Interface Development using SQL and Visual Basic for an Amazonian Soil, Vegetation, and Spectral Database Supported by Oracle The development of networking technology has enabled remotely sharing databases supported by a client/server database management system (DBMS) such as Oracle and SQL Server. The technology of integrating DBMS into GIS is significant for developing large networking GIS using the data storage and communication abilities of client/server DBMS. Environmental projects often require a great quantity of data, especially, when remote sensing images are a vital element of research. The most difficult task is the development of techniques to store spatially related data in relational database systems and process large data sets like remote sensing images. In order to ensure the speed to display remote sensing images, storing them on the front-end instead of the back-end server is one practical solution. This method wastes much storage space, thus more research is required to solve the problem. This research has provided a comprehensive integration and organization of all IU/ISU/INPE LBA project data (on both client and server sides) which permits sophisticated displays of data subsets relevant to a specific project need. In addition this system is developed to accept additional interfaces which facilitates statistical analyses (i.e. factor, principal component, regression, multiple regression, correlation) and modeling needs of project research using data stored in the Oracle system. However, additional research can improve the efficiency of the technologies developed in this project. The Indiana University/Indiana State University (IU/ISU/ INPE) LBA – Ecology project “Human Dimension of Amazonia: Forest Regeneration and Landscape Structure” has one of the largest field, interview, and spectral databases in the Amazon Basin. These data, from seven study sites, include detailed field measurements of vegetation parameters (primarily in mature forest and various succession classes) including trees, herbs and economic species, soils including carbon at five levels, landuse history, and landscape metrics. A spectral data base with more than 30 Landsat TM scenes supplemented by JERS radar currently exists with additional data to be added. These data can be associated at four geographical levels which include region, site, plot, and subplot. A vital element in using this vast data resource to address LBA research issues requires that it be organized in a manner which permits retrieval of all data in any combination in tabular, image, and graphic forms. Organization and manipulation of the field data are supported by Oracle that is running on the server side. Remote sensing images are stored on the client side. Integration, query and display of various databases are being conducted using PL/SQL and Visual Basic programming to create user interfaces. This system permits tabular display of all field-acquired data in any combination designated. In addition, an image viewer can display raw remote sensing images, location of sample sites on remotely sensed images, and graphs of multispectral and/or multitemporal spectral data associated with sample sites. The tabular field data can be displayed simultaneously with graphics and image displays. On the client machine (front side), tabular data stored in the database can be updated. Operations such as adding and deleting records are also allowed. A query using SQL by linking relational tables can be created. For example, this query shows tree information in each plot and the host site of each plot by linking SITE_INFO, PLOT_ INFO, and TREE_ DATA tables. Querying the information of all trees within a site in the study region Pedra. The pink polygon shows the selected site. Showing the soil information and average spectral pattern of the selected site. The combination of graph and tabular data shows the average spectral patterns of sites with the same secondary succession stage. The combination of graph and tabular data shows the dynamics of average spectral patterns of a site in different years. Soil, vegetation, spectral, and site polygon data are stored in the backbone database supported by the Oracle Database System. Ping Jiang, Paul Mausel (Department of Geography, Geology, and Anthropology, Indiana State University) Eduardo Brondizio and Emilo Moran (ACT/Department of Anthropology, Indiana University) Remote sensing images are stored on the local machine (client side). The image viewer displays a color composite of multi- spectral TM data. Sample site polygons can be overlaid on the image. Zoom in/out and labeling site functions are also available. From the viewer, soil, vegetation, and average spectral statistics of each sample site can be spatially queried by clicking on the site.