The enterprise GIS consists of tabular, vector and raster data from existing and custom-derived datasets. The proprietary data purchased

Infrastructure and Capacity Building: Creating an Enterprise GIS for Multi-scale, Interdisciplinary Analysis of Farmers’ Land Use Decisions

Dana Peterson, Jude Kastens, Chris Bishop, Chris Brown, Stephen Egbert, Kevin Dobbs, Vijay Barve, Eunmok Lee, and Ryan Surface, The University of Kansas

The Kansas Applied Remote Sensing (KARS) Program is developing a statewide, enterprise level geographic information system (GIS) containing statewide, temporal (2000-2013) field-level representation of a suite of data including climate, soils, socio-economic data and land use/land cover, among others. The enterprise GIS is built on an ArcSDE and MS SQL framework that allows remote access to large, integrated geospatial datasets. User accounts are password protected and have set permissions to protect sensitive and proprietary datasets. With the enterprise GIS, team members will login to the database and develop spatial or tabular queries of the integrated data, allowing analyses to be performed at any meaningful spatial scale (such as field, farm, county or statewide). This will facilitate modeling farmers’ decisions to grow biofuel feedstocks and the potential impacts of those decisions on water quantity, water quality, and other environmental impacts, and also potential impacts of climate change on Kansas agriculture.

sub-fiels or sub-CLUs is another custom database being generated. The existing CLU database described above contains delineations with varying level of detail, with some CLUs representing multiple fields. An objected-based image analysis approach that uses both spatial context and spectral information from satellite imagery is being used to derive the sub-field boundaries. In addition, an annual land use/land cover (LULC) time-series is under development. While the FMiD dataset provides field level crop type information, it does not provide irrigation status for the entire study period. Furthermore, the data are proprietary, and the data use agreement restricts the use of the data beyond this project. Our approach enhances existing LULC data and leverages FMiD data for image classification training for years when no LULC data are available. Additional geospatial data including hydrography, watersheds, transportation networks, ecoregions and administrative boundaries were acquired and can be used for map production, spatial analysis and modeling. See the digital display for more information on customized dataset development.

Common Land Units (CLUs): 2007,

1.4 million polygons

Farm Service Agency (FSA) Compliance Data: 1990-2010; crop type & irrigation status for most years

Grower Totals Data

Grower Demographic Data: 100+ Attributes

Successful Farming Survey Data

from Farm Market iD (FMiD) includes the 2007 Common Land Unit (CLU) geospatial data representing field boundaries and a set of tabular data that can be spatially linked to the CLU data. The FMiD tabular data consists of FSA compliance data, grower totals, grower demographic data and Successful Farming survey data.

Soils, climate, and terrain geospatial data were obtained, processed and imported into the GIS. Separate geodatabases for biofuel facilities and grain elevators are being developed at Kansas State. University (KSU). Geocoded locations will contain targeted attributes including facility capacities and years of operation. The

Flint Hills

Smoky Hills

Rolling Plains and Breaks

Prairie Tableland

Great Bend Sand Prairie

Loess and Glacial Drift Hills

Canadian/Cimarron BreaksNorthern Cross Timbers

Administrative Boundaries: State, County, Zip-Code and Public Land Survey System

Level I- IV Ecoregions Hydrologic Unit Codes (HUCs)

National Hydrography Dataset

Rail & Road Networks

Year Corn Acreage % Change in Corn

Acreage Since 2006

2006 273,798 --

2007 366,851 34.0%

2008 348,892 27.4%

2009 354,109 29.3%

2010 430,155 57.1%

2011 382,503 39.7%

Year Corn Acreage % Change in Corn

Acreage Since 2006

2006 159,323 --

2007 186,690 17.2%

2008 195,906 23.0%

2009 191,003 19.9%

2010 211,697 32.9%

2011 210,988 32.4%

This work was funded by the Kansas NSF EPSCoR grant, No. EPS-0903806 Climate Change Renewable Energy, Biofuels and Climate Change: Farmers' Land Use Decisions (BACC: FLUD).

Points of Diversion

Surface Water

Ground Water

Designated Place of Use

locations of participants from numerous focus groups, interviews and direct mail surveys have been geocoded to allow linkage to other field level data. These datasets are sensitive, and use is limited to a specific set of project personnel. These data are being processed and coded, and attribute information has yet to be determined.

To meet project needs, custom-derived datasets are also being developed. Several customized datasets focus on ground and surface water use for irrigation. Data from the Kansas Division of Water Resources (DWR) contains water rights and water use information. Points of diversion (PODs) in the database are linked to a field or CLU. To determine surface water use for irrigation, two databases are under development. One database links PODs to the nearest USGS stream flow gages. The second dataset contains irrigation canals diverted from reservoirs and links turn-outs along the canals to fields or CLUs. The delineation of

Land Use & Land Cover: 2000-2013; Crop Type &

Irrigation Status

Points of Diversion

Surface Water

Ground Water

Designated Place of Use

Water Rights & Water Use; DWR

USGS Stream Gages & Stream Irrigation

Reservoir Water Use for Irrigation

Climate (NARR): 1979-Present, Daily;

Tmin, Tmax, Precip; 32km

Terrain: Elevation, Slope &

Aspect; 10m

Soil Survey Geographic Database (SSURGO):

200+ Attributes

Biofuel Plants & Grain Elevators

Focus Groups, Interviews & Surveys

Sub-CLU Delineation

2007 CLU Boundaries

Sub-CLUs derived from satellite imagery

The large quantity of data and the need to integrate spatial and tabular data for data queries and extracts at multiple scales (especially field level) is beyond the capabilities of ArcGIS Desktop. Therefore, the project purchased a Dell server outfitted with dual 6-core processors, 64Gb of RAM, and a 2Tb hard-drive to develop an enterprise GIS using ArcSDE and Microsoft SQL 2008 as the relational database management system (RDBMS). The vector, raster and tabular data are currently being integrated into an ArcSDE geodatabase. The database is unrestricted in size and in the number of users accessing the data. Access permissions are established by the database administrator to ensure that only authorized users can access restricted data. A replication of the enterprise database will be stored off-site with the project team at KSU.

This data infrastructure development effort, which included team member training in ArcSDE & SQL, was designed to ensure that the database will be flexible and expandable and have utility beyond this project.

To access the database, users login to the GIS server using their unique id and password. Data queries and data extracts are performed using SQL statements. The data extracts can consist of a table (data view) or map (spatial view). Below is an example of a spatial and data view from a basic query.

Query: Retrieve corn fields and area information from 2006-2011 within a 40 mile radius around (1) the location of the Conestoga/Bonanza Bioengery facility, and (2) a location with no ethanol facility. Using the buffers and LULC data, the query extracts all corn mapped between 2006-2011. The spatial view shows the corn mapped within the buffers, while the data view could list the acreage for each corn field or could be summarized as shown below. This example shows the corn acreage by year and the percent change in corn acreage from 2006.

The enterprise database will be used for coupled systems modeling.

Corn, 2006 Corn, 2010 Corn, 2006 Corn, 2010