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New Hampshire Land Cover Assessment - 2001

New Hampshire Land Cover Assessment - 2001

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Metadata:


Identification_Information:
Citation:
Citation_Information:
Originator: Complex Systems Research Center, University of New Hampshire
Publication_Date: 20020101
Title: New Hampshire Land Cover Assessment - 2001
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:
<URL:http://www.granit.sr.unh.edu/cgi-bin/nhsearch?dset=nhlc01/nh>
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: <URL:http://www.granit.sr.unh.edu>
Description:
Abstract:
The New Hampshire Land Cover Assessment categorizes land cover and land use into 23 classes, based largely on the classification of Landsat Thematic Mapper (TM) imagery.
Purpose:
The goal of the New Hampshire Land Cover Assessment is to provide a multi-purpose data set to support regional analysis. Particular emphasis is placed on delivering as much detail as possible in the forested and agricultural classes.
Supplemental_Information:
Data distribution tile: Statewide 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 8.x, select "ASCII to Grid" 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 New Hamsphire Land Cover Assessment was made possible by financial support from the Cooperative Institute for Coastal and Estuarine Environmental Technology CICEET), USDA Forest Service, NH Department of Resources and Economic Development, NH Department of Fish and Game, USDA Natural Resources Conservation Service, NH Space Grant, and UNH Cooperative Extension.

Please cite as "New Hampshire GRANIT. 2001. New Hampshire Land Cover Assessment. New Hampshire GRANIT, Durham, NH."

Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 19900908
Ending_Date: 20011201
Currentness_Reference:
Dates of TM imagery, field data collection, and final classification
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -72.594653
East_Bounding_Coordinate: -70.664747
North_Bounding_Coordinate: 45.30723
South_Bounding_Coordinate: 42.693632
Keywords:
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: Land Cover
Theme_Keyword: Land Use
Theme_Keyword: Remote Sensing
Theme_Keyword: Classification
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: United States
Place_Keyword: Northeast
Place_Keyword: New England
Place_Keyword: New Hampshire
Access_Constraints:
Acknowledgement 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 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: USA
Contact_Voice_Telephone: (603) 862-1792
Contact_Facsimile_Telephone: (603) 862-0188
Contact_Electronic_Mail_Address: granit@unh.edu
Hours_of_Service: 8:30 AM - 5:00 PM, EST
Browse_Graphic:
Browse_Graphic_File_Name:
<URL:http://www.granit.sr.unh.edu/cgi-bin/load_file?PATH=/data/database/d-webdata/nhlc01/browse.gif>
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 project achieved an overall accuracy of 82.2% at the full 23-class level. Below is a summary of User's and Producer's Accuracy for each of these classes.

CLASS - Code PRODUCER'S ACC. USER'S ACC. Residential/Commercial/Industrial - 110 86.9% 88.3% Transportation - 140 100.0% 85.0% Row Crops - 211 94.6% 88.3% Hay/Pasture - 212 84.6% 91.7% Orchards - 221 97.4% 92.5% Beech/Oak - 412 68.1% 53.3% Paper Birch/ Aspen - 414 28.6% 28.6% Other Hardwood - 419 53.2% 70.0% White/Red Pine - 421 90.7% 81.7% Spruce/Fir - 422 93.8% 80.4% Hemlock - 423 95.1% 65.0% Pitch Pine - 424 100.0% 97.5% Mixed Forest - 430 39.7% 62.5% Alpine (Krumholz) - 440 100.0% 80.0% Water - 500 100.0% 100.0% Forested Wetland - 610 74.3% 86.7% Open Wetland - 620 88.2% 75.0% Tidal Wetland - 630 100.0% 100.0% Disturbed - 710 90.0% 90.0% Bedrock/ Veg. - 720 100.0% 100.0% Sand Dunes - 730 100.0% 100.0% Other Cleared - 790 82.4% 93.3% Tundra - 800 100.0% 100.0%

When the classification is collapsed to the 17-class level, the overall accuracy is 88.4%, and the User's and Producer's Accuracies are as follows:

CLASS - Code PRODUCER'S ACC. USER'S ACC. Residential/Commercial/Industrial - 110 86.9% 88.3% Transportation - 140 100.0% 85.0% Crops/Pasture - 211-212 95.0% 95.8% Orchards - 221 97.4% 92.5% Deciduous Forest - 410-419 90.7% 94.8% Coniferous Forest - 420-429 97.3% 81.9% Mixed Forest - 430 39.7% 62.5% Alpine (Krumholz) - 440 100.0% 80.0% Water - 500 100.0% 100.0% Forested Wetland - 610 74.3% 86.7% Open Wetland - 620 88.2% 75.0% Tidal Wetland - 630 100.0% 100.0% Disturbed - 710 90.0% 90.0% Bedrock/ Veg. - 720 100.0% 100.0% Sand Dunes - 730 100.0% 100.0% Other Cleared - 790 82.4% 93.3% Tundra - 800 100.0% 100.0%

So that users can interpret the data most effectively, rules were created to develop broader ("fuzzier") categories of "right" and "wrong" and to assess the accuracy using these fuzzy sets. We applied the linguistic scale developed by Woodcock and Gopal (2000):

(1) Absolutely wrong: This answer is absolutely unacceptable. Very wrong. (2) Understandable but wrong: Not a good answer. There is something about the site that makes the answer understandable, but there is clearly a better answer. This answer would pose a problem for users of the map. Not right. (3) Reasonable or acceptable answer: May not be the best possible answer but it is acceptable; this answer does not pose a problem to the user if it is seen on the map. Right. (4) Good answer: Would be happy to find this answer on the map. Very right. (5) Absolutely right: No doubt about the match. Perfect.

Each accuracy assessment site was given a fuzzy rating (see fuzzyratings.pdf for definitions). The overall accuracy of the 23- class classification increases to 89.1% when the "good answers" are included as "right," and to 92.0% when "reasonable or acceptable answers" are included as well. Please see the project's final report for a full discussion of the accuracy assessment.

Logical_Consistency_Report: These data are believed to be logically consistent.
Completeness_Report:
These data are considered complete for the study area - the State of New Hampshire.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
The data were derived from the classification of several Landsat Thematic Mapper images (see citation details). Two of these images were georeferenced by the staff at the Complex Systems Research Center to SPOT panchromatic 10m resolution images, and the rest were georeferenced by the USGS or ImageLinks, Inc. RMS error for the data georeferenced by CSRC was less than 0.5 pixel.
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: 20010101
Title: Landsat Thematic Mapper imagery
Edition: One
Geospatial_Data_Presentation_Form: Image
Publication_Information:
Publication_Place: Sioux Falls, SD
Publisher: EROS Data Center, USGS
Other_Citation_Details:
The source data for this project were the following Landsat Thematic Mapper images:

Image Type Path-Row Bands Date Georeferencing/ Terrain Correction performed by:

Landsat 5 TM 12-30 1-7 8-Sep-90 CSRC Landsat 5 TM 12-30 1-7 14-May-94 USGS Landsat 5 TM 12-30 1-7 24-Oct-95 CSRC Landsat 5 TM 12-30 1-7 22-Jul-96 USGS Landsat 5 TM 13-29 1-7 13-May-91 USGS Landsat 5 TM 13-29 1-5, 7 6-Oct-92 USGS Landsat 5 TM 13-29 1-7 12-Oct-94 USGS Landsat 7 ETM+ 13-29 1-8 31-Aug-99 ImageLinks, Inc. Landsat 5 TM 13-30 1-5, 7 6-Oct-92 USGS Landsat 5 TM 13-30 1-7 28-Oct-94 USGS Landsat 5 TM 13-30 1-7 14-Apr-98 USGS Landsat 7 ETM+ 13-30 1-8 31-Aug-99 ImageLinks, Inc.

Ancillary data comprised numerous holdings from the GRANIT archive (the NH statewide GIS), including watershed boundaries, panchromatic Digital Orthophotoquads (DOQs), Digital Raster Graphics (DRGs), USGS Digital Line Graphs (DLGs) for hydrography, NH Department of Transportation road centerlines, Digital Elevation Models (DEMs), SPOT panchromatic (10 meter resolution) images, protected lands, and US Fish and Wildlife Service National Wetlands Inventory (NWI) maps.

Type_of_Source_Media: Image
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 19900908
Ending_Date: 19990831
Source_Currentness_Reference: Ground condition
Source_Citation_Abbreviation: TM
Source_Contribution: Basis of image processing for the classification
Process_Step:
Process_Description:
The NH Land Cover Assessment was conducted separately for each of three regions of the state: the coastal area, the southwest, and the north country. While each region was processed separately, the same general procedure was followed for each. Twelve Landsat Thematic Mapper images (see above) were selected as the basis for the initial classifications. The images were subset to comprise the geographic extent of three primary study areas, and the 6 reflective bands (1-5, and 7) from a summer (leaf on) and spring (leaf off) image were "layer stacked" or combined into a single 12-band data set for each region. To minimize error due to shadows in the imagery (particularly problematic in steep sloped areas), the layer-stacked images were subset into slope categories (based on the DEMs) that were then processed separately.

The first product generated for each region was a generalized data set. Archived data from previous projects were used to create representative signatures, and a supervised, maximum likelihood classification was applied to each image subset. These classifications grouped each image subset into five broad categories: deciduous forest, coniferous forest, mixed forest, agricultural/cleared, and wetlands/water. The resulting classes were visually evaluated using DOQ's, other ancillary data sets, and local knowledge. Acceptable classes were carried through to the final data set, while unacceptable classes were used to mask various image band combinations and/or band transformations. This was followed by unsupervised classifications using the ISODATA cluster routine. At each iteration, the generalized classes were evaluated, and either archived for incorporation in the interim generalized product or retained for additional processing. As many as four supervised and unsupervised classification iterations using various image date/band derivatives were run on the resulting data sets. Finally, each of the general classifications was recoded to reflect the appropriate land cover value and mosaicked to generate the full, region-wide generalized land cover data set.

Class-specific classifications were accomplished through a series of image subsets, masks, and classification iterations to produce the final product. Each class-specific procedure was initialized by creating a layer-stack of various bands/band derivations. These were selected in part by applying the ERDAS Imagine signature separability tool to the layer stack and using the Transformed Divergence measure. Once bands were selected, the image composite was masked to retain pixels of interest (e.g., the forest-specific classification retained forested classes from the generalized land cover). This was followed by an iterative process of classifications using a combination of techniques (similar to that of the general classification) to derive the final data for that class.

The series of specific classifications typically began with a supervised classification, using both archived training sites and training sites collected for this project. Over 1,400 new data points were collected to supplement 1,200 archived sites from previous projects. A large number of non-forested sites were available from pre-existing sources, such as DOQ's, DRG's, NWI, and local knowledge. Forested sites, as well as some wetland and agricultural sites, required field sampling. Field crews navigated to each site using a Trimble Pro-XRS GPS receiver obtaining real time corrections, and at each forested location conducted two to four 10 BAF prism tallies to quantify the canopy composition.

In the southeast, the three forested classes (coniferous, deciduous, and mixed) from the generalized land cover were each processed independently, while in the north and southwest regions, the three classes were processed together because it was determined that there was no appreciable improvement in classification quality by separating the three.

As with the general classification, there was a series of iterative classifications from which acceptable results were saved to a final data layer and unacceptable results were used to mask subsequent data sets. For the forested classes, 14 iterations were needed to achieve an acceptable data layer. A total of 2,794 training signatures were used in these classifications (though in some cases the same training site was used to produce signatures for multiple images). For the cleared sites, 542 signatures were used in 12 classifications, and 126 signatures were used in 6 wetlands classifications. Our use of NWI data and the ISODATA clustering routine reduced the number of signatures needed to classify wetlands.

Some ancillary data were applied in this process as well: NWI data were used as a mask in the North Country to help distinguish many forested wetlands from spruce/fir forests; orchards were screen digitized from DRG's and DOQ's; and other data sets such as DRG's and DOQ's were used to determine the reliability of classes. Elevation data from USGS digital elevation models were used to change forest classes based on certain thresholds. Beech/Oak above 2,500 feet and Other Hardwoods above 3,000 feet were converted to Paper Birch/Aspen; White/Red Pine above 1,500 feet and Hemlock above 2,400 feet were converted to Spruce/Fir; and any forested class above 4,200 feet was converted to Alpine (Krumholz).

Several post processing refinements were applied to the provisional land cover data in the ESRI Grid environment. NH Department of Transportation road data (resident in the GRANIT data base, 2001) were "burned in" to the land cover data set, effectively overwriting any coincident class. Also, DLG hydrography data were used to update double banked river, lake, and pond edges. Finally, several filters were applied to remove speckling and produce minimum map units of one acre. In order to maintain the integrity of linear features, filtering was preceded by the REGIONGROUP command, such that the majority filter applied would only operate on groups of pixels smaller than approximately one acre (five pixels). This filter was followed by a second REGIONGROUP and contiguous pixels in sets less than five were finally NIBBLED to eliminate those pixels that were not eliminated by the majority filter.

A total of 975 sites were evaluated for the accuracy assessment. More than 600 of these were field visited, and others were evaluated using ancillary data such as NWI maps, DOQ's, and TM imagery. All sites classified as forest or agriculture, and most classified as wetland, were field visited using Trimble Pro-XRS GPS units receiving real time differential correction. At forested sites, field crews recorded stand information and conducted up to five 10 BAF prism tallies to quantify stand composition.

As with the classification itself, the accuracy assessment was conducted separately for each of the three geographic regions. In each region, we attempted to sample 30 sites per land cover class, but in some cases we were unable to do so because of limited area covered by the class, post data-collection re-classification, or for other reasons. Conversely, some classes were over-sampled, because of post data-collection re-classification or because we decided to merge subclasses. In order to limit distortion due to disparate sample sizes among classes, we randomly selected 20 sites from each class in each region to tabulate in the error matrices. This yielded a total of 60 sites per class for the full state (though some classes, particularly those like Tundra that are regionally focused, still have fewer sample sites).

Error matrices were generated for the Level 3 (23 class), Level 2 (16 class) and Level 1 (7 class) classifications, and user's and producer's accuracy were calculated. Additionally, the Level 3 classification was assessed using fuzzy set rules. See the Attribute Accuracy report above and the project's final report for more information.

Source_Used_Citation_Abbreviation: TM
Process_Date: 20011201

Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 10174
Column_Count: 5311
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:
New Hampshire Land Cover Assessment Data Key Developed 110 Residential, commercial, or industrial 140 Transportation Active agricultural land 211 Row crops 212 Hay/rotation/permanent pasture 221 Fruit orchards Forested 412 Beech/oak 414 Paper birch/aspen 419 Other hardwoods 421 White/red pine 422 Spruce/fir 423 Hemlock 424 Pitch pine 430 Mixed forest 440 Alpine (Krumholz) Water 500 Open water Wetlands 610 Forested wetlands 620 Non-forested wetlands 630 Tidal wetlands Barren Land 710 Disturbed 720 Bedrock/vegetated 730 Sand dunes 790 Cleared/other open Tundra 800 Tundra
Entity_and_Attribute_Detail_Citation:
The following rules were used to determine forest type: Deciduous stands (41x) are forested stands comprising less than 25% coniferous basal area per acre. Coniferous stands (42x) are forested stands comprising greater than 65% coniferous basal area per acre. Mixed stands (430) are forested stands comprising greater than 25% and less than 65% coniferous basal area per acre. Alpine areas (440) contain stunted vegetation, either hardwood or softwood (usually paper birch or spruce/fir), and occur just below tree line in the White Mountains.

Beech/oak stands (412) are deciduous stands comprising at least 30% beech and oak. Paper birch/aspen stands (414) are deciduous stands comprising at least 20% paper birch and aspen. Other deciduous stands (419) are deciduous stands not meeting either the beech/oak or paper birch/aspen criteria.

White/red pine stands (421) are coniferous stands in which white and red pine constitute a plurality of the coniferous basal area. Spruce/fir stands (422) are coniferous stands in which spruce and fir constitute a plurality of the coniferous basal area. Hemlock stands (423) are coniferous stands in which hemlock constitutes a plurality of the coniferous basal area. Pitch pine stands (424) are coniferous stands in which pitch pine constitutes a plurality of the coniferous basal area.

Other class definitions are as follows:

Developed (110) - built-up areas. (Note that this class was coded as 100 in early releases of the data.) Active agriculture (200) - hay fields, row crops, plowed fields, etc. Water (500) - lakes, ponds, some rivers or any other open water feature. Wetlands (600) - areas dominated by wetland characteristics defined by the U. S. Fish and Wildlife Service National Wetlands Inventory. Basically hydric soils, hydrophytic vegetation and the hydrologic conditions that result in water at or near the surface for extended periods of the growing season. Disturbed (710) - gravel pits, quarries or other areas where the earth and vegetation have been altered or exposed. Bedrock/vegetated (720) - exposed bedrock or ledge (usually in the mountains) that may have some forms of stunted vegetation growing in cracks or lichens growing on the surface rock. Sand dunes (730) - areas along the seacoast that are dominated by sand. Cleared/other open (790) - clear cut forest, old agricultural fields that are reverting to forest, etc. Tundra (800) - areas dominated by short vegetation that occurs above tree line in the White Mountains (only mapped on Mt Washington). (Note that this class was previously coded as 810 in early releases of the data.)


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: USA
Contact_Voice_Telephone: (603) 862-1792
Contact_Facsimile_Telephone: (603) 862-0188
Contact_Electronic_Mail_Address: granit@unh.edu
Hours_of_Service: 8:30 AM - 5:00 PM, 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 (CSRC), under contract to the NH Office of State Planning (OSP), 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
Transfer_Size: 265 MB
Digital_Transfer_Option:
Offline_Option:
Offline_Media: CD-ROM
Recording_Format: Ascii Grid
Fees:
No charge when downloaded from the internet. Cost of reproduction when provided on CD-ROM or other media.
Ordering_Instructions:
Contact the GRANIT Database Manager, granit@unh.edu or (603) 862-1792, for more information.

Metadata_Reference_Information:
Metadata_Date: 20020111
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: USA
Contact_Voice_Telephone: (603) 862-1792
Contact_Facsimile_Telephone: (603) 862-0188
Contact_Electronic_Mail_Address: granit@unh.edu
Hours_of_Service: 8:30 AM - 5:00 PM, EST
Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001-1998

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