Data Management Plan (Deprecated)

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 data is 2015, 2016, or 2017 (depending on the exact date of imagery used). These maps are developed through the automated classification of high resolution National Agriculture Imagery Program (NAIP) imagery, available Lidar digital elevation data, and assorted ancillary information.

While produced as part of the Coastal Change Analysis Program (C-CAP), these products should not be compared directly to past dates of 30-meter C-CAP to identify change, as there will be vast differences caused by the different methods and the classes mapped.

These data should be considered to be BETA-level or draft products. They are based on 1-meter land cover mapping that were entirely automated and the relationship of those data to existing wetlands data. As such, there may be issues that result from the different vintages of these products, as well as the errors included in each. While not perfect, the data should provide an example of what level of detail would be possible through such higher-resolution mapping.

These data are not jurisdictional or intended for use in litigation. NOAA does not assume liability for any damages or misrepresentations caused by inaccuracies in the data, or as a result of the data used on a particular system. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute such a warranty.

Process Steps:

• 2018-11-01 00:00:00 - This dataset was created by NOAA's Ocean Service, Office for Coastal Management (OCM). Process_Description: This dataset was created by the NOAA National Ocean Service (NOS), Office for Coastal Management (OCM). It was based on a 6 category land cover that was produced using a random forest classifier and Geographic Object-Based Image Analysis (GEOBIA) processing framework. That classification was performed by EarthDefine LLC (under contract to NOAA OCM), as part of NOAA’s Coastal Change Analysis Program (C-CAP) efforts. This classification is based on high resolution National Agriculture Imagery Program (NAIP) imagery, available Lidar digital elevation data, and assorted ancillary information. The resulting land cover was then combined with U.S. Fish and Wildlife Servie’s (USFWS) National Wetland Inventory (NWI) data, using a logic based rule set. The final classification includes up to 15 categories. 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. Resampling: The resulting 1-meter land cover was then resampled to a 10-meter raster. This was done using a 10x10 focal pixel window to compute the percent value for each land cover type in the 100 pixel neighborhood around each target pixel, and subsequently performing a nearest neighbor resampling of the resulting values. Land cover was then assembled based on the land cover category that represented the largest overall percentage of the output 10-meter cell (i.e. the majority cover type), except where values of impervious exceeded 20% in which case Impervious Developed would be forced into the classification (even if not the majority for that cell). Wetlands: Wetlands were derived through a modeling process which used the National Wetlands Inventory (NWI), exported to a 10-meter raster grid to a classification that matched the wetland categories typically included within C-CAP land cover products. A logic based rule set was then applied. This rule set accounted for changes in condition of wetland features, since the NWI mapping occurred. This was based on how those features were mapped in the 6 category land cover described above, as compared to the NWI class. 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.