extracted datasets was then verified using Google Earth high-resolution image. Finally, a systematic analysis was made on the temporal and spatial variation characteristics of cotton planting from multiple perspectives. The results showed that: 1) The spatial distribution pattern of cotton was basically consistent with the soil and water conditions, where mainly distributed in the south of Tianshan Mountains and clustered in the northeast of southern Xinjiang, indicating a "core-edge" structure with Aksu region as the core, while Kashgar and Northern Bazhou as the margin. 2) There were significant differences between type I cultivated land and other types in different years, indicating the pretty obvious spatial differentiation. The active regions of cotton planting variation were mainly distributed in Aksu, Kashgar, and northern Bazhou, indicating the main cotton-growing regions in southern Xinjiang. There was the most significant correlation in the flow conversion between type I and type II cultivated land, grassland, and artificial land surface, indicating that the flow increased sharply. 3) The spatial distribution of cotton showed the "northeast to southwest" trend. The cotton planting center basically kept stable in Aksu City after a major migration in recent 20 years, with a total migration distance of 91.5 km and an annual migration rate of 4.58 km/a. 4) In detecting "hot spots" of cotton planting areas, the cold spots were mainly distributed in Kezhou and Hetian in southern Xinjiang, indicating a gradual concentration to the southwest after 2005. Correspondingly, the distribution pattern of hot spots changed significantly from year to year. Furthermore, the hot spots were mainly distributed in Aksu prefecture before 2005. The hot spots gradually extended to the northeast of southern Xinjiang after 2005, where mainly concentrated in Aksu prefecture and the north of Bazhou. Consequently, the temporal and spatial variation characteristics of cotton planting using EVI data can widely be expected for large-scale, long-term information monitoring. The yield estimation model can also be further constructed using the cotton growth curve, as well as the relationship with cotton actual output. Finally, quantitative remote sensing can be realized on cotton yield prediction. The findings can provide sound support to optimize the cotton structure distribution for the decision-making and formulation of regional land management.