As Georgia’s population and development continue to expand and grow, so does the need to understand, prepare, plan, and manage the resources and infrastructure required to support that growth. The implementation of geospatial technologies and data have become a critical tool used by scientists, engineers, planners, and managers in helping to deal with those issues, especially within increasingly difficult financial and budgetary constraints. This technology, supported by the underlying data, allows professionals to make better more accurate decisions in less time, and lower cost than might have been done in the past, if done at all. However, as with any information-based technology, the final results are only as good as the data used in the decision making process. One of the most fundamental layers of geographic information used for describing the landscape is elevation or topography. Elevation data serves as the foundation for many of the data layers used by and critical for geo-spatial applications including flood mapping and hydrologic models, emergency planning and response, facility sighting, utility and transportation infrastructure planning and maintenance. Unfortunately, it is also one of the most expensive and difficult data layers to acquire. Because of this, most areas in Georgia do not have elevation data available at a suitable and accurate scale. The purpose of this paper is to assess the current status of state-wide high-resolution elevation data and to look at options for improving on the existing data inventory.
So, what is high-resolution elevation? In general, it is elevation suitable for local-scale mapping applications such as flood-plain modeling, water-resource planning, site plans and preliminary site designs. Traditionally, this would be contour maps at 1 or 2 foot intervals, created using surveying methods combined with stereoscopic imagery analysis to develop the contour maps. More recently, it is data acquired using airborne or ground-based laser technology called LiDAR (Light Detecting and Ranging). Although there are some areas of Georgia that have land-surface models built using the traditional stereo-pair derived contours, most existing data has come from LiDAR. For the purpose of this paper, high-resolution does not necessarily have to meet engineering or survey-grade elevation data specifications, although that data would certainly fall into this category.
LiDAR data can vary significantly in accuracy depending on many factors. The U.S. Geological Survey (USGS) and the Federal Emergency Management Agency (FEMA), working with other agencies and organizations have jointly developed standards for LiDAR data in order to meet the various requirements of each agencies mission (http://lidar.cr.usgs.gov/). It should be noted that these are general base guidelines, and may not be suitable for all applications. And because LiDAR is able to acquire much more information than just the land-surface (trees, buildings, etc.), there are also many other uses for the data beyond acquiring elevations. And as the technology for LiDAR has improved, the cost for such data has decreased while the accuracy and usefulness has increased.
So, for purposes of this assessment, high-resolution elevation data is that which meets, or comes close to meeting, the specifications outlined in the current USGS specifications or previously published FEMA guidelines: that is, a vertical accuracy of 15 to 18 cm. with a point spacing of 2 meters or less, and capable of meeting ASPRS guidelines for generating 2 ft. contours and suitable for ingestion into the USGS National Elevation Dataset (NED). There are many other factors in actually meeting elevation requirements, so it could be that while the above specs are met, under scrutiny, the data may not pass for all applications. Only a detailed analysis of the data can make that determination.
Many communities around the state have acquired high-resolution elevation data on their own initiative for various purposes. Gwinnett County, for example, uses LidAR along with ortho-imagery to derive impervious areas used in tax assessments on property owners to recover storm-water management costs. Because of this, the county regularly updates their data to reflect changes in land-use and track development. Newton County has used LiDAR to help plan and develop a water storage reservoir. The availability of that data helped to significantly reduce planning and on-site survey costs to the extent that the LiDAR has paid for itself. And all of these cities and counties are able to provide site plans (usually contour maps) to developers and planners, helping to promote quality development at lower costs. But probably the most widely used application of high-res data is in meeting the FEMA flood-plain mapping requirements. This information has a major impact on property owners since it is used to determine vulnerabilities and flood insurance requirements and eligibility.
Unfortunately, the vast majority of the State is still lacking adequate elevation data to meet these needs. In these areas the best available data is from Digital Elevation Models (DEMs) derived from the existing USGS topographic maps. These maps are often out-of-date, and suffer from inaccuracies as much as 5, 10, or even 20 feet in elevation! It is simply impossible to build an accurate land-surface model suitable for local applications from that data. The results, particularly in regards to the flood maps, are misleading and lead to inaccurate insurance rates and undetermined vulnerabilities. At minimum, it is costing the citizens of the State of Georgia money that they should not have to spend, and at worst, it could potentially cost lives and significant property loss due to inadequate and improper planning.
In addition to existing data collected by municipalities, a number of initiatives have taken place over the last several years to help address the problem. These have largely been cooperative projects involving multiple counties or cities, Regional Commissions, Federal, and State agencies. Here is a brief summary:
Dade and Walker Counties, 2008: LiDAR collected by the USGS and funded by the Natural Resources Conservation Service (NRCS).
Georgia Mountains Regional Commission 2009: This project collected LiDAR for 4 counties covering 931 sq. miles, and was a partnership between the Regional Commission, the counties, and the USGS.
Coastal Georgia Elevation Project (CGEP): Managed by the Coastal Georgia Regional Commission (CGRC), this project, when combined with existing data from Chatham, Liberty, and Glynn counties, will cover 13 coastal counties (8743 sq. miles) with LiDAR, to be completed by winter 2010. Project partners included NOAA, FEMA, the USGS, Ga. DNR/CRD, and the local counties and cities.
Atlanta Regional Commission, 2010:LiDAR for 3 counties and several cities in the ARC region, covering about 1196 square miles. Funding was from local sources and the USGS.
Lake Lanier/Upper Chattahoochee ARRA, 2010: This partnership between the U.S. Army, Corps of Engineers and the USGS was 100% funded through the Federal stimulus (ARRA) program. LiDAR was collected for the entire Lake Lanier basin, and most areas within the upper-Chattahoochee watershed currently lacking LiDAR. It was expanded to include all of Hall, White, Habersham, Rabun, Towns, and Union counties, covering 1983 square miles.
Charlton/Ware (Okefenokee) ARRA, 2010:Another 100% federally funded project using an ARRA grant awarded to the University of West Ga. from the USGS, for LiDAR in Charlton and Ware counties, covering 1690 square miles.
Combined with existing data, the State is currently about 30% covered by high-resolution elevation data (approximately 18,300 square miles), with about 59,500 square miles remaining (Figure 1.).
Figure 1. -- Areas with high-resolution LiDAR derived elevation data holdings.
A number of potential projects have recently been discussed involving the USGS, Regional Commissions, and local governments. In particular, the NE Ga. RC, Middle Ga. RC, and the SW Ga. RC, have all expressed an interest in potential collections over the next 2-3 years for the communities within their respective domains. Due to the current economic situation and funding shortfalls in many of these counties, combined with uncertain funding from the federal side (primarily the USGS), the likelihood of these projects taking place is far from certain. None the less, it is imperative that planning continue to move forward in order to take advantage of funding opportunities that may materialize. For example, FEMA is looking at expending considerable resources to enhance their flood modeling program. It is too early to tell how this will develop, but there may be some funds available from that source. Other federal agencies that may be interested in potential data partnerships include the Corps of Engineers, NRCS, EPA, U.S. Forest Service, and the Dept. of Homeland Security (agencies other than FEMA). And the USGS anticipates eventual restoration of its partnership funding. The larger the area of interest, and the more participating agencies and governments, the more likely a project is to receive funding from the federal government and the lower the costs for everyone. A coordinated state-wide effort would greatly reduce the redundancies in planning and implementation, increase the value and usability of data, and most likely significantly reduce the overall cost per area, as opposed to piecemeal county-wide or even region wide projects.
Cost and Benefits of a Statewide Collection
Much of the existing data in the State was paid entirely out of local funds. These communities have recognized the benefit of their investment, and in many cases, continue to upgrade or replace their data on a regular cycle. Generally, these are communities that also have resources to process and manage their data effectively. Because communities have different needs and applications of this data, as well as products derived from the initial LiDAR collection (contours for example), these costs vary considerably and may not reflect accurate costs of the base collection. In recent partnerships with the USGS, costs per square mile have ranged from about $180 to $350. The CGEP project is perhaps the most representative of a large-area USGS-spec project, and was about $250/sq. mi. Typical contributions from the USGS have ranged from 20%-25% of base LiDAR costs. For the CGEP, with additional funding from FEMA, the entire federal contribution was over 50%. It is not possible at this time to estimate what a federal contribution would bring to a state-wide acquisition until funding sources are identified and budgets approved. However, there is considerable interest in such projects from the USGS and FEMA in particular, as well as other agencies. Every effort would be made to include a reasonable participation from the federal government, especially if there is State and local funding to match. Beyond the benefits of the data, the benefits of a state-wide coordinated project are significant:
Remove redundancies in proposals, instead of multiple RFP’s coming from perhaps dozens of entities. Reduces planning and management costs, particularly for local governments.
Consistency in standards and specifications. Current practices induce significant variability in data quality making regional planning more difficult.
‘Open’ data useful across municipal boundaries. Many entities are not forthcoming with sharing data outside of their organization, creating roadblocks and inconsistencies for regional or statewide projects.
Increased competition from vendors. A large project is highly valued and will entice more competitive participation.
And most importantly, reduced unit-area project costs. The larger the area, the more efficient for flight planning and acquisition, and data processing.
Whether planning for regional reservoirs, flood inundation modeling, updating flood insurance rate maps, planning road construction, water and sewer construction, or a new industrial facility; accurate and reliable information on the topographic landscape is critical for intelligent decision making. On a statewide level, the existing digital elevation data for Georgia is out-of-date and of insufficient accuracy to be useful for anything beyond a generalized analysis and does not meet the needs at a local level. Even the existing high-resolution elevation data is piecemeal and often inconsistent in quality and accuracy. The need for better elevation data around the State is quite clear. Those communities that have it have realized the significant value and cost-saving benefits to the extent that many of them try to maintain updates on a regular basis. Many other cities and counties that do not have this data have expressed the need to acquire it, but lack the full resources to do so. A consolidated and coordinated effort to develop a plan to acquire a state-wide high-resolution elevation model would be of significant benefit to all communities and citizens within the State of Georgia, and ultimately help to reduce costs, improve cooperation and planning, and perhaps even prevent property loss and save lives.