资源与环境模型标准文档库及其与GIS集成

论述了中国资源与环境模型标准文档库的结构和内容。通过研究总结数学模型及其研究现状发现 ,中国资源与环境模型标准文档库建设需要完善尚有缺陷的数学模型、创建尚缺少的数学模型 ;通过归纳现有数学模型与地理信息系统的现有集成方法发现 ,目前的集成方法不能满足区域可持续发展集成模型的需要 ,据此讨论了数学模型与地理信息系统有效集成需要深入研究的内容。最后 ,提出了通过大量案例研究 ,形成区域可持续发展集成模型和中国资源与环境模型标准文档库 2个软件包的可行研究思路。

资源环境综合模型的集成分析

针对资源环境问题的复杂性和综合性,在对海量资源环境模型进行分析并构建了资源环境模型库系统(REMS)的基础上,运用综合集成的方法论理念,根据复杂性资源环境问题综合模拟分析过程中系列子模型各自所承担的模拟功能和重要性,从资源环境学科背景的研究角度,探索性地提出了资源环境综合模型的串联集成、并联集成、混联集成等三种通用的综合集成模式。以HLZ生态系统时空变化趋势及情景分析模型集成为例,对集成模式的有效性和可行性进行了论证分析。

1990年来中国城镇建设用地占用耕地的效率和驱动机理时空分析

定量揭示城镇建设用地与耕地的时空变化关系和相互作用机理,是如何实现城镇建设用地需求与耕地资源保护二者间动态平衡的关键问题之一。基于1990—2015年全国城镇建设用地及耕地的空间数据,在对比分析中国31个省份近25年来的城镇建设用地及耕地时空格局变化的基础上,定量求算因城镇建设用地扩张导致耕地减少的速率,并引入数据包络分析法和地理探测器,实现自1990年以来中国城镇建设用地占用耕地的驱动效用机理。结果表明:1)在时间维度上,1990—2015年间,中国城镇建设用地增长2.6×10^(4) km^(2),增速107%,而扩张速率以2.4%/5 a逐渐降低。1990—2000年耕地呈增加趋势(增加2.96×10^(4) km^(2)),2000年后呈减少趋势,总体减少速率为0.29%/5 a。全国新增城镇建设用地占用2.12×10^(4) km^(2)耕地,占城镇新增总量的72.5%;2)在空间分布上,全国城镇建设用地扩张面积由东向西逐渐减小,但2010后的西部区域扩张速度呈上升趋势。耕地面积在西北和东北地区有所增加,东部和中部呈减少趋势,城镇建设用地占用耕地比例由东部向西部逐渐减弱,但中东部耕地被建设用地占用形式仍然严重;3)在城镇建设用地占用耕地的效用上,1990—2015年,全国城镇建设用地占用耕地的产出效益呈现降低趋势,其中产出效益超过0.8的省份主要分布在沿海地区,西北地区产出效益普遍较低。分析结果显示,经济发展因素是新增城镇建设用地占用耕地的主要驱动因素,其次为空间位置因素和政策措施,自2010年后政策因素的驱动作用强度呈增加趋势。

中蒙俄经济走廊荒漠化时空格局变化及其驱动因子

针对如何定量揭示中蒙俄经济走廊荒漠化的时空变化规律及其驱动因子的影响作用,在构建荒漠化程度判别标准和指标体系的基础上,基于Google Earth Engine云计算平台,在对分类回归树(CART)、支持向量机(SVM)、随机森林(RF)和Albedo-NDVI 4个模型精度进行对比分析的基础上,选取精度最高的CART模型实现中蒙俄经济走廊区域2000—2015年的荒漠化的时空变化分析。另外,在拓展线性趋势法的基础上,构建荒漠化驱动因子定量评估模型,实现气候变化和人类活动对荒漠化驱动效应的定量测度。结果表明:1)CART模型在中蒙俄经济走廊区域荒漠化信息提取精度最高,总体精度和Kappa系数分别85%和0.754;2)极重度荒漠化区域主要分布在中国内蒙古自治区西部,蒙古国的南戈壁盟、东戈壁盟和中戈壁盟;3)2000—2015年间,中蒙俄经济走廊荒漠化总体呈扩张趋势,但极重度、重度和中度荒漠化面积呈缩减趋势。其中,中国的荒漠化面积呈明显缩减趋势,荒漠化程度净改善面积为15.18万km^2,而蒙古国和俄罗斯的荒漠化现象在加重。另外,中蒙俄经济走廊荒漠化恢复区域的气候变化驱动贡献率为68.8%;而荒漠化退化区域的人类活动驱动贡献率为69.68%,表明中蒙俄经济走廊荒漠化程度加重区域的驱动作用主要来自于人类活动。

黄土高原生态系统过渡带土地覆盖的时空变化分析

在全球气候变化及其生态环境效应研究中,生态系统过渡带作为气候变化和人类活动的敏感区域,其土地覆盖的时空变化分析逐渐成为土地利用科学研究的热点问题。基于GIS的时空分析方法,在对Holdridge生命地带模型的判别标准进行改进的基础上,构建了生态系统过渡带的时空分析模型。在建立土地覆盖正向和逆向转换规则的基础上,构建了土地覆盖正向和逆向转换指数模型。并以黄土高原为案例区,在定量识别生态系统过渡带类型及其空间格局的基础上,定量评价了各种生态系统过渡带类型土地覆盖的转换情况。模拟分析结果表明,黄土高原地区共有14种生态系统过渡带类型,其总面积占整个黄土高原的25.21%。在1985—2005年期间,黄土高原生态系统过渡带内的耕地面积平均每10 a减少0.93%,而湿地和水体、林地、草地的面积则平均每10 a分别增加3.47%、0.24%、0.06%。整个过渡带区域土地覆盖的转换率从28.53%降低到21.91%,且其正向转换和逆向转换面积总体上均呈减少的趋势。另外,黄土高原生态系统过渡带区域和非过渡带区域的土地覆盖转换率对比分析显示,过渡带区域土地覆盖的转换率高于非过渡带区域。

中国气温未来情景的降尺度模拟

由于GCM模拟的气温数据分辨率不高,很难用于区域尺度上各种生态系统的模拟。本文基于长时间序列(1964～2007年)的全国气温观测数据,结合经纬度数据、以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均气温降尺度模型的基础上,运用高精度曲面建模(HASM)方法对HadCM3的A1Fi、A2a和B2a三种情景1961～1990、2010～2039、2040～2069、2070～2099年时段的全国未来平均气温进行高精度曲面模拟。模拟结果显示,在四个时段内,A1Fi、A2a和B2a三种情景的全国未来平均气温均呈持续上升趋势。其中,平均气温在A1Fi情景中上升速度最快,B2a情景中增速最慢;A1Fi和A2a两种情景的平均气温均呈加速上升和增加趋势,而B2a情景的平均气温则呈减速上升和增加趋势。本文构建的降尺度模拟方法可以有效地实现IPCCGCM的低分辨率的气温未来情景数据降尺度转换成高分辨率气温数据。

中国降水未来情景的降尺度模拟

基于长时间序列(1964～2007年)的全国降水观测数据,结合经纬度数据以及DEM、坡向、坡度等系列地形特征数据,利用空间统计方法,在构建年平均降水降尺度模型的基础上,运用高精度曲面建模(HASM)方法对经过降尺度分析的HadCM3的A1Fi、A2a和B2a三种情景T1～T4时段的全国未来平均降水进行高精度曲面模拟。模拟结果显示,在T1～T4时段内,A1Fi、A2a和B2a三种情景的全国平均降水均呈持续增加趋势。其中,平均降水在A1Fi情景中增加速度最快,B2a情景中增加速度最慢;A1Fi和A2a两种情景的平均降水均呈加速增加趋势,而B2a情景的平均降水则呈减速增加趋势。模拟结果表明,本文构建的降尺度模拟方法可以有效地实现IPCC GCM的低分辨率的降水情景数据降尺度转换成高分辨率的降水数据。

Quantitative Analysis of Land Degradation in Mongolia from the Perspective of Geographical Zone

Natural and anthropogenic disturbances accelerate land degradation(LD)in arid,semi-arid,and dry sub-humid areas,leading to reduced land quality and productivity,loss of biodiversity,degradation of ecosystem services,and a decline in the quality of life of local people.To address this issue,the United Nations Convention to Combat Desertification(UNCCD)has set a target for LD neutrality(LDN).However,quantifying and comparing the status of LD at global or regional scales remains challenging due to the lack of coherent quantitative methods and tools.In this study,we focused on Mongolia,a region with significant LD problems,to examine patterns of LD and changes from 2015 to 2020,accounting for regional differences.Trends.Earth was used,as recommended by the UNCCD.The main findings are as follows:(1)Overall,the degraded land area in Mongolia accounted for 12.11%of the total land area,predominantly located in the southwest desert and desert steppe,gradually spreading to the northeast steppe.(2)The areas showing improvement in the land productivity index and degradation were 17.62%and 11.79%,respectively,with the most severely degraded areas concentrated in the southern desert and desert steppe regions.(3)The areas of improvement and degradation in the land cover index were 1.80%and 0.16%,respectively,with degraded areas scattered across regions of steppe,high mountains,and mountain taiga.(4)The areas of improvement and degradation in the land organic carbon index were 1.54%and 0.22%,respectively,with degradation primarily observed in adjacent areas of mountain taiga,steppe,and desert steppe.(5)The improved area(2.999×10^(5)km^(2))of LDN are more than the degraded area(1.895×10^(5)km^(2)),indicating a positive trend toward LDN in Mongolia.

Vegetation Changes from 2014 to 2023 in the Mongolian Plateau Permafrost Region under Climate Change

The permafrost region is one of the most sensitive areas to climate change.With global warming,the Mongolian Plateau permafrost is rapidly degrading,and its vegetation ecosystem is seriously threatened.To address this challenge,it is essential to understand the impact of climate change on vegetation at different permafrost degradation stages on the Mongolian Plateau.Based on the general permafrost distribution,in this study,we divided different permafrost regions and explored the response of vegetation to climate change at different stages of permafrost degradation by the idea of“space instead of time”from 2014 to 2023.The results of the study showed that:(1)Normalized difference vegetation index(NDVI)values showed a decreasing trend,and the proportion of the decreasing region was in the order of sporadic permafrost region>isolated and sparse permafrost region>continuous and discontinuous permafrost regions.(2)The main controlling factors of vegetation growth in permafrost regions are different,air temperature is the main controlling factor of vegetation growth in isolated and sparse permafrost region(r=-0.736)and sporadic permafrost regions(r=-0.522),and precipitation is the main controlling factor of vegetation growth in continuous and discontinuous permafrost region(r=-0.498).(3)The response of NDVI to climate change varies at different stages of permafrost degradation.In the early stages of permafrost degradation,increased land surface temperature(LST)and air temperature favored vegetation growth and increased vegetation cover,whereas increased precipitation impeded vegetation growth;as the permafrost degraded,increased LST and air temperature impeded vegetation growth,whereas increased precipitation promoted vegetation growth.

Characteristics of Spatial and Temporal Vegetation Index Variability and Its Responses to Temperature and Precipitation in Mongolia

The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate warming.Such studies can enhance our understanding of regional vegetation responses to global warming and contribute to the establishment of a stronger ecological barrier in northern China.Here,we analyzed the spatial and temporal characteristics of the NDVI(normalized difference vegetation index)in Mongolia using 8 km resolution GIMMS NDVI3g data from 1990 to 2022,along with temperature,precipitation,and elevation data.Trend analysis and correlation methods were used to examine the relationships between the NDVI and temperature,as well as precipitation.The results showed four important aspects of these relationships.(1)The NDVI in Mongolia increased significantly from 1990 to 2022 at a rate of 0.0015 yr^(-1)(P<0.05).(2)Mongolia’s NDVI increased from 1990 to 2022 in 60.73%of the country.Of this total,the area with a significant increase accounted for 31.67%and was concentrated on the eastern and western edges.The area experiencing a significant decrease accounted for 15.67%and was mainly located on the southwestern edges.(3)The NDVI analysis revealed significant increasing trends in all regions except for those at elevations of 1500-2000 m.The greatest rate of increase was observed between 500 and 1000 m,and the increasing trend weakened as elevation continued to increase before gradually becoming significant again.Additionally,the NDVI increased significantly across different slopes,and the rate of increase decreased as the slope increased.(4)From 1990 to 2022,Mongolia’s NDVI was mostly negatively correlated with temperature.This occurred over 66.75%of the total land area,with 17.21%of the region exhibiting a significant negative correlation,mainly in the southwest.Conversely,the NDVI demonstrated a positive correlation with precipitation,encompassing 86.71%of the total land area.Approximately 40.44%of the region had a significant positive correlation,primarily in the southwest.In conclusion,throughout the experimental period,the vegetation state in Mongolia improved.However,due to the warming and drying climate,more attention should be paid to vegetation degradation in the south-central region.

Issues,Progress,and Recommendations in the Construction of Ecological Barrier on the Mongolian Plateau from the Perspective of Big Data

The Mongolian Plateau(MP),situated in the transitional zone between the Siberian taiga and the arid grasslands of Central Asia,plays a significant role as an Ecological Barrier(EB)with crucial implications for ecological and resource security in Northeast Asia.EB is a vast concept and a complex issue related to many aspects such as water,land,air,vegetation,animals,and people,et al.It is very difficult to understand the whole of EB without a comprehensive perspective,that traditional diverse studies cannot cover.Big data and artificial intelligence(AI)have enabled a shift in the research paradigm.Faced with these requirements,this study identified issues in the construction of EB on MP from a big data perspective.This includes the issues,progress,and future recommendations for EB construction-related studies using big data and AI.Current issues cover the status of theoretical studies,technical bottlenecks,and insufficient synergistic analyses related to EB construction.Research progress introduces advances in scientific research driven by big data in three key areas of MP:natural resources,the ecological environment,and sustainable development.For the future development of EB construction on MP,it is recommended to utilize big data and intelligent computing technologies,integrate extensive regional data resources,develop precise algorithms and automated tools,and construct a big data collaborative innovation platform.This study aims to call for more attention to big data and AI applications in EB studies,thereby supporting the achievement of sustainable development goals in the MP and enhancing the research paradigm transforming in the fields of resources and the environment.

黑河流域植被类型分布模拟分析

针对黑河流域植被类型空间分布的垂直地带性特征,本文基于支持向量机算法构建黑河流域植被类型空间分布的模拟分析模型,并运用Kappa系数和混淆矩阵检验方法对模拟精度进行检验。验证结果显示,模型总体精度(OA)值为75.54%,Kappa系数值为0.66,表明了该方法在植被分布模拟上具有较好的结果,适用于区域尺度下植被类型分布的空间模拟。模拟结果表明,该方法对半灌木-矮半灌木荒漠和温带禾草-杂类草草甸草原类型的模拟精度最高,分别为(90.20%和90.02%);分布面积最大的植被类型(如半灌木-矮半灌木荒漠,灌木荒漠、嵩草-杂类草高寒草甸等)相比于其他面积较小的植被类型具有显著优异的模拟结果;人工经济作物、荒漠植被类型以及草原草甸等植被类型对于所选环境因子的敏感性更强,而灌丛类型和乔木类型的模拟结果在不同类型间的波动较大;空间分布上,环境要素差异性明显、植被类型丰富的上游地区具有更好的模拟结果,优于地势平坦、气候差异性小的黑河中下游地段,但模拟结果在景观形态上具有更高的破碎度。

Spatio-temporal Distribution of Drought in the Belt and Road Area During 1998–2015 Based on TRMM Precipitation Data

Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Based on the Tropical Rainfall Measuring Mission Satellite（TRMM） 3 B43 precipitation data, we used the Precipitation Abnormity Percentage drought model to study the monthly spatio-temporal distribution of drought in south region of N50° of the Belt and Road area. It was observed that drought during winter was mainly distributed in Northeast Asia, Southeast Asia, and South Asia, while it was mainly distributed in Central Asia and West Asia during summer. The occurrence of historical droughts indicates an obvious seasonal cycle. The regional variations in drought were analyzed using the Breaks for Additive Season and Trend tool（BFAST） in six sub-regions according to the spatial distribution of six economic corridors in the Belt and Road area. The average drought conditions over the 18 years show a slight decreasing trend in Northeast Asia, West Asia, North Africa, South Asia, Central and Eastern Europe, and a slight increasing trend in Central Asia. However, it was a fluctuating pattern of first increasing and then decreasing in Southeast Asia. The results indicate that the total drought area in the Belt and Road region showed a general decreasing trend at a rate of 40,260 km^2 per year from 1998 to 2015.

Estimation of Grassland Production in Central and Eastern Mongolia from 2006 to 2015 via Remote Sensing

Mongolia is an important part of the Belt and Road Initiative"China-Mongolia-Russia Economic Corridor"and a region that has been severely affected by global climate change.Changes in grassland production have had a profound impact on the sustainable development of the region.Our study explored an optimal model for estimating grassland production in Mongolia and discovered its temporal and spatial distributions.Three estimation models were established using a statistical analysis method based on EVI,MSAVI,NDVI,and PsnNet from Moderate Resolution Imaging Spectroradiometer(MODIS)remote sensing data and measured data.A model evaluation and accuracy comparison showed that an exponential model based on MSAVI was the best simulation(model accuracy 78%).This was selected to estimate the grassland production in central and eastern Mongolia from 2006 to 2015.The results show that the grassland production in the study area had a significantly fluctuating trend for the decade study;a slight overall increasing trend was observed.For the first five years,the grassland production decreased slowly,whereas in the latter five years,significant fluctuations were observed.The grassland production(per unit yield)gradually increased from the southwest to northeast.In most provinces of the study area,the production was above 1000 kg ha with the largest production in Hentiy,at 3944.35 kg ha.The grassland production(total yield)varied greatly among the provinces,with Kent showing the highest production,2341.76x1〇4 t.Results also indicate that the trend in grassland production along the China-Mongolia railway was generally consistent with that of the six provinces studied.

Predicting Potential Geographic Distribution of Tibetan Incarvillea younghusbandii Using the Maxent Model

Incarvillea younghusbandii is a well-known Tibetan medicinal plant with considerable development and research value distributed widely throughout the Tibetan plateau.It is important to study spatial distribution patterns of the plant in order to develop effective protection measures.Based on field survey work and environmental data, the potential geographic distribution of Incarvillea younghusbandii was delineated using a Maximum Entropy (Maxent)model with 28environmental variables that screened for climate,topography,human activity and biological factors.Our results showed that the main geographic range of Incarvillea younghusbandii included the valley between the Yarlung Zangbo river and the Duoxiong Zangbo river,the valley in the middle section of the Himalaya Mountains,and the area between the north side of the east section of the Himalayas and the south bank of the middle reach of the Yarlung Zangbo river.Distribution may spread to parts of the eastern Himalayas.The Jackknife test indicated that soil types,ratio of precipitation to air temperature,extreme atmospheric pressure differences and annual precipitation were the most important predictive factors for the model,while other variables made relatively small contributions.

Quantitative Assessment of the Effects of Climate Change and Human Activities on Grassland NPP in Altay Prefecture

Grassland degradation in Altay Prefecture is of considerable concern as it is a threat that hinders the sustainable development of the local economy and the stable operation of the livestock industry.Quantitative assessment of the relative contributions of climate change and human activities,which are considered as the dominant triggers of grassland degradation,to grassland variation is crucial for understanding the grassland degradation mechanism and mitigating the degraded grassland in Altay Prefecture.In this paper,the Carnegie-Ames-Stanford Approach model and the Thornthwaite memorial model were adopted to simulate the actual net primary productivity(NPP_(A))and potential net primary productivity(NPP_(P))in the Altay Prefecture from 2000 to 2019.Meanwhile,the difference between potential NPP and actual NPP was employed to reflect the effects of human activities(NPP_(H))on the grassland.On this basis,we validated the viability of the simulated NPP using the Pearson correlation coefficient,investigated the spatiotemporal variability of grassland productivity,and established comprehensive scenarios to quantitatively assess the relative roles of climate change and human activities on grassland in Altay prefecture.The results indicate three main points.(1)The simulated NPP_(A) was highly consistent with the MOD17 A3 dataset in spatial distribution.(2)Regions with an increased NPP_(A) accounted for 70.53% of the total grassland,whereas 29.47% of the total grassland area experienced a decrease.At the temporal scale,the NPP_(A) presented a slightly increasing trend(0.83 g C m^(-2) yr^(-1))over the study period,while the trends of NPP_(P) and NPP_(H) were reduced(-1.31 and-2.15 g C m^(-2) yr^(-1)).(3)Compared with climate change,human activities played a key role in the process of grassland restoration,as 66.98% of restored grassland resulted from it.In contrast,inter-annual climate change is the primary cause of grassland degradation,as it influenced 55.70% of degraded grassland.These results could shed light on the mechanisms of grassland variation caused by climate change and human activities,and they can be applied to further develop efficient measures to combat desertification in Altay Prefecture.

Impact of Land Use Changes on Habitat Quality in Altay Region

Altay region is located in the northern part of Xinjiang,and has complex and diverse internal geomorphic types,undulating terrain and a fragile ecosystem.Studying the impact of land use changes on habitat quality is of great significance to regional ecological protection and development,rational planning and utilization,and ensuring the sustainable development of the ecological environment.Based on the InVEST model,combined with land use panel data and topographic relief data of the Altay region,this paper studied the habitat quality from 1995 to 2018.The results show that cultivated land,water area and construction land increased gradually from 1995 to 2018,while grassland and unused land decreased.Forestland remained stable in the first five periods,but increased significantly in 2018.During 1995-2018,all land use types were transferred,mainly between cultivated land,forestland,grassland and unused land in the flat and slightly undulating areas.Poor habitat quality was dominant during 1995-2018.Habitat quality decreased significantly in 2015,which was related to the rapid expansion of cultivated and construction land as threat sources,as well as the decrease of forest and grassland as sensitive factors.However,habitat quality improved significantly in 2018,because a large amount of cultivated land and unused land were converted into forest land and grassland with high habitat suitability.Land use type has an important influence on habitat quality.The distribution characteristics of habitat quality for topographic relief types from good to bad were:large undulating area>medium undulating area>small undulating area>flat area>slightly undulating area.The findings of this study are of great significance for coordinating social,economic,and ecological development in this region and in similar areas.

Spatial Structure and Development of Tourism Resources based on Point Pattern Analysis: A Case Study in Hainan Island, China

Tourism resources are the basic materials of tourism development, and they also provide the support for regional tourism spatial competition. The development of tourism depends on the degree to which tourism resources are utilized, and it is of great guiding significance for their development and utilization to study their spatial structure. Based on a large sample of data on tourism resources, and starting from the characteristics of multi-type,multi-level and multi-combination, this paper puts forward a framework and method for analyzing the spatial structure of tourism resources. Taking Hainan Island as an example, this paper describes the spatial structure of tourism resources in Hainan Island by using the method of point pattern analysis, identifies the tourism resource development zones, and puts forward some suggestions for the development of tourism resources. The results are as follows:(1) The characteristic scale of the spatial structure of tourism resources in Hainan Island is 30.5 km, and there are significant differences in the distributions of all kinds of tourism resources.(2) Through the spatial structure map of tourism resources, the tourism resource development zones are identified, including three tourist central city levels, “one horizontal and three vertical” tourist belts and four tourist combination areas.(3) By combing the distribution of tourism resources and the development zones in Hainan Island, the cross-border characteristics of the tourism resources and development zones are obvious. In order to give full play to the spatial combination and superposition effect of tourism resources, a change from a single isolated development mode to the overall combined development between regions is suggested. On the provincial scale, it is relatively accurate to describe the spatial structure of tourism resources for point data with a large sample size. However, the method of point pattern analysis can not only accurately describe the spatial structure of tourism resources, but it can also provide reference for other types of regional spatial analyses. The research results provide a scientific basis for the spatial planning of regional tourism resources and have practical significance for the development of regional tourism.

Spatial Distribution and Dynamic Changes in Research Hotspots for Desertification in China based on Big Data from CNKI

Desertification research plays a key role in the survival and development of all mankind.The Normalized Comprehensive Hotspots Index(NCH)is a comprehensive index that reveals the spatial distribution of research hotspots in a given research field based on the number of relevant scientific papers.This study uses Web Crawler technology to retrieve the full text of all Chinese journal articles spanning the 1980s-2018 in the Chinese Academic Journal full-text database(CAJ)from CNKI.Based on the 253,055 articles on desertification that were retrieved,we have constructed a research hotspot extraction model for desertification in China by means of the NCH Index.This model can reveal the spatial distribution and dynamic changes of research hotspots for desertification in China.This analysis shows the following:1)The spatial distribution of research hotspots on desertification in China can be effectively described by the NCH Index,although its application in other fields still needs to be verified and optimized.2)According to the NCH Index,the research hotspots for desertification are mainly distributed in the Agro-Pastoral Ecotone and grassland in Inner Mongolia,the desertification areas of Qaidam Basin in the Western Alpine Zone and the Oasis-Desert Ecotone in Xinjiang(including the extension of the central Tarim Basin to the foothills of the Kunlun Mountains,the sporadic areas around the Tianshan Mountains and the former hilly belt of the southern foothills of the Altai Mountains).Among these three,the Agro-Pastoral Ecotone in the middle and eastern part of Inner Mongolia includes the most prominent hotspots in the study of desertification.3)Since the 1980s,the research hotspots for desertification in China have shown a general downward trend,with a significant decline in 219 counties(10.37%of the study area).This trend is dominated by the projects carried out since 2002.The governance of desertification in the eastern part of the Inner Mongolia-Greater Khingan Range still needs to be strengthened.The distribution of desertification climate types reflects the distribution of desertification in a given region to some extent.The Normalized Comprehensive Hotspots Index provides a new approach for researchers in different fields to analyze research progress.

Spatiotemporal Pattern and Driving Force Analysis of Vegetation Variation in Altay Prefecture based on Google Earth Engine

Quantitative evaluation and driving mechanism analysis of vegetation dynamics are essential for promoting regional sustainable development.In the past 20 years,the ecological environment in Altay Prefecture has changed significantly due to global warming.Meanwhile,with increasing human activities,the spatiotemporal pattern and driving forces of vegetation variation in the area are uncertain and difficult to accurately assess.Hence,we quantified the vegetation growth by using the Normalized Difference Vegetation Index(NDVI)on the Google Earth Engine(GEE).Then,the spatiotemporal patterns of vegetation from 2000 to 2019 were analyzed at the pixel scale.Finally,significance threshold segmentation was performed using meteorological data based on the correlation analysis results,and the contributions of climate change and human activities to vegetation variation were quantified.The results demonstrated that the vegetation coverage in Altay Prefecture is mainly concentrated in the north.The vegetation areas representing significant restoration and degradation from 2000 to 2019 accounted for 24.08% and 1.24% of Altay Prefecture,respectively.Moreover,spatial correlation analysis showed that the areas with significant correlations between NDVI and temperature,precipitation and sunlight hours accounted for 3.3%,6.9% and 20.3% of Altay Prefecture,respectively.In the significant restoration area,18.94% was dominated by multiple factors,while 3.4% was dominated by human activities,and 1.74% was dominated by climate change.Within the significant degradation area,abnormal degradation and climate change controlled 1.07% and 0.17%,respectively.This study revealed the dynamic changes of vegetation and their driving mechanisms in Altay Prefecture,and can provide scientific support for further research on life community mechanism theory and key remediation technology of mountain-water-forest-farmland-lake-grass in Altay Prefecture.