An Internet-Based Integrated Resource Management System (IRMS)
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1 An Internet-Based Integrated Resource Management System (IRMS) Third Quarter Report, Year II 4/1/2000 6/30/2000 Prepared for Missouri Department of Natural Resources Missouri Department of Conservation Submitted by Yan Z. Barnett Center for Agricultural, Resource and Environmental Systems College of Agriculture, Food and Natural Resources University of Missouri - Columbia August 15, 2000
2 1. Project Objectives and Tasks The goal of this research project is to develop a user friendly Internet-based decision support system (DSS) that addresses total resource management by integrating ecological and economic models with a geographic information system (GIS). Specifically, research is proposed to develop and implement an integrated resource management system (IRMS). This DSS is designed to assist natural resource-based agencies in developing management plans. For example, IRMS will be used by MDNR Soil and Water Conservation Program to prioritize Special Land Area Treatment Agricultural Non-Point Source (SALT-AGNPS) projects. IRMS will also be used as screening tool for identifying costs and benefits of potential SALT-AGNPS projects. Specific objectives of the proposed project are as follows: 1. Develop an Internet-based Integrated Resource Management System (IRMS) that addresses changes in land use and/or its management practices by integrating economic and environmental simulation models. 2. Develop feedback loops with IRMS end users and conduct three workshops for selected agency field staff. 2. Research Approach IRMS will have three components: an Internet-based geographic information system (GIS) building upon ArcView Internet Map Server, a graphical user interface (GUI), and a modeling system. The GUI includes the menus that allow a user to select parameters and evaluation criteria needed to run IRMS. It will be developed using Java, JavaScript, HTML Form components and ArcView Avenue programming languages. The interface enables the decision maker to manipulate land use/management practices, execute the models, and view results within the GIS. The GIS layers to be incorporated in IRMS include: soils, land use, digital orthophoto quadrangles (DOQs), hypsography, and hydrography. Depending on the data needs of the models, other layers may also be digitized with IRMS. Digitization of these layers should require a modest effort given scanning technologies, object character recognition software and other software algorithms. Although some of these layers do not currently exist statewide, the intent of this research is to have the appropriate tools in place before the layers do become available. The proposed modeling system initially included the Cost and Return Estimator (CARE) model and habitat models. CARE is a farm budget generator, developed by USDA Soil Conservation Services (SCS) from 1985 to 1994, and primarily used as a field office or farm PC tool. Based on an extensive research and evaluation of economic models taken at the beginning of this project, the profits and costs model (ProCosts) was chosen to replace the CARE model. The reasons were twofold: (1) ProCosts is a profit and cost analysis program that handles crop budgeting, livestock budgeting, and conservation practices. It is 1
3 developed by the Natural Resource Conservation Services (NRCS) to phase out CARE. (2) In addition to the standalone version, a web-based ProCosts version would be implemented with efficient database design to accommodate simultaneous access of multiple users. The model seemed to fit well with objectives and applications of IRMS project. However, the release of the ProCosts model has been postponed for various reasons and was not foreseeable in the near future. In lieu of the situation, the project contract was amended to use a different model or approach in order to complete the project in time. Therefore, U.S. demographic and Socioeconomic data were to be integrated for public access online. The integration of demographic and socio-economic database was an attempt to link environmental issues with human factor. The database would be a useful source for answering questions such as the population composition in a watershed in terms of farmers and non-farmers, and etc. In addition to the database, several analytic tools will be developed for the users to look at the trends over time and more. The first habitat model has been developed by Wes Burger, Mississippi State University (see "Habitat Model to Predict Landscape Use of Northern Bobwhite in Missouri"). Subsequent models will be incorporated onto the tool as they are developed by Burger and others. The purpose of integrating the habitat models is to streamline and automate the process of constructing habitat suitability surfaces for large-scale habitat assessment. 3. Work Schedule IRMS is a three-year project extending from October 1, 1998 to September 28, The table below lists the proposed timelines for IRMS: Tasks Consult with agencies on assigning field staff to project and establish formal feedback loops Develop prototype IRMS by integrating CARE model Develop prototype of habitat models (CARE still under development) Complete integration of CARE model *Develop prototype IRMS by integrating demographic and socio-economic database Complete integration of habitat models Year 1 Year 2 Year 3 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 X X X X X X X X X X X X X X X Activate feedback loops X X X X X X X X X X Conduct workshops X X X Prepare quarterly reports to funding agencies, collaborators X X X X X X X X X X X X X 2
4 and specified field staff Meeting with funding agencies, collaborators, model developers and field staff regarding direction of project X X X Prepare on-line users manual X X X Prepare final report/distribute final version of IRMS * See the Amendment in the First Quarter Report, Year II, submitted on December 31, X 4. Quarterly Progress Presentations of the Project Chris Fulcher presented the project methodologies and current results to a group of scientists at the National Agricultural Mechanization Research Institute, Rural Development Administration in Suwon, South Korea in June 2000, and at the International Society of Ecological Economics Congress 2000 held in Canberra, Australia in July 5-8, Both presentations received a lot of interests and follow-up discussions. Development of An Integrated Mapping Website An major effort of this quarter was to revamp the Website to provide an truly integrated resource management system. CARES houses several Interactive Map Servers (IMS) associated with respective research projects, such as CARES Watershed Information Clearinghouse, Missouri Digital Soils Survey, and Saline County Study. Each project provides its own specialized datasets. These specialized datasets can only be accessed through the project website. In the meantime, all projects also provide access to several general reference datasets such as county boundaries and highways. There has been a great redundancy in listing and maintaining these general datasets. As new research projects producing more and more data, there was an increasing need to integrate all the individual project Internet mapping sites so the user can access any dataset for any area of interest easily. This integrated mapping site was named "Map Room", and planned for debut in November, As shown on Figure 1, the Map Room will provide access to several sections of Internetbased mapping functionality: (1) Interactive Maps - the user can select area of interest and data layers to generate a map and interact with the it, (2) Atlas Maps - the user can download or print static maps which are pre-made or dynamically made upon request but with pre-selected data layers, (3) Analysis & Modeling - the user can perform specialized analysis on the Internet such as Habitat Suitability modeling or Livestock site selection, (4) Data Download - the user can specify area of interest to cut data layers for downloading from a simple HTML page, without starting a mapping session. With the Map Room, the user can access all geographic data layers currently available at CARES for any given area of interest in Missouri. The user can specify an area of interest by selecting a county, a public land survey system (township, range and section), a river 3
5 basin, a school district, a street address, a USGS 7.5-Minute quadrangle, or zip code (Figure 2). All available data layers are grouped into 27 categories: Administrative, Agricultural, Base Map, Cultural, Drinking Water, Facility, Flood, Geology, Health, Housing, Hydrography, Income, Land Cover, Political, Population, Soil, Topography, Transportation, Water Quality, Watershed, and Wetland (Figure 3). Some of the data layers are crosslisted in multiple categories. The new website provides an one-stop site for public access to Missouri environmental and socio-economic datasets. In addition, the Map Room will allow for easy and user-friendly navigation by using index card format for simple step-by-step user actions (see Figure 2). Figure 1, Map Room homepage 4
6 Figure 2. Specify Area of Interest in Map Room 5
7 Figure 3. Select data layers in Map Room To test the usability of the Map Room, two focus groups and follow-up discussions were organized on June 7 th, Each focus group consisted of 5 participants, paired with 5 observers from CARES to keep track of evaluator's actions and comments. All participants were from outside of CARES, and had none GIS or mapping background. Their professional levels varied from university professor to office clerk. We developed two short lists of tasks (one for each group). The tasks were designed to take about half an hour to complete. After completing the tasks, the participants were gathered together for a brief discussion. Based on the results of two focus groups, a number of changes and improvements were made to the Map Room. It was a successful learning experience for CARES staff with respect to design and develop a website un-technically. The second round of focus group testing will be conducted in later August. Integration of Demographic and Socio-economic Data We collected Missouri statewide 1990 US census data to be included in the Map Room. The data will be grouped into 3 categories: Population, Housing and Income. Figure 4 shows the Population data list in the Map Room. This group includes sub-categories of General Population by Block, General Population by Block Group, Gender, Race, Age, and 6
8 Education and Employment. Figure 5 shows the Housing data list in the Map Room. This group includes sub-categories of Households, Housing Units by Block, and Housing Units by Block Group. Figure 6 shows the Income data list in the Map Room. This group includes Income by Family and Income by Households. Each sub-category includes a number of data layers. The census databases available on Missouri Spatial Data and Information Service (MSDIS) are separated into individual counties. We downloaded the data by each county, and joined the datasets into statewide coverage for seamless data display and access. This data processing consists of several time and labor consuming procedures. These statewide datasets will be further processed for use in Internet map server to show individual themes and for the user to query and download any interested areas. 7
9 Figure 4. Population data list 8
10 Figure 5. Housing data list 9
11 Figure 6. Income data list Develop prototype of habitat models 1. Habitat Model I - Winter Habitat Model The modeling scripts were developed in last quarter. The scripts were sent to Prof. Wes Burger for validating in April. Prof. Burger applied the scripts back to his initial Winter Habitat Model research area, and generated habitat suitability surface (Figure 7). The validation shows very good prediction of the winter habitat model. 10
12 The scripts will be linked to an Internet-based interface for web access. This interface will be integrated into Map Room. 2. Habitat Model II - Summer Habitat Model The Summer Habitat model equation will be provided by Prof. Wes Burger to be incorporated into IRMS. An overall habitat model will be generated by combing the results of winter habitats and summer habitats. Figure 7. Winter model validation 11
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