The impacts of this increase in sea level, will vary from place-to-place and depend on a range of factors, including the human response. To initiate a national assessment of sea level rise impacts, the U.S. Environmental Protection Agency (EPA) is working with state, county, and local officials to identify the lands likely to receive shoreline protection. Those judgments incorporate state policies and regulations, local concerns, land-use data, and general planning judgment. The resulting data distinguishes areas likely to receive shoreline protection (e.g., beach nourishment and armoring with seawalls or dikes) from the areas where shores will probably retreat naturally, either because the cost of holding back the sea is greater than the value of the land, or because there is a current policy of allowing the shore to retreat. This data should be used in conjunction with information contained in the corresponding planning report ("Assessment of Sea Level Rise Response Scenarios in New York").
Through the development of data on the likelihood of shoreline protection, this research seeks to (1) improve future assessments of the impacts of climate change through incorporation of a richer understanding of local land use policies and trends; (2) improve the understanding among federal, state, and local levels of government on the effect of current coastal policies on coastal development and conservation; and (3) identify opportunities for policy refinement to facilitate a more efficient response to rising seas that limits the impact on coastal property, wetlands, and recreational resources.
For more information on the goals of the study and this data set, please refer to the Introduction section of the report.
Users should display wetlands and the outside-of-study-area layers on top of this data set. This study generally focused on dry land that is either below the 3.5 meter contour or within 1000 feet of the shore. In the case of Nassau County, however, the study area was limited to dry land within the 500 year floodplain (as a result of the limited data provided by the County). The response data for lands located outside of the study area or beneath non-tidal wetlands is typically misleading and has not been reviewed. Wetlands data and the outside-of-study-area data layers are available separately.
For additional information on sea level rise planning, see EPA publications available at: <http://risingsea.net/ERL> or <http://risingsea.net/ERL/NY.html> or <http://plan.risingsea.net>
For Suffolk and Nassau County, the counties' parcel data served as the core data source (Suffolk's data has a scale of 1:2,400 and Nassau's data has a scale of 1:800). The state wetland data has a scale of 1:2,400. Stakeholder review changes were implemented using the existing boundaries of the parcel data. A small number of final review changes required site-specific editing of the existing polygons; however, there were a minimal number of these changes and the resulting scale of the data should not have been degraded significantly. We recommend that users treat both the data for these counties as having a scale of better than 1:24,000.
For the five New York City Boroughs (Kings, Queens, Manhattan, Staten Island, and Bronx), we used 1995 Land Use data with a scale of 1:66,360. The state wetland data has a scale of 1:2,400. Stakeholder and final review changes were generally implemented using the existing boundaries of the land use data. A small number of final review changes were made based on hand edits made on 1:100,000 scale maps; with changes generally based on road layers with a scale of 1:24,000 or better. Therefore, we recommend that users treat the data for New York City as having a scale better than 1:100,000 or better.
For Westchester County, we used 1996 Land Use data provided by the county, which has a scale of 1:24,000. The state wetland data has a scale of 1:2,400. Stakeholder and final review changes were generally implemented using the existing boundaries of the land use data. A small number of final review changes were made based on hand edits made on 1:100,000 scale maps; however, these edits were not sufficiently numerous so as to deteriorate the scale to worse than 1:50,000. Therefore, we recommend that users treat both these data sets as having a scale of 1:50,000 or better.
The first step in creating the draft maps was to define the study area. The intention was to include all dry lands either below the 20-foot elevation contour from the USGS 1:24,000 scale maps, or within 1000 feet of the shore (to account for possible erosion). Although the study area might seem over inclusive, the authors do not want the study to be limited to a specific estimate of projected rise in sea levels; instead, the results of the sea level planning studies should apply to the general impact of sea level rise regardless of the extent. Nevertheless, the authors lacked a readily available data set based on the USGS 20-foot contour when they began the study. Therefore, for New York City and Suffolk County, Daniel Hudgens of Industrial Economics provided a study-area based on the 3.5-meter contour from Titus and Richman (2001) plus all land within 1000 feet of the tidal wetlands. Jue Wang of ICF Incorporated later provided as mask based on the 20-foot USGS contour for Westchester County, which was undertaken last.
The Nassau County study area, was defined by all areas within the 500-year flood plain. The study area for this county was more limited because the parcel data provided by the county was limited to the flood plain.
To better understand New York's likely sea level rise responses, Jay Tanski researched relevant laws and regulations and conducted interviews with state and local managers and planners familiar with coastal regulations as well as land use patterns and trends. Managers received an overview and summary of the project purpose and goals prior to the meetings.
Tanski asked the managers to consider lands potentially vulnerable to sea level rise on a relatively generic basis. To focus discussions during the interview, he provided digital maps depicting inundation zones associated with Category 1, 2, and 3 hurricanes based on the SLOSH numerical model developed by the National Weather Service to indicate areas already vulnerable to flooding and erosion hazards.
Consultations revealed which factors determined lands likely be protected versus those likely to be abandoned as sea level rises. Also, they highlighted area-specific concerns and provided direction as to where potential modifications were advisable in relation to what geospatial information suggested.
Statewide land use data that provided the resolution and level of detail needed for this analysis was not readily available during the time of the study. The most up to date and comprehensive information was collected and maintained at the county level.
For Nassau County, shoreline protection designations were based on parcel centroids (point files) that identified public versus private lands and land use. Consequently, developed areas were interpolated using the location of the parcel centroids in relation to existing polygon layers (delineating parks, buildings, roads, and other planimetric features).
Shoreline protection designations for New York City (boroughs of Brooklyn, Queens, Manhattan, Staten Island, and Bronx) were based on a 1995 land use map provided by the New York City Department of City Planning. In order to transfer the map (stored as a .tif file) into a workable GIS layer, the map was first digitized using a large format, 2400dpi UMAX Scanner and then rectified using ESRI's Network Analyst software. Where necessary, information on vacant parcel ownership was obtained manually through the New York City Open Accessible Space Information System (http://www.oasisnyc.net).
For Suffolk County and Westchester County, Jay Tanski was able to use the data provided by the counties without further modification. He differentiated the shoreline protection designations based upon the land use categories provided by the data.
Initially, when mapping the sea level rise responses Jay Tanski used three sea level rise scenarios (except for Westchester County). The first scenario identifies lands for which local policies and practices allow protection. The second identifies land that planners feel is likely to be protected. The third scenario uses the second scenario as a starting point, but assumes greater efforts would be undertaken to preserve natural resources (e.g., tidal wetlands) or protect historical structures.
All lands within the study area were assigned a protection designation based on applying the aforementioned "decision rules" to the available GIS layers. These "decision rules" (as outlined in Process Step 2) were the product of the planners' general assumptions regarding land use development and protection efforts (please note that these rules do not represent their official position on the likelihood of protection for specific areas).
Wetlands data for the New York shoreline were provided by two sources, the New York State Department of Conservation (NYSDEC) and New York State Department of State (NYSDOS). The NYSDEC wetland data only includes the areas from Moriches Bay to Montauk on the south shore and Gardiners Bay between the forks. NYSDOS maps highlighted wetlands along the south shore estuary. Although Westchester County provided its own wetlands data on its county data clearinghouse webpage, it originates from the same wetland maps used by NYSDEC. Upon data capture, wetlands information was clipped and reflected onto the study area.
Specific data sets and the procedures used for processing and analyzing the information are described in greater depth for each county in the appropriate section of the planning report.
In 2001, the EPA project manager realized that it would be possible to display all three scenarios on a single map, without losing any information, because the lands protected in scenario 3 were always protected in scenario 2, and the lands protected in scenario 2 were always protected in scenario 1. Therefore, the Project Manager defined lands protected in all three scenarios as "shore protection almost certain"; lands protected under scenarios 1 and 2 as "shore protection likely", and lands protected under scenario 1 as "shore protection unlikely." Lands not protected under any scenario were defined as "no protection". Although the interviews were conducted in [year], New York Seagrant?s contract with Industrial Economics for Suffolk, Nassau, and New York City was based on the pre-2001 formulation of the study. During 2004, based upon guidance from Daniel Hudgens of Industrial Economics, Tanski modified the maps to use a single map with multiple colors that represent the varying likelihoods of shoreline protection. For more details, users should refer to the planning report. The Westchester County portion of the study was conducted in 2004.
Jay Tanski conducted an additional consultation with relevant planners at the county level to review the final response map and draft report. Prior to the review, all parties received and reviewed copies of the draft report and map. These consultations verified previous modifications and, in some cases, provided further changes to reflect recent development.
To implement the stakeholder review changes, Jay Tanski selected the individual parcel or land use polygons identified by the planners and then revised the attributes as necessary.
For all localities with the exception of Nassau County, Jay Tanski provided Kevin Wright of ICF Consulting with the source data and ArcView project that identified the approach used to produce the maps.
For Nassau County, data license agreements prevented sharing the raw data. As a result, Tanski converted the resulting response maps for this County into a raster image and then provided this as a single layer to Wright. [Specify cell size of the raster image.]
During this step, the EPA project manager performed a final review of the GIS data and planning report. This review sought to identify map changes that were still needed. These changes usually involved cases where the requested stakeholder review changes had not been implemented correctly, or the GIS data failed to recognize recent development or newly planned development and the resulting map showed an area as less likely to be protected than anticipated (for example, a recent development might show as unlikely to be protected because the land use data did not reflect the presence of residences that would likely protect their land if ever threatened).
Brit Poole and Kevin Wright of ICF Consulting made the necessary edits and incorporated the data into the GIS project. To implement these changes, Poole and Wright selected the associated polygon(s) that existed within the area and revised the likelihood of protection identified in the layer attributes. Afterwards, they added the new layers to the county project. When the boundaries of the site-specific change did not overlap with the boundaries of land use polygons, they used ArcGIS's edit functions. All edits were then implemented through heads-up digitizing using ArcGIS software.
The fact that the review took place at a scale of approximately 1:100,000 could potentially reduce the resolution of our maps, if the reviewer changes were not as precise as the 1/50 inch assumed by National Map Accuracy Standards. We do not believe that the deterioration was significant. The types of changes that the officials sought were generally for relatively large areas corresponding to the size of parks and new communities. The primary source of error for these maps is not the precision of well-defined boundaries, but rather the uncertainty of how land use will evolve in undeveloped areas.
Kevin Wright and Brit Poole of ICF Consulting developed several geoprocessing models, using ESRI's Model Builder, to "flatten" the data into single state-wide files. The process of flattening the data involves combining or unioning each of the source data layers together to create the single file.
The models take the data layers that collectively create a state's sea level rise protection scenarios and flatten them into a single file. During the flattening process, all files are projected into an appropriate projection for the state. The models assign common attributes of shore protection, an appropriate source, whether or not it is military owned land, county name, state name, and if it is to override wetland data. Counties are flattened individually and then another model is used to combine all counties into a single state layer. Any edits that have been made to the protection scenarios are flattened and all attributes are verified.
Using this "flattened data", ICF created 1:100,000 "comparison maps" for the EPA manager to review. Those maps explicitly highlighted areas that had been erroneously masked (as wetland or high ground) during previous phases of the study, and hence not received the same level of scrutiny as most of the study area. We refer to areas erroneously excluded from the study area as ?unveiled? because they were erroneously masked. The comparison maps included 1:24,000 TIGER road layer data.
The project manager examined the comparison maps and made corrections for three reasons
First, , these maps used the out-of-study-area mask provided with this data set.((see data at <http://maps.risingsea.net/data.html>). The new data unveiled areas that had been covered by the draft elevation. The original mask was the 3.5-m contour from a 1:250,000 data set, while the new mask was based upon a 20ft contour from a 1:24,000 data set. . Unlike the other states, Tanski clipped his data along the outside of study area boundary. Therefore, no additional information was ?unveiled? with the corrected study area mask. [Is that true with NYC?]. Therefore, in most cases, the unveiled areas show as ?not considered?.
Second, projection shifts caused the study area to often be substantially narrower than 1000 feet in areas of high ground. The project manager examined gave these ?unveiled? areas scrutiny as well.
With a focus on the unveiled areas, the project manager looked for lands that would not be protected due to our decision rules?or showed up as not consideredbut would be inherently protected by the protection of nearby lands. For example, if a land area were shown as unlikely to be protected but surrounded by land almost certain to be protected, then the protection level for the surrounded polygon would be set to ?protection certain? to match the nearby area. If an area was on high ground (and thus only at risk of erosion), then land inland of areas likely to be protected are?at the very least?likely to be protected Along relatively high ground shores, where erosion is the primary risk, protecting shorefront developed lands has the direct effect of protecting undeveloped inland farms, whether or not protection is otherwise expected for that land use category. In lower areas, lands can be submerged from the back side even if shorefront homes are protected. For those areas, he edited the protection designation only if a polygon is entirely surrounded by land that are more likely to be protected.
Poole and Wright then implemented the final changes by selecting the corresponding polygons in the final response data and changing the source and scenario response fields accordingly.