20171213
Massachusetts Bureau of Geographic Information (MassGIS)
(617) 619-5611
paul.nutting@state.ma.us
One Ashburton Place
Boston
MA
02108
9 AM - 5 PM
Download from https://docs.digital.mass.gov/dataset/massgis-data-massdep-wetlands-2005
Shapefile
Shapefile
233.742
MassDEP Wetland Polygons
Massachusetts Department of Environmental Protection (MassDEP)
Michael McHugh
Wetlands Conservancy Program
michael.mchugh@state.ma.us
1 Winter Street
Boston
MA
02108
US
617-556-1163
vector digital data
2017-12-13T00:00:00
Massachusetts Bureau of Geographic Information (MassGIS)
paul.nutting@state.ma.us
One Ashburton Place
Boston
MA
02108
US
(617) 619-5611
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN STYLE="font-size:10pt">The MassDEP Wetlands dataset comprises two ArcGIS geodatabase feature classes:</SPAN></P><UL><LI><P><SPAN STYLE="font-size:10pt">The </SPAN><SPAN STYLE="font-weight:bold;font-size:10pt">WETLANDSDEP_POLY </SPAN><SPAN STYLE="font-size:10pt">layer contains polygon features delineating mapped wetland resource areas and attribute codes indicating wetland type.</SPAN></P></LI><LI><P><SPAN STYLE="font-size:10pt">The </SPAN><SPAN STYLE="font-weight:bold;font-size:10pt">WETLANDSDEP_ARC </SPAN><SPAN STYLE="font-size:10pt">layer was generated from the polygon features and contains arc attribute coding based on the adjacent polygons as well as arcs defined as hydrologic connections.</SPAN></P></LI></UL><P><SPAN STYLE="font-size:10pt">Together these statewide layers enhance and replace the original MassDEP wetlands layers, formerly known as DEP Wetlands (1:12,000). It should be noted that these layers provide a medium-scale representation of the wetland areas of the state and are for planning purposes only. </SPAN><SPAN STYLE="font-weight:bold;font-size:10pt">Wetlands boundary determination for other purposes, such as the Wetlands Protection Act MA Act M.G.L. c. 131 or local bylaws must use the relevant procedures and criteria</SPAN><SPAN STYLE="font-size:10pt">.</SPAN></P><P><SPAN STYLE="font-size:10pt">The original MassDEP wetlands mapping project was based on the photo-interpretation of 1:12,000, stereo color-infrared (CIR) photography, captured between 1990 and 2000, and included field verification by the MassDEP Wetlands Conservancy Program (WCP). In 2007 the MassDEP WCP began a statewide effort to assess and where necessary update the original wetlands data. The MassDEP WCP used ESRI ArcGIS Desktop software, assisted by the PurVIEW Stereo Viewing extension, to evaluate and update the original wetlands features based on photo-interpretation of 0.5m, (1:5,000) digital stereo CIR imagery statewide, captured in April 2005. No field verification was conducted on this updated 2005 wetlands data.</SPAN></P><P><SPAN STYLE="font-size:10pt">The 2005 </SPAN><SPAN STYLE="font-weight:bold;font-size:10pt">WETLANDSDEP_POLY </SPAN><SPAN STYLE="font-size:10pt">layer includes polygon features that distinguish it from its predecessor by overall changes in size and shape. In addition, new polygons have been created and original ones deleted. Many of the polygons, however, remain the same as in the original layer. All changes have been made according to the techniques described below. For the purpose of cartographic continuity, a small number of coastal polygons outside the state boundary where added based on data provided by the United States Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA).</SPAN></P><P><SPAN STYLE="font-size:10pt">The 2005 </SPAN><SPAN STYLE="font-weight:bold;font-size:10pt">WETLANDSDEP_ARC </SPAN><SPAN STYLE="font-size:10pt">layer was generated to support map display and was designed to cartographically enhance the rendering of wetland features on a base map. Arc features in this layer were generated from the wetland polygons and coding (ARC_CODE) was assigned based on the adjacent polygon types. Hydrologic connection features (ARC_CODE = 7) were then added. Where delineated, these arc features indicate an observed hydrologic connection to or between wetland polygons. Although efforts were made to be comprehensive and thorough in mapping hydrologic connections, due to the limitations of aerial photo-interpretation some areas may have been missed.</SPAN></P><P STYLE="margin:0 0 14 0;"><SPAN STYLE="font-size:10pt">The types of updates made to the original wetland features include alteration, movement/realignment and reclassification. In some cases original wetland areas have been deleted and new areas have been added. Updates to original wetland features resulted from the following factors: changes in the natural environment due to human activity or natural causes; advances in the field of remote sensing, allowing for more refined mapping.</SPAN></P><P STYLE="margin:7 0 7 0;"><SPAN STYLE="font-weight:bold;font-size:10pt">Edit changes to the original wetland data include:</SPAN></P><UL><LI><P STYLE="text-align:Justify;font-size:16pt"><SPAN STYLE="font-size:9pt">Addition of new wetland and hydrologic connection features</SPAN></P></LI><LI><P STYLE="text-align:Justify;font-size:16pt"><SPAN STYLE="font-size:9pt">Appending (expansion or realignment) of existing (original) wetland and hydrologic connection features</SPAN></P></LI><LI><P STYLE="text-align:Justify;font-size:16pt"><SPAN STYLE="font-size:9pt">Reclassification of wetlands features, due to change in wetlands environment from the original classification</SPAN></P></LI><LI><P STYLE="font-size:16pt"><SPAN STYLE="font-size:9pt">Movement (or shifting) of original wetland features to better match the source imagery</SPAN></P></LI><LI><P STYLE="font-size:16pt"><SPAN STYLE="font-size:9pt">Deletion of original wetland or hydrologic connection features due to changes in wetlands environment or inconsistency with mapping criteria.</SPAN></P></LI></UL><P><SPAN STYLE="font-size:10pt">Please note that although efforts were made to be comprehensive and thorough in the evaluation and mapping of statewide wetland resources some areas of the state may have been missed. Many of the wetland and hydrologic connection features remain the same as in the original data. The polygon attribute SOURCE_SCALE may be used to identify areas that have been altered from the original wetlands. The SOURCE_SCALE code 5000 indicates an updated wetland area. The SOURCE_SCALE code 12000 indicates an unaltered, original wetland polygon.</SPAN></P></DIV></DIV></DIV>
Identification and delineation of Massachusetts wetlands features. Purposes include analysis, planning, monitoring, and supervision to enhance and protect the Massachusetts wetlands environments.
Massachusetts Department of Environmental Protection (MassDEP)
Michael McHugh
Wetlands Conservancy Program
michael.mchugh@state.ma.us
1 Winter Street
Boston
MA
02108
US
617-556-1163
Michael McHugh
wetlands swamp marshes marsh bogs open water beach rocky shore tidal salt features ponds lakes hydrologic
MassDEP Wetlands Conservancy Program water wetlands swamps marsh bogs beach ponds lakes reservoir tidal dune rocky shore features streams hydrology
ESRI ArcGIS 9x and 10x
publication date
0
-73.526483
-69.410358
40.884
42.908627
1
-73.526483
-69.410358
42.908627
40.884000
Massachusetts Deptartment of Environmental Protection (MassDEP) Wetlands Conservancy Program (WCP)
James Brown
Massachusetts Department of Environmental Protection (MassDEP)
Wetlands Conservancy Program GIS Anaylst
1 Winter St
Boston
MA
02108
US
jim.brown@state.ma.us
9 AM - 5 PM
617-574-6890
James Brown
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN><SPAN>It should be noted that these layers provide a medium-scale representation of the wetland areas of the state and are for planning purposes only. </SPAN></SPAN><SPAN STYLE="font-weight:bold;"><SPAN>Wetlands boundary determination for other purposes, such as the Wetlands Protection Act MA Act M.G.L. c. 131 or local bylaws must use the relevant procedures and criteria.</SPAN></SPAN></P><P><SPAN /></P></DIV></DIV></DIV>
199633
WETLANDSDEP_POLY
Feature Class
199633
FID
FID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
AREAACRES
AREA IN ACRES
AREAACRES
Double
19
0
0
MassDEP
SOURCE
ORIGINATOR OF FEATURE
SOURCE
String
12
0
0
MassDEP
SHAPE
FEATURE GEOMETRY
ESRI
Coordinates defining the features.
Shape
Geometry
0
0
0
IT_VALDESC
WETLAND CONSERVANCY PROGRAM TYPE DESCRIPTION
IT_VALDESC
String
60
0
0
MassDEP
WETCODE
WETLAND CONSERVANCY PROGRAM TYPE CODE
WETCODE
Integer
10
10
0
MassDEP
IT_VALC
WETLAND CONSERVANCY PROGRAM TYPE ABBREVIATION
OW
OPEN WATER
BB-OW
BARRIER BEACH-OPEN WATER
BB-DM
BARRIER BEACH-DEEP MARSH
BG
BOG
BB-WS2
BARRIER BEACH-WOODED SWAMP CONIFEROUS
D
COASTAL DUNE
TF
TIDAL FLAT
BA
COASTAL BANK BLUFF OR SEA CLIFF
BE
COASTAL BEACH
WS1
WOODED SWAMP DECIDUOUS
CB
CRANBERRY BOG
BB-BE
BARRIER BEACH-COASTAL BEACH
BB-D
BARRIER BEACH-COASTAL DUNE
M
SHALLOW MARSH MEADOW OR FEN
BB-WS1
BARRIER BEACH-WOODED SWAMP DECIDUOUS
RS
ROCKY INTERTIDAL SHORE
DM
DEEP MARSH
SS
SHRUB SWAMP
N/A
NOT INTERPRETED
SM
SALT MARSH
WS3
WOODED SWAMP MIXED TREES
WS2
WOODED SWAMP CONIFEROUS
BB-M
BARRIER BEACH-MARSH
BB-BG
BARRIER BEACH-BOG
BB-WS3
BARRIER BEACH-WOODED SWAMP MIXED TREES
BB-SS
BARRIER BEACH-SHRUB SWAMP
BB-SM
BARRIER BEACH-SALT MARSH
BB
BARRIER BEACH SYSTEM
IT_VALC
String
16
0
0
MassDEP
SOURCE_SCA
SOURCE_SCA
Integer
10
10
0
AREASQMI
AREA IN SQUARE MILES
AREASQMI
Double
19
0
0
MassDEP
POLY_CODE
SIMPLIFIED POLY CODE FROM HYDRO25K_POLY
5
SALT MARSH
4
CRANBERRY BOG
88
NOT INTERPRETED
3
WOODED SWAMP
8
BEACH/DUNES
10
OCEAN
9
OPEN WATER - TIDAL, BRACKISH, SALT POND
7
TIDAL FLAT/ROCKY SHORE
1
RESERVOIR (PWSID CODED)
6
OPEN WATER
2
MARSH
POLY_CODE
Integer
10
10
0
MassDEP
SHAPE_AREA
SHAPE_AREA
Double
19
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
SHAPE_LEN
SHAPE_LEN
Double
19
0
0
dataset
EPSG
7.4.1
James Brown
Massachusetts Department of Environmental Protection (MassDEP)
Wetlands Conservancy Program GIS Analyst
1 Winter St
Boston
MA
02108
US
jim.brown@state.ma.us
9 AM - 5 PM
(617) 574-6890
James Brown
Michael McHugh
Massachusetts Department of Environmental Protection (MassDEP)
Wetlands Conservancy Program
michael.mchugh@state.ma.us
617-556-1163
MassDEP Wetlands Polygons
MassDEP Wetlands Conservancy Program
20171213
Identification and delineation of Massachusetts wetlands features. Purposes include analysis, planning, monitoring, and supervision to enhance and protect the Massachusetts wetlands environments.
The MassDEP Wetlands dataset comprises two ArcGIS geodatabase feature classes:
• The WETLANDSDEP_POLY layer contains polygon features delineating mapped wetland resource areas and attribute codes indicating wetland type.
• The WETLANDSDEP_ARC layer was generated from the polygon features and contains arc attribute coding based on the adjacent polygons as well as arcs defined as hydrologic connections.
Together these statewide layers enhance and replace the original MassDEP wetlands layers, formerly known as DEP Wetlands (1:12,000). It should be noted that these layers provide a medium-scale representation of the wetland areas of the state and are for planning purposes only. Wetlands boundary determination for other purposes, such as the Wetlands Protection Act MA Act M.G.L. c. 131 or local bylaws must use the relevant procedures and criteria.
The original MassDEP wetlands mapping project was based on the photo-interpretation of 1:12,000, stereo color-infrared (CIR) photography, captured between 1990 and 2000, and included field verification by the MassDEP Wetlands Conservancy Program (WCP). In 2007 the MassDEP WCP began a statewide effort to assess and where necessary update the original wetlands data. The MassDEP WCP used ESRI ArcGIS Desktop software, assisted by the PurVIEW Stereo Viewing extension, to evaluate and update the original wetlands features based on photo-interpretation of 0.5m, (1:5,000) digital stereo CIR imagery statewide, captured in April 2005. No field verification was conducted on this updated 2005 wetlands data.
The 2005 WETLANDSDEP_POLY layer includes polygon features that distinguish it from its predecessor by overall changes in size and shape. In addition, new polygons have been created and original ones deleted. Many of the polygons, however, remain the same as in the original layer. All changes have been made according to the techniques described below. For the purpose of cartographic continuity, a small number of coastal polygons outside the state boundary where added based on data provided by the United States Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA).
The 2005 WETLANDSDEP_ARC layer was generated to support map display and was designed to cartographically enhance the rendering of wetland features on a base map. Arc features in this layer were generated from the wetland polygons and coding (ARC_CODE) was assigned based on the adjacent polygon types. Hydrologic connection features (ARC_CODE = 7) were then added. Where delineated, these arc features indicate an observed hydrologic connection to or between wetland polygons. Although efforts were made to be comprehensive and thorough in mapping hydrologic connections, due to the limitations of aerial photo-interpretation some areas may have been missed.
The types of updates made to the original wetland features include alteration, movement/realignment and reclassification. In some cases original wetland areas have been deleted and new areas have been added. Updates to original wetland features resulted from the following factors: changes in the natural environment due to human activity or natural causes; advances in the field of remote sensing, allowing for more refined mapping.
Edit changes to the original wetland data include:
• Addition of new wetland and hydrologic connection features
• Appending (expansion or realignment) of existing (original) wetland and hydrologic connection features
• Reclassification of wetlands features, due to change in wetlands environment from the original classification
• Movement (or shifting) of original wetland features to better match the source imagery
• Deletion of original wetland or hydrologic connection features due to changes in wetlands environment or inconsistency with mapping criteria.
Please note that although efforts were made to be comprehensive and thorough in the evaluation and mapping of statewide wetland resources some areas of the state may have been missed. Many of the wetland and hydrologic connection features remain the same as in the original data. The polygon attribute SOURCE_SCALE may be used to identify areas that have been altered from the original wetlands. The SOURCE_SCALE code 5000 indicates an updated wetland area. The SOURCE_SCALE code 12000 indicates an unaltered, original wetland polygon.
English
For the purpose of cartographic continuity, a small number of coastal polygons outside the state boundary where added based on data provided by the United States Geological Survey (USGS) and the National Oceanic and Atmospheric Administration (NOAA).
20171213
publication date
None planned
None
Wetlands boundary determination for other purposes, such as the Wetlands Protection Act MA Act M.G.L. c. 131 or local by-laws, must use the relevant procedures and criteria.
Massachusetts Department of Environmental Protection (MassDEP) Wetlands Conservancy Program (WCP)
geodatabase feature class
Massachusetts Bureau of Geographic Information (MassGIS)
617-619-5611
paul.nutting@state.ma.us
9am - 5pm
mailing and physical address
One Ashburton Place
Boston
MA
02108
United States
Downloadable Data
James Brown
MA Dept. of Environmental Protection (MassDEP)
Wetlands Conservancy Program - GIS Analyst
617-574-6890
jim.brown@state.ma.us
9am - 5pm
FGDC Content Standards for Digital Geospatial Metadata
None
None
False
False
False
False
False
False
False
Simple
FALSE
199633
TRUE
FALSE
20171023
18060900
1.0
FGDC CSDGM Metadata
FALSE
WETLANDSDEP_POLY
002
34476.019256
370684.843417
739141.312250
962000.000309
1
233.742
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_StatePlane_Massachusetts_Mainland_FIPS_2001
<ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/10.4'><WKT>PROJCS["NAD_1983_StatePlane_Massachusetts_Mainland_FIPS_2001",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",200000.0],PARAMETER["False_Northing",750000.0],PARAMETER["Central_Meridian",-71.5],PARAMETER["Standard_Parallel_1",41.71666666666667],PARAMETER["Standard_Parallel_2",42.68333333333333],PARAMETER["Latitude_Of_Origin",41.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26986]]</WKT><XOrigin>-36530900</XOrigin><YOrigin>-28803200</YOrigin><XYScale>122610652.81195112</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26986</WKID><LatestWKID>26986</LatestWKID></ProjectedCoordinateSystem>
20171213
13484500
20171213
13502200
50000
5000
FGDC
Massachusetts Bureau of Geographic Information (MassGIS)
(617) 619-5611
paul.nutting@state.ma.us
One Ashburton Place
Boston
MA
02108
9 AM - 5 PM
Massachusetts Office of Geographic Information (MassGIS)
State Plane Massachusetts Mainland Meters (FIPS 2001)
North American Datum of 1983
Geodetic Reference System 80
6378137.000000
298.257222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=