CSIR Research

Regional Comprehensive Visual Sensitivity Assessment

Regional Comprehensive Visual Sensitivity Assessment - Technical Report

As interest in developing sustainable methods of energy production increases in the United States, rural regions with the land base to accommodate large-scale renewable energy projects, such as wind farms and solar arrays are in a position to benefit economically. At the same time, research indicates that amenities contribute significantly to economic growth and quality of life in many rural regions of the United States (Deller, Tsai, Marcouiller, & English, 2001). The visual impacts of proposed renewable energy project are a major reason many rural community members reject them (Wolsink, 2007).

Rural jurisdictions are attempting to encourage these projects, while mitigating for visual impacts on the landscape. To reduce resistance and develop a diverse and sustainable economic base, it is important for jurisdictions to develop a comprehensive understanding of the qualities of visibility within the landscape. Knowledge of visually sensitive areas in a regional can aid decision-makers in creating comprehensive zoning plans for the location of potential renewable energy projects. The results can help site development responsibly and limit the impact to aesthetic amenities.

To aid rural jurisdictions in mitigating visual impacts of large-scale renewable energy development, RGIS-PNW developed a methodology for creating a visual sensitivity model of a regional landscape. The model is based on cumulative visibility analysis, which identifies the frequency with which locations in the landscape can be seen from other locations (Llobera, 2005; Wheatley, 1995).

When a single viewshed is created using Geographic Information Systems, the terrain is given a Boolean classification of visible or not visible from the observer point. A cumulative visibility surface is created by overlaying multiple viewsheds calculated over the same terrain and summing the number of intersections across that terrain. The result is a model of cardinality, which identifies the number of times locations in the terrain are visible from the sampled observer point set (DeFloriani & Magill, 2003). This cumulative visibility surface reveals areas of low and high visibility within that terrain. A standard cumulative visibility surface is too simplistic for use in community planning because it does not account for the number of people that can potentially see the terrain from the observer point.

The model developed by RGIS-PNW incorporates information about regional population to weight the importance of each viewshed based on population density at the observer point. The weighted visual sensitivity model identifies areas of low and high visibility to the population by summing the weights, based on population density at the observer point, of overlapping viewshed. In the final model, visually sensitive areas are locations that have high weighted values, which indicate that they can be seen by a large portion of the regional population.

The weighted cumulative visibility model is an objective measure of visibility within a landscape. The cultural importance of views and the scenic preferences of the population for different types of renewable energy development are not considered in the model. The results of this model are meant to be analyzed in conjunction with data pertaining to culturally important places in the landscape and the local inhabitants' scenic preferences. Modeling visual sensitivity is a useful for designating zoned locations for potential renewable energy projects. The results can help site development projects responsibly and limit their impact on scenic amenities.

In addition to creating a comprehensive visual sensitivity assessment methodology, this project also developed a repeatable process for creating a digital terrain model (DTM) which incorporates heights of buildings and trees. Standard USGS digital elevation models (DEMS) do not include structures or vegetation, which greatly reduces the accuracy of viewsheds that are calculated using them. Digital terrain models that accurately represent top surface elevations that include buildings and trees, rather than bare earth, are difficult for rural jurisdictions to obtain. Lidar is not widely available in rural regions and it is expensive to obtain.

As part of this objective RGIS-PNW created a DTM that includes buildings and vegetation. The DTM was derived from 1m resolution NAIP orthorectified color aerial photographs and USGS 10m DEMs. ESRI ArcGIS and Visual Learning Systems' Feature Analyst were used to extract building and tree features from the NAIP color aerial photographs (Miller, Nelson, & Hess, 2009). The resulting extracted features were assigned average heights based on photograph and field analysis. The modeled elevations of these features were added to standard USGS 10m DEMs to create a top surface DTM.

To test the methodologies, RGIS-PNW conducted a case study in Kittitas County . Census population statistics for the county were used to calculate population densities and weight the viewsheds that were generated for the model. The cumulative weighted visibility model was created from a sample of 17,735 locations.

Sample locations were selected from publicly accessible locations that have a high likelihood of public use. Sample locations were located on highways, local roads, and trails. The sampling scheme captured samples on paths and nodes (Lynch, 1960). Paths were defined as roads and trails. Nodes were defined as intersections of paths and trails. Hawth's Tools extension for ArcGIS was used to generate a systematic sample of observer points approximately 150 m apart on all roads and trails and at all intersections.

This research resulted in an online technical report describing: 1) a repeatable methodology to model the visual sensitivity of terrain in a regional landscape, 2) a methodology for creating a digital terrain model that incorporated buildings and trees from free data for input into the visual sensitivity modeling, 3) a DTM for Kittitas County that incorporates trees and buildings, and 4) a comprehensive weighted visual sensitivity model for Kittitas County and a separate each incorporated city

Use of Geospatial Techniques for Aesthetic Resource Inventories

Land use planning along shorelines is often required to consider aesthetic values as part of decision-making processes, which has resulted in various efforts to identify and quantify visual attributes of landscapes (Ayad, 2005). These have included various component-based field survey methods (e.g. Sommerville et al., 2003), surveys of visual preference based on photography and field visits (e.g. Morgan and Williams, 1999), as well as use of remotely sensed data and GIS modeling (e.g. Ayad, 2005).

In Washington State, as in many other states, shoreline management programs require aesthetic resources to be protected. However, data pertaining to shoreline aesthetics are usually not available and standardized procedures for developing this data generally do not exist. As a result, shoreline aesthetic qualities are often not adequately addressed in many comprehensive shoreline management plans and inappropriate development continues to threaten these resources.

This project developed a methodology for assessing aesthetic resources for parks along marine shorelines in Washington State. First, an internet-based, scenic preference survey instrument (Wherrett, 2000) was developed based on a literature review of best practices (e.g. Daniel and Boster, 1976; Shuttlesworth,1980; Zube, Pitt, & Anderson, 1975).. The survey instrument combines digital aerial photographs, maps, and panoramic photographs in an application that can be used to gather spatially referenced data concerning shoreline aesthetic resources from stakeholders via a web-based, Likert scale questionnaire. This is accomplished by linking representative panoramic photographs, taken at the shore’s edge, to an interactive map modeled partially after a University of Wisconsin Sea Grant Great Lakes Circle Tour Project using OpenLayers (Hart, 2007).

The site has panorama viewing functionality, and interactive mapping capabilities using both Openlayers. Custom code was created by RGIS-PN to display the viewing direction of the panorama viewer on an interactive map. This interactive map allows users to visit representative coastal views as a tourist, as well as spatially locate and evaluate scenic amenities in a 360 degree panoramic view divided into four equal segments, each representing waterward, shoreward or alongshore views. All survey results are stored in a MySQL database. The results of the survey may be used to rank-order view directions, locations, and parks on the basis of scenic preference.

Geospatial techniques were developed to analyze the results of the scenic preference survey in conjunction with planimetric physical, biological, and cultural geospatial data. Using a 10 meter resolution digital elevation model that integrated top surface LIDAR data, viewsheds were constructed in ArcGIS for 40 locations. The viewsheds were divided into quadrants corresponding to the scenes evaluated in the preference survey. The quadrants were further divided into three zones based on view distance. These quadrants were then geospatially analyzed to identify and quantify the landscape characteristics in each distance zone, including available geospatial data for geomorphic types and conditions, vegetation cover, habitat information, shoreline alterations, land use, and distance of vista..

The project has been implemented as a pilot for five Washington State parks, representing a diversity of shoreline morphologies and cultural settings along the Puget Sound, and the internet application for collecting scenic preference data has been tested using response groups from lower- and upper-level university classes. The methodology will be further tested this upcoming year using the general public and park managers. The methodology has broad application for environmental planners, as the software and techniques developed in this research are useful for inventorying aesthetic resources in any shoreline environment.

Use of Geospatial Techniques to Aid Rapid Assessment, Monitoring and Aesthetic Evaluations of Lake Shorelines

This project explored various methods of how to rapidly collect relevant geo-referenced field data and integrate it with geospatial techniques to address a wide variety of shoreline management issues commonly facing lake managers. Data collection focused on filling “white holes” often identified in geospatial data sets, including lack of information on shore protection structures, docks, condition of riparian vegetation, ecological health or condition, and scenic resources.

Shoreline features were mapped at representative shorelines using a combination of: 1) GPS mapping using a Trimble Juno SB unit; 2) offset mapping using the Trimble Juno SB paired with the LTI Laser Rangerfinder (TruPulse 360 B) (both have Bluetooth capabilities); and 3) videomapping using Red Hen Mapping Hardware (VMS 300) and Red Hen Mapping Software (GeoVideo) along with a Sony handheld camcorder. The videomap images were then used to input shoreline features into an ArcMap database. The accuracy and location of shoreline features mapped by each method were analyzed related to aerial photography and the results of each method.

The aesthetic evaluation component used a modified version of the methodology developed in the RGIS-PN 2008 project for assessing aesthetic resources along marine shorelines. Geoserver, OpenLayers, PostGreSQL with the PostGIS extention were used to develop a web interface for viewing the videomapping output. PostgreSQL/PostGIS is a spatial database that was used to store the video mapping paths and associated attributes. Geoserver Internet map servering software that was used to serve the PostgreSQL/PostGIS data as maps over the Internet. OpenLayers is a javascript library that was used for displaying the map and spatial data in a web browser.

Videos were converted from mpg format to flash video (flv) format to allow for smaller size and easier manipulation in a web browser. Flowplayer was used to display the flv videos in the web browser and OpenLayers along with Geoserver where used to display the map with the route of the video. In order to display a location on the map to correspond to the time/location in the video, a temporary layer is used that changes location each second as the video plays. This is done by creating a query to query the PostGreSQL database to find the point in the path layer on the map that holds the same time variable as the current time in the video.

A slider evaluation bar was also inputed to allow users to rate the scene they are viewing by either a Likert based scale of attactiveness (for aesthetic evaluations) or rapid natural assessment criteria gleaned from the literature (e.g. Pritchard, 1999; Stevensen and Mills, 1999; Hu et al., 2003). The shoreline images are also broken into reach segments that can be tied to digital field data forms to input professional assessments of ecological conditions.

The results of the surveys are automatically georeferenced, and can be used to rank-order views on the basis of scenic preference. In addition, the results of the scenic preference survey can be analyzed in conjunction with physical, biological, and cultural characteristics for each shoreline segment obtained from existing GIS databases compiled by RGIS-PN as part of a decision support system for lake assessment developed with the Washington Department of Ecology (Donoghue et al., 2006).

SoundMap: Puget Sound Public Resource Mapping Project

In Washington State, as in many other states, cities and counties are compelled by state law to develop shoreline management plans for shorelines of state-wide significance. The Washington Shoreline Management Act requires local jurisdictions to create comprehensive plans that establish appropriate shoreline uses, protect environmental resources, and ensure public access to shorelines. The heavily populated Puget Sound has especially been a management priority; in 2005 Washington State’s Governor Gregoire established the Puget Sound Partnership to protect the second largest estuary in the U.S., with the express goal of “identifying significant ecosystem problems, evaluate potential solutions, and restore and preserve critical nearshore habitat” (Nyerges et al., 2007).

As a related initiative, the Puget Sound Nearshore Ecosystem Restoration Project is a collaborative effort between the U.S. Corps of Engineers, the Washington Department of Fish and Wildlife, and other state and federal agencies, tribes, industries, and environmental organizations. Most comprehensive planning laws require the involvement of the public in the decision making process. As a result, jurisdictions have begun to explore collaborative methods of planning (Koontz, 2005). Collaboration shifts power away from planning practices that are dominated by expert planners and government officials, and relies more upon community members. Most existing data related to shoreline management is developed by experts at government agencies (Talen, 2000).

In addition to existing expert data, local knowledge from residents is needed to fill data gaps in large state-wide datasets and create data related to specific local concerns. Internet technology is increasingly being used to document local knowledge in a geospatial context for use in environmental planning (Carver, Evans, Kingston, and Turton, 2001; Cordner, 2007; Hall and Leahy, 2006; Rantanen and Kahila, 2009).

To facilitate the incorporation of local knowledge into shoreline management planning processes, RGIS-Pacific Northwest (PN) developed an internet-based data collection methodology that is part of a public participatory geographic information system (PGIS).

To develop the project, 1) gaps that exist in expert generated data related to shoreline environmental resources along the Puget Sound were identified through review of literature and geospatial data sources; 2) a determination was made as to which of these data can be collected using local knowledge; 3) a methodology and techniques were developed to collect these data in a spatial context over the internet with consistency and reliability, focusing on a representative pilot area along the Puget Sound, and 4) a spatial database to contain local knowledge was developed for incorporation into shoreline management and planning.

Data collection utilizes an interactive map that allows participants to digitize points, lines, or polygons representing different shoreline features using a web browser and attach attributes to those features. The internet-based PGIS was created using software that is mature and actively being developed and additionally, free and open source. The website was developed using OpenLayers for client-side mapping, Geoserver for serving spatial datasets over the internet, PostgreSQL/PostGIS for storing spatial data, and PHP for server-side scripting.

Development of an Interactive Web-based Geospatial Database for Mapping & Analyzing Volunteer Monitoring Data

Coastal managers need to incorporate socio-economic, cultural, and environmental factors, and their interactions, in a scientifically sound and timely manner (Burbridge, 1998; Westmacott, 2001). Resource managers and planners have increasingly used volunteer-based monitoring to augment data collection for a myriad of marine topics such as sediment transport and seasonal beach response (Bokuniewicz, 1981), seabird surveys (Harris et al., 2006), water quality assessment (e.g., Jackson, 2009), and assessing marine habitat diversity (Edgar and Stuart-Smith, 2009).

Besides gathering valuable information for managers, participation in volunteer monitoring efforts is often intended to also increase public awareness of environmental conditions and processes (Bokuniewicz, 1981; Gouveia et al., 2004; Jackson, 2009).

However, volunteer collected data is often dispersed and unstructured (Gouveia et al., 2004), as well as containing little spatial context, thereby limiting its utility. Information and communication technologies including GIS may be used to improve access and use of such data sets, while also facilitating data collection and analysis, as well as communication between stakeholders, thereby increasing public involvement and awareness (Gouveia et al., 2004).

A customized map viewer was developed to view the collected data in a geo-synchronized manner, including scale bars, coordinates, and zoom and pan functions. The map viewer enables the user to easily navigate and compare data from up to four different years in four separate map panels; navigational changes in one map panel are reflected in all the panels. Each map panel also includes access through a table of contents to view and compare all available years of data, allowing one to ‘customize’ the data type, position and years visible in the map frame.

In addition, the map viewer allows access to other geospatial data sets that could be used to help interpret ecological and geomorphic distributions and trends, including recent aerial photography and other geospatial datasets such as drift cell and shore protection information, geology and substrate, shoreline type, land use available through government agencies such as the Washington Department of Natural Resources, Washington Department of Ecology, and the Environmental Protection Agency. The web-based map portfolio also allows access to nearshore profile data collected through the monitoring program. These profiles are accessible through links to each sample site, and allow users to create customizable graphs to view and compare profiles for all available years of data for each site, providing a means to visualize seasonal and annual trends.

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