General description

This repository includes the datasets of the Co-UDlabs Transnational Access Project INDOOR-GRASP (Intercomparison of the hydrological Response of Green Roofs Across Scales, sites and experimental setups). The novelty of this project lies especially in the idea to conduct a paired green roof experiment, considering open site experimental plots at INSA Lyon (GROOF) and smaller indoor test plots built in the laboratory. Therefore, a 3x3 sq. m and a 1x1 sq. m test plot have been installed at the GROOF facility on the roof a building of the Institut National des Sciences Appliquées (INSA, Lyon). Measurements have been collected between September 2024 and March 2025. The project aims at developing a model which can be utilized to scale between both type of dimensions. In a later step, indoor experiments are also foreseen to focus on differences between open field and indoor test plots for green roofs. Whilst being a fascinating research question itself, it has high practical relevance: with this approach, the results of shorter (indoor) measurement campaigns can be scaled to long-term behavior through the outcome of this paired experimental and hydrological model approach. New green roof products can be tested more readily in order to proof their functionality.

Data description

indoor_grasp.csv file (time series)

temporal resolution: 1 min.

Description of columns:

missing_values.json file

This file includes all data gaps in a machine-readable format

Log files for the 1x1 and 3x3 sq. m green roof experiments

3x3 sq. m setup

EVENTS OVER THE PERIOD

09/24/2024 14:10-14:30 12:10-12:30UTC: Watering of the JIM roof

09/30/2024 15:00-15:10 13:00-13:10UTC: Watering of the JIM roof

10/17/2024 15:30-16:00 13:30-14:00UTC: Reboot of the PC and time reset on the Campbell central unit

10/31/2024 10:00-11:00 09:00-10:00UTC: Disconnection of the weight measurement system to install the 1m² roof

11/04/2024 10:30-12:00 09:30-11:00UTC: Verification of 10g trays of JIM, pluviometer and 1m² roof

no event in December

no event in January

02/06/2025: visit

02/13/2025 10:19:00: Time adjustment of control centers

02/25/2025: visit

02/26/2025: visit

03/26/2025: visit

RAW DATA

Sept/Oct: Only 2 minutes of data are missing in the raw dataset (10/17/2024 - 14:12 and 14:13UTC), likely due to intervention on the central unit that day. Maximum and minimum wind speeds have been filled by propagating the last recorded value. The mass of JIM, air temperature, humidity, wind speed, wind direction, solar radiation, evaporation, and Qt_tot were filled by linear interpolation. The two watering events explain the observed peaks in outflow from the roof on September 24 and 30. The disconnection of the weight measurement system on 10/31/2024 at 08:59 UTC caused a negative spike in weight tracking. This value was corrected, as the weights recorded in the minutes before and after were identical (at 956kg).

Nov: No minutes are missing in November.

The tips from November 4th for JIM and the pluviometer were erased.

Dec: No minutes are missing in December.

Jan: No minutes are missing in January.

Feb: No minutes are missing in February. A correction was made on 02/13/2025 at 10:19 on JIM’s weight, probably due to the synchronization of the control center. Since the points before and after were at 1037 kg, the point at 10:19 was also set to 1037 kg.

March: No minutes are missing in March.

1x1 sq. m setup

EVENTS OVER THE PERIOD

11/04/2024 14:15-15:30 13:15-14:30UTC: Verification of the rain gauge buckets and the 1x1 roof.

no event in December

no event in January

02/06/2025: visit

02/13/2025 10:19:00: Time adjustment of control centers

02/25/2025: visit

02/26/2025: visit

RAW DATA

Nov/Dec: No minutes are missing in November and December. The tips from November 4th for 1x1 and the pluviometer were erased.

Jan: No minutes are missing in January.

Feb: No minutes are missing in February.

March: No minutes are missing in March. A correction on the 1x1 weight was made on 03/26/2025 between 13:33 and 13:39. These weights were fixed at 156.6 kg due to some unusual values, probably caused by the visit.

Acknowledgements

The authors acknowledge financial support from the European Union under the Horizon 2020 program within a
contract for Integrating Activities for Starting Communities (Ref. 101008626).

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Summary: The files contained herein represent green roof footprints in NYC visible in 2016 high-resolution orthoimagery of NYC (described at https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_AerialImagery.md). Previously documented green roofs were aggregated in 2016 from multiple data sources including from NYC Department of Parks and Recreation and the NYC Department of Environmental Protection, greenroofs.com, and greenhomenyc.org. Footprints of the green roof surfaces were manually digitized based on the 2016 imagery, and a sample of other roof types were digitized to create a set of training data for classification of the imagery. A Mahalanobis distance classifier was employed in Google Earth Engine, and results were manually corrected, removing non-green roofs that were classified and adjusting shape/outlines of the classified green roofs to remove significant errors based on visual inspection with imagery across multiple time points. Ultimately, these initial data represent an estimate of where green roofs existed as of the imagery used, in 2016. These data are associated with an existing GitHub Repository, https://github.com/tnc-ny-science/NYC_GreenRoofMapping, and as needed and appropriate pending future work, versioned updates will be released here. Terms of Use: The Nature Conservancy and co-authors of this work shall not be held liable for improper or incorrect use of the data described and/or contained herein. Any sale, distribution, loan, or offering for use of these digital data, in whole or in part, is prohibited without the approval of The Nature Conservancy and co-authors. The use of these data to produce other GIS products and services with the intent to sell for a profit is prohibited without the written consent of The Nature Conservancy and co-authors. All parties receiving these data must be informed of these restrictions. Authors of this work shall be acknowledged as data contributors to any reports or other products derived from these data. Associated Files: As of this release, the specific files included here are: GreenRoofData2016_20180917.geojson is in the human-readable, GeoJSON format, in geographic coordinates (Lat/Long, WGS84; EPSG 4263). GreenRoofData2016_20180917.gpkg is in the GeoPackage format, which is an Open Standard readable by most GIS software including Esri products (tested on ArcMap 10.3.1 and multiple versions of QGIS). This dataset is in the New York State Plan Coordinate System (units in feet) for the Long Island Zone, North American Datum 1983, EPSG 2263. GreenRoofData2016_20180917_Shapefile.zip is a zipped folder containing a Shapefile and associated files. Please note that some field names were truncated due to limitations of Shapefiles, but columns are in the same order as for other files and in the same order as listed below. This dataset is in the New York State Plan Coordinate System (units in feet) for the Long Island Zone, North American Datum 1983, EPSG 2263. GreenRoofData2016_20180917.csv is a comma-separated values file (CSV) with coordinates for centroids for the green roofs stored in the table itself. This allows for easily opening the data in a tool like spreadsheet software (e.g., Microsoft Excel) or a text editor. Column Information for the datasets: Some, but not all fields were joined to the green roof footprint data based on building footprint and tax lot data; those datasets are embedded as hyperlinks below. fid - Unique identifier bin - NYC Building ID Number based on overlap between green roof areas and a building footprint dataset for NYC from August, 2017. (Newer building footprint datasets do not have linkages to the tax lot identifier (bbl), thus this older dataset was used). The most current building footprint dataset should be available at: https://data.cityofnewyork.us/Housing-Development/Building-Footprints/nqwf-w8eh. Associated metadata for fields from that dataset are available at https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_BuildingFootprints.md. bbl - Boro Block and Lot number as a single string. This field is a tax lot identifier for NYC, which can be tied to the Digital Tax Map (http://gis.nyc.gov/taxmap/map.htm) and PLUTO/MapPLUTO (https://www1.nyc.gov/site/planning/data-maps/open-data/dwn-pluto-mappluto.page). Metadata for fields pulled from PLUTO/MapPLUTO can be found in the PLUTO Data Dictionary found on the aforementioned page. All joins to this bbl were based on MapPLUTO version 18v1. gr_area - Total area of the footprint of the green roof as per this data layer, in square feet, calculated using the projected coordinate system (EPSG 2263). bldg_area - Total area of the footprint of the associated building, in square feet, calculated using the projected coordinate system (EPSG 2263). prop_gr - Proportion of the building covered by green roof according to this layer (gr_area/bldg_area). cnstrct_yr - Year the building was constructed, pu...

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Download In State Plane Projection Here. The pavement boundaries were traced from aerial photography taken between April 13 and April 26, 2002 and then updated from photography taken between March 15 and April 25, 2018. This dataset should meet National Map Accuracy Standards for a 1:1200 product. Lake County staff reviewed this dataset to ensure completeness and correct classification. In the case of a divided highway, the pavement on each side is captured separately. Island features in cul-de-sacs and in roads are included as a separate polygon.These building outlines were traced from aerial photography taken between April 13 and April 26, 2002 and then updated from successive years of photography. The most recent aerial photography was flown between March 11 and April 12, 2017. This dataset should meet National Map Accuracy Standards for a 1:1200 product. All the enclosed structures in Lake County with an area larger than 100 square feet as of April 2014 should be represented in this coverage. It should also be noted that a single polygon in this dataset could be composed of many structures that share walls or are otherwise touching. For example, a shopping mall may be captured as one polygon. Note that the roof area boundary is often not identical to the building footprint at ground level. Contributors to this dataset include: Municipal GIS Partners, Inc., Village of Gurnee, Village of Vernon Hills.

Mayor Greg Fischer formed the Louisville Metro Office of Sustainability in 2012 with a mission of promoting environmental conservation, the health, wellness and prosperity of our citizens, and embedding sustainability into the culture of the Louisville community. Creating a culture of sustainability will be achieved through broad-based education and awareness efforts as well as implementation of projects and initiatives to influence behavior change.Data Dictionary: NEIGHBORHOOD - The neighborhood in Louisville.TOTAL NEW GREEN ROOFS - The number of green roofs installed. Each green roof is assumed to be 10,000 square feet.TOTAL GRASS PLANTED - The amount of bare dirt land planted with grass or other greenery, measured in hectares.TOTAL TREES PLANTED - The number of new trees planted.TOTAL COOL PAVING - Cool paving is pavement material engineered to exhibit a higher reflectivity than conventional pavement. Cool paving can be porous, made of a light colored material, or both. Cool paving is measured in hectares.TOTAL NEW COOL ROOFS - The number of cool roofs installed. Each cool roof is assumed to be 10,000 square feet. A cool roof can be steep-sloped or low-sloped or flat. A cool roof is define as a roof with a top-level material certified by ENERGY STAR or rated by the Cool Roof Rating Council as "cool." More information is available at https://louisvilleky.gov/government/sustainability/incentives#1Contact: sustainability@louisvilleky.gov

As of June 2019, these are the most current building roofprints for structures in Dukes County, MA. These roofprints were delineated from aerial photos by MassGIS and their subcontractor. The roofprints are not equivalent to footprints. See MassGIS for full methodolgy details. Roofprints can represent any structure (i.e. house, guest house, business, barn, shed, garage, etc). The MVC has also provided building centriods (produced from the roofprint polygon). All centroids were forced to be located within the roofprint polygon.The MVC also appended some assessor's data (or deduced some info from the assessor's data) for each roofprint centroid. The field of [Status] indicates if a parcel is owned by a Year-round ("YR") or Seasonal ("S") person. This deduction was made based on the owner's mailing address zip code. Off-island zip codes were assigned "S" seasonal and on-Island zip codes were assigned "YR" year-round. The field of [UseType] was deduced from the assessor's use code. "NR" - non residential; "R" - residential

These data files summarize key techno-economic metrics used in the NREL dGen model for modeling adoption of distributed solar by representative residential commercial and industrial entities for each county in the continental United States. As described further below many of the metrics are derived as summaries of outputs from dGen. Specifically each county and sector in these file are summarized as a single agent that is the weighted average of 10 statistically-representative agents weighed by the statistical frequency. The dGen simulation used to derive this dataset was conducted in 2018 using the NREL 2018 Standard Scenario Mid Case assumptions https//www.nrel.gov/docs/fy19osti/71913.pdf.

This dataset contains photogrammetrically compiled roof outlines of buildings. All near orthogonal corners are square. Buildings that are less than 400 square feet are not captured. Special consideration is given to garages that are less than 400 square feet and will be digitized when greater than 200 square feet. Interim rooflines, such as dormers and party walls, as well as minor structures, such as carports, decks, patios, stairs, etc., and impermanent structures, such as sheds, are not shown. Large buildings which appear to house activities that are commercial or industrial in nature are shown as commercial/industrial. Structures that appear to be primarily residential in nature, including hotels and apartment buildings are shown as residential buildings. Structures which appear to be used or owned primarily by governmental, nonprofit, religious, or charitable organizations, or which serve a public function are shown as public buildings. Structures which are closely associated with a larger building, such as a garage, are shown as an out building. Structures which cannot be clearly defined as Industrial/Commercial; Residential; Public; or Out Buildings are flagged as such for later categorization. The classification of buildings is subject to the interpretation from the aerial photography and may not reflect the building’s actual use. Buildings that have an area less than the minimum required size for data capture will occasionally be present in the Geodatabase. Buildings are not removed after they have been digitized and determined to be less than the minimum required size.

Development Notes: Data meets or exceeds map accuracy standards in effect during the spring of 1992 and updated as a result of a flyover in the spring of 2004 and 2015. Original data was derived from aerial photography flown in the spring of 1992 for the eastern half of the County and the spring of 1993 for the western half of the County. Photography was produced at a scale of 1"=1500'. Mapping was stereo digitized at a scale of 1"=200'.

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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 contains building, roofing, electrical, mechanical, demolition, and driveway issued permits for Douglas County. City-issued permits are not in this dataset.

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The roofing, siding and insulation wholesaling industry is experiencing a surge in demand for durable, weather-resistant materials because of unprecedented extreme weather events and climate disasters. In 2024 alone, 27 weather-related billion-dollar incidents exacerbated the need for impact-resistant shingles, high-quality waterproofing membranes and advanced insulation products. A gain in the aging housing stock requiring upgrades also drives demand for non-wood roofing materials, reflecting the need for modern solutions to replace aging infrastructures. Growth in non-residential construction has also translated into higher order volumes for wholesalers, particularly from sectors such as healthcare, education, data centers and industrial buildings. Through the end of 2025, industry revenue has climbed at a CAGR of 5.3% to reach $82.7 billion, including a 1.0% gain in 2025 alone. There has been a notable uptick in M&A activity in this industry as large entities aim to consolidate a fragmented market. Recent instances include The Home Depot's acquisition of SRS Distribution and QXO's agreement to acquire Beacon Roofing Supply. This consolidation is not merely a response to the recurring demand for roof replacements and exterior renovations but also serves as strategic mitigation against the increasingly complex project requirements that contractors and remodelers face. Technological advancements in materials and distribution—such as adopting e-commerce platforms and improved supply chain management—have also contributed to operational efficiencies and cost savings, causing profit to climb. The industry is poised to prosper over the five years to 2030 because of steady growth in residential renovations as homeowners prioritize personalizing their existing spaces over buying new properties. An anticipated climb in demand for insulation materials owing to stricter energy conservation regulations, rising energy costs and a strong push for sustainability in construction will also bode well for wholesalers. While technology will play a transformative role, with leading wholesalers like Beacon Roofing Supply pushing for digital sales channels and investing in digital platforms, AI and automation, M&A will continue to be a defining force as the industry seeks scale, geographic reach and operational synergies. Industry revenue will strengthen at a CAGR of 2.6% to reach $93.9 billion in 2030.

The Buildings (BG) layer consists of photogrammetrically interpreted polygons representing roof outlines of manmade structures in Jefferson County, Kentucky in Spring of 2016. A building is a manmade structure which may be habitable by human beings, animals or which stores materials and is at a minimum 10' x 10' in roof surface area. A building may house a variety of activities at one time, or sequentially over its life. A building may also sit vacant, be in a partial state of destruction, or construction. A feature classified as building but not having a roof (silo, tank or water tower) will show outline of the features shape. View detailed metadata.Information on Building Height Attributes:Minimum Height – Feet: Minimum Height Feet calculated from Z_Max height (feet)Maximum Height – Feet: Maximum Height Meters calculated from Z_Max height (feet)Average Height – Feet: Average Height Feet calculated from Z_Max height (feet)SArea or Surface_Area: 3D surface area for the region defined by each polygon.Min_Slope: Slope value closest to zero within the area defined by the polygon.Max_Slope: Highest slope value along the line or within the area defined by the polygon.Avg_slope - Average slope value within the area defined by the polygon.Maximum Height Meters - Max Height Meters calculated from Z_Max height (feet)