This ArcGIS model inserts a file name into a feature class attribute table. The tool allows an user to identify features by a field that reference the name of the original file. It is useful when an user have to merge multiple feature classes and needs to identify which layer the features come from.

MassGIS Level 3 Parcel Data: Data Fiscal Year: Aquinnah 2019, Chilmark 2020, Edgartown 2021, Gosnold 2015, Oak Bluffs 2020, Tisbury 2020, West Tisbury 2021.Building Info Table: Acquired by MVC from Town Assessors in FY20.Downloaded from MassGIS,, this polygon file represents the parcel bounds for the 7 towns in Dukes County MA (Aquinnah, Chilmark, Edgartown, Godnold, Oak Bluffs, Tisbury, West Tisbury). Each town has their own parcel data consultant and then the data are forwarded to MassGIS for final processing. All data comply with the MassGIS Level 3 Parcel Data Standard. This file geodatabase only includes the TaxPar feature class and Assess table for each town. All TaxPar feature classes were appended into one feature class (Parcels_duk) by the MVC.Each assess table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Assess table. The Assess Table contains info about ownership and assessed values. This is not a detailed building table. If there are multiple owners associated with a property, then the Assess table will have multiple records for that property/parcel (such as for condo parcels).Each building table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Bldg table. The Bldg (building) table contains info about each building on the parcel (such as number of bedrooms, number of bathrooms, the living area square footage, etc.). NOTES of CAUTION: The Living Area Square Footage may not represent the exact same thing in each town. As a generalization, Living Area is interior space that is heated. Regarding West Tisbury, their building table only contains info for one building on the parcel. It is uncertain at this time if the info is the most recent, most primary, or some kind of summarization where multiple buildings on a parcel exist.The field of [assess_mYB] is appended to the TaxPar feature class based on an analysis of the info provided in the building table. This field [assess_mYB] is utilized in the Historic Structures App found in ArcGIS OnLine.

MassGIS Level 3 Parcel Data: Data Fiscal Year: Aquinnah 2019, Chilmark 2020, Edgartown 2021, Gosnold 2015, Oak Bluffs 2020, Tisbury 2020, West Tisbury 2021.Building Info Table: Acquired by MVC from Town Assessors in FY20.Downloaded from MassGIS,, this polygon file represents the parcel bounds for the 7 towns in Dukes County MA (Aquinnah, Chilmark, Edgartown, Godnold, Oak Bluffs, Tisbury, West Tisbury). Each town has their own parcel data consultant and then the data are forwarded to MassGIS for final processing. All data comply with the MassGIS Level 3 Parcel Data Standard. This file geodatabase only includes the TaxPar feature class and Assess table for each town. All TaxPar feature classes were appended into one feature class (Parcels_duk) by the MVC.Each assess table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Assess table. The Assess Table contains info about ownership and assessed values. This is not a detailed building table. If there are multiple owners associated with a property, then the Assess table will have multiple records for that property/parcel (such as for condo parcels).Each building table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Bldg table. The Bldg (building) table contains info about each building on the parcel (such as number of bedrooms, number of bathrooms, the living area square footage, etc.). NOTES of CAUTION: The Living Area Square Footage may not represent the exact same thing in each town. As a generalization, Living Area is interior space that is heated. Regarding West Tisbury, their building table only contains info for one building on the parcel. It is uncertain at this time if the info is the most recent, most primary, or some kind of summarization where multiple buildings on a parcel exist.The field of [assess_mYB] is appended to the TaxPar feature class based on an analysis of the info provided in the building table. This field [assess_mYB] is utilized in the Historic Structures App found in ArcGIS OnLine.

MassGIS Level 3 Parcel Data: Data Fiscal Year: Aquinnah 2019, Chilmark 2020, Edgartown 2021, Gosnold 2015, Oak Bluffs 2021, Tisbury 2021, West Tisbury 2021.Building Info Table: Acquired by MVC from Town Assessors in FY20.Downloaded from MassGIS,, this polygon file represents the parcel bounds for the 7 towns in Dukes County MA (Aquinnah, Chilmark, Edgartown, Godnold, Oak Bluffs, Tisbury, West Tisbury). Each town has their own parcel data consultant and then the data are forwarded to MassGIS for final processing. All data comply with the MassGIS Level 3 Parcel Data Standard. This file geodatabase only includes the TaxPar feature class and Assess table for each town. All TaxPar feature classes were appended into one feature class (Parcels_duk) by the MVC.Each assess table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Assess table. The Assess Table contains info about ownership and assessed values. This is not a detailed building table. If there are multiple owners associated with a property, then the Assess table will have multiple records for that property/parcel (such as for condo parcels).Each building table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Bldg table. The Bldg (building) table contains info about each building on the parcel (such as number of bedrooms, number of bathrooms, the living area square footage, etc.). NOTES of CAUTION: The Living Area Square Footage may not represent the exact same thing in each town. As a generalization, Living Area is interior space that is heated. Regarding West Tisbury, their building table only contains info for one building on the parcel. It is uncertain at this time if the info is the most recent, most primary, or some kind of summarization where multiple buildings on a parcel exist.The field of [assess_mYB] represents the Minimum/Earliest Year Built for any building on the parcel and is appended to the TaxPar feature class based on an analysis of the info provided in the building table. This field [assess_mYB] is utilized in the Historic Structures App found in ArcGIS OnLine.

MassGIS Level 3 Parcel Data: Data Fiscal Year: Aquinnah 2019, Chilmark 2021, Edgartown 2021, Gosnold 2015, Oak Bluffs 2021, Tisbury 2021, West Tisbury 2021.Building Info Table: Acquired by MVC from Town Assessors in FY20.Downloaded from MassGIS,, this polygon file represents the parcel bounds for the 7 towns in Dukes County MA (Aquinnah, Chilmark, Edgartown, Godnold, Oak Bluffs, Tisbury, West Tisbury). Each town has their own parcel data consultant and then the data are forwarded to MassGIS for final processing. All data comply with the MassGIS Level 3 Parcel Data Standard. This file geodatabase only includes the TaxPar feature class and Assess table for each town. All TaxPar feature classes were appended into one feature class (Parcels_duk) by the MVC.Each assess table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Assess table. The Assess Table contains info about ownership and assessed values. This is not a detailed building table. If there are multiple owners associated with a property, then the Assess table will have multiple records for that property/parcel (such as for condo parcels).Each building table is utilized in that town's respective relationship join (1 to Many) for linking the parcel polygon to the related record(s) in the Bldg table. The Bldg (building) table contains info about each building on the parcel (such as number of bedrooms, number of bathrooms, the living area square footage, etc.). NOTES of CAUTION: The Living Area Square Footage may not represent the exact same thing in each town. As a generalization, Living Area is interior space that is heated. Regarding West Tisbury, their building table only contains info for one building on the parcel. It is uncertain at this time if the info is the most recent, most primary, or some kind of summarization where multiple buildings on a parcel exist.The field of [assess_mYB] represents the Minimum/Earliest Year Built for any building on the parcel and is appended to the TaxPar feature class based on an analysis of the info provided in the building table. This field [assess_mYB] is utilized in the Historic Structures App found in ArcGIS OnLine.

Soil map units are the basic geographic unit of the Soil Survey Geographic Database (SSURGO). The SSURGO dataset is a compilation of soils information collected over the last century by the Natural Resources Conservation Service (NRCS). Map units delineate the extent of different soils. Data for each map unit contains descriptions of the soil’s components, productivity, unique properties, and suitability interpretations. Each soil type has a unique combination of physical, chemical, nutrient and moisture properties. Soil type has ramifications for engineering and construction activities, natural hazards such as landslides, agricultural productivity, the distribution of native plant and animal life and hydrologic and other physical processes. Soil types in the context of climate and terrain can be used as a general indicator of engineering constraints, agriculture suitability, biological productivity and the natural distribution of plants and animals. Data from thegSSURGO databasewas used to create this layer. To download ready-to-use project packages of useful soil data derived from the SSURGO dataset, please visit the USA SSURGO Downloader app. Dataset Summary Phenomenon Mapped:Soils of the United States and associated territoriesGeographic Extent:The 50 United States, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American SamoaCoordinate System:Web Mercator Auxiliary SphereVisible Scale:1:144,000 to 1:1,000Source:USDA Natural Resources Conservation Service Update Frequency:AnnualPublication Date:December 2024 What can you do with this layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS Online Add this layer to a map in the map viewer. The layer is limited to scales of approximately 1:144,000 or larger but avector tile layercreated from the same data can be used at smaller scales to produce awebmapthat displays across the full scale range. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter forFarmland Class= "All areas are prime farmland" to create a map of only prime farmland.Add labels and set their propertiesCustomize the pop-upArcGIS Pro Add this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of theLiving Atlas of the Worldthat provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics. Data DictionaryAttributesKey fields from nine commonly used SSURGO tables were compiled to create the 173 attribute fields in this layer. Some fields were joined directly to the SSURGO Map Unit polygon feature class while others required summarization and other processing to create a 1:1 relationship between the attributes and polygons prior to joining the tables. Attributes of this layer are listed below in their order of occurrence in the attribute table and are organized by the SSURGO table they originated from and the processing methods used on them. Map Unit Polygon Feature Class Attribute TableThe fields in this table are from the attribute table of the Map Unit polygon feature class which provides the geographic extent of the map units. Area SymbolSpatial VersionMap Unit Symbol Map Unit TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the table using the Map Unit Key field. Map Unit NameMap Unit KindFarmland ClassInterpretive FocusIntensity of MappingIowa Corn Suitability Rating Legend TableThis table has 1:1 relationship with the Map Unit table and was joined using the Legend Key field. Project Scale Survey Area Catalog TableThe fields in this table have a 1:1 relationship with the polygons and were joined to the Map Unit table using the Survey Area Catalog Key and Legend Key fields. Survey Area VersionTabular Version Map Unit Aggregated Attribute TableThe fields in this table have a 1:1 relationship with the map unit polygons and were joined to the Map Unit attribute table using the Map Unit Key field. Slope Gradient - Dominant ComponentSlope Gradient - Weighted AverageBedrock Depth - MinimumWater Table Depth - Annual MinimumWater Table Depth - April to June MinimumFlooding Frequency - Dominant ConditionFlooding Frequency - MaximumPonding Frequency - PresenceAvailable Water Storage 0-25 cm - Weighted AverageAvailable Water Storage 0-50 cm - Weighted AverageAvailable Water Storage 0-100 cm - Weighted AverageAvailable Water Storage 0-150 cm - Weighted AverageDrainage Class - Dominant ConditionDrainage Class - WettestHydrologic Group - Dominant ConditionIrrigated Capability Class - Dominant ConditionIrrigated Capability Class - Proportion of Mapunit with Dominant ConditionNon-Irrigated Capability Class - Dominant ConditionNon-Irrigated Capability Class - Proportion of Mapunit with Dominant ConditionRating for Buildings without Basements - Dominant ConditionRating for Buildings with Basements - Dominant ConditionRating for Buildings with Basements - Least LimitingRating for Buildings with Basements - Most LimitingRating for Septic Tank Absorption Fields - Dominant ConditionRating for Septic Tank Absorption Fields - Least LimitingRating for Septic Tank Absorption Fields - Most LimitingRating for Sewage Lagoons - Dominant ConditionRating for Sewage Lagoons - Dominant ComponentRating for Roads and Streets - Dominant ConditionRating for Sand Source - Dominant ConditionRating for Sand Source - Most ProbableRating for Paths and Trails - Dominant ConditionRating for Paths and Trails - Weighted AverageErosion Hazard of Forest Roads and Trails - Dominant ComponentHydric Classification - Presence Rating for Manure and Food Processing Waste - Weighted Average Component Table – Dominant ComponentMap units have one or more components. To create a 1:1 join component data must be summarized by map unit. For these fields a custom script was used to select the component with the highest value for the Component Percentage Representative Value field (comppct_r). Ties were broken with the Slope Representative Value field (slope_r). Components with lower average slope were selected as dominant. If both soil order and slope were tied, the first value in the table was selected. Component Percentage - Low ValueComponent Percentage - Representative ValueComponent Percentage - High ValueComponent NameComponent KindOther Criteria Used to Identify ComponentsCriteria Used to Identify Components at the Local LevelRunoff ClassSoil loss tolerance factorWind Erodibility IndexWind Erodibility GroupErosion ClassEarth Cover 1Earth Cover 2Hydric ConditionHydric RatingAspect Range - Counter Clockwise LimitAspect - Representative ValueAspect Range - Clockwise LimitGeomorphic DescriptionNon-Irrigated Capability SubclassNon-Irrigated Unit Capability ClassIrrigated Capability SubclassIrrigated Unit Capability ClassConservation Tree Shrub GroupGrain Wildlife HabitatGrass Wildlife HabitatHerbaceous Wildlife HabitatShrub Wildlife HabitatConifer Wildlife HabitatHardwood Wildlife HabitatWetland Wildlife HabitatShallow Water Wildlife HabitatRangeland Wildlife HabitatOpenland Wildlife HabitatWoodland Wildlife HabitatWetland Wildlife HabitatSoil Slip PotentialSusceptibility to Frost HeavingConcrete CorrosionSteel CorrosionTaxonomic ClassTaxonomic OrderTaxonomic SuborderGreat GroupSubgroupParticle SizeParticle Size ModCation Exchange Activity ClassCarbonate ReactionTemperature ClassMoist SubclassSoil Temperature RegimeEdition of Keys to Soil Taxonomy Used to Classify SoilCalifornia Storie IndexComponent Key Component Table – Weighted AverageMap units may have one or more soil components. To create a 1:1 join, data from the Component table must be summarized by map unit. For these fields a custom script was used to calculate an average value for each map unit weighted by the Component Percentage Representative Value field (comppct_r). Slope Gradient - Low ValueSlope Gradient - Representative ValueSlope Gradient - High ValueSlope Length USLE - Low ValueSlope Length USLE - Representative ValueSlope Length USLE - High ValueElevation - Low ValueElevation - Representative ValueElevation - High ValueAlbedo - Low ValueAlbedo - Representative ValueAlbedo - High ValueMean Annual Air Temperature - Low ValueMean Annual Air Temperature - Representative ValueMean Annual Air Temperature - High ValueMean Annual Precipitation - Low ValueMean Annual Precipitation - Representative ValueMean Annual Precipitation - High ValueRelative Effective Annual Precipitation - Low ValueRelative Effective Annual Precipitation - Representative ValueRelative Effective Annual Precipitation - High ValueDays between Last and First Frost - Low ValueDays between Last and First Frost - Representative ValueDays between Last and First Frost - High ValueRange Forage Annual Potential Production - Low ValueRange Forage Annual Potential Production - Representative ValueRange Forage Annual Potential Production - High ValueInitial Subsidence - Low ValueInitial Subsidence - Representative ValueInitial Subsidence -

Data in this Address_Points layer was loaded from the interim Building_Points_Joined layer, the result of a spatial join performed between Building_Points (centroids) and Parcels.The Building_Points layer was created on 11/ 08/2013 using the Feature to Point geoprocessing tool; input feature class was Building_Footprints_2010.Process outline:Create a copy of Building_Footprints_2010 in a local, file geodatabasePerform Feature to Point on copy of Building_Footprints_2010; result - Building_PointsPerform spatial join of Parcels to Building_Points; give each point the attribute values of the parcel within which it fallsAdd fields to Building_Points_Joined (FULLNAME, ADDRNUMSUF, ADDRCLASS) and calculate based on values in other attribute fieldsFULLNAME values are the result of a function which concacatenated, then trimmed, using STREET_DIR, STREET_NAM, STREET_TYP from the Parcels table.ADDRNUMSUF values are the result of a parsing operation in which '1/2' addresses were split from applicable HOUSE values. ADDRCLASS values resulted from a calculation based on the Parcels' BLDG_TYPE field.Data loaded to SiteAddressPoint feature class in a local gdb, sourced by Building_Points_Joined.SiteAddressPoint feature class copied to vector.GIS sdeSITEADDID calculated by GENERATE_ID value method using the DynamicValue table.On_Create rule established for SITEADDID when new features are created.Municipality calculated by INTERSECTING_FEATURE value method using the Dynamic Value table.CAPTUREMETH populated with value 'Other' to match the PointCollectionMethoddomain for that field.ZIP will require calculation when a reliable ZIP Codes layer has been secured. Questions? Contact Us

The VEGETATION_WIDTH_R table is the Statistical Summary table for the Vegetation Width Metric at the Reach level. The ISC2010_VEGETATION_WIDTH_R table is designed to JOIN to the …Show full descriptionThe VEGETATION_WIDTH_R table is the Statistical Summary table for the Vegetation Width Metric at the Reach level. The ISC2010_VEGETATION_WIDTH_R table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_R feature class. River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography. A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources. The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics. Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

The ISC2010_LARGE_TREES_R table is the Statistical Summary table for the Large Trees Metric at the Reach level.

The ISC2010_LARGE_TREES_R table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_R feature class.

River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography.

A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources.

The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics.

Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

The ISC2010_STRUCTURE1_S table is the Statistical Summary table for the Structure1 Metric at the 100m Section level. Structure 1 represents Vegetation Cover for two grouped height categories: Shrubs which are defined as vegetation in the height range 1.5m to 5m and Trees which are defined as vegetation with height greater than 5m.

The ISC2010_STRUCTURE1_S table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_S feature class.

River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography.

A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources.

The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics.

Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

The ISC2010_BARE_GROUND_S table is the Statistical Summary table for the Bare Ground Metric at the 100m Section level.

The ISC2010_BARE_GROUND_S table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_S feature class.

River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography.

A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources.

The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics.

Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

The ISC2010_VEGETATION_WIDTH_S table is the Statistical Summary table for the Vegetation Width Metric at the 100m Section level.

The ISC2010_VEGETATION_WIDTH_S table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_S feature class.

River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography.

A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources.

The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics.

Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

The ISC2010_BANK_CONDITION_R table is the Statistical Summary table for the Bank Condition Metric at the Reach level. The Bank Condition Metric is an assessment of the proportion of the bank face that is eroding above expected rates.

The ISC2010_BANK_CONDITION_R table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_R feature class.

River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography.

A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources.

The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics.

Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

The Aquinnah MA parcel bounds and related Assess table were compiled by Cartographic Associates in FY19 and forwarded to MassGIS for final processing into the Commonwealth's Level 3 Parcel Data Standard. The related table of building information was provided to the Martha's Vineyard Commission from the Town's assessing department in the year 2020. All related tables join to the feature class based on [Loc_ID].

The ISC2010_FRAGMENTATION_S table is the Statistical Summary table for the Fragmentation Metric at the 100m Section level.

The ISC2010_FRAGMENTATION_S table is designed to JOIN to the ISC2010_RIVER_CENTRELINES_S feature class.

River condition in Victoria is assessed every 5 years using the Index of Stream Condition (ISC). The Department of Environment and Primary Industries (DEPI) developed a methodology to assess the Physical Form and Riparian Vegetation components of the ISC using remote sensing data, specifically LIDAR and aerial photography.

A State Wide mapping project was undertaken in 2010-13 to accurately map the Physical Form and Riparian Vegetation metrics of the ISC . Other ISC metrics were not assessed in the project and were derived from other sources.

The Physical Form and Riparian Vegetation Metric products are a combination of mapped Vector and Raster data as well as Tabular Summary Statistics about the mapped features. In the context of the project, the term Metrics is used to refer to both the mapped features and the summary statistics.

Remote sensing data used includes 15cm true colour and infra-red aerial photography and four return multi-pulse LiDAR data. This source data was used to derive a variety of Raster data sets including Digital Terrain Models, Slope, Vegetation Height and Vegetation Cover. The Digital Terrain and Slope rasters were used to map Physical Form metrics including Stream Bed, Top of Bank and River Centre Lines while the Vegetation Height and Cover rasters were used to map the Riparian Vegetation metrics. The Project Report "Aerial Remote Sensing for Physical Channel Form and Riparian Vegetation Mapping" describes the remote sensing and mapping approach used to create this data set.

Feature layer generated from running the Join Features solution. Join of oak plantings and oak monitoring table joined on tree_id one to many. This feature class should retain its relationship as more monitoring surveys are conducted. First joined 11/29/21

This table provides additional soil information for Land Type Associations (LTAs), one of the ecological classification units of the National Hierarchical Framework of Ecological Units (NHFEU). The Land Type Associations polygon feature class can be joined to this table using the LTA_CODE field. Note that the LTA feature class contains 3 more records than the table, so the join results in 3 records that lack matching soil information.

The Aquinnah MA parcel bounds and related Assess table were compiled by Cartographic Associates in FY19 and forwarded to MassGIS for final processing into the Commonwealth's Level 3 Parcel Data Standard. The related table of building information was provided to the Martha's Vineyard Commission from the Town's assessing department in the year 2020. All related tables join to the feature class based on [Loc_ID].

Generalized attribute values -- From the parcel data (Aquinnah FY22, Chilmark FY23, Edgartown FY23, Gosnold FY21, Oak Bluffs FY22, Tisbury FY22, West Tisbury FY23) the Assess Table was summarized based on unique Loc_ID for the 'first' owner zip code, the 'first' use code, the minimum year built, and the maximum year built. The summarized table for each town was joined to the building centroid points based on Loc_ID. For the field [YrRnd] a value of "S" (seasonal) was assigned to those buildings where the first owner zip code was NOT an MV or Gosnold zip code; all other building centroid points received a value of "YR" for year-round. This is a gross assumption.For the field [Res] a value of "R" (residential) was assigned to those buildings where the first use code began with a value of 1. All other building centroid points received a value of "NR" for non-residential. NOTE: Some 'residential' properties may be vacant but developable or undevelopable per the assessor.The field of [MinYrBlt] is based on the minimum year built for all records associated with that parcel in the Assess table in the parcel file geodatabase. This minimum year built value from the Assess table was copied into this Build Structure Points feature class based on the join field of [Loc_ID]. If there are multiple structures on a parcel, they all received the same Minimum Year Built.A similar process, as [MaxYrBlt], was followed to populate [MaxYrBlt].The Min & Max year built are provided for a quick & dirty/general gist/approximation as to when that structure was developed. You are encouraged to do more research if you are doing site specific analysis regarding development. A NOTE about the Assess Table that's in the Level 3 Parcel Geodatabases: The assess table will have multiple entries for each parcel only if there are multiple owners (such as a parcel containing condos). The assess table does NOT have multiple records if the parcel contains multiple buildings. The Year Built included in the Assess Table might be for the first structure developed on the property or maybe it's for the primary/largest structure on the parcel ...basically, it's anyone's best guess. Aside from reviewing the detailed property cards for every property, it's impossible to know which specific structure on the property the Year Built corresponds to. Regarding Use Code, it is possible that the use will vary based on the owner (doesn't happen often - but it happens). Simply extracting the 'first' use code where there are multiple records/owners for a parcel, this is just a quick & easy way to assign a plausible use to each structure on the parcel.A NOTE about the Structures: -- These could be a main house, a guest house, or a barn or shed or garage, etc. Any and All structures are included in this dataset.This dataset consists of 2-dimensional roof outlines ("roofprints") for all buildings larger than 150 square feet, as initially interpreted by a contractor (Rolta) for the whole area of the Commonwealth using DigitalGlobe ortho images obtained in 2011 and 2012, supplemented with LiDAR (Light Detection And Ranging) data collected from 2002 to 2011 for the eastern half of the state.The roofprints as delivered by Rolta were enhanced by MassGIS using Normalized Digital Surface Models (NDSMs) derived from the same LiDAR data. Other layers were used, including the Standardized Parcels, to aid in review, especially where LiDAR data were not available.In 2019, MassGIS refreshed the data to a baseline of 2016 and continues to update features using newer aerial imagery that allows MassGIS staff to remove, modify and add structures to keep up with more current ground conditions. Structures from the original compilation that are removed are stored in an "archive" feature class for edit tracking and historical purposes. Also in 2019, MassGIS replaced the polygons in Boston with data from the city. In March 2021, the layer was updated with 2017 and 2018 structure review edits along with the first data edits compiled atop spring 2019 imagery. In July 2021, MassGIS completed the statewide update based on 2019 imagery. In September 2022, MassGIS completed the statewide update based on 2021 imagery.Last updated on 9/19/2022.In ArcSDE the layer is named STRUCTURES_POLY.

This dataset is intended for read-only use. This table represents a surface ownership feature class to a Fund business table join with a foreign key in the table that matches the unique ID in the feature class. The surface ownership feature class is prefixed by S_USA.BdyOwn_LSRS, and the Fund table links the list of codes associated with the authorized funding mechanism to the feature. The purpose of these data is to provide display, identification, and analysis tools for determining current boundary information for Forest Service managers, GIS specialists, and others.