3 datasets found
  1. Z

    Data from: Remapping California's Wildland Urban Interface: A Property-Level...

    • data.niaid.nih.gov
    • zenodo.org
    Updated Jan 21, 2025
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    Berg, Aleksander K (2025). Remapping California's Wildland Urban Interface: A Property-Level Time-Space Framework, 2000-2020 [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_10015378
    Explore at:
    Dataset updated
    Jan 21, 2025
    Dataset provided by
    Kedron, Peter J.
    Connor, Dylan S.
    Frazier, Amy E.
    Berg, Aleksander K
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    California
    Description

    Maps of California's Wildland Urban Interface (WUI) generated using the Time Step Moving Window (TSMW) method outlined in the paper "Remapping California's Wildland Urban Interface: A Property-Level Time-Space Framework, 2000-2020".

    Please cite the original paper:

    Berg, Aleksander K, Dylan S. Connor, Peter Kedron, and Amy E. Frazier. 2024. “Remapping California’s Wildland Urban Interface: A Property-Level Time-Space Framework, 2000–2020.” Applied Geography 167 (June): 103271. https://doi.org/10.1016/j.apgeog.2024.103271.

    WUI maps were generated using Zillow ZTRAX parcel level attributes joined with FEMA USA Structures building footprints and the National Land Cover Database (NLCD).

    All files are geotiff rasters with WUI areas mapped at a ~30m resolution. A raster value of null indicates not WUI, raster value of 1 indicates intermix WUI, and a raster value of 2 indicates interface WUI.

    Three WUI maps were generated using structures built on of before the years indicated below:

    2000 - "CA_WUI_2000.tif"

    2010 - "CA_WUI_2010.tif"

    2020 - "CA_WUI_2020.tif"

    Acknowledgments -

    We thank our reviewers and editors for helping us to improve the manuscript. We gratefully acknowledge access to the Zillow Transaction and Assessment Dataset (ZTRAX) through a data use agreement between the University of Colorado Boulder, Arizona State University, and Zillow Group, Inc. More information on accessing the data can be found at http://www.zillow.com/ztrax. The results and opinions are those of the author(s) and do not reflect the position of Zillow Group. Support by Zillow Group Inc. is acknowledged. We thank Johannes Uhl and Stefan Leyk for their great work in preparing the original dataset. For feedback and comments, we also thank Billie Lee Turner II, Sharmistha Bagchi-Sen, and participants at the 2022 Global Conference on Economic Geography, the 2022 Young Economic Geographers Network meeting, and the 2023 annual meeting of the American Association of Geographers. Funding for our work has been provided by Arizona State University's Institute of Social Science Research (ISSR) Seed Grant Initiative. Additional funding was provided through the Humans, Disasters, and the Built Environment program of the National Science Foundation, Award Number 1924670 to the University of Colorado Boulder, the Institute of Behavioral Science, Earth Lab, the Cooperative Institute for Research in Environmental Sciences, the Grand Challenge Initiative and the Innovative Seed Grant program at the University of Colorado Boulder as well as the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under Award Numbers R21 HD098717 01A1 and P2CHD066613.

  2. T

    Vital Signs: List Rents – by property

    • data.bayareametro.gov
    • open-data-demo.mtc.ca.gov
    application/rdfxml +5
    Updated Dec 8, 2016
    + more versions
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    real Answers (2016). Vital Signs: List Rents – by property [Dataset]. https://data.bayareametro.gov/dataset/Vital-Signs-List-Rents-by-property/wfp9-cb9q
    Explore at:
    tsv, json, application/rdfxml, xml, csv, application/rssxmlAvailable download formats
    Dataset updated
    Dec 8, 2016
    Dataset authored and provided by
    real Answers
    Description

    VITAL SIGNS INDICATOR List Rents (EC9)

    FULL MEASURE NAME List Rents

    LAST UPDATED October 2016

    DESCRIPTION List rent refers to the advertised rents for available rental housing and serves as a measure of housing costs for new households moving into a neighborhood, city, county or region.

    DATA SOURCE real Answers (1994 – 2015) no link

    Zillow Metro Median Listing Price All Homes (2010-2016) http://www.zillow.com/research/data/

    CONTACT INFORMATION vitalsigns.info@mtc.ca.gov

    METHODOLOGY NOTES (across all datasets for this indicator) List rents data reflects median rent prices advertised for available apartments rather than median rent payments; more information is available in the indicator definition above. Regional and local geographies rely on data collected by real Answers, a research organization and database publisher specializing in the multifamily housing market. real Answers focuses on collecting longitudinal data for individual rental properties through quarterly surveys. For the Bay Area, their database is comprised of properties with 40 to 3,000+ housing units. Median list prices most likely have an upward bias due to the exclusion of smaller properties. The bias may be most extreme in geographies where large rental properties represent a small portion of the overall rental market. A map of the individual properties surveyed is included in the Local Focus section.

    Individual properties surveyed provided lower- and upper-bound ranges for the various types of housing available (studio, 1 bedroom, 2 bedroom, etc.). Median lower- and upper-bound prices are determined across all housing types for the regional and county geographies. The median list price represented in Vital Signs is the average of the median lower- and upper-bound prices for the region and counties. Median upper-bound prices are determined across all housing types for the city geographies. The median list price represented in Vital Signs is the median upper-bound price for cities. For simplicity, only the mean list rent is displayed for the individual properties. The metro areas geography rely upon Zillow data, which is the median price for rentals listed through www.zillow.com during the month. Like the real Answers data, Zillow's median list prices most likely have an upward bias since small properties are underrepresented in Zillow's listings. The metro area data for the Bay Area cannot be compared to the regional Bay Area data. Due to afore mentioned data limitations, this data is suitable for analyzing the change in list rents over time but not necessarily comparisons of absolute list rents. Metro area boundaries reflects today’s metro area definitions by county for consistency, rather than historical metro area boundaries.

    Due to the limited number of rental properties surveyed, city-level data is unavailable for Atherton, Belvedere, Brisbane, Calistoga, Clayton, Cloverdale, Cotati, Fairfax, Half Moon Bay, Healdsburg, Hillsborough, Los Altos Hills, Monte Sereno, Moranga, Oakley, Orinda, Portola Valley, Rio Vista, Ross, San Anselmo, San Carlos, Saratoga, Sebastopol, Windsor, Woodside, and Yountville.

    Inflation-adjusted data are presented to illustrate how rents have grown relative to overall price increases; that said, the use of the Consumer Price Index does create some challenges given the fact that housing represents a major chunk of consumer goods bundle used to calculate CPI. This reflects a methodological tradeoff between precision and accuracy and is a common concern when working with any commodity that is a major component of CPI itself. Percent change in inflation-adjusted median is calculated with respect to the median price from the fourth quarter or December of the base year.

  3. ScrapeHero Data Cloud - Free and Easy to use

    • datarade.ai
    .json, .csv
    Updated Apr 11, 2022
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    Scrapehero (2022). ScrapeHero Data Cloud - Free and Easy to use [Dataset]. https://datarade.ai/data-products/scrapehero-data-cloud-free-and-easy-to-use-scrapehero
    Explore at:
    .json, .csvAvailable download formats
    Dataset updated
    Apr 11, 2022
    Dataset provided by
    ScrapeHero
    Authors
    Scrapehero
    Area covered
    Bhutan, Bahamas, Ghana, Dominica, Slovakia, Anguilla, Portugal, Chad, Niue, Bahrain
    Description

    The Easiest Way to Collect Data from the Internet Download anything you see on the internet into spreadsheets within a few clicks using our ready-made web crawlers or a few lines of code using our APIs

    We have made it as simple as possible to collect data from websites

    Easy to Use Crawlers Amazon Product Details and Pricing Scraper Amazon Product Details and Pricing Scraper Get product information, pricing, FBA, best seller rank, and much more from Amazon.

    Google Maps Search Results Google Maps Search Results Get details like place name, phone number, address, website, ratings, and open hours from Google Maps or Google Places search results.

    Twitter Scraper Twitter Scraper Get tweets, Twitter handle, content, number of replies, number of retweets, and more. All you need to provide is a URL to a profile, hashtag, or an advance search URL from Twitter.

    Amazon Product Reviews and Ratings Amazon Product Reviews and Ratings Get customer reviews for any product on Amazon and get details like product name, brand, reviews and ratings, and more from Amazon.

    Google Reviews Scraper Google Reviews Scraper Scrape Google reviews and get details like business or location name, address, review, ratings, and more for business and places.

    Walmart Product Details & Pricing Walmart Product Details & Pricing Get the product name, pricing, number of ratings, reviews, product images, URL other product-related data from Walmart.

    Amazon Search Results Scraper Amazon Search Results Scraper Get product search rank, pricing, availability, best seller rank, and much more from Amazon.

    Amazon Best Sellers Amazon Best Sellers Get the bestseller rank, product name, pricing, number of ratings, rating, product images, and more from any Amazon Bestseller List.

    Google Search Scraper Google Search Scraper Scrape Google search results and get details like search rank, paid and organic results, knowledge graph, related search results, and more.

    Walmart Product Reviews & Ratings Walmart Product Reviews & Ratings Get customer reviews for any product on Walmart.com and get details like product name, brand, reviews, and ratings.

    Scrape Emails and Contact Details Scrape Emails and Contact Details Get emails, addresses, contact numbers, social media links from any website.

    Walmart Search Results Scraper Walmart Search Results Scraper Get Product details such as pricing, availability, reviews, ratings, and more from Walmart search results and categories.

    Glassdoor Job Listings Glassdoor Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Glassdoor.

    Indeed Job Listings Indeed Job Listings Scrape job details such as job title, salary, job description, location, company name, number of reviews, and ratings from Indeed.

    LinkedIn Jobs Scraper Premium LinkedIn Jobs Scraper Scrape job listings on LinkedIn and extract job details such as job title, job description, location, company name, number of reviews, and more.

    Redfin Scraper Premium Redfin Scraper Scrape real estate listings from Redfin. Extract property details such as address, price, mortgage, redfin estimate, broker name and more.

    Yelp Business Details Scraper Yelp Business Details Scraper Scrape business details from Yelp such as phone number, address, website, and more from Yelp search and business details page.

    Zillow Scraper Premium Zillow Scraper Scrape real estate listings from Zillow. Extract property details such as address, price, Broker, broker name and more.

    Amazon product offers and third party sellers Amazon product offers and third party sellers Get product pricing, delivery details, FBA, seller details, and much more from the Amazon offer listing page.

    Realtor Scraper Premium Realtor Scraper Scrape real estate listings from Realtor.com. Extract property details such as Address, Price, Area, Broker and more.

    Target Product Details & Pricing Target Product Details & Pricing Get product details from search results and category pages such as pricing, availability, rating, reviews, and 20+ data points from Target.

    Trulia Scraper Premium Trulia Scraper Scrape real estate listings from Trulia. Extract property details such as Address, Price, Area, Mortgage and more.

    Amazon Customer FAQs Amazon Customer FAQs Get FAQs for any product on Amazon and get details like the question, answer, answered user name, and more.

    Yellow Pages Scraper Yellow Pages Scraper Get details like business name, phone number, address, website, ratings, and more from Yellow Pages search results.

  4. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
Berg, Aleksander K (2025). Remapping California's Wildland Urban Interface: A Property-Level Time-Space Framework, 2000-2020 [Dataset]. https://data.niaid.nih.gov/resources?id=zenodo_10015378

Data from: Remapping California's Wildland Urban Interface: A Property-Level Time-Space Framework, 2000-2020

Related Article
Explore at:
Dataset updated
Jan 21, 2025
Dataset provided by
Kedron, Peter J.
Connor, Dylan S.
Frazier, Amy E.
Berg, Aleksander K
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
California
Description

Maps of California's Wildland Urban Interface (WUI) generated using the Time Step Moving Window (TSMW) method outlined in the paper "Remapping California's Wildland Urban Interface: A Property-Level Time-Space Framework, 2000-2020".

Please cite the original paper:

Berg, Aleksander K, Dylan S. Connor, Peter Kedron, and Amy E. Frazier. 2024. “Remapping California’s Wildland Urban Interface: A Property-Level Time-Space Framework, 2000–2020.” Applied Geography 167 (June): 103271. https://doi.org/10.1016/j.apgeog.2024.103271.

WUI maps were generated using Zillow ZTRAX parcel level attributes joined with FEMA USA Structures building footprints and the National Land Cover Database (NLCD).

All files are geotiff rasters with WUI areas mapped at a ~30m resolution. A raster value of null indicates not WUI, raster value of 1 indicates intermix WUI, and a raster value of 2 indicates interface WUI.

Three WUI maps were generated using structures built on of before the years indicated below:

2000 - "CA_WUI_2000.tif"

2010 - "CA_WUI_2010.tif"

2020 - "CA_WUI_2020.tif"

Acknowledgments -

We thank our reviewers and editors for helping us to improve the manuscript. We gratefully acknowledge access to the Zillow Transaction and Assessment Dataset (ZTRAX) through a data use agreement between the University of Colorado Boulder, Arizona State University, and Zillow Group, Inc. More information on accessing the data can be found at http://www.zillow.com/ztrax. The results and opinions are those of the author(s) and do not reflect the position of Zillow Group. Support by Zillow Group Inc. is acknowledged. We thank Johannes Uhl and Stefan Leyk for their great work in preparing the original dataset. For feedback and comments, we also thank Billie Lee Turner II, Sharmistha Bagchi-Sen, and participants at the 2022 Global Conference on Economic Geography, the 2022 Young Economic Geographers Network meeting, and the 2023 annual meeting of the American Association of Geographers. Funding for our work has been provided by Arizona State University's Institute of Social Science Research (ISSR) Seed Grant Initiative. Additional funding was provided through the Humans, Disasters, and the Built Environment program of the National Science Foundation, Award Number 1924670 to the University of Colorado Boulder, the Institute of Behavioral Science, Earth Lab, the Cooperative Institute for Research in Environmental Sciences, the Grand Challenge Initiative and the Innovative Seed Grant program at the University of Colorado Boulder as well as the Eunice Kennedy Shriver National Institute of Child Health & Human Development of the National Institutes of Health under Award Numbers R21 HD098717 01A1 and P2CHD066613.

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