This tile service is derived from a digital raster graphic of the historical 15-minute USGS topographic quadrangle maps of coastal towns in Massachusetts. These quadrangles were mosaicked together to create a single data layer of the coast of Massachusetts and a large portion of the southeastern area of the state.The Massachusetts Office of Coastal Zone Management (CZM) obtained the map images from the Harvard Map Collection. The maps were produced in the late 1890s and early 20th century at a scale of 1:62,500 or 1:63,360 and are commonly known as 15-minute quadrangle maps because each map covers a four-sided area of 15 minutes of latitude and 15 minutes of longitude.

This monochromatic image dataset was generated from MassGIS' 2005 elevation surface so that for a specific position of the sun, the values in the image represent the amount of light theoretically reflected to a position directly above the scene. The position of the sun was chosen as follows: - Solar azimuth: 315 degrees measured clockwise from due north (northwest). - Solar elevation: 45 degrees above the horizon. Slopes that face the direction of the sun appear highlighted and slopes that face away from the sun appear in darker shades. The data values have been scaled so that a value of 1 represents zero light reflectance, and a value of 255 represents maximum light reflectance. Shaded relief images are used in analysis, as well as making it easier visually to interpret slope, aspect, and changes in elevation. Shadows are not modeled.

This tiled cached map service is hosted in MassGIS' ArcGIS Online account for fast display.

View metadata at http://www.mass.gov/anf/research-and-tech/it-serv-and-support/application-serv/office-of-geographic-information-massgis/datalayers/elev2005.html.

The data in this map service is a raster (100-meter resolution) that uses average transmissivity from SURFGEO24K_T_AY, topographic relief, and groundwater recharge to calculate the water table ratio. Positive values indicate that the region has a topography-controlled water table, and negative numbers indicate a recharge-controlled water table. For further methods see Gleeson et al. (2011).The Hydrogeologic Atlas of Massachusetts provides data on the hydraulic properties of the statewide surficial aquifers. The datasets were developed using surficial geology, bedrock altitude, a statewide groundwater flow model, and a compilation of hydraulic property data from U.S. Geological Survey groundwater reports, Massachusetts Department of Environmental Protection Zone II reports, and other Massachusetts-specific journal articles (a total of 23 sources).One of the goals of this project was to understand current and projected future groundwater flooding risks across the state. To understand groundwater flooding risks, we developed a statewide three-dimensional groundwater flow model to simulate the water table elevation. The Hydrogeologic Atlas of Massachusetts compiles new datasets developed as input into the groundwater model, groundwater model simulation results, and other statewide map products created through this project. For further information regarding the methods of this study see Corkran et al. (2024), a report submitted to the Massachusetts Executive Office of Energy and Environmental Affairs.Suggested Citation:Corkran, D., Kirshen, A., Moran, B.J., Blin, N., King, R., Bresee, M., & Boutt, D. (2024). Massachusetts State-wide Groundwater Model and Flooding Risk Assessment 1.0. Report funded by the Massachusetts Executive Office of Energy and Environmental Affairs and published on the ResilientMass website.See full metadata.

High resolution land cover dataset for City of Boston, MA. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The primary sources used to derive this land cover layer were 2013 LiDAR data, 2014 Orthoimagery, and 2016 NAIP imagery. Ancillary data sources included GIS data provided by City of Boston, MA or created by the UVM Spatial Analysis Laboratory. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:2500 and all observable errors were corrected.

High resolution land cover dataset for City of Boston, MA. Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The primary sources used to derive this land cover layer were 2013 LiDAR data, 2014 Orthoimagery, and 2016 NAIP imagery. Ancillary data sources included GIS data provided by City of Boston, MA or created by the UVM Spatial Analysis Laboratory. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 1:2500 and all observable errors were corrected.

Credits: University of Vermont Spatial Analysis Laboratory in collaboration with the City of Boston, Trust for Public Lands, and City of Cambridge.

This image in this map service shows the thickness of the overburden across Massachusetts at 100-meter resolution. This raster image is a model of the depth to bedrock at 100-meter resolution determined by subtracting an altitude model of the bedrock surface from topography; all at 100-meter resolution. The altitude model from which the depth to bedrock is estimated is based on the data points feature class.Tile service also available.See full metadata page.

This data release provides a vector digital dataset developed from the published metamorphic map of Massachusetts. This data release is a digital representation of the metamorphic map shown on sheet 2 of the bedrock geologic map of Zen and others (1983). The original publication from 1983 was available in paper only. A scanned raster version of the 1983 map was obtained from the National Geologic Map Database catalog and converted to the geologic map schema known as GeMS. The original metamorphic map was published at 1:500,000-scale. The data release contains GIS files and a metadata file for the database and for each feature class. The GIS files include CartographicLines and ContactsAndFaults as lines, MapUnits and OverlayPolys as polygons. The metamorphic map units range from greenschist to granulite facies. Boundaries between map units include contacts, metamorphic facies boundaries, and faults. References: Zen, E-an, Goldsmith, Richard, Ratcliffe, N.M., Robinson, Peter, Stanle ...

Tile cache of Impervious Surface data for Massachusetts from 2005.The Impervious Surface raster layer represents impervious surfaces covering the Commonwealth of Massachusetts. The surfaces were extracted using semi-automated techniques by Sanborn Map Company from 50-cm Vexcel UltraCam near infrared orthoimagery that was acquired in April 2005 as part of the Color Ortho Imagery project. The pixel size for the impervious surface data is 1-meter.Impervious surfaces are defined as: All constructed surfaces such as buildings, roads, parking lots, brick, asphalt, concrete.Also included are areas of man-made compacted soil or material such as mining or unpaved

parking lots (no vegetation present) Non-impervious surfaces can be defined as: All vegetated areas, natural and man-madeWater bodies and wetland areaSki runsNatural occurring barren areas (i.e. rocky

shores, sand, bare soil)See the full metadata.

This is a seven-category land-cover map of Boxford, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

This is a seven-category land-cover map of Beverly, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

This is a seven-category land-cover map of Danvers, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the chemical soil variable organic carbon density (ocd) which measures carbon mass in proportion to volume of soil (mass divided by volume.)From Agriculture Victoria: Soil carbon provides a source of nutrients through mineralisation, helps to aggregate soil particles (structure) to provide resilience to physical degradation, increases microbial activity, increases water storage and availability to plants, and protects soil from erosion.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for organic carbon density are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Organic carbon density in kg/m³Cell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for ocd were used to create this layer. You may access organic carbon density values in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map: In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "world soils soilgrids" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "world soils soilgrids" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

This is a seamless bare earth digital elevation model (DEM) created from lidar terrain elevation data for the Commonwealth of Massachusetts. It represents the elevation of the surface with vegetation and structures removed. The spatial resolution of the map is 1 meter. The elevation of each 1-meter square cell was linearly interpolated from classified lidar-derived point data.This version of the DEM stores the elevation values as integers. The native VALUE field represents the elevation above/below sea level in meters. MassGIS added a FEET field to the VAT (value attribute table) to store the elevation in feet as calculated by multiplying VALUE x 3.28084.Dates of lidar data used in this DEM range from 2010-2015. The overlapping lidar projects were adjusted to the same projection and datum and then mosaicked, with the most recent data replacing any older data. Several very small gaps between the project areas were patched with older lidar data where necessary or with models from recent aerial photo acquisitions. See https://www.mass.gov/doc/lidar-project-areas-original/download for an index map.This DEM is referenced to the WGS_1984_Web_Mercator_Auxiliary_Sphere spatial reference.See the MassGIS datalayer page to download the data as a file geodatabase raster dataset.View this service in the Massachusetts Elevation Finder.

This is a seven-category land-cover map of Wenham, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

This is a seven-category land-cover map of Andover, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

This layer includes the 1-meter raster cells coded as deciduous or evergreen forest in MassGIS's 2016 C-CAP high resolution land cover raster. The C-CAP dataset 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.

This is a seven-category land-cover map of Andover, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

This is a seven-category land-cover map of Groveland, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

This is a seven-category land-cover map of the Plum Island Sound estuary, Massachusetts. The seven categories are: water, tidal flats and soils, Spartina alterniflora, Spartina patens, trees, grass, impervious surface. These medium resolution true color images are considered the new "basemap" for the Commonwealth by MassGIS. The photography for the entire commonwealth was captured in April 2005 when deciduous trees were mostly bare and the ground was generally free of snow. Image type is 4-band (RGBN) natural color (Red, Green, Blue) and Near infrared in 8 bits (values ranging 0-255) per band format.

This is a seven-category land-cover map of North Reading, Massachusetts. The seven categories are: bare soil, coniferous trees, decidous trees, grass, impervious surface, water, and wetlands. Note: Complete metadata is available within the downloaded zip file. This metadata can be viewed with ESRI ArcGIS software, and can be exported to FGDC and ISO metadata formats.

To map the predicted sea level rise for Barnstable County (Cape Cod) the most accurate elevation data was obtained and adjusted to account for vertical datum variations as well as localized tidal information. This adjusted data, was then separated into areas below sea level and into 1 ft increments (up to 6ft) above sea level. Topographical elevation data was sourced from remotely sensed LiDAR data which was collected in the Winter and Spring of 2011, while no snow was on the ground, rivers were at or below normal levels and within 90 minutes of the daily predicted low tide. For Barnstable County, the LiDAR was processed and classified to meet a bare earth Fundamental Vertical Accuracy (FVA) of 18.13 cm at a 95% confidence level. The topological elevation data was in a grid format, as a Digital Elevation Model (DEM) with a cell size of 1 meter. In order to incorporate tidal variability within an area when mapping sea level rise, a “modeled” surface (or raster) is needed that represents this variability. In addition, this surface must be represented in the same vertical datum as the elevation data. To account for the datum and tidal differences across the county the DEM was adjusted to localized conditions using the NOAA VDatum (Verticle Datum Transformation) software. The VDatum program was used to convert a 500m grid of points that covered the entire Barnstable County area from the source of North American Vertical Datum 88 (NAVD 88) to Mean Higher High Water (MHHW). MHHW is the average of the higher high water height of each tidal day observed over the National Tidal Datum Epoch. The 500m MHHW grid was then interpolated into a 1m grid that was identical in spatial extent to the 1m topographical DEM. The topographical DEM was then adjusted on a cell-by-cell basis to account for the MHHW elevation.