Short Citation:
Office for Coastal Management, 2020: C-CAP Land Cover, Massachusetts, 2016, https://www.fisheries.noaa.gov/inport/item/54917.

Item Identification

Title: C-CAP Land Cover, Massachusetts, 2016
Status: Completed
Publication Date: 2018-11-20
Abstract:

The NOAA Coastal Change Analysis Program (C-CAP) produces national standardized land cover and change products for the coastal regions of the U.S. C-CAP products inventory coastal intertidal areas, wetlands, and adjacent uplands with the goal of monitoring changes in these habitats. The timeframe for this metadata is summer 2016. These maps are developed utilizing high resolution National Agriculture Imagery Program (NAIP) imagery, and can be used to track changes in the landscape through time. This trend information gives important feedback to managers on the success or failure of management policies and programs and aid in developing a scientific understanding of the Earth system and its response to natural and human-induced changes. This understanding allows for the prediction of impacts due to these changes and the assessment of their cumulative effects, helping coastal resource managers make more informed regional decisions. NOAA C-CAP is a contributing member to the Multi-Resolution Land Characteristics consortium and C-CAP products are included as the coastal expression of land cover within the National Land Cover Database.

Purpose:

C-CAP is dedicated to the development, distribution, and application of land cover and change data for the coastal regions of the U.S. This effort is being conducted in close coordination with state coastal management agencies, the interagency Multi-Resolution Land Characteristics (MRLC) consortium, and the National Land Cover Database (NLCD).

Supplemental Information:

Attributes for this product are as follows:

0 Background,

1 Unclassified (Cloud, Shadow, etc),

2 Impervious,

3

4

5 Developed Open Space,

6 Cultivated Land,

7 Pasture/Hay,

8 Grassland,

9 Deciduous Forest,

10 Evergreen Forest,

11 Mixed Forest,

12 Scrub/Shrub,

13 Palustrine Forested Wetland,

14 Palustrine Scrub/Shrub Wetland,

15 Palustrine Emergent Wetland,

16 Estuarine Forested Wetland,

17 Estuarine Scrub/Shrub Wetland,

18 Estuarine Emergent Wetland,

19 Unconsolidated Shore,

20 Bare Land,

21 Open Water,

22 Palustrine Aquatic Bed,

23 Estuarine Aquatic Bed,

24 Tundra,

25 Snow/Ice,

Recommended Citation. NOAA Coastal Change Analysis Program (C-CAP) Regional Land Cover Database. Data collected 1995-present. Charleston, SC: National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management. Data accessed at coast.noaa.gov/landcover.

Keywords

Theme Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Instrument Keywords Earth Remote Sensing Instruments > Passive Remote Sensing > Photon/Optical Detectors > Cameras > CAMERAS
Global Change Master Directory (GCMD) Platform Keywords Aircraft > AIRCRAFT
Global Change Master Directory (GCMD) Science Keywords Earth Science > Land Surface > Land Use/Land Cover
Global Change Master Directory (GCMD) Science Keywords Earth Science > Land Surface > Land Use/Land Cover > Land Use/Land Cover Classification
ISO 19115 Topic Category imageryBaseMapsEarthCover
None Land Cover
None Land Cover Analysis
None Remotely Sensed Imagery/Photos

Spatial Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Location Keywords Ocean > North America > United States of America > Massachusetts
None Coastal Zone
None MA
None Massachusetts

Physical Location

Organization: Office for Coastal Management
City: Charleston
State/Province: SC

Data Set Information

Data Set Scope Code: Data Set
Maintenance Note:

5 years

Data Presentation Form: Image (digital)
Distribution Liability:

Users must assume responsibility to determine the usability of these data.

Support Roles

Data Steward

CC ID: 800796
Date Effective From: 2018-11-20
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Distributor

CC ID: 800798
Date Effective From: 2018-11-20
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Metadata Contact

CC ID: 800799
Date Effective From: 2018-11-20
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Point of Contact

CC ID: 800797
Date Effective From: 2018-11-20
Date Effective To:
Contact (Organization): NOAA Office for Coastal Management (NOAA/OCM)
Address: 2234 South Hobson Ave
Charleston, SC 29405-2413
Email Address: coastal.info@noaa.gov
Phone: (843) 740-1202
URL: https://coast.noaa.gov

Extents

Currentness Reference: Acquisition date of the NAIP imagery

Extent Group 1

Extent Group 1 / Geographic Area 1

CC ID: 800794
W° Bound: -73.612
E° Bound: -69.808
N° Bound: 42.985
S° Bound: 41.14

Extent Group 1 / Time Frame 1

CC ID: 800793
Time Frame Type: Discrete
Start: 2016-08-15

Spatial Information

Spatial Representation

Representations Used

Grid: No

Access Information

Security Class: Unclassified
Data Access Constraints:

None

Data Use Constraints:

Data set is not for use in litigation. While efforts have been made to ensure that these data are accurate and reliable within the state of the art, NOAA, 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. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.

URLs

URL 1

CC ID: 800800
URL: https://coast.noaa.gov/htdata/raster1/landcover/bulkdownload/hires
URL Type:
Online Resource

URL 2

CC ID: 800801
URL: https://coast.noaa.gov/digitalcoast/data/ccaphighres
URL Type:
Online Resource

URL 3

CC ID: 830036
URL: https://coast.noaa.gov/dataviewer/#/landcover/search/where:ID=8690
Name: Data Access Viewer
URL Type:
Online Resource

Technical Environment

Description:

Microsoft Windows XP Version 5.1 (Build 2600) Service Pack 3; ESRI ArcCatalog 9.2.2.1350

Data Quality

Accuracy:

According to the accuracy assessment performed by NOAA Office for Coastal Management staff, the overall accuracy of this product is 94.2%. There were 446 total points distributed across the state. The accuracy of each class is as follows (Producer's, User's accuracies):

Impervious (93.7%, 96.8%)

Open Space Developed (92.3%, 88.9%)

Cultivated (100%, 100%)

Pasture/Hay (91.7%, 91.7%)

Grassland (92.9%, 76.5%)

Deciduous Forest (91.1%, 96.5%)

Evergreen Forest (96.6%, 93.4%)

Shrub/Scrub (96.0%, 100%)

Palustrine Forested Wetland (97.1%, 89.2%)

Palustrine Shrub/Scrub Wetland (81.8%, 100%)

Palustrine Emergent Wetland (95.8%, 88.5%)

Estuarine Shrub/Scrub Wetland (N/A, N/A)

Estuarine Emergent Wetland (100%, 90.9%)

Unconsolidated Shore (88.9%, 100%)

Bare Land (100%, 100%)

Water (100%, 96.9%)

Palustrine Aquatic Bed (91.7%, 100%)

Estuarine Aquatic Bed (N/A, N/A)

Overall accuracy (94.2%)

Points were sampled using a stratified random sampling scheme, with a minimum target sample of 10 points per class. A few of the rarer categories did not meet this minimum threshold target. Estuarine Forested Wetland, Estuarine Shrub/Scrub Wetland, and Estuarine Aquatic Bed Wetland were not sampled at all due to the relatively low total area of those classes. Additionally, Unconsolidated Shore ended up with only 9 sample locations. Ideally, a larger number of samples would have been included. The correct land cover classification was determined through analyst interpretation of the imagery used in creating the map, as well as possible references to GoogleEarth in order to reference additional dates/seasons of imagery for that location. All points were interpreted by two analysts, plus a third who made a final determination when there was not agreement on the call. All analysts were able to identify both a primary call as well as a fuzzy call when/if the point location caused any level of confusion as to what the land cover category was.

Completeness Report:

Data does not exist for all classes.

There are no pixels representing class 11 (Mixed Forest), 24 (Tundra), 25 (Perennial Ice/Snow), 26 (Dwarf Scrub - Alaska specific class), 27 (Sedge/Herbaceous), and 28 (Moss - Alaska specific). Developed classes have been altered to exclude the percentage breakdown of impervious surfaces as the breakdown is not appropriate for high resolution mapping (Developed High Intensity (2), Developed Medium Intensity (3), and Developed Low Intensity (4) are reduced to Impervious (Class 2)).

Conceptual Consistency:

Tests for logical consistency indicate that all row and column positions in the selected latitude/longitude window contain data. Conversion and integration with vector files indicates that all positions are consistent with earth coordinates covering the same area. Attribute files are logically consistent.

Lineage

Process Steps

Process Step 1

CC ID: 800809
Description:

This dataset was created by NOAA's Ocean Service, Office for Coastal Management (OCM).

Random Forest Classification: The initial 1m spatial resolution 6 class high resolution land cover product was developed using a Geographic Object-Based Image Analysis (GEOBIA) processing framework. This involves taking each image to be classified and grouping the pixels based on spectral and spatial properties into regions of homogeneity called objects. The resulting objects are the primary units for analysis. Additionally, these objects introduce additional spectral, shape, textural and contextual information into the mapping process and are utilized as independent variables in a supervised classification. Each object is labeled using a Random Forest Classifier which is ensemble version of a Decision Tree. Training data for the initial 6 classes (Herbaceous, Bare, Impervious, Water, Forest and Shrub) were generated through photo interpretation. The resulting Random Forest model was applied to the input data sets to create the initial automated map.

Water Refinement: Commission and omission errors associated with the Water class were addressed through manual interpretation and clean up in ERDAS Imagine. Once the review and edits were complete, the refined Water class was incorporated back into the land cover data set.

Unconsolidated Shore:

Unconsolidated substrate features were extracted primarily through unsupervised classification and manual editing in ERDAS Imagine. This process relied on the USGS Color Orthoimagery (2013/2014) as a primary data source since it was collected at a lower tidal stage relative to other available imagery. Once these features were inserted into the land cover additional object based clean up algorithms were applied.

Agriculture:

Cultivated land and Pasture/Hay features were incorporated into the grassland category of the initial land cover product through a modeling process which relied on multiple dates of imagery as well as the 2005 statewide land use data set. Manual edits were made based on feedback from local experts.

Wetlands:

Wetlands were derived through a modeling process which used ancillary data such as Soils (SSURGO), the National Wetlands Inventory (NWI) and topographic derivatives. Forest, shrub and grassland objects within the initial land cover that exhibited hydric characteristics based on the input ancillary layers were designated to their appropriate wetland category. The process relied mainly on the NWI to determine palustrine and estuarine distinctions.

Open Space Developed:

Managed grasses and other low lying vegetation associated with development were derived using information in the 2005 statewide land use data set. Grassland features in the land cover data that intersected selected land use polygons were designated as Open Space Developed (OSD). To capture OSD features that have appeared since the 2005 land use data was developed, polygons with land use codes that were likely candidates for change were analyzed for the presence of impervious surface based on the 2015 land cover. If the polygon was occupied by a certain percent of impervious surface, the associated grass pixels were changed to Open Space Development. Additional clean up was performed to remove speckle and slivers.

Process Date/Time: 2018-11-01 00:00:00

Catalog Details

Catalog Item ID: 54917
Metadata Record Created By: Erik Hund
Metadata Record Created: 2018-11-20 12:55+0000
Metadata Record Last Modified By: Erik Hund
Metadata Record Last Modified: 2020-09-08 14:47+0000
Metadata Record Published: 2019-02-25
Owner Org: OCM
Metadata Publication Status: Published Externally
Do Not Publish?: N
Metadata Next Review Date: 2020-02-26