Long-term desertification process monitoring and driving factors analysis in rare earth mining area

With the exploitation of rare earth elements (REE) in southern China, desertification has become a serious ecological problem in this region. To accurately understand the desertification process in mining areas and formulate targeted ecological restoration programs, taking the Lingbei mining area in Ganzhou City, Jiangxi Province as the study area, we explored desertification information extraction methods, desertification dynamics monitoring, and desertification drivers in REE mining areas using multisource data from 1986 to 2021. The results show that from the method of extracting desertification information, Random Forest is the prominent (83.33%), followed by Albedo–NDVI (Normalized Difference Vegetation Index) space (74.44%), and thirdly Linear Spectral Mixture Model (65.56%). From 1986 to 2021, the desertification land area in Lingbei mining areas first increased and then decreased, showing a reverse trend, but it has not recovered to the pre-mining level. The government's ecological reclamation measures are the key factors for the restoration of desertification land. There are still 17.81 km² areas that have not been restored, of which 2.16 km² are at the level of severe desertification. Moderate desertification and light desertification have not been completely curbed, which needs continuous attention. Vegetation coverage has the highest explanatory power to the distribution of land desertification in mining areas, followed by land use classification, indicating that human activities have a great influence on the spatial differentiation of land desertification in mining areas, and it is necessary to pay attention to regional balanced and sustainable development in the future.     

Trend Patterns of Vegetative Coverage and Their Underlying Causes in the Deserts of Northwest China over 1982 – 2008

We identified the spatiotemporal patterns of the Normalized Difference Vegetation Index (NDVI) for the years 1982–2008 in the desert areas of Northwest China and quantified the impacts of climate and non-climate factors on NDVI changes. The results indicate that although the mean NDVI has improved in 24.7% of the study region; 16.3% among the region has been stagnating in recent years and only 8.4% had a significantly increasing trend. Additionally, 45.3% of the region has maintained a stable trend over the study period and 30.0% has declined. A multiple regression model suggests that a wetter climate (quantified by the Palmer Drought Severity Index, PDSI) is associated with higher NDVI in most areas (18.1% of significance) but these historical changes in PDSI only caused an average improvement of approximately 0.4% over the study region. Contrasting the regression results under different trend patterns, no significant differences in PDSI impacts were detected among the four trend patterns. Therefore, we conclude that climate is not the primary driver for vegetative coverage in Northwest China. Future studies will be required to identify the impacts of specific non-climatic factors on vegetative coverage based on high-resolution data, which will be beneficial in creating an effective strategy to combat the recent desertification trend in China.     

1995-2018年石羊河流域下游荒漠化动态变化

以石羊河流域下游甘肃省民勤县为研究区,选取1995、2000、2005、2010、2015、2018年6期遥感影像作为数据源,利用RS和GIS理论和方法,基于归一化植被指数(NDVI)和地表反照率(Albedo)建立Albedo-NDVI特征空间,构建荒漠化差值指数,对民勤县荒漠化动态变化进行分析.结果 表明:石羊河流...     

喀斯特关键带植被时空变化及其驱动因素

中国南方喀斯特地区广泛面临着生态问题,植被的保护与恢复倍受关注,对这一区域植被覆盖的进行监测和预测是非常必要的。以MODIS-NDVI为数据源,分析2000—2016年间,研究区不同地质背景,多种土地覆被类型的NDVI时空变化特征及驱动因素。结果表明:(1)从2000—2016年间,研究区植被覆盖整体呈增长趋势;其中喀斯特区域增长情况略优于非喀斯特区域。植被覆盖在空间上呈现东高西低;其中林地的NDVI值最高,耕地次之,依次草地,居民用地,水域,未利用地最低;在林地和耕地中,非喀斯特区域的NDVI值比喀斯特高,其余的土地覆被类型中都比喀斯特区域低。(2)研究区植被覆盖改善的地区占60.19%,退化地区占17.06%;草地,耕地区改善明显,退化主要在水域和建设用地; Hurst指数显示在研究区持续性改善的NDVI大于持续性退化;相比非喀斯特区域,喀斯特区域改善及持续性改善情况更佳。(3)整体而言,海拔对NDVI的空间分布影响力最大,温度次之,依次为降雨,夜间灯光指数;相比而言,非喀斯特区域NDVI空间分布更易受地形因子影响;喀斯特区域NDVI空间分布更易受气候差异及人类活动影响。(4)研究区分别有49%,45%,61%的NDVI与气温,降雨,日照的相关系数通过a=0.05的显著性检验;相比非喀斯特而言,喀斯特区域植被生长更易受气候变化的影响。     

科尔沁沙地沙漠化过程中土壤有机碳和全氮含量变化

通过地面调查,研究了沙漠化对科尔沁沙地农田和草地土壤有机碳和全氮含量的影响.结果表明,随着沙漠化的发展,科尔沁沙地土壤碳、氮含量明显下降.和非沙漠化农田相比,轻度、中度、重度和严重沙漠化农田土壤有机碳和全氮含量分别下降12.3%和15.3%、22.2%和24.7%、39.5%和44.7%、64.4%和63.5%;和非沙漠化草地相比,轻度、中度、重度和严重沙漠化草地土壤有机碳和全氮含量分别下降了56.3%和48.7%、78.4%和74.4%、88.9%和84.6%、91.6%和84.6%.截至2000年,科尔沁沙漠化总面积已经达到50197.5 km2,由于沙漠化而导致的土壤有机碳和全氮损失总量分别为36.39 Mt和7.89 Mt,其中草地分别占91.12%和86.06%,农田分别占8.88%和13.94%.相关分析结果表明,土壤有机碳和全氮的损失主要源于风蚀所引起的土壤粘粉粒的减少.因此,在科尔沁沙地,防治土壤风蚀对于减少农田和草地土壤碳、氮损失极为重要.     

西南喀斯特地区石漠化时空演变过程分析

喀斯特地区石漠化对当地社会经济的可持续发展有严重的阻碍作用,因此,研究喀斯特石漠化时空特征及演变规律,对石漠化治理有着重要的意义。以西南八省为研究区,利用归一化差分植被指数（Normalized Difference Vegetation,NDVI）、净初级生产力（Net Primary Productivity,NPP）、地表反照率（Surface Albedo）和坡度（Slope）数据,借助ArcGIS等软件平台,分析石漠化在不同的坡度、土地利用和生态保护区内的变化。结果显示：（1）轻度和中度石漠化是西南主要的石漠化类型。从空间分布来看,石漠化发生分布面积最广的是贵州,其次为云南和广西。（2）从不同土地利用来看,2000-2015年间无石漠化面积最多,潜在石漠化次之。石漠化主要发生在耕地和林地两种土地类型上,其他用地上石漠化发生面积最少,但是极重度石漠化在其他用地上的发生比例很大,平均在11%左右。（3）从不同坡度来看,石漠化严重程度不随坡度的增加而加剧,在坡度6°-25°之间石漠化发生面积最大。（4）从生态保护区来看,2000和2015年西南喀斯特生态保护区是石漠化面积分布最多的区域,分别为27481.86 km²和21738.65 km²。最少的是大别山山地生态功能保护区,从变化量来看,增加最多的是三峡库区,增加1641.22 km²,减少最多的是西南喀斯特生态功能保护区,减少5743.22 km²。（5）利用NPP、NDVI、地表反照率和坡度能较精准的反演石漠化,其反演权重依次为0.33、0.42、0.15和0.1。研究时段内,西南生态环境逐渐得到改善。     

Influence of land-use types and climatic variables on seasonal patterns of NDVI in Mediterranean Iberian ecosystems

Question: What is the influence of management on the functioning of vegetation over time in Mediterranean ecosystems under different climate conditions? Location: Mediterranean shrublands and forests in SE Iberia (Andalusia). Methods: We evaluated the Normalized Difference Vegetation Index (NDVI) for the 1997-2002 time series to determine phenological vegetation patterns under different historical management regimes. Three altitudinal ranges were considered within each area to explore climate × management interactions. Each phenological pattern was analysed using time series statistics, together with precipitation (monthly and cumulative) and temperature. Results: NDVI time series were significantly different under different management regimes, particularly in highly transformed areas, which showed the lowest NDVI, weakest annual seasonality and a more immediate phenological response to precipitation. The NDVI relationship with precipitation was strongest in the summer-autumn period, when precipitation is the main plant growth-limiting factor. Conclusions: NDVI time series analyses elucidated complex influences of land use and climate on ecosystem functioning in these Mediterranean ecosystems. We demonstrated that NDVI time series analyses are a useful tool for monitoring programmes because of their sensitivity to changes, ease of use and applicability to large-scale studies.     

Land surface phenology and temperature variation in the International Geosphere–Biosphere Program high-latitude transects

The International Geosphere–Biosphere Program has delineated five study areas that form a northern high‐latitude network for the analyses of vegetation and carbon dynamics. We examined the magnitude and significance of changes in the land surface phenologies of ecoregions within these transects using the NASA Pathfinder Advanced Very High‐Resolution Radiometer Land dataset. We applied the seasonal Mann–Kendall (SMK) trend test, a robust and nonparametric approach, to determine the significance of trends in the normalized difference vegetation index (NDVI) over the five transects. The SMK trend test provides an important alternative over the frequently used but unreliable trend analysis based on linear regression. In addition, we modeled the land surface phenology using quadratic or nonlinear spherical models to relate the NDVI data to accumulated growing degree‐days (base 0°C). Nonlinear spherical models parsimoniously describe the green‐up dynamics in taiga and tundra ecoregions. Models for each ecoregion within each transect were fitted separately for two time periods (1985–1988 and 1995–1999) and their parameter coefficient estimates were compared. In 10 of 24 ecoregions that comprise 72% of the land area in the transects, the date of the peak NDVI value was significantly earlier (range 2–18 days) in the second study period than in the first study period. This progression was more pronounced in North America than in Siberia (weighted average of 9.3 vs. 6.3 days earlier). Understanding of what constitutes significant change in land surface phenology amidst background variation is a critical component of global change science. A diversity of datasets, techniques, and study areas has led to a range of conclusions about boreal phenology. We discuss statistical pitfalls in standard analyses and offer a framework to conduct statistically reliable change assessments of land surface phenologies.     

Spatiotemporal evolution of desertification based on integrated remote sensing indices in Duolun County,Inner Mongolia

Desertification causes not only a reduction of vegetation cover and surface moisture but also the expansion of sandy land. Considering that the modified soil adjusted vegetation index (MSAVI) is linearly related to canopy cover, albedo plays a significant role in the surface energy balance, and the sandy feature index (SFI) can identify sandy land. This paper proposed a desertification monitoring index (DMI) based on MSAVI, albedo and SFI to accurately monitor desertification. In addition, three classification methods (quantile grading, the susceptibility index segmentation method, and Jenks Natural Breaks) were used to divide the DMI into non-desertification, mild desertification, moderate desertification, and severe desertification. The relative exponential entropy model was adopted to select the optimal method for desertification classification. Spatiotemporal distributions of desertification in Duolun County were finally observed from 2005 to 2020. The results show that (1) although MSAVI, albedo and SFI have their own advantages in monitoring desertification, a single indicator is not suitable for various land uses. The DMI can combine the advantages of MSAVI, albedo and SFI in desertification monitoring and is more consistent with the real desertification levels. (2) Compared with quantile grading and susceptibility index segmentation methods, Jenks Natural Breaks has the smallest relative exponential entropy (2.124), with an overall classification accuracy of 88.21%, indicating that Jenks Natural Breaks is an optimal method for desertification monitoring. (3) Although approximately 1708.60 km² of desertification areas have improved from 2005 to 2020, accounting for 44.23% of the whole area, the remaining areas are still under fluctuating or degraded conditions. This shows that the local government has made some progress in desertification protection, but the areas under fluctuating or degraded conditions still require protection or management.     

DETECTING DESERTIFICATION PROCESSES USING TM AND ETM+ DATA, NORTH OF ISFAHAN, IRAN

 Aims Desertification results in ecological and biological diminution of the earth, and can happen naturally or cause by anthropogenic activities. This process especially affects arid and semi-arid regions, such as the Isfahan region, where the spread of desertification is reaching critical proportions. The aim of this study is to use remotely sensed data to review the trend of desertification in the northern of Isfahan, Iran. Methods Multi-temporal images were employed to evaluate the trend of desertification, specifically the TM and ETM+ data of September, 1990 and September, 2001. Geometric and radiometric corrections were applied to each image prior to image processing and supervised classification, and vegetation indices were applied to produce a land use map of each image in nine classes. The land use classification s in the two map images were compared and changes between land use classes were detected over the 11 year period using a fuzzy and post-classification technique. Important findings The maps and their comparison with false color composite images showed the differences efficiently. With the fuzzy and post-classification method the land use changes were sited on the map. Fuzzy confirmed 53% changed area and 47% unchanged areas in the study region. The results verify the desertification expansion in the study areas. Because of poor land management, agricultural lands converted to desert and abandoned areas, and some marginal pasture lands had to be changed to agricultural land which are desertification spreading according to United Nations Conference on Desertification (UNCOD). Also farmland and pastures have been converted to urban and industrial areas, and the rangelands have been spoiled due to opencast mine excavations. With the mine margins eroding as well as their debris accumulating on the pasture lands, desertification has become worse. Three areas of less-elevated mountains have remained unchanged. This study confirmed that the anthropogenic activities accelerated the desertification process and severely endangered the remaining areas.     

荒漠化治理中生态系统、社会经济系统协调发展问题探析——以中国北方半干旱荒漠区沙漠化防治为例

全球变暖导致的区域干旱使得干旱区水资源日益匮乏,而迅速增长的人口和社会经济发展进一步加剧水资源危机,使得有限的水资源成为全球沙漠化防治瓶颈,严重制约了沙化土地治理进程,影响了联合国"土地退化总面积零增长"目标的实现,也影响了中国社会经济的可持续和协调发展。传统的沙化土地治理生物措施重视植被盖度增加,忽视生态系统其他要素,如土壤水分、养分等与植被的相互关系,导致一些治理措施相对简单,生态系统不能协调发展。而沙化土地治理的物理措施和化学措施由于忽视了沙区社会和经济效益,其可持续性也受到科学家质疑。近期获批的国家重点研发计划项目"中国北方半干旱荒漠区沙漠化防治关键技术与示范"(2016YFC0500900)拟针对此问题开展研究,以沙化土地稳定恢复为首要目标,在认识半干旱荒漠区沙化土地正/逆过程演变机制和荒漠生态系统稳定性的基础上,研究沙化土地稳定恢复的生态阈值;以毛乌素沙地、库布齐沙漠东部、科尔沁沙地西部和呼伦贝尔沙地为典型区,针对不同沙化土地特点,研发防沙治沙关键技术,开展模式优化和试验示范;在防沙治沙模式与工程效益评估基础上,集成产业化技术体系,为国家防沙治沙工程建设提供理论基础与技术支撑。     

基于耦合协调度的黄土高原地区NDVI与降水关系的变异诊断

植被是地表生态系统的重要"指示器",在能量交换、水循环、碳循环、生物地球化学循环和维持中发挥着重要作用,降水是影响植被变化的主要气候因子,研究两者之间的作用关系具有重要的意义和价值。利用Mann-Kendall趋势检验法和Hust指数分析了黄土高原地区归一化植被指数（NDVI）的变化趋势,使用相对发展率（RDR）指数和重心转移模型分析了NDVI变化的时空差异,并构建了基于耦合协调度理论和Pettitt检验方法的NDVI与降水关系的变异诊断方法,识别了黄土高原地区NDVI与降水关系的突变点,探讨了降水对NDVI变化的影响以及造成NDVI与降水关系变化的原因。结果表明：（1）黄土高原地区73.49%面积的NDVI在1998-2017年有呈现显著增加趋势（P<0.05）,大部分地区NDVI在未来依旧呈现增加趋势;（2）黄土高原地区丘陵沟壑区与高原沟壑区的NDVI增加幅度大于黄土高原地区整体的增加幅度,而北部风沙区和农灌区以及黄土高原地区边界区域的NDVI增加滞后于区域整体变化;（3） NDVI与降水耦合协调程度逐年增强,两者关系在2006年发生显著突变（P<0.05）;（4） NDVI呈现显著增加区域降水明显高于不显著变化区域（P<0.05）,降水对NDVI变化存在一定影响,在丘陵沟壑区、高原沟壑区北部和东部河谷及土石山区北部NDVI和降水存在显著正相关关系（P<0.05）,然而黄土高原地区大部分区域的降水并不存在显著变化趋势（P>0.05）,因此造成黄土高原地区NDVI与降水关系在2006年发生显著突变的主要原因应该是人类活动（P<0.05）。研究成果有助于进一步理解黄土高原植被变化与降水的相互作用,为黄土高原生态建设和水土流失治理提供一定的科学支撑。     

基于遥感和GIS的土地利用分类方法及其在土地退化程度分析中的应用——以陕西横山雷龙湾地区为例

基于陕西省横山县雷龙湾地区的遥感ETM＋影像,分别采用最大似然法和光谱角制图分类（SAM）方法进行了该区的土地利用类型分类。其中,光谱角制图分类利用最小噪声分离（MNF）及像元纯净指数（PPI）方法提取研究区的地类终端端元,在此基础上绘制土地利用类型图。最大似然法对水体及耕地的分类精度较高,而其它地类精度稍差,沙地有较大漏分;而基于像元纯净指数的光谱角制图法分类对沙地、水体分类效果较好,对建筑用地和非建筑用地区分度较高,但林地和草地有一定混分。根据研究区反照率影像、NDVI以及湿度图像构造了一个土地退化程度指数模型,并选择一定的系数对研究区的土地退化程度进行了分类,利用GIS软件成图输出。利用光谱角制图分类的纯净像元样本进行比较分析,发现土地退化程度指数与土地利用的相关性较强,表明该方法可以较好地反映当地的土地退化程度情况。     

华北地区2001-2014年植被变化对SPEI气象干旱指数多尺度的响应

近年降水量的减少以及全球气候变暖的影响导致我国华北区域干旱程度加剧,影响植被生长状况,使得区域生态环境恶化。基于华北地区2001-2014年的TRMM及MODIS数据,以归一化植被指数NDVI、净初级生产力NPP、植被状态指数VCI作为植被状况表征指数,以标准化降水蒸散指数SPEI作为气象干旱表征指数,对华北地区近年的气象干旱及植被状况时空变化进行评价,并分析植被对干旱的多尺度响应。结果表明：（1）华北地区干旱在西南部地区呈明显加重趋势,东北部地区干旱状况有所好转;针对不同时间尺度的SPEI表示干旱的变化趋势,得出月份尺度干旱呈现干湿交替特征,选取SPEI时间尺度越长,干旱化趋势越明显;（2）NDVI与NPP所反馈的植被长势空间分布略有差异,总体而言华北地区植被状况大部分地区呈好转趋势,但研究区中部部分地区及部分沿海地区植被状况转差;（3）植被状况指数与SPEI指数在大部分地区呈正相关,NPP与SPEI的相关性强于NDVI与SPEI的相关性,且相关程度在草原地区及中高海拔地区最高,林地对干旱的敏感度最弱;各植被类型在植被生长季的多数月份对SPEI-3响应最明显,且在夏季相关程度最高,夏季及其前期的季尺度干旱更易影响植被生长状况,SPEI-12对植被的影响主要表现为影响植被生长季初期的植被状态。     

基于MODIS数据的中国三种主要土地类型变化的空间特征分析

人类活动使得土地利用和植被覆盖发生了巨大变化,直接影响着全球气候。本研究通过从2000—2013年对中国三种主要土地利用类型的NDVI变化特征进行了分析,结果表明:(1)14年来,中国三种主要土地利用类型NDVI平均值均有增强的趋势。(2)三种主要土地利用类型中除耕地中的水田,林地中的有林地和草地中的高覆盖草地增长速率不显著外,其他土地类型增长速率均显著。(3)三种土地利用类型均以改善面积大于退化面积,耕地中改善面积占总耕地的64.21%,退化的区域占18.50%;林地改善的区域占总林地的54.21%,退化的区域占20.13%;草地改善的区域占55.53%,退化的区域占18.23%。三种土地类型均有所改善且改善明显的区域主要集中在甘肃以南,陕西以北和东北部分地区。     

Current Distribution of Ecosystem Functional Types in Temperate South America

We described, classified, and mapped the functional heterogeneity of temperate South America using the seasonal dynamics of the Normalized Difference Vegetation Index (NDVI) from NOAA/AVHRR satellites for a 10-year period. From the seasonal curves of NDVI, we calculated (a) the annual integral (NDVI-1), used as an estimate of the fraction of photosynthetic active radiation absorbed by the canopy and hence of primary production, (b) the relative annual range of NDVI (RREL), and (c) the date of maximum NDVI (MMAX), both of which were used to capture the seasonality of primary production. NDVI-1 decreased gradually from the northeastern part of the study region (southern Brazil and Uruguay) toward the southwest (Patagonia). High precipitation areas dominated by rangelands had higher NDVI-1 and lower RREL values than neighboring areas dominated by crops. The relative annual range of NDVI was maximum for the northern portion of the Argentine pampas (high cover of summer crops) and the subantarctic forests in southern Chile (high cover of deciduous tree species). More than 25% of the area showed an NDVI peak in November. Around 40% of the area presented the maximum NDVI during summer. The pampas showed areas with sharp differences in the timing of the NDVI peak associated with different agricultural systems. In the southern pampas, NDVI peaked early (October–November); whereas in the northeastern pampas, NDVI peaked in late summer (February). We classified temperate South America into 19 ecosystem functional types (EFT). The methodology used to define EFTs has advantages over traditional approaches for land classification that are based on structural features. First, the NDVI traits used have a clear biological meaning. Second, remote-sensing data are available worldwide. Third, the continuous record of satellite data allows for a dynamic characterization of ecosystems and land-cover changes. Received 6 October 1999; accepted 2 April 2001.     

我国三北地区植被变化的动因分析

地表植被变化是气候变化、人类活动等多种因素共同作的结果。然而,以往的研究要么集中在与气候变化有关的气象因素,要么集中在与人类活动有关的人为因素,鲜有基于长期数据监测下对自然与社会因素之间相互作用的定量评估。因此,气候变化和人为因素对地表植被变化的相互作用并不明确,各个因素对植被变化影响的量化贡献仍然不确定。为了评价生态修复项目对荒漠化防治的效果、以及在土地荒漠化防治中自然与社会因素对我国植被变化的影响、及其复杂的相互作用机理,该研究应用卫星遥感影像资料,通过面板数据混合回归模型大数据分析方法,计算了1983年至2012年气候变化和人类活动对我国北方地区植被变化的贡献率。结果表明,气候变化和人类活动对NDVI变化均有重要作用,其中人类活动对植被覆盖度变化的影响占58.2%—90.4%、气候变化占9.6%—41.8%;不同地区表现出不同的地理分异特征,并存在时滞效应。由此可见,荒漠化防治必须充分考虑不同因素的综合作用和地域特征,才能取得事半功倍的效果。研究结果较好地体现了卫星遥感影像资料在大尺度(省域尺度)下与社会经济统计指标的融合,为进一步中尺度(县域尺度)研究提供了方法借鉴。     

Protected areas buffer the Brazilian semi‐arid biome from climate change

The Caatinga is a botanically unique semi‐arid ecosystem in northeast Brazil whose vegetation is adapted to the periodic droughts that characterize this region. However, recent extreme droughts events caused by anthropogenic climate change have challenged its ecological resilience. Here, we evaluate how deforestation and protection status affect the response of the Caatinga vegetation to drought. Specifically, we compared vegetation responses to drought in natural and deforested areas as well as inside and outside protected areas, using a time‐series of satellite‐derived Normalized Difference Vegetation Index (NDVI) and climatic data for 2008–2013. We observed a strong effect of deforestation and land protection on overall vegetation productivity and in productivity dynamics in response to precipitation. Overall, deforested areas had significantly lower NDVI and delayed greening in response to precipitation. By contrast, strictly protected areas had higher productivity and considerable resilience to low levels of precipitation, when compared to sustainable use or unprotected areas. These results highlight the importance of protected areas in protecting ecosystem processes and native vegetation in the Caatinga against the negative effects of climate change and deforestation. Given the extremely small area of the Caatinga currently under strict protection, the creation of new conservation areas must be a priority to ensure the sustainability of ecological processes and to avoid further desertification.     

盐池县2000-2012年植被变化及其驱动力

荒漠草原区的植被对防治荒漠化、维护生态屏障具有决定性作用,宁夏盐池县作为其典型代表,近13年的植被变化深受气候变化和人类活动的综合影响。基于MODIS NDVI等数据,运用趋势分析、经验模态分解和空间叠置分析等方法,对盐池县2000—2012年的植被动态变化进行研究,结果表明:(1)2000—2012年盐池县NDVI在0.2—0.4之间呈波动上升趋势,上升幅度为0.078/10 a,上升趋势显著;总体来说,植被稳定性低,年际间波动或转换频繁、幅度大;(2)NDVI的波动分量与残余分量方差贡献率各占50%,且NDVI波动呈减弱趋势。促使NDVI波动的主控因子是年降水量,但其影响在减弱;(3)推动NDVI趋势性上升的主要因素是土地利用方式改善和类型变化,但土地利用方式改善对NDVI的贡献远远大于土地利用类型变化对NDVI的贡献。因此,荒漠草原区的生态改善应以保护为主,辅之以必要的生态重建,走以适度开发带动整体保护的道路。     

贵州省后寨河小流域地形因子、人为干扰与石漠化定量研究

为定量研究喀斯特区域地形因子、人为干扰和石漠化之间的关系。基于网格法和实地观测,建立后寨河流域石漠化信息数据库并分析。结果表明:后寨河流域石漠化面积为14.43 km~2,不同利用类型石漠化面积呈以下规律:荒地坡耕地乔木林地耕地灌木林地灌草地草地弃耕地园地乔灌木林地水田经果林地;流域内岩石裸露率和土壤厚度主要受到坡度、坡位和人为干扰的制约,而人为干扰具有主观性,主要在岩石裸露率低、土壤较厚和坡度较缓的区域进行农业生产活动。荒地和弃耕地占据了石漠化面积的32.64%,且存在较大潜在石漠化的风险。回归模型发现人为干扰程度对岩石裸露率(负效应-0.286)和土壤厚度(正效应0.264)的直接效应最大,坡向对岩石裸露率(正效应0.067)和土壤厚度(负效应-0.054)的直接效应最小。认清地形因子、人为干扰和石漠化之间的耦合关系有利于喀斯特小流域石漠化治理。