试用参与式贫富排序法识别高校经济困难学生

采用参与式贫富排序方法来识别高校经济困难学生对象,并实地检测该方法的有效性、适用性和可行性。     

国有林区林业用地经济分类及经营布局调整与重构

林业用地是国有林区可持续发展的物质基础，是国有林区可持续发展能力建设的基本内容。从国有林区林业用地的实际利用状况出发，根据可持续发展的要求对林业用地进行经济分类，并在此基础上对原有经营布局进行调整和重构。     

石灰性土壤钙磷分级测定法研究

笔者探索了石灰性土壤中Ca—P的分级测定方法,使Ca—P总量提取率高于张守敬法的41.3％、苏联的53.5％。相关分析证明,其有效性亦以笔者的方法(r=0.680)为优,从而使该法成为判断石灰性土壤储磷能力的可靠手段,也为土壤肥力的研究和土壤基层分类提出了依据。     

利用遥感进行旺苍县立地分类与评价的研究

本文叙述利用多级遥感技术进行森林立地分类与质量评价。首先采用卫星磁带数据进行图象处理,在图象判读的基础上,提供了旺苍县的立地分区。进而利用航空象片进行立地因子的判读,按影响立地的因子划分立地类型和评价立地质量。由于立地研究是以遥感图象为载体,所以在研究中立地分类与立地制图相结合。本文的最后部分还讨论了立地分类与评价在防护林工程中的应用。试验表明,本方法与常规技术相比,不仅具有速度快,效率高和成本低的特点,而且立地信息丰富,便于生产中应用。     

三维及相关辅助信息在提高图像分类精度中的研究

该文对应用高程、坡向及土壤等辅助信息提高分类精度进行了研究.在GIS支持下，运用GIS的空间分析技术综合研究高程、坡向等辅助信息与植被类型的内在关系,运用模糊数学的基本原理将这种内在关系量化,形成可以反映植被与辅助信息间规律的模糊矩阵，综合应用所得到的模糊矩阵通过后分类法来修正无监、有监分类得到的初分类图像.该研究以贺兰山中段汝箕沟一带为研究对象，成功地应用该方法得到了研究区的植被分类图像.研究表明，三维及相关辅助信息可以有效地提高遥感图像的分类精度.     

新疆盐成土壤系统分类

盐成系列的土壤，是新疆面积大，分布广泛的类型之一，其中一部分历来被视为殖对象和耕地后备土壤资源。对它进一步研究，区分类型，具有多方面的意义。故被列入由中国科学院南京土壤研究所主持开展的中国土壤系统分类研究之中。新疆盐成土性态独特复杂，类型多样，几乎同中国土壤系统分类中所列的类型都能相对应。如干旱正常盐成土和潮湿正常盐成土及分别下属的众多亚类。     

喷射绿化技术及其在水土保持中的应用

喷射绿化技术是一项快速恢复植被和美化环境的先进技术。自20世纪80年代末引入我国后，在高速公路和水电站等工程建设后期地被植物的恢复中得到广泛应用，但在荒漠化防治等领域的研究和应用却较少；该技术在我国应用上已取得一些成绩，得到不断发展，但尚未形成自己完整成套的技术；该技术随着发展，出现了名称混乱的现象。因此，对喷射绿化技术的分类、发展和应用领域进行了探讨，并提出了今后应加强研究的方向。     

Fuzzy k-means classification of topo-climatic data as an aid to forest mapping in the Greater Yellowstone Area, USA

Previous attempts to quantify topographic controls on vegetation have often been frustrated by issues concerning the number of variables of interest and the tendency of classification methods to create discrete classes though species have overlapping property sets (niches). Methods of fuzzy k-means classification have been used to address class overlap in ecological and geographical data but previously their usefulness has been limited when data sets are large or include artefacts that may occur through the derivation of topo-climatic attributes from gridded digital elevation models. This paper presents ways to overcome these limitations using GIS, spatial sampling methods, fuzzy k-means classification, and statistical modelling of the derived stream topology. Using data from a ca. 3600 km² forested site in the Greater Yellowstone Area, we demonstrate the creation of meaningful, spatially coherent topo-climatic classes through a fuzzy k-means classification of topo-climatic data derived from 100 m gridded digital elevation models (DEMs); these classes were successfully extrapolated to adjacent areas covering a total of ca. 10000 km². Independently derived land cover data and middle infrared corrected Landsat TM derived estimates of Normalised Difference Vegetation Index (M_NDVI) at 575 independently sampled sites were used to evaluate the topo-climatic classes and test their extrapolation to the larger area. Relations between topo-climatic classes and land cover were tested by ² analysis which demonstrated strong associations between topo-climatic class and 11 of the 15 cover classes. Relations between M_NDVI and topo-climatic classes proved to be stronger than relations between M_NDVI and the independent cover classes. We conclude that the fuzzy k-means procedure yields sensible and stable topo-climatic classes that can be used for the rapid mapping of large areas. The value of these methods for quantifying topographic controls on biodiversity and the strength of their relations with computed NDVI values warrant further investigation.     

数量化理论I在土地分级中的应用

阐述了数量化理论Ⅰ应用于农业综合开发示范小区土地分级地基本原理,并运用这一理论对一个村级水平的示范小区的土地资源进行了实际分级。结果表明,应用这一方法在微地域上能客观、迅速地对土地质量作出综合评价。