Combined New England City and Town Areas; 2020 Census - January 1, 2020 vintage

Background and Data Limitations The Massachusetts 1830 map series represents a unique data source that depicts land cover and cultural features during the historical period of widespread land clearing for agricultural. To our knowledge, Massachusetts is the only state in the US where detailed land cover information was comprehensively mapped at such an early date. As a result, these maps provide unusual insight into land cover and cultural patterns in 19th century New England. However, as with any historical data, the limitations and appropriate uses of these data must be recognized: (1) These maps were originally developed by many different surveyors across the state, with varying levels of effort and accuracy. (2) It is apparent that original mapping did not follow consistent surveying or drafting protocols; for instance, no consistent minimum mapping unit was identified or used by different surveyors; as a result, whereas some maps depict only large forest blocks, others also depict small wooded areas, suggesting that numerous smaller woodlands may have gone unmapped in many towns. Surveyors also were apparently not consistent in what they mapped as ‘woodlands’: comparison with independently collected tax valuation data from the same time period indicates substantial lack of consistency among towns in the relative amounts of ‘woodlands’, ‘unimproved’ lands, and ‘unimproveable’ lands that were mapped as ‘woodlands’ on the 1830 maps. In some instances, the lack of consistent mapping protocols resulted in substantially different patterns of forest cover being depicted on maps from adjoining towns that may in fact have had relatively similar forest patterns or in woodlands that ‘end’ at a town boundary. (3) The degree to which these maps represent approximations of ‘primary’ woodlands (i.e., areas that were never cleared for agriculture during the historical period, but were generally logged for wood products) varies considerably from town to town, depending on whether agricultural land clearing peaked prior to, during, or substantially after 1830. (4) Despite our efforts to accurately geo-reference and digitize these maps, a variety of additional sources of error were introduced in converting the mapped information to electronic data files (see detailed methods below). Thus, we urge considerable caution in interpreting these maps. Despite these limitations, the 1830 maps present an incredible wealth of information about land cover patterns and cultural features during the early 19th century, a period that continues to exert strong influence on the natural and cultural landscapes of the region. For users without access to GIS software, the data are available for viewing at: http://harvardforest.fas.harvard.edu/research/1830instructions.html

  Acknowledgements
  Financial support for this project was provided by the BioMap Project of the Massachusetts Natural Heritage and Endangered Species Program, the National Science Foundation, and the Andrew Mellon Foundation. This project is a contribution of the Harvard Forest Long Term Ecological Research Program.

Revised Delineations of Metropolitan Statistical AreasPursuant to 44 U.S.C. § 3504(e)(3), 31 U.S.C. § 1104(d), and Executive Order No. 10,253 (June 11, 1951), 0MB delineates Metropolitan Statistical Areas, Metropolitan Divisions, Micropolitan Statistical Areas, Combined Statistical Areas, and New England City and Town Areas for use in Federal statistical activities. 0MB issues periodic updates of the areas between decennial censuses based on Census Bureau data. Metropolitan Statistical Areas have at least one urbanized area of 50,000 or more population, plus adjacent territory that has a high degree of social and economic integration with the core as measured by commuting ties.This layer is used in the map(s): Latest City Boundaries (TIGER)

(:unav)...........................................

March 2024

All data compiled into this dataset is available under public domain. This set is designed to provide some insight into sales trends across the state of Connecticut as well as the individual towns within. It is also specifically structured to highlight changes in trends due to the COVID-19 pandemic.

Variables

list_year: grand list year of the property (grand list years run from Oct. 1 through Sept. 30). town: name of the town that the property was sold in. population: population of the town that the property was sold in. residential_type: single family, two family, three family, four family, or condo. month: the month the sale was recorded. year: the year the sale was recorded. in_pandemic: boolean value indicating whether the selling date was after March 11, 2020. assessed_value: tax assessed value of the property at the time of the sale. sale_amount: final closing sale amount of the property. price_index: the Consumer Price Index (CPI) for that month/year. Used to normalize dollar values. norm_assessed_value: CPI-normalized assessed value (assessed_value / price_index * 100). norm_sale_amount: CPI-normalized sale amount (sale_amount / price_index * 100). norm_sales_ratio: CPI-normalized assessment to sale ratio (norm_assessed_value / norm_sale_amount). latitude: latitude for the property's town. longitude: longitude for the property's town.

Note: the original dataset also contained the street address and exact sale date for each record. Those variables were removed as they were not relevant to the analysis being conducted and to afford the individuals associated with each sale a stonger degree of personal privacy. Records from October 2000 to October 2010 from the original dataset were omitted due to timeliness issues. Records of non-residential types were omitted as they lacked enough historic records to be of consequence to the analysis.

Data sources

Real estate records: https://data.ct.gov/Housing-and-Development/Real-Estate-Sales-2001-2020-GL/5mzw-sjtu Township shapes: https://data.ct.gov/Government/Town-Boundary-Index-Map/evyv-fqzg Consumer price index: https://www.bls.gov/regions/new-england/data/consumerpriceindex_us_table.htm Town populations: https://www.connecticut-demographics.com/cities_by_population

Living England is a multi-year project which delivers a broad habitat map for the whole of England, created using satellite imagery, field data records and other geospatial data in a machine learning framework. The Living England habitat map shows the extent and distribution of broad habitats across England aligned to the UKBAP classification, providing a valuable insight into our natural capital assets and helping to inform land management decisions. Living England is a project within Natural England, funded by and supports the Defra Natural Capital and Ecosystem Assessment (NCEA) Programme and Environmental Land Management (ELM) Schemes to provide an openly available national map of broad habitats across England.This dataset includes very complex geometry with a large number of features so it has a default viewing distance set to 1:80,000 (City in the map viewer).Process Description:A number of data layers are used to develop a ground dataset of habitat reference data, which are then used to inform a machine-learning model and spatial analyses to generate a map of the likely locations and distributions of habitats across England. The main source data layers underpinning the spatial framework and models are Sentinel-2 and Sentinel-1 satellite data from the ESA Copernicus programme, Lidar from the EA's national Lidar Programme and collected data through the project's national survey programme. Additional datasets informing the approach as detailed below and outlined in the accompanying technical user guide.Datasets used:OS MasterMap® Topography Layer; Geology aka BGS Bedrock Mapping 1:50k; Long Term Monitoring Network; Uplands Inventory; Coastal Dune Geomatics Mapping Ground Truthing; Crop Map of England (RPA) CROME; Lowland Heathland Survey; National Grassland Survey; National Plant Monitoring Scheme; NE field Unit Surveys; Northumberland Border Mires Survey; Sentinel-2 multispectral imagery; Sentinel-1 backscatter imagery; Sentinel-1 single look complex (SLC) imagery; National forest inventory (NFI); Cranfield NATMAP; Agri-Environment HLS Monitoring; Living England desktop validation; Priority Habitat Inventory; Space2 Eye Lens: Ainsdale NNR, State of the Bog Bowland Survey, State of the Bog Dark Peak Condition Survey, State of the Bog Manchester Metropolitan University (MMU) Mountain Hare Habitat Survey Dark Peak, State of the Bog; Moors for the Future Dark Peak Survey; West Pennines Designation NVC Survey; Wetland Annex 1 inventory; Soils-BGS Soil Parent Material; Met Office HadUK gridded climate product; Saltmarsh Extent and Zonation; EA LiDAR DSM & DTM; New Forest Mires Wetland Survey; New Forest Mires Wetland Survey; West Cumbria Mires Survey; England Peat Map Vegetation Surveys; NE protected sites monitoring; ERA5; OS Open Built-up Areas; OS Boundaries dataset; EA IHM (Integrated height model) DTM; OS VectorMap District; EA Coastal Flood Boundary: Extreme Sea Levels; AIMS Spatial Sea Defences; LIDAR Sand Dunes 2022; EA Coastal saltmarsh species surveys; Aerial Photography GB (APGB); NASA SRT (Shuttle Radar Topography Mission) M30; Provisional Agricultural Land Classification; Renewable Energy Planning Database (REPD); Open Street Map 2024.Attribute descriptions: Column Heading Full Name Format Description

SegID SegID Character (100) Unique Living England segment identifier. Format is LEZZZZ_BGZXX_YYYYYYY where Z = release year (2223 for this version), X = BGZ and Y = Unique 7-digit number

Prmry_H Primary_Habitat Date Primary Living England Habitat

Relblty Reliability
Character (12) Reliability Metric Score

Mdl_Hbs Model_Habs Interger List of likely habitats output by the Random Forest model.

Mdl_Prb Model_Probs Double (6,2) List of probabilities for habitats listed in ‘Model_Habs’, calculated by the Random Forest model.

Mixd_Sg Mixed_Segment Character (50) Indication of the likelihood a segment contains a mixture of dominant habitats. Either Unlikely or Probable.

Source Source

Description of how the habitat classification was derived. Options are: Random Forest; Vector OSMM Urban; Vector Classified OS Water; Vector EA saltmarsh; LE saltmarsh & QA; Vector RPA Crome, ALC grades 1-4; Vector LE Bare Ground Analysis; LE QA Adjusted

SorcRsn Source_Reason

Reasoning for habitat class adjustment if ‘Source’ equals ‘LE QA Adjusted’

Shap_Ar Shape_Area

Segment area (m2) Full metadata can be viewed on data.gov.uk.