Monitoring sandy desertification of Otindag Sandy Land based on multi-date remote sensing images

Sandy desertification is now the main ecological problem in the Otindag Sandy Land. In order to reveal the process of land degradation, especially the latest situation of sandy desertification, a method integrating remote sensing, Geographic Information System (GIS) and field survey was employed to build a sandy desertification dataset for analysis. Remote sensing images included the Landsat Thematic Mapper (TM) image in 1987, the Enhanced Thematic Mapper Plus (ETM⁺) image in 2000, and the image with the Charge-Coupled Device Camera (CCD) on the China-Brazil Earth Resources Satellite (CBERS) in 2006. Five land-cover classes, including active sand dunes, fixed sand dunes, semi-fixed sand dunes, inter-dune grassland and wetlands, were identified. Results showed that the Otindag Sandy Land has been suffering sandy desertification since 1987 with 2 different desertified stages. The first stage from 1987 to 2000 was a severe sandy desertification period, characterized by the fixed sand dunes decreasing at a high speed, and the semi-fixed and active sand dunes increasing remarkably. The second stage spanned from 2000 to 2006 and the sandy desertification was weakened greatly. Although a large area of fixed sand dunes were transformed to other types, fixed sand dunes were still the dominant type in the Ointdag region at 2006. Spatial change detection based on active sand dunes showed that the expansion area was much larger than the reversion area in the past two decades, and that several active sand belts had been formed, suggesting that sandy desertification controlling of the Otindag Sandy Land will be a long-term task.     

Monitoring sandy desertification of Otindag Sandy Land based on multi-date remote sensing images

Sandy desertification is now the main ecological problem in the Otindag Sandy Land. In order to reveal the process of land degradation, especially the latest situation of sandy desertification, a method integrating remote sensing, Geographic Information System (GIS) and field survey was employed to build a sandy desertification dataset for analysis. Remote sensing images included the Landsat Thematic Mapper (TM) image in 1987, the Enhanced Thematic Mapper Plus (ETM⁺) image in 2000, and the image with the Charge-Coupled Device Camera (CCD) on the China-Brazil Earth Resources Satellite (CBERS) in 2006. Five land-cover classes, including active sand dunes, fixed sand dunes, semi-fixed sand dunes, inter-dune grassland and wetlands, were identified. Results showed that the Otindag Sandy Land has been suffering sandy desertification since 1987 with 2 different desertified stages. The first stage from 1987 to 2000 was a severe sandy desertification period, characterized by the fixed sand dunes decreasing at a high speed, and the semi-fixed and active sand dunes increasing remarkably. The second stage spanned from 2000 to 2006 and the sandy desertification was weakened greatly. Although a large area of fixed sand dunes were transformed to other types, fixed sand dunes were still the dominant type in the Ointdag region at 2006. Spatial change detection based on active sand dunes showed that the expansion area was much larger than the reversion area in the past two decades, and that several active sand belts had been formed, suggesting that sandy desertification controlling of the Otindag Sandy Land will be a long-term task.     

科尔沁沙地沙漠化土地恢复面临的挑战

对科尔沁沙地近50年来沙漠化土地面积、水资源可利用性、土地利用与草地植物生产力的变化进行了分析.结果发现：科尔沁沙地的土地沙漠化在经历了20世纪50—80年代中期的快速发展之后,80年代后期发生了逆转.在过去的50年中,西辽河径流量持续减小,1999年在西辽河中游的内蒙古自治区通辽市段断流;近20年来,位于科尔沁沙地腹地的西湖水位下降近10 m, 2001年干涸.科尔沁沙地草场的地上生物量由1937年的520 g·m^-2下降到2005年的197 g·m^-2.产生这种结果的主要原因是土地利用方式的变化,即基于灌溉的沙漠化治理规模的扩大和灌溉农田面积的增加,导致用水量增加.这也是科尔沁沙地实现土地沙漠化持续逆转面临的严峻挑战.     

基于多时相遥感影像的浑善达克沙地沙漠化监测

沙漠化是浑善达克沙地面临的主要环境问题.为了揭示该地区沙漠化过程,特别是其最新状态,利用1987年和2000年的Landsat TM/ETM 及2006年的中巴资源卫星CCD数据,在地面考察资料及地理信息系统(GIS)的支持下,提取了固定沙地、半固定沙地、流动沙地、丘间草原及湿地5种地表覆被类型,建立了浑善达克沙地沙漠化数据库.结果表明浑善达克沙地在过去20a里发生了沙漠化,但是可分为两个阶段.第一阶段从1987年到2000年,为沙漠化快速发展期,固定沙地面积显著减少,而半固定沙地和流动沙地则明显增加;第二阶段从2000年到2006年,为沙漠化缓减期.尽管发生了沙漠化,但固定沙地仍然是浑善达克沙地面积最大的类型.针对流动沙地的空间变化检测表明在过去20a里沙地恶化的面积远远大于逆转的面积,并且已经形成了几条流动沙带,这意味着浑善达克沙地沙漠化的遏制是一个长期的过程.     

基于RS和GIS的玛曲高原土地沙漠化时空演变研究

基于RS和GIS空间分析技术,以玛曲高原多期Landsat遥感数据为主要信息源,监测分析了1977—2014年玛曲高原沙漠化土地的时空演变规律。结果表明:近40年来玛曲高原的土地沙漠化经历了迅速发展—缓慢发展—急速逆转—缓慢逆转—快速逆转的变化过程。1977—1995年玛曲高原沙漠化处于快速扩张阶段,年均扩张速率为3.01%;1995—2014年沙漠化扩张趋势出现逆转,年均逆转速率为4.14%。沙漠化土地的发展和逆转区域主要分布在东北部欧拉秀玛乡和尼玛乡黄河沿岸、东南部采日玛乡和曼日玛乡沼泽区、西南部齐哈玛乡和中部阿万仓乡黄河支流两岸。玛曲高原沙漠化土地的发展和逆转过程并非逐级递增或递减,而是在15—20年内交替出现,不同等级沙漠化土地之间的转移也存在明显的跃变。从整体来看,玛曲高原土地沙漠化呈现逆转趋势,区域生态环境得到明显改善。     

黄河源区沙漠化及其景观格局的变化

本研究以1975年的MSS数据、1990年和2005年的TM数据、以及2000年的ETM数据为数据源,通过遥感（RS）与地理信息系统（GIS）技术,获得了黄河源区在1975－2005年间沙漠化的发展特征,并采用景观指数运算软件（FRAGSTATS3.3）对黄河源区沙漠化土地的景观格局变化进行了分析。研究发现：在1975－1990年间,黄河源区的沙漠化土地面积大幅增加;在1990－2000年间,沙漠化土地面积保持稳定;在2000－2005年间,沙漠化土地面积出现了小幅度的减小趋势。黄河源区沙漠化土地的景观格局变化显著,在1975－1990年间,沙漠化土地发生了严重的破碎化;在1990－2000年间,沙漠化土地出现了连片的现象,从而使得沙漠化土地的破碎度有所下降,景观多样性降低;在2000－2005年间,沙漠化土地破碎度的增加,斑块形状趋于复杂。     

石羊河中游沙漠化逆转过程土壤种子库的动态变化

在石羊河中游,应用空间代替时间的方法,选择流动沙丘以及封育恢复5a、15a和25a的沙漠化逆转过程序列,研究了沙漠化逆转过程土壤种子库的变化特征。结果表明:石羊河中游沙漠化土地土壤种子库由4科12种植物组成,种子库主要分布于表层0-5cm。在沙漠化逆转过程中,土壤种子库物种数趋于增加,物种组成以1年生草本植物占优势逐渐向多年生草本植物和半灌木植物转变;种子库密度、表层土壤种子比例、物种多样性指数、与地上植被的相似性呈现先增大后降低趋势;沙漠化土地生态恢复间隔的时间越长,土壤种子库间的相似性程度越低;沙漠化土地与地带性植被区种子库的相似性逐渐增大,但是恢复25a沙漠化土地也仅达到0.36。研究认为,沙漠化逆转过程也是沙漠化土地土壤种子库向地带性植被土壤种子库演变的过程,而且是一个十分缓慢的过程,该研究有助于丰富干旱区土壤种子库的理论和指导干旱内陆河流域沙漠化土地的生态恢复实践。     

Impact of land use intensity on sandy desertification: An evidence from Horqin Sandy Land,China

It has been widely accepted that high land use intensity contributes to sandy desertification in Northern China. However, it is surprising that it is even not easy to find an explicit definition and proper indicator for the term “land use intensity” in the sandy desertification related literatures. To better understand the association between sandy desertification and its driving factors, especially in the context of the synergistic roles of both climatic and anthropogenic variables, an indicator for land use intensity was developed in this paper for quantifying the relative role of land use output on different kinds of vegetation cover. The results indicated land use intensity increased rapidly from 1980 to 1995, obviously decreased from 1995 to 2000, and increased slowly after 2000 as a result of the continued increase of socioeconomic pressures and the fluctuating changes in vegetative cover.An ARDL model was established and applied to analyze the correlation between the area of bare sand land and land use intensity with the influence of annual precipitation in temporal dimension. The area of bare sand land was significantly affected by land use intensity in the long run. However, in the short run, the area of bare sand land was mainly impacted by the auto-correlation effect of itself in temporal dimension and by the annual precipitation. The improvement of the sand dunes obviously reduced the risk of sandy desertification under the condition of specific land use intensity.Before analyzing the correlation between land use intensity and sandy desertification, specific skills were applied to improve the model, including data interpolation and regression verification, since there would be regression biases resulting from the acquisition and processing of time-series data of different sources. Results showed that the area of bare sand land (S_t)and the land use intensity (LI_t) were time-independent. Lag terms of these two variables were added to improve original model.Changes in socioeconomic pressures and ecological restoration projects had obvious influences on land use intensity. Along with the steady increase of socioecological pressures on land and the changes in vegetative cover resulting from various ecological protection strategies and ecological restoration projects, shifts in land use intensity followed a different trend with the population and the social-economic demands. Nonetheless, the continuous increase of socioeconomic demands will increase land use intensity in the long run, so that the risk of sandy desertification remains high.     

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...     

科尔沁沙地农田沙漠化演变中土壤颗粒分形特征

研究了科尔沁沙地农田沙漠化过程中土壤的粗粒化和养分的贫瘠化特征 ,土壤颗粒分形维数的变化特征 ,以及分形维数与土壤性状的关系。结果表明 :土壤沙粒含量越高 ,土壤分形维数越低 ,表征农田沙漠化程度越高 ;土壤颗粒分形维数与土壤有机 C、全 N、粘粉粒含量之间存在显著的线性关系。说明分形维数能很好地表征农田沙漠化演变中土壤结构和养分状况以及沙漠化的程度 ,可作为评价土壤沙漠化演变的一项综合性定量指标。     

Effectiveness of sand-fixing measures on desert land restoration in Kerqin Sandy Land,northern China

In the semi-arid Kerqin Sandy Land of north China, land desertification and frequent sand storms in the spring strongly affect the growth of grassland vegetation and crops, and give rise to large reductions in yield as a result of wind erosion and sand dune movement. To bring desertification under control and reduce its influence on grassland and farmlands, many measures have been developed and implemented for stabilizing mobile sand dunes and restoring desertified grasslands. This study was conducted from 1996 to 2003 to evaluate the effectiveness of desert land restoration after implementation of sand-fixing measures. The results showed that construction of straw checkerboards and planting of shrub seedlings significantly enhances topsoil development on the dune surface, increasing silt and clay content and facilitating accumulation of soil carbon and total N, as well as accelerating an increase in plant diversity, vegetation cover and plant density. These findings suggest that using straw checkerboards and planting shrubs are successful methods for mobile sand dune stabilization and desertified grassland restoration in semiarid regions. The mechanism creating these changes is a reduction in wind erosion and improvement of the soil environment for plants. In addition, our results showed that construction of straw checkerboards was slightly more effective in vegetation and soil restoration in comparison with planting shrub seedlings, especially at the primary stage.     

科尔沁沙地荒漠化及生态恢复研究展望

评述了科尔沁沙地荒漠化及其生态恢复的研究,从科学研究动态和生态环境退化以及恢复研究的现实需要两方面论述了科尔沁沙地荒漠化与生态恢复研究的若干核心问题;植被过程研究,生态水文过程研究,景观过程研究,科尔沁沙地区域环境评估和预测与生态恢复研究。     

黔中喀斯特坡地浅层裂隙土壤机械组成对降雨的响应

运用野外取样调查结合室内吸管法,分析黔中喀斯特坡地不同土地利用类型浅层裂隙土壤机械组成随降雨的变化特征,以期为该区地下土壤漏失研究提供理论依据和技术支撑.结果表明: 黔中喀斯特坡地浅层裂隙土壤粒径含量总体以粉粒为主,约占57％.在不同降雨量的作用下,坡耕地裂隙土壤颗粒含量变化整体表现为细砂粒含量的减少和粉粒、黏粒含量的增大.草地裂隙土壤颗粒的变化主要是细砂粒含量的减少和黏粒含量的增加.乔木林地和灌木林地裂隙土壤颗粒的变化不规律.降雨量与土壤砂粒含量变化之间存在正相关关系.随着土层深度的增加,各土地利用类型的裂隙对粉粒和极粗砂粒含量的变化有一定影响,其中,粉粒含量随土层深度的增加而减少.     

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.     

贵州北盘江不同强度石漠化区木本植物多样性及生态功能群研究

该研究通过典型群落抽样和聚类分析方法,分析贵州北盘江不同石漠化强度等级的木本植物多样性变化特征,以明确不同石漠化强度等级上的适应性功能群树种组成。结果表明:(1)随着石漠化强度的增大,木本植物的科、属、种数皆呈下降趋势,适生树种数减少;落叶型植物种类相对增加,常绿型植物种类相对减少;矮、小高位芽植物的适应种类相对增加,中、高位芽植物的适应种类相对减少。(2)欧氏距离为6.5时,将46种优势种划分为8个功能群,其中,轻度石漠化型有3个功能群共21个树种;中度石漠化型有3个功能群共14个树种;强度石漠化型有2个功能群共10个树种。     

Land cover change of arid environment in Tunisia based on analysis of Landsat images

The impact of Land use/land cover (LULC) change was assessed through monitoring the distribution of ecological indicators and tracking the aeolian deposits, which provides valuable information on desertification and climate change in Tunisian arid regions. This study was conducted in Oum Zessar area, in southeastern Tunisia. Both visual interpretation and automated classification approach were developed to extract sand features using Landsat images for 2000, 2008 and 2014. The automated classification includes a decision tree classifier (DT) and an unsupervised classification applied to the principal components extracted from Knepper ratios composite. The validation of the classification methods showed that the DT had an overall accuracy over 84%. The results of the change detection have shown an increase in the classes of Agriculture behind tabia by 10.68%, the rangelands and croplands by 24.37% and the mountain rangelands by 14.93%, and a decrease in the classes of Agriculture behind jessour by 33.65%, sand encroachments by 12.93% and halophyte rangelands by 3.4%, respectively. These resulting maps seem to be the suitable decision-support tools for management of land use in arid regions of Tunisia, in particular, for land degradation assessment and water and soil conservation.     

内蒙古奈曼旗农牧交错区土地利用/覆被变化的区域分异

基于内蒙古奈曼旗1975、1985、1995和2005年4期遥感影像,运用土地利用动态度、土地利用相对变化率对研究区土地利用动态变化的区域分异进行了分析,并选取多度和重要值分析了研究区土地利用/覆被变化的空间分布特征.结果表明：1975—2005年间,研究区土地利用/覆被类型趋于多样化,年变化率较大,区域分异显著.研究区北部冲积平原区以林地面积的大幅增加和沙地面积的显著减少为主要特点,其草地和沙地的变化速度最大,居民地的变化速度最小,沙地转化为耕地和沙地转化为林地这两种变化形式在该区的分布最广泛;中部沙区以沙地分布为主,各土地利用类型的变化相对较小,以耕地和沙地的互相转化为该区的主要变化形式;南部黄土区以耕地面积占绝对优势,且变化速度最小,草地和沙地的变化速度最大,该区以草地转化为耕地和草地转化为林地为主要变化形式.自然因素决定了研究区各区域土地利用结构的主体特征,人为因素决定了区域内各土地利用类型的动态变化趋势.     

沙质草地生境中大型土壤动物对土地沙漠化的响应

沙质草地沙漠化过程中土壤动物群落结构变化是沙漠化生物过程中的一个重要方面,对于掌握沙漠化过程中生物退化规律和提出合理沙漠化防治对策具有重要指导作用。选取处于不同沙漠化阶段的流动沙地、半流动沙地、半固定沙地、固定沙地和丘间低地5种生境类型,采用手拣法对其大型土壤动物群落进行了调查。共获得36个动物类群,属于8目32科,优势类群为蚁科,常见类群有22个类群,两个类群的个体数共占群落个体总数的93.33%;稀有类群有13个类群,其个体数占群落个体总数的6.67%。结果显示,丘间低地、固定沙地、半固定沙地和半流动沙地大型土壤动物群落个体数量、类群数和多样性显著高于流动沙地(P<0.05);固定沙地大型土壤动物生物量显著高于其它生境类型(P<0.05);沙质草地严重沙漠化显著地影响大型土壤动物多样性及其生物量。并且,不同土壤动物类群个体对不同沙漠化阶段生境的适应性存在一定差异,产生了不同的响应模式。土壤有机碳和酸碱度以及土壤含水量差异是影响大型土壤动物类群分布与生长的主要因素。研究表明,固定沙地是大型土壤动物的适宜沙地生境,具有较多的个体数量和较高的生物量;丘间低地、半固定沙地、半固定沙地和流动沙地影响大型土壤动物存活,其个体数量和生物量较低。     

土壤有机碳动态:风蚀效应

土壤风蚀是引起土壤退化最广泛的形式和原因之一。土壤风蚀对土壤碳动态的影响机制一方面是土壤风蚀引起土壤退化使土壤生产力下降,输入土壤的碳数量减少;另一方面是富含有机碳的细粒物质直接移出系统。风蚀土壤碳的去向包括:(1)就近沉积,(2)沉积于水渠和河流,输入水体;(3)以粉尘形式运移,在远离风蚀区的地域沉积;(4)氧化释放至大气。风蚀引起土壤碳的迁移和沉积不仅导致土壤有机碳在地域间的再分布,使土壤性状的空间异质性增加,也显著改变了土壤系统中碳矿化的生物学过程。土壤有机碳的保持可以促进团聚体的形成,使土壤物理稳定性增加,减缓风蚀。对易风蚀土地进行退耕还林还草、实行保护性耕作等措施可以有效增加土壤碳的固存。     

基于SNIC-CNN-SVM模型的京津风沙源二期工程区土地利用/土地覆盖遥感识别研究

稀疏植被覆盖(草地、沙地、戈壁)演变能够直接表征区域生态环境和人类活动的动态影响变化。但由于大尺度稀疏植被区一般都具有地理跨度大,景观结构复杂多样,破碎化程度高,现有地表覆盖分类产品针对性不足等问题,使得该区域内林草沙的遥感提取难度较大,精度普遍偏低,直接制约生态效应评价模型的应用效果。因此,以典型大尺度稀疏植被区——京津风沙源治理二期工程区为研究区,研建了SNIC-CNN-SVM(SCS)模型,实现了大尺度稀疏植被区林草沙典型要素的信息自动提取和主要土地利用/土地覆盖类型识别。研究结果表明：1)引入惩罚性机制优化后的SNIC分割算法,有效提升了稀疏植被区与沙地区的边界区分度,有助于分类精度的提升;2)基于改进SNIC-CNN-SVM模型方案的研究区总体分类精度达89.41%,较优化前提高了11.17%,特别是乔、灌、草、沙地和戈壁的分类识别精度显著提升,表明该优化方案在以研究区为代表的稀疏植被区域分类中具有较好的应用效果和推广价值;3)分类结果显示,2020年工程区草地面积最大,占到了一半以上(51.52%),沙地占比11.96%,稀疏植被覆盖(草地、沙地、戈壁)区域占比68.68%...