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Government Agencies: Papers 2

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(ECP and CTSP grantees, reports, and other sites of interest for conservation geograpy, mapping and GIS. Grantees are coded by program and year of grant at the end of their name/state, i.e. e91 means ECP grant in 1991. c=cstp, cm=ctsp-mac, cs=ctsp-software)


-Introduction to the Gap Analysis Program (GAP) . (1997 ESRI Paper: Patrick Crist GAP Analysis Program 530 S Asbury St Suite 1 Moscow, ID 83843, Telephone: 208-885-3901 Fax: 208-885-3618 E-mail: pcrist@uidaho.edu , Michael Jennings ) . Defining Issue: Conservation of biodiversity requires the development of GIS data on land cover, animal distribution, and land stewardship; analyzed and interpreted for landowners, managers, planners, and decision makers. GIS Solution: GAP is one of the most demanding GIS projects ever launched with a full involvement of remote sensing technology for land cover mapping, GIS modeling and spatial analysis, and database storage and analysis. Delivery of data over the Internet and by CD ROM is also pushing the electronic publishing frontier. Methodology: Development of the biological data sets and stewardship maps (ownership and management status for biodiversity conservation) provides the public with estimates of the representation of plant communities and animal species (elements) on lands managed for biodiversity maintenance. "GAPS" are those elements that are insufficiently represented and may be at risk of endangerment in the future unless changes in their management status are made. The data sets have thus far been used for numerous applications for both conservation and development planning, as well as scientific research. GAP is conducted in cooperation with over 400 institutions from all state and federal land management agencies, academia, nonprofit, and industry groups. Software: The individual GAP projects conduct the project using a variety of software packages including ESRI ArcInfo, ERDAS, Intergraph, SPECTRUM, PCI Oracle, dBASE, and GRASS, among others. The purpose of this presentation is to provide participants with an overview of the program structure, status, operations, goals, methods, and products. We will identify methods to access and use the data including access through the Internet.

Louisiana GAP Analysis Project: Usage of Auxiliary Data Sets . (1997 ESRI Paper: Steve Hartley U.S. Geological Survey 700 Cajundome Boulevard Lafayette, LA 70506 , Telephone: 318-266-8543 Fax: E-mail: hartleys@nwrc.gov , Jimmy Johnston, Pat O'Neil ) . Good ancillary data sets are rare. Fortunately, Louisiana is blessed with an abundance of good quality auxiliary data sets. The most important of these data sets is the National Wetlands Inventory data, which cover approximately one-third of the southern half of the State. The Louisiana GAP Project is using these data in conjunction with Thematic Mapper (TM) imagery to produce a vegetation map of the State. The merging of these two data sets is not arbitrarily straightforward. One must consider the origin and format of the two different data sets. One data set is vector (NWI) and produced by photointerpretation of aerial photography, and the other is raster (TM) from satellite imagery. In order to merge the two data sets, the NWI Cowardin classification scheme had to be reclassified to the Louisiana GAP classification scheme and converted from vector to a raster data format. This procedure allows the two different data sets to be merged into one; however, it does not take into account the spatial resolution of the two different data sets or the temporal changes between the sets. Temporal changes were limited to change in upland forest evergreen and mixed categories along the merge line between the two different data sets. In order to accommodate these differences we had to subset the NWI upland forest evergreen and mixed categories and integrate TM imagery for further processing. The poster depicts several output steps used to produce the final merge of classified NWI and TM data sets. Other auxiliary data sets used in the Louisiana GAP vegetation classification include 1995 color infrared photography (CIR), SPOT data, and ground truthing data. These data sets are of significant help to classify the TM imagery.

Procedures for collection, analysis, and display of data collected at several geographic scales , John R. Sauer, BRD Patuxent Wildlife Research Center: 12100 Beech Forest Road, Suite 4039 Laurel, Maryland 20708-4039 USA Telephone: 301-497-5500 Fax: 301-497-5505 ) "We propose to investigate procedures for collecting and summarizing information at several geographic scales....Managers will be able to access information from the projects using Internet. Placing these data sources into a common GIS framework will allow an assessment of the relative importance of information collected at different scales for addressing management issues at each scale, and will allow us to understand better the constraints on use of information collected at each scale."

A Proposed Protocol for Identifying Potential Research Natural Areas with Gap Analysis Data . (1997 ESRI Paper: Max Moritz University of California, Santa Barbara, Santa Barbara, CA 93106-4060, Telephone: 805-893-7815 Fax: 805-893-3146 E-mail: maxm@geog.ucsb.edu , David Stoms, Mark Borchert, Frank Davis ) . Defining Issue: The U.S. Forest Service attempts to establish Research Natural Areas (RNAs) to represent vegetation communities, yet there is no formal protocol for selecting the best sites. GIS Solution: We have developed a procedure using several ArcInfo functions (both raster and vector) to identify, characterize, and select potential RNA sites. Methodology: The land cover and land management GIS coverages from the Gap Analysis Program (GAP) are used to identify the set of sites with the vegetation community for all types that occur primarily on national forest lands. Each of these sites is characterized with regard to its environmental properties such as elevation and precipitation. All sites are then rated for their suitability as potential RNAs as a function of the spatial extent of the target type in a watershed and its representation of the type regionally. An optimization model is applied to select the most efficient set of highly suitable sites to represent all types. The protocol is illustrated with an example for four mixed evergreen forest types in the Los Padres National Forest of the central coast of California. Software: This application used a combination of ARC GRID functions to do the query, characterization, and optimization analysis.

The Southern Appalachian Assessment GIS (1996 ESRI Conf. Paper, Karl A. Hermann)...In October, 1994, the cooperating partners of the multiagency Southern Appalachian Man and the Biosphere Program (SAMAB) decided to collaborate on an assessment of the status and condition of the ecological resources in the Southern Appalachian Region. ...The GIS effort included the identification, compilation, integration, and analysis of ecological and supporting data for the assessment activities.

Supporting Search for Spatial Data on the Internet: What it means to be a Clearinghouse Node (1996 ESRI Conf. Paper, Douglas D. Nebert, Clearinghouse Coordinator Federal Geographic Data Committee U.S. Geological Survey, Mail Stop 590 Reston, VA 22092 Telephone: (703) 648-4151 Fax: (703) 648-5755 E-Mail: ddnebert@usgs.gov) The Federal Geographic Data Committee (FGDC) has been facilitating the accessibility of digital spatial information on the Internet among federal and state organizations. By Executive Order of the President, all agencies are required to document their digital spatial data and make it available to the public to encourage re-use of expensive information. The National Geospatial Data Clearinghouse is a FGDC-sponsored activity that provides a series of technical solutions to making spatial data discoverable on the Internet. The Clearinghouse is an implementation of concepts that define service within the National Spatial Data Infrastructure (NSDI). This paper describes the requirements for a site to be considered a service node within the National Geospatial Data Clearinghouse.

Using GIS for Automated Selection of Significant Natural Areas of California . (1997 ESRI Paper: Lora Konde State of California 1220 S Street Sacramento, CA 95814 , Telephone: 916-445-5758 Fax: 916-324-0475 E-mail: LKONDE@dfg.ca.gov ) . Defining Issue: California Assembly Bill 1039 requires the Department of Fish and Game to meet five goals relating to natural diversity: (1) Develop and maintain a data management system for natural resources, (2) identify the most significant natural areas in California, (3) ensure the recognition of these areas, (4) seek the long-term perpetuation of these areas, and (5) provide coordinating services for other public agencies and private organizations interested in protecting natural areas. Determination of Significant Natural Areas (SPA) within California needed to be automated so that current information would be available to agencies for use in planning and protection. GIS Solution: Using the California Natural Diversity Database (CNDDB) and ArcInfo, an AML was developed to determine which element occurrences from the CNDDB meet the criteria for a Significant Natural Area. An SPA region coverage is created, identifying the element occurrences that comprise each SPA. This coverage can then be updated as new information is added to the CNDDB. Methodology: Oracle SQL scripts were written to extract any potential element occurrence records from the CNDDB that meet the criteria for a SPA. SNAs are identified using biological and spatial criteria. The following are the criteria used to select SNAs: -Areas supporting extremely rare species or natural communities -Areas supporting associations or concentrations of rare species or communities -Areas exhibiting representative examples of common or rare communities -Areas of high species richness or habitat richness ArcInfo is then used to reselect element occurrences that meet proximity and area criteria by using buffers, reselects, unions, frequencies, and statistics. Additional coverages are unioned with the SPA region coverage to identify SNAs that are in developed or disturbed areas. Cursors are used for automating a unique site number for each SPA. Software: SQL scripts written for Oracle, and AML, using the ARC and ARCPLOT modules. The purpose of this paper is to demonstrate how GIS solved the problem and met the need for automating and updating the selection of Significant Natural Areas.

The Wilderness Society's Center for Landscape Analysis: Outreach and Cooperation Efforts (1995 Paper, Susan E. Balikov) ...The Wilderness Society's (TWS) GIS and remote sensing program, The Center for Landscape Analysis, has grown into a strong contributor to the national and regional conservation efforts of many organizations. This paper will describe past, current and future efforts to cooperate with, and contribute to, the work of these organizations.


All text by the respective organizations, January 2, 1997

Compilation & web design: Charles Convis, ESRI Conservation Program, April 2, 1996

 

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