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                <pubDate>2019-05-15T00:00:00</pubDate>
                			
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        <idPurp>This statewide dataset contains a combination of land cover mapping from 2016 aerial imagery and land use derived from standardized assessor parcel information for Massachusetts.</idPurp>
        		
        <idAbs>&lt;DIV STYLE="text-align:Left;"&gt;&lt;DIV&gt;&lt;DIV&gt;&lt;P&gt;&lt;SPAN&gt;This statewide dataset contains a combination of land cover mapping from 2016 aerial imagery and land use derived from standardized assessor parcel information for Massachusetts. &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Each location in this layer is associated with a land cover class value as well as a parcel use code&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Although both land cover and land use information are included, each of these aspects can be accessed independently, or in interesting and useful combinations with one another. For instance, a user can simply display impervious surfaces (land cover), or commercial parcels (land use). In combination, it is possible to display and measure the portions of the commercial parcels that are covered by impervious surfaces or the portions of residential parcels used as developed open space.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;This layer is the result of a cooperative project between MassGIS and the National Oceanic and Atmospheric Administration’s (NOAA) Office of Coastal Management (OCM). Funding was provided by the Mass. Executive Office of Energy and Environmental Affairs.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;MassGIS stores the data as a single statewide polygon feature class named &lt;/SPAN&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;LANDCOVER_LANDUSE_POLY&lt;/SPAN&gt;&lt;SPAN&gt;in the spatial reference of NAD_1983_Contiguous_USA_Albers (EPSG: 5070).&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;Data development&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;The following sections describe the development and features of the two components, land cover and land use, as well as the final combined dataset.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN STYLE="font-style:italic;font-weight:bold;"&gt;Land cover&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;The thematic land cover dataset was created in raster format by NOAA's Coastal Change Analysis Program (C-CAP). C-CAP has produced numerous standardized land cover products which are included in the National Land Cover Database. These products are used in numerous ways to assess urban growth, inventory wetlands, coastal intertidal areas, and adjacent uplands, and delineate wildlife habitat to monitor changes in these areas. This information helps in the understanding of the landscape's response to natural and human-caused changes. OCM worked in close coordination with MassGIS to produce the land cover. OCM delivered the data to MassGIS in an Albers projection.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;2016 NAIP imagery This 2016 land cover information was initially developed as a 1-meter, 6-category draft raster derived from 2016 USDA National Agricultural Imagery Program (NAIP) aerial multispectral imagery. Classes were impervious, bare, grass, shrub, tree, and water. Additional reference data were used to create this 19-class version, including: 2016 WorldView multispectral satellite imagery, lidar-based terrain elevation data, 2016-era 2D structures data, and other ancillary data such as MassDOT Roads, MassDEP Wetlands, etc. The wetlands in the final land cover product are exclusively from the C-CAP program and will differ from the MassDEP Wetlands data.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;The land cover information in this product is consistent with C-CAP’s High-Resolution Land Cover Classification Scheme (PDF). Also see General information about C-CAP High-Resolution Land Cover.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN STYLE="font-style:italic;font-weight:bold;"&gt;Land use&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;The land use component of the data layer is represented by the Property Type Classification Code associated with each parcel in MassGIS' Standardized "Level 3" Parcels layer. These "use codes" come from the Mass. Department of Revenue Division of Local Services (DLS), along with custom use codes some municipalities include in their parcel data.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;For this project, MassGIS created a parcel layer using data deliverables as close as possible to the time of the 2016 NAIP imagery used for the land cover. Since parcel data complying with Level 3 of the MassGIS standard was not available from every municipality for the year 2016, some information was selected from a different year to use data as close to 2016 as possible, with the following rules:&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;If Fiscal Year (FY) 2016 data was available, it was used. Otherwise, data was used from other years in the following order: 2017 (+1), 2015 (-1), 2018 (+2), 2014 (-2), 2013 (-3), 2012 (-4), 2011 (-5). Fiscal year values were retained in the final product to help indicate relative reliability of the USECODE.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;MassGIS merged these parcel data into one feature class and dissolved them based on these fields: &lt;/SPAN&gt;&lt;/P&gt;&lt;P STYLE="margin:1 1 1 20;"&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;USE_CODE&lt;/SPAN&gt;&lt;SPAN&gt;: Use code from DOR DLS, along with custom use codes some municipalities include in their parcel data.&lt;/SPAN&gt;&lt;SPAN /&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;P STYLE="margin:1 1 1 20;"&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;FY&lt;/SPAN&gt;&lt;SPAN&gt;: Fiscal year &lt;/SPAN&gt;&lt;SPAN /&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;P STYLE="margin:1 1 1 20;"&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;POLY_TYPE&lt;/SPAN&gt;&lt;SPAN&gt;: Parcel type (FEE, TAX, ROW, WATER, PRIV_ROW, RAIL_ROW)&lt;/SPAN&gt;&lt;/P&gt;&lt;P STYLE="margin:1 1 1 20;"&gt;&lt;SPAN /&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;TOWN_ID&lt;/SPAN&gt;&lt;SPAN&gt;: Town ID (1-351) &lt;/SPAN&gt;&lt;SPAN /&gt;&lt;SPAN /&gt;&lt;/P&gt;&lt;P STYLE="margin:1 1 1 20;"&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;GEN_CODE&lt;/SPAN&gt;&lt;SPAN&gt;: Generalized use code chosen by MassGIS for this project to simplify the 1,600+ USE_CODEs for map display. &lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN STYLE="font-style:italic;font-weight:bold;"&gt;Combined Land Cover – Land Use Data&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;For efficient processing and distribution, MassGIS split up the statewide land cover raster into 291 smaller, regularly sized and spaced tiles, each 10km by 10km (10,000 x 10,000 pixels).&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;The Create Fishnet tool produced a polygon index that precisely fit the tiles. The tiles were identified with a TILENAME value based on row and column position. For example, TILENAME “R07C17” identifies the tile in row 7, column 17. The index is named &lt;/SPAN&gt;&lt;SPAN STYLE="font-weight:bold;"&gt;LANDCOVER_USE_INDEX_POLY&lt;/SPAN&gt;&lt;SPAN&gt;. Aside from TILENAME, the other field is SHP_LINK, which stores a link to download a zipped land cover-land use shapefile for each tile.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;Each land cover image was converted to a polygon shapefile using a Raster to Shapefile model in ERDAS IMAGINE. This method preserves the thematic attributes and simplifies the polygons very slightly.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;MassGIS carried out the following steps in ArcGIS 10.6.1: &lt;/SPAN&gt;&lt;/P&gt;&lt;UL&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Reprojected the land use polygons from Massachusetts State Plane to the same Albers projection of the land cover.&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Used the Identity tool to geometrically combine the land cover polygons with the dissolved parcel data to produce a land cover-land use feature class for each tile.&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Checked and repaired the geometry of the Identity output.&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;LI&gt;&lt;P&gt;&lt;SPAN&gt;Converted all multipart polygons to single-part polygons in the Identity output.&lt;/SPAN&gt;&lt;/P&gt;&lt;/LI&gt;&lt;/UL&gt;&lt;P&gt;&lt;SPAN&gt;The Identity created numerous very small polygons because the two components (land cover and land use) were not spatially correlated. To preserve the input data, MassGIS decided not to eliminate polygons or perform any other cartographic refinement at this point. Users can easily perform these operations if desired.&lt;/SPAN&gt;&lt;/P&gt;&lt;P&gt;&lt;SPAN&gt;As part of final QA, MassGIS modified the attributes of a small number of polygons with erroneous land cover or generalized land use codes, including a few right-of-way polygons in Boston that did not have the correct USEGENCODE of 55.&lt;/SPAN&gt;&lt;/P&gt;&lt;/DIV&gt;&lt;/DIV&gt;&lt;/DIV&gt;</idAbs>
        		
        <idCredit>The land cover dataset was created in raster format by the Coastal Change Analysis Program (C-CAP) of the National Oceanic and Atmospheric Administration (NOAA) Ocean Service, Office for Coastal Management (OCM). C-CAP has produced numerous standardized land cover products which are included in the National Land Cover Database. Parcel data are developed at the municipal level and compiled and standardized by MassGIS. Funding was provided by the Mass. Executive Office of Energy and Environmental Affairs.</idCredit>
        		
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            <keyword>Massachusetts</keyword>
            			
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            <keyword>commercial</keyword>
            			
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            <attr>
                				
                <attrlabl Sync="TRUE">LanduseSimple</attrlabl>
                				
                <attalias Sync="TRUE">LanduseSimple</attalias>
                				
                <attrtype Sync="TRUE">String</attrtype>
                				
                <attwidth Sync="TRUE">50</attwidth>
                				
                <atprecis Sync="TRUE">0</atprecis>
                				
                <attscale Sync="TRUE">0</attscale>
                			
            </attr>
            			
            <attr>
                				
                <attrlabl Sync="TRUE">Shape_Length</attrlabl>
                				
                <attalias Sync="TRUE">Shape_Length</attalias>
                				
                <attrtype Sync="TRUE">Double</attrtype>
                				
                <attwidth Sync="TRUE">8</attwidth>
                				
                <atprecis Sync="TRUE">0</atprecis>
                				
                <attscale Sync="TRUE">0</attscale>
                				
                <attrdef Sync="TRUE">Length of feature in internal units.</attrdef>
                				
                <attrdefs Sync="TRUE">Esri</attrdefs>
                				
                <attrdomv>
                    					
                    <udom Sync="TRUE">Positive real numbers that are automatically generated.</udom>
                    				
                </attrdomv>
                			
            </attr>
            			
            <attr>
                				
                <attrlabl Sync="TRUE">Shape_Area</attrlabl>
                				
                <attalias Sync="TRUE">Shape_Area</attalias>
                				
                <attrtype Sync="TRUE">Double</attrtype>
                				
                <attwidth Sync="TRUE">8</attwidth>
                				
                <atprecis Sync="TRUE">0</atprecis>
                				
                <attscale Sync="TRUE">0</attscale>
                				
                <attrdef Sync="TRUE">Area of feature in internal units squared.</attrdef>
                				
                <attrdefs Sync="TRUE">Esri</attrdefs>
                				
                <attrdomv>
                    					
                    <udom Sync="TRUE">Positive real numbers that are automatically generated.</udom>
                    				
                </attrdomv>
                			
            </attr>
            		
        </detailed>
        	
    </eainfo>
    	
    <mdDateSt Sync="TRUE">20260403</mdDateSt>
    	
    <Binary>
        		
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        </Thumbnail>
        	
    </Binary>
    	
    <mdChar>
        		
        <CharSetCd value="004">
		</CharSetCd>
        	
    </mdChar>
    	
    <mdContact>
        		
        <editorSource>external</editorSource>
        		
        <editorDigest>a258336ed64c9a9dba524b8ce0322c94</editorDigest>
        		
        <rpOrgName>MassGIS</rpOrgName>
        		
        <rpCntInfo>
            			
            <cntAddress addressType="both">
                				
                <delPoint>One Ashburton Place, Room 819</delPoint>
                				
                <city>Boston</city>
                				
                <adminArea>MA</adminArea>
                				
                <postCode>02108</postCode>
                				
                <country>US</country>
                			
            </cntAddress>
            			
            <cntPhone>
                				
                <voiceNum tddtty="">617-619-5611</voiceNum>
                			
            </cntPhone>
            		
        </rpCntInfo>
        		
        <editorSave>True</editorSave>
        		
        <displayName>MassGIS</displayName>
        		
        <role>
            			
            <RoleCd value="001">
			</RoleCd>
            		
        </role>
        	
    </mdContact>
    	
    <mdMaint>
        		
        <maintFreq>
            			
            <MaintFreqCd value="012">
			</MaintFreqCd>
            		
        </maintFreq>
        	
    </mdMaint>
    	
    <dqInfo>
        		
        <dqScope>
            			
            <scpLvl>
                				
                <ScopeCd value="005">
				</ScopeCd>
                			
            </scpLvl>
            		
        </dqScope>
        		
        <report dimension="" type="DQAbsExtPosAcc">
            			
            <measDesc>According to the accuracy assessment performed by NOAA Office for Coastal Management staff, the overall accuracy of the land cover data 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%)</measDesc>
            			
            <evalMethDesc>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 Google Earth 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.</evalMethDesc>
            			
            <evalMethType>
                				
                <EvalMethTypeCd value="002">
				</EvalMethTypeCd>
                			
            </evalMethType>
            		
        </report>
        		
        <dataLineage>
            			
            <statement>Land cover raster data creation</statement>
            			
            <prcStep>
                				
                <stepDesc>The land cover data were 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 speckles and slivers.</stepDesc>
                				
                <stepDateTm>2018-11-20T00:00:00</stepDateTm>
                				
                <stepProc>
                    					
                    <rpOrgName>NOAA Office for Coastal Management </rpOrgName>
                    					
                    <role>
                        						
                        <RoleCd value="006">
						</RoleCd>
                        					
                    </role>
                    					
                    <rpCntInfo>
                        						
                        <cntAddress addressType="both">
                            							
                            <eMailAdd>coastal.info@noaa.gov</eMailAdd>
                            							
                            <delPoint>2234 South Hobson Ave</delPoint>
                            							
                            <city>Charleston</city>
                            							
                            <adminArea>SC</adminArea>
                            							
                            <postCode>29405-2413</postCode>
                            							
                            <country>US</country>
                            						
                        </cntAddress>
                        						
                        <cntPhone>
                            							
                            <voiceNum tddtty="">(843) 740-1202</voiceNum>
                            						
                        </cntPhone>
                        					
                    </rpCntInfo>
                    				
                </stepProc>
                			
            </prcStep>
            		
        </dataLineage>
        	
    </dqInfo>
    
</metadata>