Datasets contain original and revised Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI), as well as sub-components that were used to develop the indices and water quality data used to revise and/or evaluate the indices. This dataset is associated with the following publication: Johnson, Z.C., S. Leibowitz, and R.A. Hill. Revising the index of watershed integrity national maps. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 651: 2615-2630, (2018).

This layer represents the composite count overlap of six polygon source data sets that consider ecosystem structure, function, and composition in order to estimate relative ecological integrity across the High Divide region. We define and estimate ecological integrity by assembling publicly available spatial data that describe “elements of composition, structure, function, and ecological processes” (after Parrish et al. 2003; Wurtzebach and Schultz 2016) as described below.

These are the discrete sampling locations brought out of the Water Quality Sampling Data dataset [https://data.austintexas.gov/Environmental/Water-Quality-Sampling-Data/5tye-7ray] for ease of mapping. SampleSiteNo in this table maps to SAMPLE_SITE_NO in the larger dataset. Note that not all samples in the larger dataset have a match in this table ... this table only contains sampling locations with valid latitude/longitude values. Reasons for samples not having a valid physical location: the data represents a non-spatial object like a product or a lab standard or blank; the data was collected at a protected karst feature; the data was collected prior to GIS or GPS and the information never existed or was lost.

Datasets contain original and revised Index of Watershed Integrity (IWI) and Index of Catchment Integrity (ICI), as well as sub-components that were used to develop the indices and water quality data used to revise and/or evaluate the indices. This dataset is associated with the following publication: Johnson, Z.C., S. Leibowitz, and R.A. Hill. Revising the index of watershed integrity national maps. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 651: 2615-2630, (2018).

CDFW BIOS GIS Dataset, Contact: Marcus Beck, Description: Stream management goals for biological integrity may be difficult to achieve in developed landscapes where channel modification and other factors impose constraints on in-stream conditions. To evaluate potential constraints on biological integrity, we developed a statewide landscape model for California that estimates ranges of likely scores for a macroinvertebrate-based index that are typical at a site for the observed level of landscape alteration.

No description was included in this Dataset collected from the OSF

Watershed Integrity MethodologySee also: https://www.cmap.illinois.gov/2050/maps/watershed

3571 Global import shipment records of Integrity Stent with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

See https://wa-stateparks.maps.arcgis.com/home/item.html?id=be76cf1a59dc40c3b655ca746aee5820 for project report and metadata.

Research data and scientific software related to: Schröder W. Nickel S, Jenssen M, Riediger J 2015. Methodology to assess and map the potential development of forest ecosystems exposed to climate change and atmospheric nitrogen deposition: a pilot study in Germany. Science of the Total Environment 521-522:108-122

21 Global import shipment records of Integrity V System with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

864 Global import shipment records of Integrity Testing Equipment with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

U.S. Counties represents the counties of the United States in the 50 states, the District of Columbia, and Puerto Rico.

The seamless, county-wide parcel layer was digitized from official Assessor Parcel (AP) Maps which were originally maintained on mylar sheets and/or maintained as individual Computer Aided Design (CAD) drawing files (e.g., DWG). The CRA office continues to maintain the official AP Maps in CAD drawings and Information Systems Department/Geographic Information Systems (ISD/GIS) staff apply updates from these maps to the seamless parcel base in the County’s Enterprise GIS. The seamless parcel layer is updated and published to the Internet on a monthly basis.The seamless parcel layer was developed from the source data using the general methodology outlined below. The mylar sheets were scanned and saved to standard image file format (e.g., TIFF). The individual scanned maps or CAD drawing files were imported into GIS software and geo-referenced to their corresponding real-world locations using high resolution orthophotography as control. The standard approach was to rescale and rotate the scanned drawing (or CAD file) to match the general location on the orthophotograph. Then, appropriate control points were selected to register and rectify features on the scanned map (or CAD drawing file) to the orthophotography. In the process, features in the scanned map (or CAD drawing file) were transformed to real-world coordinates, and line features were created using “heads-up digitizing” and stored in new GIS feature classes. Recommended industry best practices were followed to minimize root mean square (RMS) error in the transformation of the data, and to ensure the integrity of the overall pattern of each AP map relative to neighboring pages. Where available Coordinate Geometry (COGO) & survey data, tied to global positioning systems (GPS) coordinates, were also referenced and input to improve the fit and absolute location of each page. The vector lines were then assembled into a polygon features, with each polygon being assigned a unique identifier, the Assessor Parcel Number (APN). The APN field in the parcel table was joined to the corresponding APN field in the assessor property characteristics table extracted from the MPTS database to create the final parcel layer. The result is a seamless parcel land base, each parcel polygon coded with a unique APN, assembled from approximately 6,000 individual map page of varying scale and accuracy, but ensuring the correct topology of each feature within the whole (i.e., no gaps or overlaps). The accuracy and quality of the parcels varies depending on the source. See the fields RANK and DESCRIPTION fields below for information on the fit assessment for each source page. These data should be used only for general reference and planning purposes. It is important to note that while these data were generated from authoritative public records, and checked for quality assurance, they do not provide survey-quality spatial accuracy and should NOT be used to interpret the true location of individual property boundary lines. Please contact the Sonoma County CRA and/or a licensed land surveyor before making a business decision that involves official boundary descriptions.

The collection contains Forest Structural Integrity Index data for the Tropical and Subtropical Moist Broadleaf Forests Biome. The collection is updated from the data provided in Hansen, A. et al. Global humid tropics forest structural condition and forest structural integrity maps. Scientific Data 6, 232, doi:10.1038/s41597-019-0214-3 (2019). Loss year extends to 2018. The spatial extent was expanded to the full biome.

The New Jersey Department of Environmental Protection (NJDEP) Bureau of Freshwater and Biological Monitoring (BFBM) performs monitoring on non-tidal freshwater streams and rivers throughout the state using fish as biological indicators of stream health. This data is used for a wide variety of purposes, including the evaluation of aquatic life use assessment for the federally required NJ Integrated Water Quality Assessment Report and the designation of Category One antidegradation classification based on exceptional ecological significance. BFBM has established fish bioassessment protocols for three different stream types in New Jersey. The Bureau initiated Fish Index of Biotic Integrity (IBI) monitoring in 2000 following the development of the Northern Fish IBI by U.S. EPA Region 2 which was based on the EPA’s Rapid Bioassessment Protocols (RBP; USEPA 1999). This, the longest fish monitoring program in the NJDEP Division of Water Monitoring and Standards (DWMS), monitors resident fish assemblages in wadable streams larger than 4-square miles in drainage area. The Southern Fish IBI was developed by BFBM in 2012 for low gradient streams in the Inner Coastal Plain eco-region of NJ. Lastly, after several years of research and analysis by the Philadelphia Academy of Natural Sciences of Drexel University and BFBM, the Headwaters IBI was completed in 2014. This program is used to monitor small first and second order streams less than 4 square miles in drainage area within the same eco-regions of Northern New Jersey as the Northern Fish IBI. The two northern programs differ not only in the size of stream monitored, but also in the assemblages monitored. The Northern Fish IBI is solely a fish-based index, whereas the Headwaters IBI uses fish, crayfish, and streamside amphibians as bio-indicators.

Summary of Landscape Integrity Index (LII) scores by land ownership type.

Credit report of Integrity Peru S.a.c. contains unique and detailed export import market intelligence with it's phone, email, Linkedin and details of each import and export shipment like product, quantity, price, buyer, supplier names, country and date of shipment.

This record presents the data underlying Skills4EOSC Deliverable D6.1 Mapping of existing professional networks and relevant documentation of the search string.

This map represents the interaction between ecosystem integrity and connectivity in the High Divide region. The ecological integrity layer was created using the composite count overlap of three data sets that consider ecosystem structure, function, and composition in order to estimate relative ecological integrity across the High Divide region. We define and estimate ecological integrity by assembling publicly available spatial data that describe “elements of composition, structure, function, and ecological processes” (after Parrish et al. 2003; Wurtzebach and Schultz 2016 https://doi.org/10.1093/biosci/biw037).