Assessing and Monitoring the Health of Western Rangeland Watersheds

The most important function of watersheds in the western U.S. is the capacity to retain soil and water, thereby providing stability in hydrologic head and minimizing stream sediment loads. Long-term soil and water retention varies directly with vegetation cover. Data on ground cover and plant species composition were collected from 129 sites in the Rio Grande drainage of south-central New Mexico. This area was previously assessed by classification of Advanced Very High Resolution Radiometry (AVHRR) imagery. The classification of irreversibly degraded sites failed to identify most of the severely degraded sites based on size of bare patches and 35% of the sites classified as degraded were healthy based on mean bare patch size and vegetation cover. Previous research showed that an index of unvegetated soil (bare patch size and percent of ground without vegetative cover) was the most robust indicator of the soil and water retention function. Although the regression of mean bare patch size on percent bare ground was significant (p < 0.001), percent bare ground accounted for only 11% of the variability in bare patch size. Therefore bare patch size cannot be estimated from data on percent bare ground derived from remote sensing. At sites with less than 25% grass cover, and on sites with more than 15% shrub cover, there were significant relationships between percent bare soil and mean bare patch size (p < 0.05). Several other indicators of ecosystem health were related to mean bare patch size: perennial plant species richness (r = 0.6, p < 0.0001), percent cover of increaser species (r = 0.5, p < 0.0001) and percent cover of forage useable by livestock (r = 0.62, p < 0.0001). There was no relationship between bare patch size and cover of species that are toxic to livestock. In order to assess the ability of western rangeland watersheds to retain soil and water using remote sensing, it will be necessary to detect and estimate sizes of bare patches ranging between at least 0.5 m in diameter to several meters in diameter.     

洪泽湖水域的环境演变遥感分析

针对传统水质监测的定点、定剖面采样分析时间及空间的局限性，为对湖泊水质进行全面系统的分析，在前人研究工作的基础上，建立了一种水域水质状况图像识别的主成分监督分类方法，通过对洪泽湖湖区的1991年12月15日和2000年1月7日，两个时相TM遥感图像数据，分别进行主成分变换，并依据不同类型水体的光学特性，分析各主成分图像的构成及其环境意义。研究表明：洪泽湖湖区的水质分布，具有从西向东，从北向南由清洁水（优）向一般水依次递减、逐年下降的特征。其清洁水体主要分布于洪泽湖西部的溧河洼、临淮头、西北部的安河洼和成子湖的北部。从1991--2000年，洪泽湖入湖的工业废水及生活污水量有所减少，湖水受污染程度明显减轻，相对“八五”期间水质污染日益加重的现象，“九五”以后水质逐渐改善。将其分类结果与所收集的洪泽湖历年水质资料对比分析表明：主成分监督分类结果与环境要素吻合较好，且基本反映了其水质环境的变化趋势。     

基于TRMM降尺度和MODIS数据的综合干旱监测模型构建

京津冀地区是我国优质冬小麦的主产区之一,但在全球气候变暖影响下,该地区干旱灾害频发,因此准确监测京津冀地区旱情既能为区域农业生产提供科学指导,又起到保障国家粮食安全等重大战略作用。综合考虑干旱发生过程中大气降水—植被生长—土壤水分盈亏等致旱因子,首先利用GWR（Geographically Weighted Regression）模型对TRMM（Tropical Rainfall Measuring Mission）3B43数据进行降尺度处理,得到1 km分辨率的降水状态参数（Precipitation Condition Index,PCI）;再结合MODIS（Moderate-Resolution Imaging Spectroradiometer）数据,得到植被状态指数（Vegetation Condition Index,VCI）、温度状态指数（Temperature Condition Index,TCI）,最后基于多元回归模型构建综合干旱指数（Comprehensive Drought Index,CDI）,以实现对京津冀地区干旱时空监测评价。结果表明：（1）基于GWR模型与占比系数法得到的1 km空间分辨率TRMM年数据、月尺度数据,不仅在空间分辨率上相比原始TRMM数据得到很大的提升,并且数据精度也通过了检验,表明降尺度分析提高了TRMM数据对研究区降水时空特征的描述能力;（2）监测模型结果与京津冀地区所经历的干旱历程等实际旱情基本一致,并且CDI指数与标准化降水指数（Standardized Precipitation Index,SPI）做相关分析,其相关系数R在0.45~0.85之间,与作物受旱面积做相关分析,相关系数R介于在-0.81~-0.86之间,与作物标准化单产进行相关分析,其相关系数R均大于0.6,并且均通过P<0.05的显著性检验,表明本文所构建的综合干旱监测模型在京津冀地区是适用的。     

基于遥感技术的圩田时空特征分析——以皖东南及其相邻地域为例

利用陆地卫星(Landsat TM)影像与地理信息技术，结合历史地理学对皖东南及邻域圩田时空特征进行研究，发现该区圩田在空间上具有不同的图型结构特征，在时间上圩田开发具有与区域环境变化相关联的强烈阶段性特征。不同图型结构圩田具有不同功能：田字型图型结构圩田具有防御、灌溉、交通综合功能；多边形图型结构圩田具有空间扩展功能；羽状水网图型结构圩田具有对洪水的良好缓冲保护功能；直条块状图型结构圩田具有机械化作业和集约化灌溉功能。通过对圩田时代—面积进行统计分析，发现本区圩田修筑面积具有阶段性特点，形成三国、宋、近现代的3个高峰时期。本区圩田开发的主要驱动因素：①芜湖古聚落军事功能的突出与增强是实现本区开发第一次飞跃的原动力；②西晋末年开始的北方人口向南方持续迁移为本区的第二次飞跃奠定必要的基础；③宋代农业经济技术的大发展实现本区第二次飞跃；④现代社会经济技术发展促成本区的第三次飞跃。     

卫星遥感技术在违法开工项目监测识别系统中的应用实例

建设项目从审批到验收,时间跨度比较长,各级环境保护部门每年审批的项目数量众多,靠传统管理手段跟踪项目建设情况比较困难,建设项目全过程监管工作还未有效开展起来,有些建设项目的重大变更到验收时才被发现,严重影响环境影响评价制度的执行效果。通过应用遥感技术,并以环评基础数据库中的相关辅助评估系统和大量数据为支撑,建立建设项目动态监管系统,达到建设项目动态监测和管理的效果。实现从单一行政手段到综合应用行政、技术手段转变来进行建设项目环评管理。     

烟花爆竹生产企业应建立远程监控系统

通过对河南省烟花爆竹生产企业一段时间内生产安全事故的分析,认为违章操作是已取得安全生产许可证企业当前安全生产中最主要的危险。进一步分析认为,违章操作产生的原因在于生产企业缺乏有效的监督管理。结合交通行业的成功经验,论述了烟花爆竹企业引入远程监控系统的必要性和可行性,并给出了具体的实施方案:企业端硬件投资约10 000元,再架设宽带网络或专用通信线路,就能实现异地远程监督。安全生产许可证制度加上远程监控系统,对烟花爆竹生产企业实现安全生产将起到积极的推动作用。     

Application of Remote Sensing and GIS in the Management of Mangrove Forests Within and Adjacent to Kiunga Marine Protected Area, Lamu, Kenya

The status of mangroves within and adjacent to Kiunga Marine Protected Area (MPA) were assessed by means of aerial photographs and intensive ground truthing. Vegetation maps (1 : 25,000) were produced on GIS environment making it possible to store, retrieve and analyze various types of information very quickly. The maps together with the digitized information provide important tools to the management of mangroves of Kiunga MPA since various proposed treatments can now be entered and summarized thus providing useful overviews for planning, implementation and monitoring.The present inventory revealed that the existing mangrove forests within and adjacent to Kiunga MPA have a net standing volume of 2,354,004.85 m³ in 16,035.94 ha. There are eight species of mangrove trees, of which Rhizophora mucronata and Ceriops tagal are dominant. The standing volume ranges between 6.85 to 710.0 m³ ha^–1 for stem with diameter above 5.0 cm. The average volume of the entire study area was 145.88 m³ ha^–1, which corresponds to a stocking rate of 1736 stems per ha. Given its high potential productivity and regeneration, mangroves within and adjacent to Kiunga MPA have excellent prospects for sustainable exploitation.     

遥感资料在分析城市布局结构中的应用

本文介绍了应用彩红外航片，黑白航片分析呼和浩特市城市居民区、工业区、商业贸易区布局结构的技术。     

替代能源措施对区域土地覆盖和土壤侵蚀的影响

以三峡地区的乐天溪流域为例，利用多时相Landsat TM/ETM影像、文献和野外调查资料研究了替代能源对流域土地利用和土壤侵蚀的影响。通过几年替代能源措施实施，乐天溪流域林草覆盖率由1997年的80.6%增加到2002年的83.2%；不仅林草覆盖率增长，而且质量也有较大提高，覆盖度较高的林地和灌丛面积增幅达18.1%和9.1%，相反疏林面积减少37.9%。强度、中度和轻度侵蚀面积分别减少了4.6 km2、26.4 km2和11.5 km2；流域的土壤侵蚀总量由507 259t减至371 592 t，减少26.8%；流域的平均侵蚀模数由1 241 t/km2减至909 t/km2。     

Vegetation monitoring using diferent scale of remote sensing data

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