An ASTER image covering the south Chocolate Mountains area, California, U.S.A. was evaluated for gold-related lithologic mapping and alteration mineral detection. A supervised classifier was first applied to the 14-channel ASTER radiance data to map lithologies related to gold deposits. Subsequently, four alteration indices were extracted from the six SWIR channels and transformed to delineate alteration zones using a PCA transformed mineralogic indices approach. Finally, a subpixel unmixing algorithm, the constrained energy minimization (CEM) technique was used to detect significant alteration minerals using the ASTER VNIR and SWIR surface reflectance data and reference spectra from the ASTER spectral library. The classification results show that the ASTER data were capable of mapping flood basalt, quartz-biotite gneiss, muscovite schist, granitic, volcanic, and metasedimentary rock units. The ASTER-derived rock units show excellent correlation with those on the reference geologic map. The overall classification accuracy is 82% and the Kappa coefficient 0.76. A group of gneisses, locally the most favorable host rocks of gold deposits, were mapped with the ASTER data with a Producer's accuracy of 86%, and more importantly were also mapped in some areas that were not shown on the field geologic map. Four alteration minerals: alunite, kaolinite, muscovite and montmorillonite were detected by subpixel unmixing analysis of the ASTER reflectance data. This study compared different methods for extracting mineralogic information from ASTER data, compared the remotely derived maps to the mapped field geology, and used the ASTER data to map minerals and lithologies related to gold exploration.

An empirical comparison of the EO-1 Hyperion, EOS ASTER, and Landsat ETM sensors was performed to examine the utility of these three sensors for gold-associated lithologic mapping in the southeastern Chocolate Mountains area, California. Three images were evaluated with respect to three aspects: classification accuracy, matched filtering score index and separability of the five significant rock types in the study area. The results show that the classifications from Hyperion and ASTER data are mostly similar with an overall accuracy of over 85 percent and kappa coefficient 0.81. Due to the presence of more SWIR and thermal bands, the Hyperion and ASTER images can achieve better lithologic mapping than ETM. The assessment of matched filtering score index and the separability also supports these findings. Hyperion can discriminate more similar classes than ASTER and ETM, while the better availability and spatial coverage makes the ASTER sensor more suitable for large-area lithologic mapping.

EO-1 Hyperion传感器是第一个可以获取可见光与近红外以及短波红外波长范围光谱信息的星载高光谱传感器。本文以美国最早的金矿采矿区之一，加利福尼亚州东南巧克力山的Rainbow金矿区作为研究案例，探讨了Hyperion数据的预处理方法，专题信息提取与填图，评估了Hyperion高光谱数据在识别与金矿有关的岩性类型的应用价值。结果表明，本文所提出的Hyperion数据预处理方法是有效的，MNF方法能有效用于Hyperion数据维数的降低和数据冗余的去除以及分类特征的提取。最大似然分类器能够有效地从Hyperion高光谱数据中提取与金矿相关的重要岩体信息，所得到的岩性单元与地质图上对应的岩性分布具有很好的一致性。岩体分类的总精度为86％ 。该研究表明，Hyperion高光谱数据能够很好识别有细微光谱差别的岩性，因而在地质学研究与找矿领域有着良好的应用前景。

The visualization of multivariate geospatial data is an important concern in environmental modeling, exploratory data analysis, and geographic/spatial applications. This paper presents an icon-based visualization technique designed for co-visualizing multiple layers of geospatial information. Icon imagemaps are based on a three-tiered image structure consisting of pixel, icon block, and image levels. In icon imagemaps it is icons rather than pixels that form meaningful visualization primitives. Graphically versatile aggregate icon constructs take several visual variables into consideration, such as color, length, width, orientation, shape, size, pattern, and texture, and thus can carry more information than conventional pixel images. The extension from pixels to icons in the icon imagemap technique enables raster GIS to represent multiple variables at a single location in the “simple” raster data model. The IconMapper software system was developed as an implementation of the icon imagemap visualization technique. The modeling of terrain traversability in the Las Vegas area was used as an example to test the usefulness of this visualization technique. This paper describes the icon imagemap approach (concept and design issues) and its implementation as a software tool. The relative simplicity and flexibility of the icon imagemap approach makes it a powerful tool for non-fused visualization of multivariate geospatial data.

利用空间信息系统所提供的强大空间数据处理和分析能力，并将之与统计分析软件包的统计分析功能进行有效的集成，建立了基于空间统计分析的可持续发展定量分析评价模型(SBSA)。从在缅甸中部Myingyan县的应用实倒来看，该模型能够揭示影响Myingyan县可持续发展能力的主导因子，通过对这些因子和可持续发展综合指数的定量化、空间化的分析,为政府部门规划区域综合发展方案，制定发展政策提供很好的决策支持。