Predictors ========== This is the full list of :ref:`parcel `-level variables used as :ref:`predictors ` and :ref:`sampling ` filters for our :ref:`models ` of fair market value (FMV). These variables are derived from geospatial :ref:`parcel boundaries ` and publicly available geospatal datasets. In addition to the variables listed here, we obtain some predictors from :any:`parcel boundaries ` (geolocation and size: :any:`lat_id`, :any:`long_id`, :any:`ha`) or :any:`transactions ` (:any:`date` of sale). ******* Terrain ******* .. attribute:: elev Average elevation of parcel (meters). :Source: USGS National Elevation Dataset (NED) 1/3 Arc-Second :Geoprocessing: Mean of pixel values within parcel (zonal statistics). Elevation raster exported at 0.00449 degrees resolution from Google Earth Engine (EPSG:4326). .. attribute:: slope Average slope of parcel (degrees). :Source: see :any:`elev` :Geoprocessing: Mean of pixel values within parcel (zonal statistics). Slope computed at 30m resolution in Google Earth Engine (EPSG:5070). ******* Climate ******* .. attribute:: clim_ppt_summer Average precipitation in summer (Jun-Aug) (mm) :Source: PRISM monthly climate normals :Access: https://prism.oregonstate.edu/ :Accessed: Aug 10, 2023 :Geoprocessing: Zonal statistics (mean) .. attribute:: clim_ppt_winter Average precipitation in winter (Dec-Feb) (mm) :Source: see :any:`clim_ppt_summer` .. attribute:: clim_tmean_summer Average temperature in summer (Jun-Aug) (C) :Source: see :any:`clim_ppt_summer` .. attribute:: clim_tmean_winter Average temperature in winter (Dec-Feb) (C) :Source: see :any:`clim_ppt_summer` ********* Hydrology ********* .. attribute:: cst_50 Percentage (0-100) of coastal waters within a 50m radius. Used as proxy for beachfront properties and boating access. :Source: ESRI North America Water Polygons :Accessed: Jun 18, 2019 .. attribute:: cst_2500 Percentage (0-100) of coastal waters within a 2500m radius. Used as proxy for ocean proximity for near-ocean properties. Positively associated with distance to coast as well as with the added value of properties surrounded by coastal waters on several sides, such as islands, peninsulas, etc. :Source: see :any:`cst_50` .. attribute:: lake_dist Distance (m) to nearest large lake (> 4ha). :Source: National Hydrographic Database (NHDPlus High Resolution) :Source: National Hydrographic Database (NHDPlus High Resolution) :Access: https://www.usgs.gov/national-hydrography/nhdplus-high-resolution :Accessed: Jun 18, 2019 .. attribute:: lake_frontage Approximate total lake frontage of the parcel (in meters). :Source: see :any:`lake_dist` :Geoprocessing: Area of intersection of parcel polygon with 50-meter-buffers around NHD lake waterbodies, divided by the buffer width (50m). .. attribute:: river_frontage Approximate total river frontage of the parcel (in meters). Only waterbody polygons from the NHD are included (no lines). :Source: see :any:`lake_dist` :Geoprocessing: see :any:`lake_frontage`, but using *river* waterbodies. .. attribute:: water_exposure :Computation: :code:`(`:any:`river_frontage`:code:`+`:any:`lake_frontage` :code:`) /` :any:`ha` .. attribute:: p_wet Percentage (0-100) of parcel area covered by wetland polygons. :Source: National Wetlands Inventory (NWI), U.S. Fish & Wildlife Service :Access: https://www.fws.gov/program/national-wetlands-inventory/wetlands-data :Accessed: Jun 18, 2019 .. attribute:: fld_fr_fath_p100 Flood risk: average meters of inundation depth within the 1% annual exceedance probability floodplain (pluvial floods). :Source: Fathom-US Flood Hazard data (`Wing et al 2018 `_) :Access: https://www.fathom.global/product/flood-hazard-data-maps/fathom-us/ (licensed) :Accessed: Mar 26, 2020 :Geoprocessing: Zonal statistics (mean) .. attribute:: fld_fr_fath_f100 Flood risk: average meters of inundation depth within the 1% annual exceedance probability floodplain (fluvial floods). :Source: see :any:`fld_fr_fath_p100` ***** Soils ***** .. aluna:aluna:: f_soil_ Fraction (0-1) of parcel area covered by `soil_class`. Eleven soil class categories are distinguished (e.g. "prime" farmland, "state priority" soil, etc.). See `Gold et al (2023) `_ for a description. :Source: SSURGO :Access: https://websoilsurvey.nrcs.usda.gov/app/WebSoilSurvey.aspx :Accessed: Aug 11, 2023 :Geoprocessing: Polygon intersections ****************** Land cover and use ****************** .. attribute:: p_barren Percentage (0-100) of pixels in parcel that were "barren" in 2011. :Source: National Land Cover Database, Year-2011 Land Cover (Edition 2014-10-10) :Access: ``_ :Accessed: June 18, 2019 .. attribute:: p_crops Percentage (0-100) of pixels in parcel that were "cropland" in 2011. :Source: see :any:`p_barren` .. attribute:: p_forest Percentage (0-100) of pixels in parcel that were "forest" (deciduous, evergreen, or mixed) in 2011. :Source: see :any:`p_barren` .. attribute:: p_grassland Percentage (0-100) of pixels in parcel that were "grassland" in 2011. :Source: see :any:`p_barren` .. attribute:: p_pasture Percentage (0-100) of pixels in parcel that were "pasture" in 2011. :Source: see :any:`p_barren` .. attribute:: p_shrub Percentage (0-100) of pixels in parcel that were "shrubland" in 2011. :Source: see :any:`p_barren` .. attribute:: irr_2000_2020 Percentage (0-100) of pixels in parcel that were "irrigated" between 2000 and 2020 (averaged across all years) :Source: IrrMapper Irrigated Lands, Version 1.2 :Access: https://developers.google.com/earth-engine/datasets/catalog/UMT_Climate_IrrMapper_RF_v1_2 :Accessed: April 11, 2022 ********* Buildings ********* All of the following indicators are derived from Microsoft’s open-source `USBuildingFootprints `_ dataset, which contains polygons of 125.2 million buildings inferred from high-resolution satellite imagery with neural networks. :Access: ``_ :Accessed: Aug 21, 2023 Microsoft's building footprints are our preferred open-source metric for the **presence of buildings** in CONUS, as they are more consistently available across CONUS than other indicators (e.g., tax assessor data). However, building footprints introduce new sources of error. For instance, footprints under trees are often missed. Alternative measures of building presence are available in tax assessor and parcel boundary datasets. However, their availability and quality varies across states and counties. For a comparison of ZTRAX-based and remote-sensing based building variables see `Nolte et al. (2023) Land Economics `_ (Appendix Figures A14-16) .. attribute:: n_bld_fp Count of building footprints on the parcel. :Geoprocessing: Polygon intersections. .. attribute:: m2_bld_fp Area of building footprints on the parcel (square meters) :Geoprocessing: Polygon intersections. .. attribute:: p_bld_fp Percentage (0-100) of the area of the parcel that is covered by footprints. :Geoprocessing: Polygon intersections. .. aluna:aluna:: p_bld_fp_* Percentage of area within the given radius (``*``, integer, in meters) that is covered by building footprints. An indicator of nearby building density. :Geoprocessing: rasterization of building footprints, pixel-based computation of average building footprint presence within circular neighborhood (2D convolution with moving-window kernel), averaged across all pixels within each parcel (zonal statistics). .. attribute:: p_bld_fp_500 % building footprints within 500m See :aluna:ref:`p_bld_fp_*` .. attribute:: p_bld_fp_5000 % building footprints within 5000m See :aluna:ref:`p_bld_fp_*` ************ Demographics ************ .. attribute:: hh_inc_med_bg_2012_2016 Median household income at the census block-group level (2012-2016) :Source: American Community Survey, via the National Historical Geographic Information System (NHGIS) :Access: ``_ :Geoprocessing: spatial joins of parcel centroids with reference units. .. attribute:: p_asian_bg_2012_2016 % population in block group identifying as "Asian" on American Community Survey. :Source: see :aluna:ref:`hh_inc_med_bg_2012_2016` .. attribute:: p_black_bg_2021_2016 % population in block group identifying as "Black or African-American" on American Community Survey. :Source: see :aluna:ref:`hh_inc_med_bg_2012_2016` .. attribute:: p_hispanic_bg_2021_2016 % population in block group identifying as "Hispanic" on American Community Survey. (Note: overlaps with 'race' categories, such as white, black, asian, etc.) :Source: see :aluna:ref:`hh_inc_med_bg_2012_2016` .. attribute:: p_mixed_bg_2021_2016 % population in block group identifying as "Mixed" on American Community Survey. :Source: see :aluna:ref:`hh_inc_med_bg_2012_2016` .. attribute:: p_native_bg_2021_2016 % population in block group identifying as "American Indian or Alaska Native" on American Community Survey. :Source: see :aluna:ref:`hh_inc_med_bg_2012_2016` .. attribute:: p_pacific_bg_2021_2016 % population in block group identifying as "Native Hawaiian or Other Pacific Islander" on American Community Survey. :Source: see :aluna:ref:`hh_inc_med_bg_2012_2016` .. attribute:: p_white_bg_2021_2016 % population in block group identifying as "White" on American Community Survey. :Source: see :aluna:ref:`hh_inc_med_bg_2012_2016` .. attribute:: bld_pop_exp_c4 Population gravity (experimental). A spatial measure of residential population, attributed to building footprints. :Geoprocessing: Zonal statistics Find out more: .. toctree:: :maxdepth: 1 population_gravity/population_gravity ************** Infrastructure ************** .. aluna:aluna:: rd_dst_pvd+ Distance to nearest paved road, including highways (meters). :Source: TIGER/Line shapefiles from the U.S. Census Bureau for the year 2019 :Access: ``_ :Accessed: Sept 10, 2020 Only computed up to 3km. .. attribute:: travel Travel time to major cities (minutes), ca. 2000 :Source: European Commission & World Bank (Nelson 2007) :Access: ``_ This dataset was computed with different specifications than :any:`travel_weiss`. The two are not intercomparable. Differences do not necessarily reflect change over time. .. attribute:: travel_weiss Travel time to major cities (minutes), ca. 2015 :Source: Weiss et al. 2017 *Nature* :Access: ``_ *************** Land protection *************** .. attribute:: p_prot_2010_5000 See :aluna:ref:`p_prot_*_*` .. aluna:aluna:: p_prot_*_* Percentage of area within a given (in meters) that is protected by fee or conservation easement in a given . :Sources: * Protected Area Database of the United States (PAD-US 2.0) * National Conservation Easement Database (NCED) * New England Protected Open Space (NEPOS) database * Colorado Ownership, Management, and Protection (COMaP) database. :Geoprocessing: Rasterization of protection polygons, pixel-based computation of average protection within circular neighborhood (2D convolution with moving-window kernel), averaged across all pixels within each parcel (zonal statistics). .. note:: Data for Colorado is licensed from COMaP and cannot be shared. .. attribute:: p_e Percentage (0-100) of parcel overlapping with a conservation easement. :Sources: see :aluna:ref:`p_prot_*_*` .. attribute:: ct_p Percentage (0-100) of parcel overlapping with a public land acquisition. :Source: Conservation Almanac (Trust for Public Land) :Access: https://conservationalmanac.org/ :Accessed: Sep 15, 2019 ************* Spatial units ************* Spatial reference units, ordered from those with few units (U.S. states) to those with many (census block groups). .. attribute:: division U.S. census division (groups of `state`) .. attribute:: state U.S. state, identified by its two-letter Alpha code (e.g. ``CA`` for California) :Source: Census Bureau, via the National Historical Geographic Information System (NHGIS) :Access: ``_ :Geoprocessing: Spatial intersection with parcel centroids .. attribute:: region_id Region identifier. :any:`Core-based regions` are an experimental geographic identifier developed at the :any:`PLACES` lab. Regions divide the contiguous U.S. into less than 1000 spatial units that are identified by their high-value "core" (city centers, resorts). We prefer modeling at the level of regions rather than counties or states, as the latter vary substantially in size and number across the U.S. geography. :Geoprocessing: Spatial intersection with parcel centroids Learn more: .. toctree:: :maxdepth: 1 regions/regions .. attribute:: fips U.S. county, identified by its five-digit county FIPS code (e.g. ``06037`` for Los Angeles county, California) :Source: NHGIS (see :any:`state`) .. attribute:: zip_id ZIP code, 2016 :Source: NHGIS (see :any:`state`) .. attribute:: tract_id Census tract identifier, 2016 :Source: NHGIS (see :any:`state`) .. attribute:: bg_id Census block group identifier, 2016 Unique within county. :Source: NHGIS (see :any:`state`)