中文摘要：

坡向对垂直带的空间分布有重要的影响作用。长期以来，垂直带坡向数据的质量较低，主要以阴坡和阳坡数据为主，4个坡向和8个坡向的数据非常罕见。数据质量的问题严重阻碍了垂直带坡向效应的定量研究。为了克服这个难题，我们利用GIS、遥感、程序设计等现代信息技术手段提出了山地垂直带坡向信息提取的方法（SAI—IMAB），实现垂直带随坡向分布情况全数字化、定量化地显示和表达。本方法包括以下步骤：1．数据预处理，2．垂直带坡向数据库的构建，3．定量表达，4．图形显示。在Matlab2010b平台下开发绘图函数，根据以下形式来表达和显示垂直带的分布情况，包括：点阵分布模式（PDP）、点阵界限模式（PLP）、曲线带谱模式（CSP）。和传统柱状图的显示方法相比，这些方法具有数据概括程度低、精度高、与现实相似度高的特点。以巴基斯坦Kaghan流域作为试验区，植被图和地形图作为数据源，利用该方法，我们高精度提取出Kaghan地区随坡向变化的山地垂直带谱数据。该方法的提出，有效地提升了山地垂直带的识别精度，提高了垂直带数据的质量，使垂直带分布规律的定量化研究成为可能，有助于更加准确地揭示山地垂直带随坡向变化的规律。

英文摘要：

Slope aspect has an important impact on the distribution of mountain altitudinal belts. For a long time, because of the barrier of surveying instrument as well as the underdevelopment of information technology, the data of altitudinal belts about slope aspect has been with lower quality. Two-aspect data are easily to be acquired, but four- aspect and eight-aspect data are difficult to be found. This condition had been impeding quantitative analysis re- search on the relationship between altitudinal belts and aspect effect seriously until now. In order to conquer this difficult problem, we proposed a Slope Aspect Information Identification of Mountain Altitudinal belts （SAIIMAB） method by the modern techniques of GIS, RS and computers. As a state - of - the - art method, SAIIMAB method is constituted of Preprocessing Part, Vegetation database Part, Graphics Part and Math Expression Part. Scanned vege- tation map of Kaghan valley in Pakistan was digitalized to shape files as the data source of this study. We integrated DEM, Aspect Map, and Vegetation map into one raster layer. Therefore, each raster cell has at least five properties, includes longitude, latitude, elevation, slope aspect and vegetation type, so the information of the whole raster layer can be expressed as a two dimensional table stored in a vegetation spatial database. Furthermore, some plot func- tions were developed on Matlab 2010b to display altitudinal belts in Point-lattice distribution pattern （PDP）, Point- lattice limit pattern （PLP） and Curve Spectra Pattern （CSP）. The altitudinal belts were depicted in separate fig- ures according to the difference of vegetation types. The introduction of point lattice and set theory enriches the de- piction and expression methods of altitudinal belts. Consequential data of altitudinal belts had been extracted by SAIIMAB method, besides, the output graphics of the SAIIMAB displays the real distribution of altitudinal belts more veritably and vividly than ever. The proposal as well as the app