1985lc_091508_v2-02_ctstp83.img

Metadata:

• Identification_Information
• Data_Quality_Information
• Spatial_Data_Organization_Information
• Spatial_Reference_Information
• Entity_and_Attribute_Information
• Distribution_Information
• Metadata_Reference_Information

Identification_Information:

Citation:

Citation_Information:

Originator: Center for Land use Education And Research (CLEAR)

Publication_Date: January 2009

Title: 1985lc_091508_v2-02_ctstp83.img

Edition: version 2.02

Geospatial_Data_Presentation_Form: remote-sensing image

Series_Information:

Series_Name: Connecticut's Changing Landscape Land Cover

Publication_Information:

Publication_Place: Storrs, CT

Publisher: Center for Land use Education And Research (CLEAR)

Online_Linkage:

\\NEMOWEB\D$\A\Data\LuLc\ccl_v2\CCLv2_02_091508_land_cover\1985lc_091508_v2-02_ctstp83.img

Description:

Abstract:

LANDSAT Thematic Mapper (TM) satellite imagery based land cover classification, circa 1985, for the state of Connecticut including local watersheds that intersect the state boundary, and towns in south central Massachusetts that are part of the Quinebaug and Shetucket Rivers Valley National Heritage Corridor. The classification depicts 12 land cover categories. These are: 1. Developed, 2. Turf & Grass, 3. Other Grasses 4. Agriculture 5. Deciduous Forest, 6. Coniferous Forest, 7. Water, 8. Non-forested Wetland, 9. Forested Wetland, 10. Tidal Wetland, 11. Barren Land, 12. Utility Corridors. Source Landsat TM image data were from April 26, 1985, May 4, 1988, and August 9, 1985. The classification was compiled using ERDAS Imagine 9.2 by the Center for Land use Education And Research (CLEAR) in the College of Agriculture and Natural Resources at the University of Connecticut.

Purpose:

To provide a synoptic view of general land cover for the greater Connecticut area circa 1985. The data is for general information purposes only and is not suitable for site-specific studies or litigation. The classification is intended for use in general, area-wide analysis that can tolerate the errors and inaccuracies within the data.

Supplemental_Information:

NOTE: While derived from CCL v 1.02 land cover, this land cover classification is considered an update and upgrade to CCL v 1.02 land cover. This land cover is not compatible or comparable with CCL v 1.02 land cover products.

Time_Period_of_Content:

Time_Period_Information:

Single_Date/Time:

Calendar_Date: 1985

Currentness_Reference: Time period based on satellite image collection date.

Status:

Progress: Complete

Maintenance_and_Update_Frequency: Unknown

Spatial_Domain:

Bounding_Coordinates:

West_Bounding_Coordinate: -73.755861

East_Bounding_Coordinate: -71.737841

North_Bounding_Coordinate: 42.313836

South_Bounding_Coordinate: 40.936281

Keywords:

Theme:

Theme_Keyword_Thesaurus: FGDC

Theme_Keyword: Land Cover

Theme_Keyword: Land Use

Theme_Keyword: Remote Sensing

Theme_Keyword: Classification

Theme_Keyword: LANDSAT

Theme_Keyword: Thematic Mapper

Theme_Keyword: Satellite Imagery

Place:

Place_Keyword: Connecticut

Place_Keyword:

Quinebaug and Shetucket Rivers Valley National Heritage Corridor

Access_Constraints: None

Use_Constraints:

These data are the intellectual property of the Center for Land use Education And Research (CLEAR) at the University of Connecticut. They may be used for educational and non-commercial purposes provided proper attribution is given. CLEAR permits but does not support secondary distribution of this data. CLEAR is committed to offering users accurate, useful, and current information about the state. Although every effort has been made to ensure the accuracy of information, errors and conditions originating from the source data and processing may be reflected in the data supplied. The user must be aware of data conditions and bear responsibility for the appropriate use of the information with respect to possible errors, original map scale, collection methodology, currency of data, and other conditions specific to this data.

Point_of_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Sandy Prisloe

Contact_Organization:

Center for Land use Education And Research (CLEAR), The University of Connecticut

Contact_Position: Geospatial Extension Specialist

Contact_Address:

Address_Type: mailing address

Address: 1066 Saybrook Road, PO Box 70

City: Haddam

State_or_Province: Connecticut

Postal_Code: 06432-0070

Country: United States

Contact_Voice_Telephone: (860) 345-4511

Contact_Facsimile_Telephone: (860) 345-3357

Contact_Electronic_Mail_Address: sandy.prisloe@uconn.edu

Hours_of_Service: 9:00 - 5:00 Eastern Standard Time

Native_Data_Set_Environment:

Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 9.3.1.1850

Cross_Reference:

Citation_Information:

Originator: Center for Land use Education And Research (CLEAR)

Publication_Date: January 2009

Title: 1985 Land Cover, Greater Connecticut

Edition: version 2.02

Geospatial_Data_Presentation_Form: map

Series_Information:

Series_Name: Connecticut's Changing Landscape Land Cover

Publication_Information:

Publication_Place: Storrs, CT

Publisher: Center for Land use Education And Research (CLEAR)

Online_Linkage: <http://clear.uconn.edu>

Data_Quality_Information:

Lineage:

Process_Step:

Process_Description:

CLOUD REMOVAL: The April 26, 1985 Landsat TM image contained some cloud and cloud shadows that covered some regions in the northwest portion of Connecticut. To remove these, the affected areas were extracted and substituted with a May 4, 1988 Landsat TM scene. This scene was chosen because it was the highest quality (fewest clouds) image close to the 1985 date available in the CLEAR image data archive. Most of the area covered by clouds was forested land that did not experience change between 1985 and 1988.

Process_Date: 2002

Process_Contact:

Contact_Information:

Contact_Person_Primary:

Contact_Person: James Hurd

Contact_Organization:

Center for Land use Education And Research (CLEAR), The University of Connecticut

Contact_Position: Research Associate

Contact_Address:

Address_Type: mailing address

Address: The University of Connecticut

Address: U-4087, Room 308, 1376 Storrs Road

City: Storrs

State_or_Province: Connecticut

Postal_Code: 06269-4087

Country: United States

Contact_Voice_Telephone: (860) 468-2840

Contact_Facsimile_Telephone: (860) 486-5408

Contact_Electronic_Mail_Address: james.hurd_jr@uconn.edu

Hours_of_Service: 9:00-5:00 Eastern Standard Time

Process_Step:

Process_Description:

ROAD NETWORK: Identification of major and local roads was necessary to adequately quantify land cover change and is critical to successful application of landscape characterization models such as forest fragmentation, development (urban) growth, and estimating impervious surfaces. In order to capture roads, vector (line) road data (circa 1986) from the Connecticut Department of Environmental Protection were used to extract image data from the TM scene. All paved roads were selected from the vector layer and converted to pixels the same size of the source imagery (100 feet). This layer was then buffered 5 pixels on either side of the road to account for areas of misalignment between the road layer and Landsat image data. All image pixels contained within the 5 pixel buffer area were extracted for analysis (Figure 2a). The intent was to focus on the classification of roads by creating an image that minimized non-road pixels. Sub-pixel classification (SPC) was used to classify road pixels. The SPC is a supervised classifier that enables the detection of materials of interest (MOIs) as whole or fractional pixel composition, with a minimum detectable threshold of 20 percent and in increments of 10 percent (i.e., 20-30%, 30-40%, … 90-100%). Because of tonal variations in the built landscape, MOIs representing different brightness classes of road and paved surfaces (i.e. dark, medium, and bright surfaces) were selected. Any pixel identified by the SPC as a paved surface, regardless of its percent composition (20% or greater), was considered a developed pixel. Final results of the SPC did not fully extract the road network. Those buffered pixels not identified as developed through the SPC technique were extracted for further evaluation using knowledge-based classification (KBC) . Bands 4 (near-infrared) and 5 (mid-infrared) were used because, together, they showed the most contrast between developed pixels and other non-developed pixels. Using KBC, a rule was created that identified developed pixels as having digital numbers (reflectance values) between 129 and 143 in band 4 and between 128 and 193 in band 5. In addition, a pixel had to be contained within the actual rasterized road layer so not to include other land cover features such a barren areas. The result of this procedure was the identification of additional developed pixels not identified using SPC. The SPC and KBC still, unfortunately, did not extract the full extent of the road network. To correct for this problem, the rasterized road layer was embedded with the final classification. Onscreen digitizing was conducted to remove areas of misalignment. While this may appear to be a step backward, the pixels identified as developed using SPC and KBC were an invaluable resource in determining the true road alignment that is critical to an accurate land cover map. The pixels also identified developed features within the buffered image that were not part of roads. The same techniques were used on the August 9, 1985 image covering the southeast portion of the analysis area.

Process_Date: 2002

Process_Step:

Process_Description:

CLASSIFICATION: Pixels identified as developed in the previous step were eliminated from the 1985 Landsat TM image. An area of approximately 18 x 10 miles along the central coast of Connecticut was subset from the overall analysis area for deriving classification signature statistics. This area was selected because it contained a significant amount of all categories identified in the classification scheme. ISODATA classification was performed generating 100 signature clusters. These clusters were identified as belonging to one of the land cover categories. Maximum likelihood classification was applied to the entire analysis area for each class using selected signatures with a distance image as output. In the distance image, pixel values represent the spectral distance from the class signature where the lower the value, the more similar a pixel is to that specific class signature. For most classes, visual examination of the distance image with the TM image resulted in the identification of a threshold used with the Knowledge Engineer to derive a complete land cover image. This method was adequate for all classes but two: tidal wetlands and bare farm fields. In April, both of these land cover features have little green, growing vegetation and, in a satellite image, look very similar to other land cover features lacking vegetation such as quarries, beaches, and concrete. A previous land cover project for Connecticut based on satellite imagery from both spring and summer was used to identify tidal wetlands and agricultural fields. The methodology was successful at identifying tidal wetlands and agricultural fields because, unlike quarries, beaches, and concrete, both tidal wetlands and agricultural fields usually have vegetation in the summertime. Those pixels that remained unclassified were extracted from the TM image and ISODATA classification was performed. The clusters were identified as belonging to one of the land cover categories. All classification layers were then merged to create a single classified image with all pixels belonging to a single category.

Process_Date: 2002

Process_Step:

Process_Description:

CLASSIFICATION CLEAN-UP: Several steps were taken to "clean-up" the classification: A digital elevation model (USGS National Elevation Dataset) was used to identify areas classified as wetlands in areas with steep northwest facing slopes. Using the Knowledge Engineer, any pixel identified as non-forested or forested wetlands that fell on a slope of 12 degrees or more was reassigned to deciduous forest. A 12 degree slope threshold was selected following visual examination of the image, DEM data, existing wetlands, and corresponding slopes calculated from the DEM. Several majority filters were used to eliminate isolated pixels resulting in a more uniform classification. Utility right-of-ways were added because they can be considered significant fragmenting features to the forest landscape. They were digitized onscreen from the forest classes only. Additional forested wetlands were derived from pixels classified as forest but identified as wetland on the rasterized versions of GIS hydrography data available from CT DEP, Mass GIS and Westchester County GIS. Lastly, extensive on-screen digitizing was used to remove any remaining apparent errors.

Process_Date: 2002

Process_Step:

Process_Description:

DATA REVISION: Errors in how the analysis area was clipped were discovered in the 1985 land cover image version 1.01. The clip layer consists of the Connecticut state boundary, Massachusett towns that are part of the Quinebaug and Shetucket Rivers Valley National Heritage Corridor, and interecting local watershed boundaries. The problem existed for those areas outside the Connecticut state boundary and Massachusett towns due to the local watershed layer containing an X and Y shift. The result is that some areas were erroneously excluded from analysis. Landsat data was re-clipped using a corrected local watershed layer, classified, and fused with the original (version 1.01) land cover image.

Process_Date: 2002

Process_Step:

Process_Description:

NEW FOR VERISON 2.02 ----- INCLUSION OF AGRICULTURAL FIELDS: Five existing land cover maps (1992 MRLC, 2000 NLCD, GAP, LERIS 1990, and LERIS 1995) for Connecticut were compared to identify agricultural areas. Where three or more of these land cover maps agreed, and the CCL 1985 land cover map identified Other Grasses, then the pixels were relabeled as Agricultural Fields. These agricultural areas were compared to NAIP high resolution color imagery collected in 2006 and to the original 1985 Landsat image to determine if the area was agriculture. Any errors were identified and labeled appropriately.

Process_Date: 2007-2008

Process_Step:

Process_Description:

NEW FOR VERISON 2.02 ----- CONVERSION OF DEVELOPMENT TO VEGETATION: Due to the process of classifying multiple years of Landsat image data that make up the Connecticut's Changing Landscape dataset, and following the assumption that the devloped category will not convert to other land cover categories over time, it was found that the developed category was being over estimated, particularly in the highly urbanized areas. To reduce the amount of development classified, pixels identified as development in the most recent Landsat data (from 2006) were extracted and reclassified as either development, turf & grass, or deciduous forest. These were then embedded in each of the five dates of land cover (1985, 1990, 1995, 2002, 2006). The result was a better representation of the development and vegetative patterns in the land cover maps, particularly in the highly urbanized areas.

Process_Date: 2008

Process_Step:

Process_Description: Metadata imported.

Source_Used_Citation_Abbreviation:

D:\A\Data\LuLc\ccl_v2\CCLv2_02_091508_land_cover\metadata\1985lc_091508_v2-02_ctstp83.img.xml

Process_Date: 20090203

Process_Time: 11303700

Spatial_Data_Organization_Information:

Direct_Spatial_Reference_Method: Raster

Raster_Object_Information:

Raster_Object_Type: Pixel

Row_Count: 5004

Column_Count: 5459

Vertical_Count: 1

Spatial_Reference_Information:

Horizontal_Coordinate_System_Definition:

Planar:

Map_Projection:

Map_Projection_Name: Lambert Conformal Conic

Lambert_Conformal_Conic:

Standard_Parallel: 41.200000

Standard_Parallel: 41.866667

Longitude_of_Central_Meridian: -72.750000

Latitude_of_Projection_Origin: 40.833333

False_Easting: 999999.999996

False_Northing: 499999.999998

Planar_Coordinate_Information:

Planar_Coordinate_Encoding_Method: row and column

Coordinate_Representation:

Abscissa_Resolution: 100.000000

Ordinate_Resolution: 100.000000

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:

Detailed_Description:

Entity_Type:

Entity_Type_Label: 1985lc_091508_v2-02_ctstp83.img.vat

Attribute:

Attribute_Label: ObjectID

Attribute_Definition: Internal feature number.

Attribute_Definition_Source: ESRI

Attribute_Domain_Values:

Unrepresentable_Domain:

Sequential unique whole numbers that are automatically generated.

Attribute:

Attribute_Label: Value

Attribute_Definition: Class numerical identifier (see class name description)

Attribute:

Attribute_Label: Red

Attribute_Definition: Red class color value (0-255)

Attribute:

Attribute_Label: Green

Attribute_Definition: Green class color value (0-255)

Attribute:

Attribute_Label: Blue

Attribute_Definition: Blue class color value (0-255)

Attribute:

Attribute_Label: Count

Attribute_Definition: Number of pixels identified as a class feature

Attribute:

Attribute_Label: Class_names

Attribute_Definition: Class name

Attribute_Domain_Values:

Enumerated_Domain:

Enumerated_Domain_Value: 1. Developed

Enumerated_Domain_Value_Definition:

High-density built-up areas typically associated with commercial, industrial and residential activities and transportation routes. These areas can be expected to contain a significant amount of impervious surfaces, roofs, roads, and other concrete and asphalt surfaces.

Enumerated_Domain:

Enumerated_Domain_Value: 2. Turf & Grass

Enumerated_Domain_Value_Definition:

A compound category of undifferentiated maintained grasses associated mostly with developed areas. This class contains cultivated lawns typical of residential neighborhoods, parks, cemeteries, golf courses, turf farms, and other maintained grassy areas. Also includes some agricultural fields due to similar spectral reflectance properties

Enumerated_Domain:

Enumerated_Domain_Value: 3. Other Grasses

Enumerated_Domain_Value_Definition:

Includes non-maintained grassy areas commonly found along transportation routes and other developed areas, and within and surrounding airport properties. Also likely to include forested clear-cut areas, and some abandoned agricultural areas that appear to be undergoing conversion to woody scrub and shrub cover.

Enumerated_Domain:

Enumerated_Domain_Value: 4. Agricultural Fields

Enumerated_Domain_Value_Definition:

Includes areas that are under agricultural uses such as crop production and/or active pasture. Also likely to include some abandoned agricultural areas that have not undergone conversion to woody vegetation.

Enumerated_Domain:

Enumerated_Domain_Value: 5. Deciduous Forest

Enumerated_Domain_Value_Definition:

Includes southern New England mixed hardwood forests. Also includes scrub areas characterized by patches of dense woody vegetation. May include isolated low density residential areas.

Enumerated_Domain:

Enumerated_Domain_Value: 6. Coniferous Forest

Enumerated_Domain_Value_Definition:

Includes southern New England mixed softwood forests. May include isolated low density residential areas.

Enumerated_Domain:

Enumerated_Domain_Value: 7. Water

Enumerated_Domain_Value_Definition: Open water bodies and watercourses with relatively deep water.

Enumerated_Domain:

Enumerated_Domain_Value: 8. Non-forested Wetland

Enumerated_Domain_Value_Definition:

Includes areas that predominately are wet throughout most of the year and that have a detectable vegetative cover (therefore not open water). Also includes some small water courses due to spectral characteristics of mixed pixels that include both water and vegetation.

Enumerated_Domain:

Enumerated_Domain_Value: 9. Forested Wetland

Enumerated_Domain_Value_Definition:

Includes areas depicted as wetland, but with forested cover. Also includes some small water courses due to spectral characteristics of mixed pixels that include both water and vegetation.

Enumerated_Domain:

Enumerated_Domain_Value: 10. Tidal Wetland

Enumerated_Domain_Value_Definition:

Emergent wetlands, wet throughout most of the year, with distinctive marsh vegetation and located in areas influenced by tidal change.

Enumerated_Domain:

Enumerated_Domain_Value: 11. Barren

Enumerated_Domain_Value_Definition:

Mostly non-agricultural areas free from vegetation, such as sand, sand and gravel operations, bare exposed rock, mines, and quarries. Also includes some urban areas where the composition of construction materials spectrally resembles more natural materials. Also includes some bare soil agricultural fields.

Enumerated_Domain:

Enumerated_Domain_Value: 12. Utility Corridors

Enumerated_Domain_Value_Definition:

Includes utility corridors. This category was manually digitized on-screen from corridors visible in the Landsat satellite imagery. The class was digitized within the deciduous and coniferous categories only.

Attribute:

Attribute_Label: Opacity

Attribute_Definition: Transparency level of class feature (0-1)

Attribute:

Attribute_Label: Acres

Attribute_Definition: Area of land cover feature.

Attribute:

Attribute_Label: Sq mi

Attribute_Definition: Area of land cover feature.

Overview_Description:

Entity_and_Attribute_Overview:

The 12 land cover categories represent general land cover features as they existed during the time of the Landsat Thematic Mapper image collection. These categories were selected based on the constraints of the source imagery, but also on the goals of the project. By maintaining general land cover categories, it can be expected that thematic accuracy will be higher.

Distribution_Information:

Distributor:

Contact_Information:

Contact_Person_Primary:

Contact_Person: Sandy Prisloe

Contact_Organization:

Center for Land use Education And Research (CLEAR), The University of Connecticut

Contact_Position: Geospatial Extension Specialist

Contact_Address:

Address_Type: mailing address

Address: 1066 Saybrook Road, PO Box 70

City: Haddam

State_or_Province: Connecticut

Postal_Code: 06438-0070

Country: United States

Contact_Voice_Telephone: (860) 345-4511

Contact_Facsimile_Telephone: (860) 345-3357

Contact_Electronic_Mail_Address: sandy.prisloe@uconn.edu

Hours_of_Service: 9:00-5:00 eastern Standard Time

Resource_Description: Downloadable Data

Standard_Order_Process:

Digital_Form:

Digital_Transfer_Information:

Format_Name: ERDAS IMAGINE

Format_Version_Number: ERDAS IMAGINE 9.2

Format_Information_Content:

Data can be downloaded for the entire analysis area, within Connecticut boundary, or by Connecticut Planning Region

File_Decompression_Technique: ZIP file

Transfer_Size: 0.000

Fees: Free

Ordering_Instructions:

Go to <http://clear.uconn.edu/projects/landscape/download.asp>
Fill out the online Registration Form to access the download page.

Metadata_Reference_Information:

Metadata_Date: 20090203

Metadata_Contact:

Contact_Information:

Contact_Organization_Primary:

Contact_Organization:

Center for Land use Education And Research (CLEAR), The University of Connecticut

Contact_Person: James Hurd

Contact_Position: Research Associate

Contact_Address:

Address_Type: mailing address

Address: The University of Connecticut

Address: U-4087, Room 308, 1376 Storrs Road

City: Storrs

State_or_Province: Connecticut

Postal_Code: 06269-4087

Country: United States

Contact_Voice_Telephone: (860) 486-2840

Contact_Facsimile_Telephone: (860) 486-5408

Contact_Electronic_Mail_Address: james.hurd_jr@uconn.edu

Hours_of_Service: 9:00 - 5:00 Eastern Standard Time

Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata

Metadata_Standard_Version: FGDC-STD-001-1998

Metadata_Time_Convention: local time

Metadata_Extensions:

Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>

Profile_Name: ESRI Metadata Profile