湖南省土地荒漠化和沙化监测布局与监测方法

我省土地荒漠化和沙化监测主要包括3个荒漠化监测站和5个沙化监测站，布设监测样地28个。确定了采集监测区域内气象、土壤、水文、生物等方面的信息和方法。     

荒漠化能量与水平衡监测系统的应用

利用卫星遥感技术进行宏观监测是我国荒漠化监测的重要手段,它具有高效经济的特点。本文阐述了中荷合作项目中荒漠化能量与水平衡监测系统的技术方法及主要应用。     

西藏沙化动态及其原区

西藏自治区是我国沙化最严重的地区之一。2004年调查结果表明，西藏沙化面积为216842．7km^2其中重度以上的沙化面积占总沙化面积的91．53％；沙化类型以戈壁占绝对优势：草地、未利用地是主要的沙化土地利用类型。全区沙化总体上呈恶化趋势，沙化土地面积增加，沙化程度加剧，但拉萨、山南等地沙化土地有所减少。西藏土地沙化变化是受自然因素与人为因素共同作用的结果。     

河北坝上地区可持续发展的创新思路

坝上地区可持续发展应充分考虑我国经济发展的现状和其所处的大北京地区的重要区位,以全球变化为背景,以持续发展理论为先导,大胆更新观念,形成一套创新制度:建设“人控环境”,实施“大范围搞生态重建,小区域搞集约生产”制度;城市化与产业化相结合,采取“鼓励农业人口转化为非农业人口,以产业化带动城市化”的积极的城市化制度;沙漠化防治与治贫治愚相结合,采取“治愚-治沙-产权-受益”制度;确立产权制度和相应利益分配机制,对口支援与生态效益转移收费制度;生物技术与工程技术相结合,制定鼓励科技创新制度。     

东北西部沙地近20年地下水变化动态及其成因分析

本文以奈曼旗为例，分析研究了我国东北西部沙地1979-1997年地下水位时空变化规律及其与降水量和沙漠化的关系。结果表明：（1）沙地多年平均地下水位为2.19m，其中农区为2.85m，牧区1.16m;(2)地下水位是1981-1983年最低为2.49-2.56m,1991-1992年最高为1.90-1.92m，1997年为2.22m，高于1979年的2.41m；（3）该区季节最高水位主要发生于春季（3-5月），发生频率占50.1% ,最低水位主要发生于冬季（12-2月），发生频率为41.2%，平均4月最高为2.07m，10月最低为2.23m;(4)地下水位的年际变化动态和降水量密切相关，但有滞后1-2年的现象；（5）地下水位空间分布上的差异与土地沙漠化及土地利用方式密切相关，沙漠化土地主要用于放牧，由于人为利用少和蒸散少，有利于地下水抬升；（6）由于耕地面积占总土地面积比例低，水浇地和粮食产量的增加尚未对地下水位造成严重影响。     

盐池半荒漠风沙区土地沙漠化发生发展规律的研究

本文耐盐池半荒漠风沙区土地沙漠化发生发展规律进行了探讨，主要分析了在土地沙漠化的过程中土壤和植被的变化过程及其成因。     

景观生态学原理与方法在荒漠化研究中应用的理论分析

荒漠化发生发展的过程实际上是指在自然和人为因素的作用下，生态系统结构遭受破坏、功能过程受阻和演变发生异化的过程，其防治的根本措施是恢复和重建健康的生态系统。所以，景观生态学理念在荒漠化的研究和防治中有着重要的意义。本文从荒漠化与生态系统结构、功能变化、荒漠化与生物多样性、荒漠化生态系统的物质循环和能量流动以及荒漠化生态系统的稳定性等方面论述了景观生态学理念在荒漠化研究中应用的可行性，并重点分析了景观生态学关于景观格局变化的评价指标与荒漠化土地动态变化之间的关系。     

土壤易氧化有机碳与溶解性有机碳对荒漠草地沙漠化过程中土壤碳库变异的表征

以干旱、半干旱地区荒漠草地不同沙漠化阶段土壤为研究对象,研究不同沙漠化阶段土壤易氧化有机碳与溶解性有机碳含量和分配比例变异规律,分析不同沙漠化阶段土壤碳库指数变化,探讨荒漠草地沙漠化过程中土壤易氧化有机碳与溶解性有机碳对土壤碳库的表征作用。结果表明,随着荒漠草地沙漠化程度的加剧,易氧化有机碳含量表现出一定的波动性,但整体呈下降趋势,溶解性有机碳含量呈线性下降。易氧化有机碳和溶解性有机碳分配比例均在荒漠草地达到最大值,在半固定沙地达到最小值。利用易氧化有机碳含量计算的土壤碳库管理指数随荒漠草地沙漠化程度增加表现出先下降后上升趋势,利用溶解性有机碳含量计算的土壤碳库管理指数呈线性下降趋势。易氧化有机碳、溶解性有机碳含量与土壤有机碳均显著正相关,但溶解性有机碳的相关系数略高于易氧化有机碳。通过比较活度敏感指数和碳库管理指数敏感指数发现,荒漠草地逆向演替至固定沙地过程中,易氧化有机碳的各项敏感指数均高于溶解性有机碳。固定沙地演替至流动沙地过程中,溶解性有机碳的各项敏感指数均高于易氧化有机碳,表明易氧化有机碳能够较好地表征荒漠草地沙漠化前期土壤碳库变化,而荒漠草地沙漠化中期和后期利用溶解性有机碳表征效果更好。     

Monitoring desertification processes in Mongolian Plateau using MODIS tasseled cap transformation and TGSI time series

Most remote sensing studies assess the desertification using vegetation monitoring method. But it has the insufficient precision of vegetation monitoring for the limited vegetation cover of the desertification region. Therefore, it offers an alternative approach for the desertification research to assess sand dune and sandy land change using remote sensing in the desertification region. In this study, the indices derived from the well-known tasseled cap transformation(TCT), tasseled cap angle(TCA),disturbance index(DI), process indicator(PI), and topsoil grain size index(TGSI) were integrated to monitor and assess the desertification at the thirteen study sites including sand dunes and sandy lands distributed in the Mongolian Plateau(MP) from 2000 to 2015. A decision tree was used to classify the desertification on a regional scale. The average overall accuracy of 2000, 2005, 2010 and 2015 desertification classification was higher than 90%. Results from this study indicated that integration of the advantages of TCA, DI and TGSI could better assess the desertification. During the last 16 years, Badain Jaran Desert, Tengger Desert, and Ulan Buh Desert showed a relative stabilization. Otindag Sandy Land and the deserts of Khar Nuur, Ereen Nuur, Tsagan Nuur, Khongoryn Els, Hobq, and Mu Us showed a slow increasing of desertification, whereas Bayan Gobi, Horqin and Hulun Buir sandy lands showed a slow decreasing of desertification. Compared with the other 11 sites, the fine sand dunes occupied the majority of the Tengger Desert, and the coarse sandy land occupied the majority of the Horqin Sandy Land. Our findings on a three or four years' periodical fluctuated changes in the desertification may possibly reflect changing precipitation and soil moisture in the MP. Further work to link the TCA, DI,TGSI, and PI values with the desertification characteristics is recommended to set the thresholds and improve the assessment accuracy with field investigation.     

Object‐Based Mapping of Karst Rocky Desertification using a Support Vector Machine

Accurate and cost‐effective mapping of karst rocky desertification (KRD) is still a challenge at the regional and national scale. Visual interpretation has been utilised in the majority of studies, while an automated method based on pixel data has been investigated repeatedly. An object‐based method coupling with support vector machine (SVM) was developed and tested using Enhanced Thematic Mapper Plus (ETM+) images from three selected counties (Liujiang, Changshun and Zhenyuan) with different karst landscapes in SW China. The method supports a strategy of defining a mapping unit. It combined ETM+ images and ancillary data including elevation, slope and Normalized Difference Vegetation Index images. A sequence of scale parameters estimation, image segmentation, training data sampling, SVM parameters tuning and object classification was performed to achieve the mapping. A quantitative and semi‐automated approach was used to estimate scale parameters for segmenting an object at an optimal scale. We calculated the sum of area‐weighted standard deviation (WS), rate of change for WS, local variance (LV) and rate of change for LV at each scale level, and the threshold of the aforementioned index that indicated the optimal segment level and merge level. The KRD classification results had overall accuracies of 85·50, 84·00 and 84·86 per cent for Liujiang, Changshun and Zhenyuan, respectively, and kappa coefficients are up to 0·8062, 0·7917 and 0·8083, respectively. This approach mapped six classes of KRD and offered a visually appealing presentation. Moreover, it proposed a conceptual and size‐variable object from the classification standard of KRD. The results demonstrate that the application of our method provides an efficient approach for the mapping of KRD. Copyright © 2012 John Wiley & Sons, Ltd.