内蒙古自治区是我国北部重要的生态屏障，在北方乃至全国的生态安全中有着极其重要的战略地位，其生态安全建设对于区域及全国的防风固沙、水资源保护和调控、生物多样性保护等方面都具有重要作用。20世纪90年代末开始，我国启动一系列生态工程，如退耕还林（草）工程、“三北”防护林体系工程建设、京津风沙源治理等，对于内蒙古自治区的生态质量进行修复治理。党的十八大以来，我国把生态文明建设摆在全局工作的突出位置，同时也对内蒙古自治区的高质量发展也提出了新的要求。综上，对内蒙古自治区开展生态质量进行密集的长时序监测评估，能更直观、准确地反映内蒙古生态质量时空变化趋势，同时，结合不同政策时段分析生态质量的可持续性，探究影响其空间分异的驱动因素，掌握内蒙古自治区生态质量现状，对于内蒙古自治区的生态文明建设及经济社会的可持续发展具有重要意义。

为准确评估内蒙古自治区生态质量的现状及其演变趋势，本文基于Google Earth Engine（GEE）平台提供的2001-2021年MODIS遥感影像数据、植被指数数据以及地表温度数据，利用主成分分析构建遥感生态指数（Remote Sensing Based Ecological Index, RSEI）来探究内蒙古自治区的长时序生态质量，结合等间距分级及莫兰指数探究其空间分布和变化特征，利用Theil-Sen趋势分析、Mann-Kendall检验剖析其时间变化趋势，并利用Hurst指数，结合MDGs（Millennium Development Goals）和SDGs（Sustainable Development Goals）的不同时段分析生态质量的变化特征，识别内蒙古自治区生态质量的持续改善、持续退化区，探究生态质量的可持续发展水平，最后基于地理探测器分析不同区域导致RSEI空间分异的驱动因素。本文主要的研究内容和结论如下：

（1）通过对2001-2021年内蒙古自治区的生态质量进行评价，结果表明：第一主成分表征生态质量，贡献率均达78%以上；且多年来，各指标与遥感生态指数的平均相关性较高，即结合绿度、湿度、温度、干度四个生态质量因子计算出的遥感生态指数，很好地综合了与生态质量息息相关的要素，可以直观、客观地代表区域内的生态质量。

（2）空间上，内蒙古自治区生态质量在空间分布上有明显的差异，形成“东高西低，中部交错”的分布格局。遥感生态指数在西南荒漠戈壁区较低，且多年来变化较小；中部的城市群、沙草交错带高低值交错分布，多年来变化较大；东北部大兴安岭地区山地的遥感生态指数较高，生态质量状况较稳定。结合莫兰指数来看，全局莫兰指数的5年均值为0.961，表明内蒙古自治区生态质量有明显的空间自相关性，呈现明显的集聚特征，且多年来西部地区多为低-低集聚区，东北地区多为高-高集聚区。时间上，内蒙古自治区大部分地区的生态质量都有改善趋势，生态质量改善的地区占全区面积的65.09%，有退化趋势的面积占全区面积的24.85%。有改善趋势的地区主要集中在自治区东北部以及近年来实施生态工程的地区，而有退化趋势的地区主要为生态工程难以触及的荒漠戈壁区，可见内蒙古自治区生态治理有明显成效，未来趋势向好。

（3）在千年发展目标（MDGs）时段（2001-2015年），内蒙古自治区生态质量整体呈退化趋势，持续退化区面积占比较大，而在东部的兴安盟、通辽市等地区，有较多的生态质量持续改善区分布；而在可持续发展目标（SDGs）时段即2015-2021年，内蒙古自治区生态质量改善幅度最大、持续性最强，生态质量有持续改善的地区广泛分布于自治区全区，SDGs背景下的生态工程及生态修复保护政策对内蒙古自治区的生态质量有着较大的正面影响，促使自治区的生态质量持续向好，大部分地区扭转了MDGs时段生态质量持续退化的趋势。

（4）持续变化典型区中，生态质量空间分异受到多种因子共同驱动。其中，气候要素构成了区域内的生态环境本底因素，在两个典型区的多种驱动因素中的解释力都为最高，主导了典型区内的生态质量空间分异。而人类活动要素中，土地利用类型的解释力在两种典型区中都为最高，分别为0.327、0.211，同样对生态质量分布格局有显著影响。持续改善典型区中，生态工程要素也是区域内的生态质量分异的主要原因之一，解释力位居第二，解释力为0.382。而在持续退化典型区中由于自然本底条件恶劣，生态工程的作用主要为遏制生态环境进一步恶化，所以解释力比持续改善典型区小。交互作用探测中，降水量及土地利用类型的是持续改善典型区中的解释力最高的组合，说明气候和人类活动共同主导生态质量的空间分异；而在持续退化典型区中，年均气温和年均风速的组合解释力最高，可见气候要素是影响当地生态质量空间分异最主要的因素。

The Inner Mongolia Autonomous Region is an important ecological barrier in northern my country and plays an extremely important strategic position in the ecological security of the north and the country. Its ecological security construction is important for regional and national windbreaks and sand fixation, water resources protection and regulation, and biodiversity protection. plays an important role. Since the late 1990s, my country has launched a series of ecological projects, such as the conversion of farmland to forest (grassland) project, the construction of the "Three North" protective forest system project, and the control of sandstorm sources in Beijing and Tianjin, etc., to restore and manage the ecological quality of the Inner Mongolia Autonomous Region. Since the 18th National Congress of the Communist Party of China, my country has placed the construction of ecological civilization in a prominent position in its overall work, and has also put forward new requirements for the high-quality development of the Inner Mongolia Autonomous Region. In summary, long-term intensive monitoring, and evaluation of ecological quality in Inner Mongolia Autonomous Region can more intuitively and accurately reflect the spatiotemporal change trend of ecological quality in Inner Mongolia. At the same time, it can analyze the sustainability of ecological quality in combination with different policy periods and explore its impact on spatial analysis. Understanding the different driving factors and understanding the current ecological quality of the Inner Mongolia Autonomous Region is of great significance to the construction of ecological civilization and the sustainable development of the economy and society in the Inner Mongolia Autonomous Region.

To accurately assess the status and evolution trend of the ecological quality of the Inner Mongolia Autonomous Region, this article uses principal component analysis to construct a remote sensing ecological index based on the MODIS remote sensing image data, vegetation index data and surface temperature data provided by the Google Earth Engine (GEE) platform from 2001 to 2021. (Remote Sensing Based Ecological Index, RSEI) to explore the long-term ecological quality of the Inner Mongolia Autonomous Region, explore its spatial distribution and change characteristics using equal-spaced classification and Moran index, and use Theil-Sen trend analysis and Mann-Kendall test to analyze its temporal changes trends, and use the Hurst index to analyze the changing characteristics of ecological quality in combination with MDGs (Millennium Development Goals) and SDGs (Sustainable Development Goals) in different periods, identify the continuous improvement and continuous degradation areas of ecological quality in Inner Mongolia Autonomous Region, and explore the sustainability of ecological quality development level, and finally analyze the driving factors leading to spatial differentiation of RSEI in different regions based on geographical detectors. The main research contents and conclusions of this article are as follows:

(1) By evaluating the ecological quality of the Inner Mongolia Autonomous Region from 2001 to 2021, the results show that: the first principal component represents the ecological quality, with a contribution rate of more than 78%; and over the years, the average correlation of each indicator with the remote sensing ecological index Higher, that is, the remote sensing ecological index calculated by combining the four ecological quality factors of greenness, humidity, temperature, and dryness, well integrates factors closely related to ecological quality, and can intuitively and objectively represent the ecological quality in the region.

(2) Spatially, the ecological quality of the Inner Mongolia Autonomous Region has obvious differences in spatial distribution, forming a distribution pattern of "high in the east and low in the west, and staggered in the middle." The remote sensing ecological index is low in the desert Gobi region of the southwest, and has changed little over the years; the urban agglomeration and sand-grass ecotone in the central part are staggered with high and low values, and have changed greatly over the years; the remote sensing ecological index in the mountains of the Daxinganling region in the northeast is relatively high, the ecological quality situation is relatively stable. Combined with the Moran Index, the five-year average value of the global Moran Index is 0.961, indicating that the ecological quality of the Inner Mongolia Autonomous Region has obvious spatial autocorrelation and shows obvious agglomeration characteristics, and the western region has been mostly low-low agglomeration areas for many years. Northeastern regions are mostly high-high agglomeration areas.

(3) Over time, the ecological quality of most areas in the Inner Mongolia Autonomous Region has an improvement trend. The areas with improved ecological quality account for 65.09% of the entire region, and the areas with degradation trends account for 24.85% of the entire region. Areas with an improvement trend are mainly concentrated in the northeastern part of the autonomous region and areas where ecological projects have been implemented in recent years, while areas with a degradation trend are mainly desert and Gobi areas that are difficult to reach by ecological projects. The ecological governance of the Inner Mongolia Autonomous Region has achieved significant results and the future trend is improving.

(4) During the Millennium Development Goals (MDGs) period, the overall ecological quality of Inner Mongolia Autonomous Region showed a degradation trend, and the area of continuously degraded areas accounted for a large proportion. In the eastern Xing'an League, Tongliao and other regions, due to the implementation of ecological restoration projects and better environmental conditions of the Inner Mongolia Autonomous Region, there are many areas with continuous improvement in ecological quality; and during the Sustainable Development Goals (SDGs) period, that is, 2015-2021, the ecological quality improvement in Inner Mongolia Autonomous Region is the largest and most sustainable. The ecological quality under the background of SDGs Engineering and ecological restoration and protection policies has a great positive impact on the ecological quality of the Inner Mongolia Autonomous Region, promoting the continuous improvement of the ecological quality of the autonomous region. Most areas have reversed the trend of continuous degradation of ecological quality during the MDGs period through governance.

(5) In typical areas of continuous change, spatial differentiation of ecological quality is driven by multiple factors. Among them, climate elements constitute the background factors of the ecological environment in the region. They have the highest explanatory power among the various driving factors in the two typical areas, and dominate the spatial differentiation of ecological quality in the typical areas. Among the human activity elements, the explanatory power of land use type is the highest in both typical areas, and it also has a significant impact on the distribution pattern of ecological quality. In the typical areas of continuous improvement, ecological engineering elements are also one of the main reasons for the differences in ecological quality within the region, and their explanatory power ranks second. In the typical areas of continuous degradation, due to the harsh natural background conditions, the role of ecological engineering is mainly to curb further deterioration of the ecological environment, so the explanatory power is smaller than in the typical areas of continuous improvement. In the interaction detection, precipitation and land use type are the combinations with the highest explanatory power in the typical areas of continuous improvement, indicating that climate and human activities jointly dominate the spatial differentiation of ecological quality; while in the typical areas of continuous degradation, the average annual temperature The combination with average annual wind speed has the highest explanatory power. Climate factors are the most important factor affecting the spatial differentiation of local ecological quality.