New Jersey 1995 Level 3 Land Cover Classification

Metadata:


Identification_Information:
Citation:
Citation_Information:
Originator:
Grant F. Walton Center for Remote Sensing and Spatial Analysis (CRSSA), Rutgers University
Publication_Date: 20001017
Title: New Jersey 1995 Level 3 Land Cover Classification
Online_Linkage: http://www.crssa.rutgers.edu/projects/lc/
Larger_Work_Citation:
Citation_Information:
Title:
This product is one in a series of three, the other two being NJ 1984 level 3 land cover and NJ 1972 level 1 land cover.
Description:
Abstract:
Land use and land cover are two approaches for describing land.  Land use is a description of the way that humans are utilizing any particular piece of land for one or many purposes.  Comparatively, land cover is the bio-physical material covering the earth's surface at any particular location.  Together land use and land cover information provide a good indication of the landscape condition and processes that are occurring at a particular place.  Time series of land use/land cover maps tell us how much of the landscape is changing, as well as what changes have occurred and where the changes are taking place.  Accurate and timely mapping of land use/land cover provides vital information on the state of the environment, development trends and wildlife habitat among others.
 
One of the most effective ways to map land use/land cover is through the use of remote sensing imagery collected from satellites and aircraft.  Remote sensing satellites orbit at hundreds of miles above the earth continually imaging the surface and transmitting the images back to ground stations for use by the research community.  This technology is an excellent medium for monitoring the condition of land throught the globe.  Photography taken from airplanes is also useful, especially where greater detail of the land surface is needed.  New satellite sensors are now approaching the detail once provided exclusively by aerial photography.  Advanced computer processing techniques allows the images to be combined with other environmental data sets to map land cover.  Mapping land use requires visual interpretation by experienced image interpreters and is a time consuming labor intensive process.  Remote sensing technology is widely used at the Grant F. Walton Center for Remote Sensing & Spatial Analysis at Rutgers University to provide data for landscape change, wildlife habitat and watershed planning, management and research.
Purpose:
In cooperation with the New Jersey Department of Environmental Protection (NJDEP) and the National Oceanic & Atmospheric Administration (NOAA), the Grant F. Walton Center for Remote Sensing & Spatial Analysis (CRSSA), Rutgers University, has completed a Land Cover Change Analysis Project for the State of New Jersey.  This project is one component of CRSSA's New Jersey Landscape Change research program (http://www.crssa.rutgers.edu/projects/lc/).  The goal of the program is to monitor New Jersey's changing landscape and provide feedback to the various local, state and federal agencies concerned with the success of failure of land use and habitat management policies in New Jersey.  The more immediate objective of this project was to develop a standardized information base on the present land cover of New Jersey and to map trends in land cover change during the 1970-1980-1990's time period.
Supplemental_Information: The land cover types are not to be taken as legally binding.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1994
Ending_Date: 1995
Currentness_Reference: publication date
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: 446196.086
East_Bounding_Coordinate: 594246.086
North_Bounding_Coordinate: 4578466.222
South_Bounding_Coordinate: 4305586.222
Keywords:
Theme:
Theme_Keyword: land cover
Theme_Keyword: satellite image classification
Theme_Keyword: change detection
Theme_Keyword: landscape
Theme_Keyword: habitat
Place:
Place_Keyword: New Jersey
Place_Keyword: Middle Atlantic States
Place_Keyword: United States
Temporal:
Temporal_Keyword: 1995
Temporal_Keyword: 1994
Access_Constraints: None.
Use_Constraints:
While efforts have been made to ensure that these data are accurate and reliable within the state of the art, Rutgers University cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. Rutgers University makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.  Any maps, publications, reports or any other type of document produced as a result of an associated project utilizing Center for Remote Sensing and Spatial Analysis (CRSSA), Rutgers University, data will credit the original author(s) as listed in the metadata as well as the Center for Remote Sensing and Spatial Analysis (CRSSA), Rutgers University.  Data set is not for use in litigation.
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Richard G. Lathrop
Contact_Organization:
Grant F. Walton Center for Remote Sensing and Spatial Analysis, Rutgers University
Contact_Position: Director
Contact_Address:
Address_Type: mailing and physical address
Address:
Grant F. Walton Center for Remote Sensing and Spatial Analysis
Natural Resources and Environmental Sciences Building
Cook College - Rutgers University
14 College Farm Road
City: New Brunswick
State_or_Province: New Jersey
Postal_Code: 08901-8551
Country: USA
Contact_Voice_Telephone: 732-932-1582
Contact_Facsimile_Telephone: 732-932-2587
Contact_Electronic_Mail_Address: lathrop@crssa.rutgers.edu
Hours_of_Service: M-F 8.30am to 4.30pm, US Eastern Standard Time
Data_Set_Credit:
Grant F. Walton Center for Remote Sensing and Spatial Analysis, Rutgers University
Native_Data_Set_Environment: Arc/Info, ERDAS IMAGINE
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
A "ground-truthing" field campaign to verify the accuracy of the 1994/1995 CCAP land cover map was used to assess the accuracy of the ENSP Delaware Bay/Cape May Habitat Map.  The ground truthing was undertaken at two time periods: 1) pre-classification - during the fall of 1994 and winter/spring months of 1995; 2) post-classification - during June 1997; and 3) again, post-classification - during May 2000.
During the first field campaign  314 field sites were visited to serve as accuracy assessment (240 points in the South Jersey study area and 73 points in the North Jersey study area).  These sites were visited by Rutgers University Center for Remote Sensing & Spatial Analysis personnel; one person was primarily responsible for this effort to ensure consistency. These field sites were chosen using a stratified random sampling technique.  The initial stratification was developed using the 1986 NJDEP ITU data.  A differential Global Positioning System (GPS) receiver was used to georeference the training site locations. Field notes and slides were taken for each field reference point.  High altitude color infrared aerial photography (acquired March 1991 and March 1995) was used to quality check the ground reference data in the accuracy assessment.  In some cases, the original GPS-derived location was moved slightly to a new location more closely correspond with the field note description and ground photo.
Two additional field campaigns were undertaken subsequent to the classification process. The southern New Jersey study area was assessed during June 9-12, 1997 and the northern New Jersey study area during May 15-17, 2000. A validation team from the NOAA Coastal Services Center participated in each data verification exercise.  The team was equipped with 2 portable color laptop computers linked to real-time differentially corrected Global Positioning System (GPS) receivers.  The field station runs software that supports the classified data as a raster background with the road network as a vector overlay with a simultaneous display of live GPS coordinates.  Accuracy assessment points were generated by NOAA Coastal Services Center personnel with ERDAS IMAGINE software using a stratified random sample. To reduce problems in locating the field reference sites due to GPS positional inaccuracy or on-the-ground observer classification indecision due to spatial heterogeneity, an additional criteria was that field reference sites were located in areas that were homogeneous within a 3x3 pixel neighborhood. To make acquisition of the field reference data more practical, a sixteen pixel buffer area around roads (i.e., 8 pixels on each side of the road) was created.  Several thousand random points were generated.  606 points were field checked in the south Jersey study area. 491 points were field checked in the North Jersey study area.  Due to the absence of concurrent field reference data, no attempt was made to independently assess the accuracy of the 1972 or 1984 time period image maps.
The pre- and post-classification field checked reference data were pooled to give 846 points for the southern New Jersey study area and 564 points for the northern New Jersey study area, for a total of 1411 points.  Only the accuracy of the Level II and I land cover maps can be assessed.  No separate validation was conducted of the Level III land cover map due to the often small areas for some of the land cover classes which it made it difficult to adequately sample these classes.  An error matrix was determined and the Producer's (a measure of omission error), User's Accuracy (a measure of commission error) and the Kappa coefficient of agreement were calculated for each class and for the overall map.  The Kappa coefficient measures the agreement between the classified and reference data corrected for chance agreement (Congalton and Green, 1999).  A value greater than 0.80 represents strong agreement and a value between 0.40 and 0.80 represents moderate agreement. A minimum sample size of thirty points per class is generally recommended for a valid accuracy assessment for that particular class.  Some of the rarer classes (i.e., those classes of land cover that represent a relatively small proportion of the state's area)  fell below this recommended minimum sample size.
See the accuracy assessment tables below for results of the data verification exercise. The overall accuracies for the Level I and Level II maps were quite high with the Level II maps greater than 85% correct and the Level I map greater than 90% correct.  The accuracy of the New Jersey Level I classification was 93.0% (Kappa coefficient = 0.9129) (Table 2). The New Jersey Level II map had a classification accuracy of 85.2% (Kappa coefficient = 0.8348) (Table 1).  However, not all categories met this level of accuracy. The classification of grasslands, such as pastures, showed accuracies in the 55% to 80% range with frequent mis-classification as cultivated land.  The upland scrub/shrub (e.g., abandoned agricultural fields in mid-to-late stages of vegetation succession, power lines, open ridges and pine barrens) and wetland scrub/shrub categories were poorly sampled making a proper accuracy assessment difficult.  Anecdotal evidence suggests that this upland scrub/shrub category is problematic and regularly mis-classified with  cultivated land, grassland and forest land.  A similar situation occurs with the wetland scrub/shrub category being frequently mis-classified with emergent and forested wetland. The unconsolidated shore (i.e., sand beaches, lakeshores and tidal mudflats) was also under-sampled due to its relative infrequent occurrence.  This category also had a lower classification accuracy due to confusion with associated categories of water and emergent wetland.
Final level III classification data were filtered to eliminate single pixel class occurrences, therefore, the minimum mapping unit is approximately a fifth of a hectare (approximately half of an acre).


Table 1A.  New Jersey Level II Accuracy Assessment: Contingency Matrix

                                        Reference Data
      Class.
      Data      1.11    1.12    1.20    1.30    1.41    1.42    1.43    1.44    1.60
      ------------------------------------------------------------------------------
      1.11      108     4       0       2       0       0       0       0       1
      1.12      8       188     4       17      9       0       6       0       0
      1.20      0       1       191     26      1       1       1       2       0
      1.30      0       1       4       58      1       0       2       3       2
      1.41      0       0       0       1       161     0       7       5       0
      1.42      0       0       0       0       0       45      3       0       0
      1.43      0       0       0       0       19      11      114     2       0
      1.44      0       0       0       0       0       0       0       0       0
      1.60      0       0       0       1       0       0       0       0       26
      2.00      0       0       0       0       0       0       0       1       0
      2.10      0       1       0       0       0       0       0       2       0
      2.30      0       0       0       0       0       0       0       0       0
      2.41      0       3       1       0       1       5       5       1       0
      2.45      0       0       0       0       0       0       0       0       0
      2.50      0       1       0       0       0       0       0       0       0
      ------------------------------------------------------------------------------
      Col
      Total     116     199     200     105     192     62      138     16      29
 

      Class.
      Data      2.00    2.10    2.30    2.41    2.45    2.50    Row Total
      -------------------------------------------------------------------
      1.11      0       1       0       0       0       0       116
      1.12      0       0       0       3       0       0       235
      1.20      0       0       0       1       0       1       225
      1.30      0       0       1       0       0       0       72
      1.41      0       0       1       2       0       0       177
      1.42      0       0       0       0       0       0       48
      1.43      0       0       0       0       0       0       146
      1.44      1       1       0       0       1       0       3
      1.60      0       0       0       0       0       0       27
      2.00      10      0       1       0       1       5       18
      2.10      2       93      1       0       0       0       99
      2.30      0       0       25      3       5       1       34
      2.41      0       1       1       127     4       0       149
      2.45      0       0       0       3       8       0       11
      2.50      0       1       1       0       0       48      51
      ------------------------------------------------------------------
      Col
      Total     13      97      31      139     19      55      1411
 

Table 1B.  New Jersey Level II Accuracy Assessment: Accuracy Measures

      Code   Land Cover Description             Number     Producer's    User's      Kappa
                                                Correct    Accuracy      Accuracy
      ------------------------------------------------------------------------------------
      1.11   Highly Developed                     108       93.1         93.1        .9249
      1.12   Moderately to Lightly Developed      188       94.5         80.0        .7672
      1.20   Cultivated                           191       95.5         84.9        .8239
      1.30   Grassland                             58       55.2         80.6        .7899
      1.41   Deciduous Forest                     161       83.8         91.0        .8954
      1.42   Coniferous Forest                     45       72.6         93.8        .9346
      1.43   Mixed D/C Forest                     114       82.6         78.1        .7571
      1.44   Scrub/shrub                            0        0.0          0.0          **
      1.60   Barren                                26       89.7         96.3        .9622
      2.00   Unconsolidated Shore                  10       76.9         55.6          **
      2.10   Estuarine Em Wetland                  93       95.9         93.9        .9349
      2.30   Palustrine Em Wetland                 25       80.6         73.5        .7293
      2.41   Palustrine For Wetland               127       91.4         85.2        .8362
      2.45   Palustrine S/S Wetland                 8       42.1         72.7          **
      2.50   Water                                 48       87.3         94.1        .9388
      ------------------------------------------------------------------------------------
             Totals                              1202                                .8348

      ** Sample Size for this Land Cover Class Too Small to Measure Accuracy/Kappa

                             Overall Classification Accuracy = 85.2%
 

NOTE: For CCAP accuracy assessment purposes we did not consider pasture and hay fields as cultivated land (Class 120) but as unmanaged grassland (Class 131). However, based on the results of the accuracy assessment, it was determined that the pasture/hay fields are more properly included in the Class 120 category.
 

Table 2A.  New Jersey Level I Accuracy Assessment: Contingency Matrix

                                        Reference Data
      Class
      Data      1.10    1.20    1.40    1.60    2.00    2.10    2.40    2.50    Row Total
      -----------------------------------------------------------------------------------
      1.10      308     23      12      1       0       1       3       0       348
      1.20      2       279     9       2       0       0       2       1       295
      1.40      0       1       372     0       1       1       4       0       379
      1.60      0       1       0       26      0       0       0       0       27
      2.00      0       0       1       0       10      0       2       5       18
      2.10      1       0       2       0       2       93      1       0       99
      2.40      3       1       12      0       0       1       176     1       194
      2.50      1       0       0       0       0       1       1       48      51
      -----------------------------------------------------------------------------------
      Col
      Total     315     305     408     29      13      97      189     55      1411
 
 

Table 2B.  New Jersey Level I Accuracy Assessment: Accuracy Measures

      Code   Land Cover Description       Number    Producer's    User's       Kappa
                                          Correct   Accuracy      Accuracy
      ------------------------------------------------------------------------------
      1.11   Developed                    308       97.8          88.5         .8520
      1.20   Cultivated/Grassland         279       91.5          94.6         .9308
      1.40   Upland Forest/Scrub/Shrub    372       91.2          98.2         .9740
      1.60   Barren                       26        89.7          96.3         .9622
      2.00   Unconsolidated Shore         10        76.9          55.6           **
      2.10   Estuarine Emergent Wetland   93        95.9          93.9         .9349
      2.40   Palustrine Wetland           176       93.1          90.7         .8929
      2.50   Water                        48        87.3          94.1         .9388
      ------------------------------------------------------------------------------
             Totals                       1312                                 .9127

      ** Sample Size for this Land Cover Class Too Small to Measure Accuracy/Kappa

                             Overall Classification Accuracy = 93.0%
 

NOTE: For CCAP accuracy assessment purposes we did not consider pasture and hay fields as cultivated land (Class 120) but as unmanaged grassland (Class 131). However, based on the results of the accuracy assessment, it was determined that the pasture/hay fields are more properly included in the Class 120 category.
 
 

Logical_Consistency_Report:
Tests for logical consistency indicate that all row and column positions in the selected geographic window contain data within the New Jersey study area mask. Attribute files appear to be logically consistent.
Completeness_Report:
The classification scheme comprehensively includes all anticipated land covers, and all pixels within the New Jersey study area mask have been classified.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
The positional accuracy and precision of this database is based on the Landsat Thematic Mapper (TM) image data. The scene was georectified to the UTM Zone 18 coordinates, spheroid GRS1980, datum nad83.
Quantitative_Horizontal_Positional_Accuracy_Assessment:
Horizontal_Positional_Accuracy_Value: +/- 0.5 pixels
Horizontal_Positional_Accuracy_Explanation: +/- 15 meters
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator:
Earth Oberstaion Satellite Company (now known as Space Imaging)
Publication_Date: Unknown
Publication_Time: Unknown
Geospatial_Data_Presentation_Form: remote-sensing image
Other_Citation_Details:
Landsat Thematic Mapper scenes processed:
Path     Row     Date
14       31      November 4, 1994   (downshifted 50%)
14       31      September 4, 1995  (downshifted 50%)
14       32      November 4, 1994   (downshifted 50%)
14       32      September 4, 1995  (downshifted 50%)
Type_of_Source_Media: CD-ROM and 8mm tape
Process_Step:
Process_Description:  A combination of unsupervised clustering, spectral mixture modeling, GIS rules-based and on-screen digitizing approaches were used to classify the corrected Landsat TM image using the ERDAS image processing software. The state was broken into two geographic regions (north and south) and the classification was accomplished separately. The southern section was completed first as a pilot, later followed by the northern section. The same initial unsupervised clusters were used and the same techniques followed to ensure as much consistency as possible. The state was also distinguished into two eco-physiographic provinces: Coastal Plain (inner and outer) and the Highlands/Piedmont. Coastal Plain habitat/land cover types were found in both the southern and northern section, while the Highlands/Piedmont types were found only in the north.
---Cluster busting

Unsupervised cluster busting was used to develop spectral classes. 50 clusters were specified in the 1st round of unsupervised classification (.95 convergence factor). Approximately 25 classes were removed and further clustered into another 50 clusters (i.e., 25 classes were "busted" further apart into 50 classes), bringing to a total of 100 clusters. Spectral classes were assigned to land cover information classes by overlaying the spectral class map on top of the original imagery and visual interpretation on-screen. The land cover percentages (e.g. Highly developed with approximately > 75% developed surface) are estimates made by ocular estimation of the 1995 digital orthophotography photography and Landsat imagery, no systematic ground checking was used to support these estimates. In this initial development of spectral classes, some clusters could not be solely assigned to one particular land cover category. For example, spectral clusters for emergent marsh wetlands did not distinguish between estuarine (Class 210) palustrine (Class 230). A GIS rules-based approach was used to make this assignment later (see below).

---Spectral mixture modeling
A spectral mixture model approach was used in several cases where unsupervised cluster busting was not satisfactory in separating certain class types. A simple linear spectral mixture model algorithm was written using the IMAGINE Modeler software employing a simple least-squares unconstrained matrix approach. Spectral endmembers (i.e. "Pure" spectral classes) were developed by visual interpretation of the spectral feature space images and supervised training set delineation of known classes. The mixture model was used to estimate the relative proportions of the spectral endmembers and then classed into appropriate land cover types. This mixture modeling approach was used in the following cases: 1) separating deciduous vs. Mixed vs. Coniferous upland forest types; 2) separating deciduous vs. Mixed vs. Coniferous wetland forest types; and 3) cultivated areas vs. Deciduous forest. Slightly separate models were developed for Coastal Plain vs. Highlands/Piedmont forests.

---Supervised classification
A supervised classification approach using seed pixel training set delineation and maximum likelihood distance thresholding was used to map certain land cover types, including: Class 244 (white cedar swamps); Class 230(emergent wetlands).

---GIS rules base approach
To assign spectral clusters to their appropriate land cover category with sufficient classification accuracy, a GIS rules-based approach was undertaken. The ITU and NWI data sets, along with user-digitized (primarily on-screen) masks were used to develop a series of classification rules in the IMAGINE Spatial Modeler. For example, a coastal littoral zone mask was digitized on-screen by visual interpretation of the LANDSAT TM imagery. This coastal mask was then used to assign the bare land spectral class to either Class 160 (Bare Upland) or Class 201 (M/E Unconsolidated Shore: Sand) and scrub/shrub to Class 151 (CP Mixed) or Class 152 (CP Maritime/Dune). Scrub/Shrub categories (Classes 151-153 and 245, 249) used a rule that applied a threshold value for the leaf-on NDVI imagery, if less than threshold NDVI and wooded, then scrub/shrub.

---Developed area masking and classification An Urban mask was created based on combining the developed "spectral clusters" from above, developed categories in the updated ITU data and 1990 block-level housing density (> 1-2 units/acre) and then buffering out an additional 5 pixels. Using digital orthophotography acquired in 1995 and 1997, the NJDEP ITU land use data was updated with new areas of development mapped using onscreen digitizing. The idea behind using an Urban Mask was to reduce the amount of commission error by reducing the amount of nondeveloped area (e.g., bare agricultural fields) being classified wrongly as developed. The pixels within the Urban Mask were then classified as some sort of development (e.g., 111 or 112) or some nondeveloped category (e.g., 131, 132 or 140). ITU data was also used to further define lightly developed categories, using the following rule: if ITU = developed and Spectral class = Wooded, then Class 113 (Lightly Developed - Wooded). A similar rule was used for Class 114 (Lightly Developed - Unwooded). AOI editing was further undertaken to clean up obvious misclassification.

---Further clean-up processing
To remove "salt and pepper" typical of digitally image processed land cover maps, the resulting classified map was clumped (8 neighbor algorithm) with clumps smaller than 2 pixels eliminated and replaced by the majority category. On-screen editing using the IMAGINE Area-of-Interest (AOI) tool and recode function was also undertaken to clean up obvious instances of misclassification and to include classes that were difficult to get otherwise (e.g., Class 133: grassland - airports). Visual interpretation of the Sept. (Leaf-on) and Nov. (Leaf-off) imagery was used in making this judgement. AOI editing was also used to fill in areas misclassified due to cloud and cloud shadows.  Final level III classification data were filtered to eliminate single pixel class occurrences, therefore, the minimum mapping unit is approximately a fifth of a hectare (approximately half of an acre).

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Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster - Arc/Info GRID
Raster_Object_Information:
Raster_Object_Type: Grid Cell, 30 x 30 meter cell resolution
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Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Geodetic_Model:
Horizontal_Datum_Name: North American Datum of 1983
Ellipsoid_Name: GRS1980
Projection: UTM
Zone: 18
Units: Meters
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Entity_and_Attribute_Information:
Detailed_Description:
Entity_Type:
Entity_Type_Label: njtm95l3lc.vat
Entity_Type_Definition: Value Attribute Table
Entity_Type_Definition_Source: None
Overview_Description:
Entity_and_Attribute_Overview:
The value attribute table contains the default 'value' and 'count' fields as well as their respective level 3 land cover codes and descriptions.  Additionally, CRSSA has included each category's respective level 2 and level 1 codes and descriptions.
* VALUE ATTRIBUTE TABLE INFORMATION
 
Field: VALUE
Input Width,Output Width,Type: 4,10,B
Description: Default GRID field - cell value

Field: COUNT
Input Width,Output Width,Type: 4,10,B
Description: Default GRID field - cell count

Field: LEVEL3
Input Width,Output Width,Type: 3,3,I
Description: Level 3 Land Cover Category number-code

Field: LEVEL3DESC
Input Width,Output Width,Type: 100,100,C
Description: Level 3 Land Cover Category Descriptions

Field: LEVEL2
Input Width,Output Width,Type: 3,3,I
Description: Level 2 Land Cover Category number-code

Field: LEVEL2DESC
Input Width,Output Width,Type: 80,80,C
Description: Level 2 Land Cover Category Descriptions

Field: LEVEL1
Input Width,Output Width,Type: 3,3,I
Description: Level 1 Land Cover Category number-code

Field: LEVEL1DESC
Input Width,Output Width,Type: 32,32,C
Description: Level 1 Land Cover Category Descriptions
 

Attribute_Domain_Values (* the LEVEL3 and LEVEL3DESC fields are defined below)
               Enumerated_Domain:
                 Enumerated_Domain_Value: 111
                 Enumerated_Domain_Value_Definition: Developed: Highly (>75% impervious surface)
                 Enumerated_Domain_Value: 112
                 Enumerated_Domain_Value_Definition: Developed: Moderately (50-75% impervious surface)
                 Enumerated_Domain_Value: 113
                 Enumerated_Domain_Value_Definition: Developed: Lightly - wooded (25-50% impervious surface)
                 Enumerated_Domain_Value: 114
                 Enumerated_Domain_Value_Definition: Developed: Lightly - unwooded (25-50% impervious surface)
                 Enumerated_Domain_Value: 120
                 Enumerated_Domain_Value_Definition: Cultivated (actively tilled, fallow and recently abandoned)
                 Enumerated_Domain_Value: 131
                 Enumerated_Domain_Value_Definition: Grassland: unmanaged (grazed land, old fields, abandoned land)
                 Enumerated_Domain_Value: 132
                 Enumerated_Domain_Value_Definition: Grassland: managed (golf courses, residential/corporate lawn, parks)
                 Enumerated_Domain_Value: 133
                 Enumerated_Domain_Value_Definition: Grassland: airport
                 Enumerated_Domain_Value: 141
                 Enumerated_Domain_Value_Definition: Upland Forest: Coastal Plain Oak dominant (Oak > 75%)
                 Enumerated_Domain_Value: 142
                 Enumerated_Domain_Value_Definition: Upland Forest: Coastal Plain Oak-pine (Oak 50-75%)
                 Enumerated_Domain_Value: 143
                 Enumerated_Domain_Value_Definition: Upland Forest: Coastal Plain Pine-oak (Pine 50-75%)
                 Enumerated_Domain_Value: 144
                 Enumerated_Domain_Value_Definition: Upland Forest: Coastal Plain Pine dominant (Pine > 75%)
                 Enumerated_Domain_Value: 145
                 Enumerated_Domain_Value_Definition: Upland Forest: Highlands/Piedmont deciduous - mixed hardwoods dominant
                 Enumerated_Domain_Value: 146
                 Enumerated_Domain_Value_Definition: Upland Forest: Highlands/Piedmont mixed deciduous/coniferous - hemlock/pine
                 Enumerated_Domain_Value: 147
                 Enumerated_Domain_Value_Definition: Upland Forest: Highlands/Piedmont mixed deciduous/coniferous - red cedar/pine
                 Enumerated_Domain_Value: 148
                 Enumerated_Domain_Value_Definition: Upland Forest: Highlands/Piedmont coniferous - hemlock/pine dominant
                 Enumerated_Domain_Value: 149
                 Enumerated_Domain_Value_Definition: Upland Forest: Highlands/Piedmont coniferous - red cedar/pine/plantation dominant
                 Enumerated_Domain_Value: 151
                 Enumerated_Domain_Value_Definition: Upland Scrub/Shrub: Coastal Plain mixed deciduous/coniferous
                 Enumerated_Domain_Value: 152
                 Enumerated_Domain_Value_Definition: Upland Scrub/Shrub: Coastal Plain mixed deciduous/coniferous - maritime/dune
                 Enumerated_Domain_Value: 153
                 Enumerated_Domain_Value_Definition: Upland Scrub/Shrub: Highlands/Piedmont mixed deciduous/coniferous
                 Enumerated_Domain_Value: 160
                 Enumerated_Domain_Value_Definition: Barren soil/rock (sand/gravel pits, barren < 25% vegetation)
                 Enumerated_Domain_Value: 201
                 Enumerated_Domain_Value_Definition: Marine/Estuarine Unconsolidated shore: sand
                 Enumerated_Domain_Value: 202
                 Enumerated_Domain_Value_Definition: Marine/Estuarine Unconsolidated shore: mud/organic
                 Enumerated_Domain_Value: 211
                 Enumerated_Domain_Value_Definition: Estuarine emergent marsh: low salt marsh - Spartina alterniflora dominant (>50%)
                 Enumerated_Domain_Value: 212
                 Enumerated_Domain_Value_Definition: Estuarine emergent marsh: high salt marsh - Spartina patens dominant (>50%)
                 Enumerated_Domain_Value: 213
                 Enumerated_Domain_Value_Definition: Estuarine emergent marsh: high salt marsh - Phragmites australis dominant (>50%)
                 Enumerated_Domain_Value: 214
                 Enumerated_Domain_Value_Definition: Brackish tidal/fresh tidal marsh: mixed species
                 Enumerated_Domain_Value: 220
                 Enumerated_Domain_Value_Definition: Riverine/lacustrine/palustrine unconsolidated shore: sand/mud/organic
                 Enumerated_Domain_Value: 230
                 Enumerated_Domain_Value_Definition: Riverine/lacustrine/palustrine emergent marsh: mixed species
                 Enumerated_Domain_Value: 241
                 Enumerated_Domain_Value_Definition: Wetland Forest: Coastal Plain hardwood swamp (>66% deciduous)
                 Enumerated_Domain_Value: 242
                 Enumerated_Domain_Value_Definition: Wetland Forest: Coastal Plain pine lowland (>66% evergreen)
                 Enumerated_Domain_Value: 243
                 Enumerated_Domain_Value_Definition: Wetland Forest: Coastal Plain mixed - hardwood/white cedar-pine-holly
                 Enumerated_Domain_Value: 244
                 Enumerated_Domain_Value_Definition: Wetland Forest: Coastal Plain white cedar swamp (>66% evergreen)
                 Enumerated_Domain_Value: 245
                 Enumerated_Domain_Value_Definition: Wetland Scrub/shrub: Coastal Plain mixed
                 Enumerated_Domain_Value: 246
                 Enumerated_Domain_Value_Definition: Wetland Forest: Highlands/Piedmont hardwood swamp (>66% deciduous)
                 Enumerated_Domain_Value: 247
                 Enumerated_Domain_Value_Definition: Wetland Forest: Highlands/Piedmont mixed - hardwood/hemlock/white cedar/pine
                 Enumerated_Domain_Value: 248
                 Enumerated_Domain_Value_Definition: Wetland Forest: Highlands/Piedmont conifer swamp - hemlock/cedar/pine dominant (>66% evergreen)
                 Enumerated_Domain_Value: 249
                 Enumerated_Domain_Value_Definition: Wetland Scrub/shrub: Highlands/Piedmont mixed deciduous/evergreen
                 Enumerated_Domain_Value: 251
                 Enumerated_Domain_Value_Definition: Marine/Estuarine Open water
                 Enumerated_Domain_Value: 252
                 Enumerated_Domain_Value_Definition: Riverine/Lacustrine/Palustrine Open water

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Distribution_Information:
Resource_Description:
The 1995 New Jersey level 3 Landsat TM satellite image land cover classification was completed as part of the Grant F. Walton Center for Remote Sensing and Spatial Analysis' on-going land cover / land use mapping efforts in the greater New Jersey region.
Distribution_Liability:
While efforts have been made to ensure that these data are accurate and reliable within the state of the art, Rutgers University cannot assume liability for any damages, or misrepresentations, caused by any inaccuracies in the data, or as a result of the data to be used on a particular system. Rutgers University makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.  Any maps, publications, reports or any other type of document produced as a result of an associated project utilizing Center for Remote Sensing and Spatial Analysis (CRSSA), Rutgers University, data will credit the original author(s) as listed in the metadata as well as the Center for Remote Sensing and Spatial Analysis (CRSSA), Rutgers University.  Data set is not for use in litigation.
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Metadata_Reference_Information:
Metadata_Date: 20001017
Metadata_Review_Date: 20001017
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: Richard G. Lathrop
Contact_Organization:
Grant F. Walton Center for Remote Sensing and Spatial Analysis, Rutgers University
Contact_Position: Director
Contact_Address:
Address_Type: mailing and physical address
Address:
Grant F. Walton Center for Remote Sensing and Spatial Analysis
Natural Resources and Environmental Sciences Building
Cook College - Rutgers University
14 College Farm Road
City: New Brunswick
State_or_Province: New Jersey
Postal_Code: 08904-8551
Country: USA
Contact_Voice_Telephone: 732-932-1582
Contact_Facsimile_Telephone: 732-932-2587
Contact_Electronic_Mail_Address: lathrop@crssa.rutgers.edu
Hours_of_Service: 8.30am to 4.30pm Eastern Standard Time (EST) USA
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998
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Generated by mp version 2.4.30 on Tue Oct 17 15:28:18 2000