Identification_Information: Citation: Citation_Information: Originator: Complex Systems Research Center, University of New Hampshire Publication_Date: 20081231 Title: Impervious Surfaces in Southern York County, Maine - 2005 Edition: 1 Geospatial_Data_Presentation_Form: raster digital data Publication_Information: Publication_Place: Durham, New Hampshire Publisher: Complex Systems Research Center, University of New Hampshire Online_Linkage: Larger_Work_Citation: Citation_Information: Originator: Complex Systems Research Center, University of New Hampshire Publication_Date: 19860101 Title: NH GRANIT Database Publication_Information: Publication_Place: Durham, New Hampshire Publisher: Complex Systems Research Center, University of New Hampshire Online_Linkage: Description: Abstract: Impervious surface acreage estimates for 2005 were developed for 11 towns in southern York County, Maine. Data were developed using a combination of subpixel and traditional image classification techniques applied to Landsat 5 Thematic Mapper (TM) imagery. Additionally, road centerline data from the Maine Department of Transportation were "burned in" to the data to capture narrow, linear features where pavement exists. Impervious surface acreage is mapped in percent ranges by individual grid cell. Users may generate area estimates by factoring the cell size (8742.25 sq. ft. or .2 acres) by the low, midpoint, or high end of the assigned range. Two related data sets, Impervious Surfaces in Southern York County, Maine - 1990 and Impervious Surfaces in Southern York County, Maine - 2000, are also available. Derived from similar data and using similar techniques, they provide prior estimates of impervious surface coverage. In addition, the southern Maine impervious data sets were developed to extend existing impervious surface data sets (1990, 2000, and 2005) for 48 towns in coastal New Hampshire (also available from the GRANIT database). Collectively, these data sets provide comprehensive coverage of the towns in the Piscataqua Region Estuaries Partnership. Purpose: These data are most appropriately used at a regional scale to generate and evaluate watershed level acreage summaries. Supplemental_Information: Data distribution tile: Piscataqua Region Estuaries Partnership Area - Maine subregion - ascii grid Users of ESRI software will need the Spatial Analyst extension or GRID. To import the ascii grid in ArcView 3.x, first enable the Spatial Analyst extension. Select "Import Data Source" from the FILE menu, and select "Ascii Raster" from the dialogue window that appears. To import the ascii grid in ArcGIS 9.x, select "ASCII to Raster" from the "Import to Raster" data conversion section of ArcToolbox, select the ascii file, name the output grid, and select "Integer" for Grid Type. Development of the 2005 Impervious Surface data was funded in part by a grant from the Piscataqua Region Estuaries Partnership, as authorized by the U.S. Environmental Protection Agency pursuant to Section 320 of the Clean Water Act. Please cite as "New Hampshire GRANIT. 2008. Impervious Surfaces in Southern York County, Maine - 2005. University of New Hampshire, Durham, NH." Time_Period_of_Content: Time_Period_Information: Single_Date/Time: Calendar_Date: 20051003 Currentness_Reference: Date of TM imagery Status: Progress: Complete Maintenance_and_Update_Frequency: Irregular Spatial_Domain: Bounding_Coordinates: West_Bounding_Coordinate: -71.030201 East_Bounding_Coordinate: -70.502079 North_Bounding_Coordinate: 43.640321 South_Bounding_Coordinate: 42.048873 Keywords: Theme: Theme_Keyword_Thesaurus: None Theme_Keyword: Impervious Surfaces Theme_Keyword: Land Cover Theme_Keyword: Land Use Theme_Keyword: Water Quality Theme_Keyword: Remote Sensing Theme_Keyword: Classification Theme_Keyword: Subpixel Place: Place_Keyword_Thesaurus: None Place_Keyword: United States Place_Keyword: Northeast Place_Keyword: New England Place_Keyword: Maine Place_Keyword: Coastal Place_Keyword: Piscataqua Region Estuaries Partnership Place_Keyword: PREP Area Access_Constraints: Acknowledgment of GRANIT would be appreciated in products derived from these data. Use_Constraints: Users must assume responsibility to determine the appropriate use of these data. Because of the nature of the source imagery (30m pixels), it is not recommended that the data be used at scales greater than 1:60,000. Consult the Data Quality Section for background on the development of the data set, and the Attribute Accuracy Report for a more detailed description of the accuracy of these data. Point_of_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: Complex Systems Research Center Contact_Person: GRANIT Database Manager Contact_Position: GRANIT Database Manager Contact_Address: Address_Type: mailing and physical address Address: Morse Hall, University of New Hampshire City: Durham State_or_Province: NH Postal_Code: 03824 Country: US Contact_Voice_Telephone: 603-862-1792 Contact_Facsimile_Telephone: 603-862-0188 Contact_Electronic_Mail_Address: granit@unh.edu Hours_of_Service: 8:30AM-5PM, EST Browse_Graphic: Browse_Graphic_File_Name: Browse_Graphic_File_Description: gif image file Browse_Graphic_file_Type: gif Native_Data_Set_Environment: ESRI GRID (converted to ASCII grid for ease of transfer) Data_Quality_Information: Attribute_Accuracy: Attribute_Accuracy_Report: The standard error matrix shows an overall accuracy of 92.0% based on 100 samples. Below is a summary of User's and Producer's Accuracy for the data set: DESCRIPTION PRODUCER'S ACCURACY USER'S ACCURACY Not impervious 92.0% 92.0% Impervious 92.0% 92.0% The above error matrix reports the approximate accuracy of the results. It presents classified data results (e.g. derived from image processing) relative to reference data (e.g. data acquired via field visits or from some other source of known reliability). However, it is important to note that this standard methodology does not fully characterize the reliability of the results because the impervious surface pixels were mapped on a percentage basis. The accuracy assessment only evaluates the presence/absence of imperviousness at a given site, not the specific percentage impervious. Further, two constraints were applied during selection of the assessment sites. First, a road proximity constraint was applied (within 5 pixels or approximately 467 feet of a road centerline) to facilitate the completion of the assessment. Second, each impervious surface feature was "shrunk" by 1 pixel width prior to the selection process to exclude confusion among edge pixels. By constraining the accuracy assessment selection technique, the site selections were probably biased in favor of those areas that are most easily mapped (e.g. large parking lots, buildings, and residential subdivisions rather than single houses and isolated features). Nevertheless, the assessment provides a general estimate of the data reliability. Logical_Consistency_Report: These data are believed to be logically consistent. Completeness_Report: These data are considered complete for the 11 towns in the study area. Positional_Accuracy: Horizontal_Positional_Accuracy: Horizontal_Positional_Accuracy_Report: Georeferencing RMS less than 0.5 pixels. A geometric model was generated from the source imagery, which was then used to reference the data to New Hampshire Stateplane coordinates, NAD83. The model was derived using approximately 25-30 ground control points selected from a Landsat 5 TM reference image. Vertical_Positional_Accuracy: Vertical_Positional_Accuracy_Report: Vertical positional accuracy was not assessed. Lineage: Source_Information: Source_Citation: Citation_Information: Originator: USGS and NASA Publication_Date: 20051003 Title: Landsat 5 Thematic Mapper Edition: One Geospatial_Data_Presentation_Form: remote-sensing image Publication_Information: Publication_Place: Sioux Falls, SD Publisher: EROS Data Center, USGS Other_Citation_Details: Landsat path/row reference: path 12, row 30 Ancillary data were retrieved in 2008 from the GRANIT archive, including watershed boundaries and the National Hydrography Dataset. Additional reference data sets were obtained in 2008 from Maine state agencies, including road centerlines (Maine DOT), high resolution orthoimagery (2003 through 2005, Maine Office of GIS), and town boundaries (Maine Office of GIS). Type_of_Source_Media: CD-ROM Source_Time_Period_of_Content: Time_Period_Information: Single_Date/Time: Calendar_Date: 20051003 Source_Currentness_Reference: ground condition Source_Citation_Abbreviation: TM Source_Contribution: Basis of image processing for the classification Process_Step: Process_Description: The impervious surface mapping began by conducting a generalized, traditional supervised classification on the TM data set to generate an initial delineation of the developed/ undeveloped land features. Past mapping efforts indicated that the subpixel technique may omit certain types of impervious features, due in part to the variety of specific surface types that constitute impervious surfaces. The generalized mapping was conducted to anticipate some of these "gaps". It also provided a reference data set to supplement the visual interpretation of the subsequent subpixel classifications. ERDAS Imagine 9.2 was used to produce this first classification on a georeferenced version of the TM data. This step produced 50 clusters which were subsequently reviewed and coded as either impervious or not impervious. Some obvious misclassifications were identified in the preliminary results. Tidal flats and wetlands, shallow water and scrub-shrub wetlands most often contributed to the problematic situations. These "problem pixels" were addressed using screen editing procedures to "erase" them from the data set. After satisfactory results were obtained, the data were available for subsequent use. The ERDAS Imagine Subpixel analysis tool was then applied to derive additional estimates of "proportion of imperviousness" for each urban cell in the study area. This methodology (more fully described at www.discover-aai.com and www.erdas.com) is capable of detecting materials of interest (MOI) - in this case, impervious surfaces - that occur within each pixel. The classification describes each pixel as having a percentage of the MOI ranging from 20 to 100, reported in increments of 10%. Additional processing using road centerline data, described further below, resulted in the inclusion of the lower, 0-19% range. Note that the spatial extent of the impervious surface (the MOI) within each pixel is not identified. Rather, the entire pixel is reported as having a certain percentage of the MOI. By factoring the area of each pixel by the percent of that pixel containing the MOI, acreage summaries may be generated. The subpixel processing approach followed generally accepted techniques (Flanagan, 2000; Flanagan and Civco, 2001; ERDAS, 2000). A set of 23 potential signatures, previously generated from a Landsat 7 Enhanced Thematic Mapper (ETM+) image acquired September 27, 2000, was evaluated by running an MOI classification and displaying the results on the underlying imagery. These signatures were augmented by a set of 9 signatures derived from the 2005 image data. The results were evaluated by visual inspection to compare the classification to 1-foot GSD true color orthophotos for the area (along with the TM data set). However, it is important to recognize that the evaluation of each classification compared the presence/absence of impervious surface MOI and not the actual percentage mapped per image pixel, as we had no data to effect the latter type of comparison. Signatures were marked as "good", having "potential", or "unusable". Good signatures were those that provided tight classifications and would require little if any on-screen editing. Signatures having "potential" were those that mapped much of an area correctly, but would need some data clean up. Potential signatures were also those that could be altered using classification tolerances, (a standard feature of the subpixel classification routine), such that more or fewer image pixels would be included in the classification set. Signatures were considered "unusable" when too many pixels were included in the classification and an unreasonable amount of on-screen editing would be required to produce an acceptable data set. As a result of these signature derivations and classification tests, 24 signatures were accepted to generate the final impervious surface data set. These signatures provided a reasonable classification that could be edited to derive a provisional impervious surface data set. Unlike traditional supervised classifications, the subpixel approach typically produces classifications based on a single signature. Accordingly, 24 data sets were produced and subsequently merged into one. This was achieved by using Imagine statistical functions to select the maximum layer value (e.g. maximum percentage of imperviousness) at each pixel. The post processing phase of the project was designed to enhance the classification phase by addressing two specific issues - the correction of any remaining, obvious errors in the classification results, and the incorporation (or "burning in") of road centerline data to optimize the mapping of pavement as an impervious surface feature. The primary ancillary data set used for this phase was the Maine Department of Transportation (MEDOT) road centerline data - both public and private roads, as of May, 2008. The provisional impervious surface classification included some recurring errors - typically misclassified pixels occurring in open water, wetland and forests. The image analyst could often quickly identify these errors using pattern recognition, past experience and in some cases, DOQ reference images. Errors were removed from the classification by "erasing" these false detections using the ArcGIS Arcscan cleanup tools. Finally, the methodology included the incorporation of MEDOT public and private road data in the final product, where the imperviousness of each pixel was assigned based on the road pavement width. (Because of their relatively narrow, linear shape, road features are occasionally omitted in the classification phase.) However, no historic road database was available. Thus, an editing task was required to subset the public and private roads that existed in 2005 (largely done by comparison to the 2005 TM imagery). In addition, the private road data did not include pavement type/width. A second editing task was required to identify the surface type (paved/unpaved) of private roads. The paved roads were then subset and assigned a default pavement width of 20 ft. The pavement width characteristic was then used to "burn" the paved roads (public and private) into the classified data set. Source_Used_Citation_Abbreviation: TM Process_Date: 2008 - various Spatial_Data_Organization_Information: Direct_Spatial_Reference_Method: Raster Raster_Object_Information: Raster_Object_Type: Grid Cell Row_Count: 2290 Column_Count: 1478 Vertical_Count: 1 Spatial_Reference_Information: Horizontal_Coordinate_System_Definition: Planar: Grid_Coordinate_System: Grid_Coordinate_System_Name: State Plane Coordinate System 1983 State_Plane_Coordinate_System: SPCS_Zone_Identifier: New Hampshire Transverse_Mercator: Scale_Factor_at_Central_Meridian: 0.999967 Longitude_of_Central_Meridian: -71.666667 Latitude_of_Projection_Origin: 42.500000 False_Easting: 984250.000000 False_Northing: 0.000000 Planar_Coordinate_Information: Planar_Coordinate_Encoding_Method: row and column Coordinate_Representation: Abscissa_Resolution: 93.500000 Ordinate_Resolution: 93.500000 Planar_Distance_Units: survey feet Geodetic_Model: Horizontal_Datum_Name: North American Datum of 1983 Ellipsoid_Name: Geodetic Reference System 80 Semi-major_Axis: 6378137.000000 Denominator_of_Flattening_Ratio: 298.257222 Entity_and_Attribute_Information: Overview_Description: Entity_and_Attribute_Overview: Value codes are as follows: 0 - 0% of this grid cell is impervious 1 - 0-19% of this grid cell is impervious 2 - 20-29% of this grid cell is impervious 3 - 30-39% of this grid cell is impervious 4 - 40-49% of this grid cell is impervious 5 - 50-59% of this grid cell is impervious 6 - 60-69% of this grid cell is impervious 7 - 70-79% of this grid cell is impervious 8 - 80-89% of this grid cell is impervious 9 - 90-100% of this grid cell is impervious Entity_and_Attribute_Detail_Citation: The classification describes each pixel as having a percentage of the Material of Interest or MOI (impervious surface material) ranging from 20 to 100, reported in increments of 10%. Additional processing using road centerline data resulted in the inclusion of the 0-19% range. Distribution_Information: Distributor: Contact_Information: Contact_Organization_Primary: Contact_Organization: Complex Systems Research Center Contact_Person: GRANIT Database Manager Contact_Position: GRANIT Database Manager Contact_Address: Address_Type: mailing and physical address Address: Morse Hall, University of New Hampshire City: Durham State_or_Province: NH Postal_Code: 03824 Country: US Contact_Voice_Telephone: 603-862-1792 Contact_Facsimile_Telephone: 603-862-0188 Contact_Electronic_Mail_Address: granit@unh.edu Hours_of_Service: 8:30AM-5PM. EST Distribution_Liability: Digital data in NH GRANIT represent the efforts of the contributing agencies to record information from the cited source materials. Complex Systems Research Center, under contract to the NH Office of State Planning, and in consultation with cooperating agencies, maintains a continuing program to identify and correct errors in these data. OSP, CSRC, and the cooperating agencies make no claim as to the validity or reliability or to any implied uses of these data. Standard_Order_Process: Digital_Form: Digital_Transfer_Information: Format_Name: ASCII Grid Format_Version_Number: One Transfer_Size: 13.2 MB Digital_Transfer_Option: Online_Option: Computer_Contact_Information: Network_Address: Network_Resource_Name: Fees: No charge when downloaded from the Internet. Cost of reproduction for provision on CD/ROM of other media. Ordering_Instructions: Email GRANIT (granit@unh.edu) or order from web site (www.granit.sr.unh.edu). Turnaround: Two weeks. Technical_Prerequisites: Non Metadata_Reference_Information: Metadata_Date: 20020131 Metadata_Contact: Contact_Information: Contact_Organization_Primary: Contact_Organization: Complex Systems Research Center Contact_Person: GRANIT Database Manager Contact_Position: GRANIT Database Manager Contact_Address: Address_Type: mailing and physical address Address: Morse Hall, University of New Hampshire City: Durham State_or_Province: NH Postal_Code: 03824 Country: US Contact_Voice_Telephone: 603-862-1792 Contact_Facsimile_Telephone: 603-862-0188 Contact_Electronic_Mail_Address: granit@unh.edu Hours_of_Service: 8:30AM-5PM, EST Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata Metadata_Standard_Version: FGDC-STD-001-1998