The pathway representation consists of segments and intersection elements. A segment is a linear graphic element that represents a continuous physical travel path terminated by path end (dead end) or physical intersection with other travel paths. Segments have one street name, one address range and one set of segment characteristics. A segment may have none or multiple alias street names. Segment types included are Freeways, Highways, Streets, Alleys (named only), Railroads, Walkways, and Bike lanes. SNDSEG_PV is a linear feature class representing the SND Segment Feature, with attributes for Street name, Address Range, Alias Street name and segment Characteristics objects. Part of the Address Range and all of Street name objects are logically shared with the Discrete Address Point-Master Address File layer. Appropriate uses include: Cartography - Used to depict the City's transportation network location and connections, typically on smaller scaled maps or images where a single line representation is appropriate. Used to depict specific classifications of roadway use, also typically at smaller scales. Used to label transportation network feature names typically on larger scaled maps. Used to label address ranges with associated transportation network features typically on larger scaled maps. Geocode reference - Used as a source for derived reference data for address validation and theoretical address location Address Range data repository - This data store is the City's address range repository defining address ranges in association with transportation network features. Polygon boundary reference - Used to define various area boundaries is other feature classes where coincident with the transportation network. Does not contain polygon features. Address based extracts - Used to create flat-file extracts typically indexed by address with reference to business data typically associated with transportation network features. Thematic linear location reference - By providing unique, stable identifiers for each linear feature, thematic data is associated to specific transportation network features via these identifiers. Thematic intersection location reference - By providing unique, stable identifiers for each intersection feature, thematic data is associated to specific transportation network features via these identifiers. Network route tracing - Used as source for derived reference data used to determine point to point travel paths or determine optimal stop allocation along a travel path. Topological connections with segments - Used to provide a specific definition of location for each transportation network feature. Also provides a specific definition of connection between each transportation network feature. (defines where the streets are and the relationship between them ie. 4th Ave is west of 5th Ave and 4th Ave does intersect with Cherry St) Event location reference - Used as source for derived reference data used to locate event and linear referencing.Data source is TRANSPO.SNDSEG_PV. Updated weekly.

This script will prompt the user for a path to a file geodatabase or a sde geodatabase connection file. Then the script will loop through the feature classes\tables and document details about the attribute rules. All of the data gathered is written to a csv file. This is a Jupyter Notebook written using arcpy.Sources used to develop this notebook:Iterate through SDE to find and export FCs with Attribute Rules with python?Attribute Rule propertiesA Python script to Automate Attribute Rules Deployment

Download .zipMaps and data associated with oil-and-gas wells represent one of the largest datasets at the Ohio Department of Natural Resources. This GIS data layer contains all the locatable oil-and-gas wells in Ohio. The feature is derived from coordinates obtained from the Division of Oil and Gas Resources Management (DOGRM) oil and gas well database – Risk Based Data Management System (RBDMS). The RBDMS database has a long history and is a comprehensive collection of well data from historic pre-1980 paper well records (digitized by the Division of Geological Survey (DGS)) to post-1980 DOGRM database solutions.Since 1860, it is estimated that more than 267,000 oil-and-gas wells have been drilled in Ohio. The compressed file also includes a feature used to connect the surface location to the bottom location of a well that has been drilled directionally or horizontally. This feature is NOT the actual wellbore path, it is simply a graphical representation indicating the relationship between the two well points.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesDivision of Oil & Gas ResourcesOil and Gas Resources Management2045 Morse Road Bldg F-2Columbus, OH, 43229-6693Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: Every Saturday

The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.

NUOnet Vision: Efficient use of nutrients to optimize production and product quality of food for animals and humans, fuel and fiber in a sustainable manner that contributes to ecosystem services. This record contains the DET and Data Dictionary for NUOnet - the data files may be found at https://usdaars.maps.arcgis.com/apps/MapSeries/index.html?appid=e90392a99d5c427487c6c37cf6d47844 Best nutrient management practices are critical for maintaining profitable economic returns, sustaining higher yields, lowering environmental impacts, optimizing nutritional quality, and providing ecosystem services. Best management practices that improve nutrient use efficiencies can reduce nutrient losses from agricultural systems. However, we need to improve our understanding of biological, physical and chemical influences on nutrient processes. For instance, crop use efficiency of nitrogen (N), the primary macronutrient regulating yield and protein content, can be reduced by processes such as denitrification (N2O and N2 emission), leaching (NH4-N, NO3-N, and organic-N), ammonia (NH3-N,) volatilization, surface runoff and erosion, disease, and non-crop competition. Similarly, we need to obtain more information about biological and physical cycles of nutrients, especially phosphorus (P), including factors that influence nutrient availability from fertilizers, crop residues, cover crops, manures, and other byproducts. We need a better understanding of relationships between soil biological communities and ecosystems, including plant roots and root exudates, and availability and uptake of macro- and micro-nutrients. In addition, we need information regarding how these practices impact yields, organoleptic qualities, and the macro- and micro-nutritional composition of plants. This information will improve our ability to develop best nutrient management practices. Optimal soil nutrient levels are critical for maximizing economic returns, increasing sustainable yields, lowering environmental impacts, sustaining ecosystem services and optimizing nutritional and organoleptic qualities of human and animal foods. Efficient management practices are crucial for increasing economic returns for land managers in a sustainable manner while producing high quality of food for animals and humans with reduced off-site transfer of nutrients from agricultural areas in watersheds. Optimizing N and P inputs requires more information about nutrient inputs from fertilizers, manures, composts, agricultural byproducts, cover crops, and other nutrient sources in addition to nutrient cycling within soils. This requires data from long-term nutrient management studies across a wide range of soils, crops, and environmental conditions. Land management needs are to connect nutrient management practices for crops with nutrient use efficiency; crop quality; crop chemical composition and nutritional value, quality and acceptability for animal and human health. Development of databases that enable the scientific exploration of connections among data generated from diverse research efforts such as nutrient management, fate and ecosystem service outcomes, nutritional composition of crops, and animal and human health, is needed. Nitrogen is a key nutrient that enhances agricultural yield and protein content, but multiple N loss pathways, as previously mentioned, reduce crop N use efficiency (NUE). Implementing proper management practices is needed to reduce N losses from agricultural systems. ARS has multidisciplinary scientific teams with expertise in soils, ecological engineering, hydrology, livestock management and nutrition, horticulture, crop breeding, human and animal nutrition, post-harvest management and processing, and other areas, and intentional collaboration among these teams offers opportunities to rapidly improve NUE and crop quality and reduce off-site N losses. Similarly, increased P use efficiencies are needed to enhance and ensure sustainable agricultural production and to reduce environmental degradation of water sources. Manure is a valuable source of P and it can be used as a soil amendment to reduce crop production costs. However, there is a need to improve our understanding of the biological and physical cycles of soil P, as well as to obtain more information about P supplies from fertilizer, crop residues, cover crops, manure, and byproducts, and livestock nutrition impacts on manure properties. There is also a need for a better understanding of soil biological communities and ecosystems, including plant roots and root exudates and how their interactions with crops and community ecology affect yield and the uptake of macro- and micro-nutrients and the ultimate nutritional composition and organoleptic qualities of the crop. Studies documenting the responses of crop-associated biological communities to management practices and genetic technologies implemented across multiple environments (e.g., soil types and chemistries, hydrologic regimes, climates) will improve our understanding of gaps in macro- and micro-nutrient management strategies. A goal of the USDA-ARS is to increase agricultural production and quality while reducing environmental impacts. The Nutrient Uptake and Outcomes (NUOnet) database will be able to help establish baselines on nutrient use efficiencies; processes contributing to nutrient losses; and processes contributing to optimal crop yield, nutritional and organoleptic quality. This national database could be used to calculate many different environmental indicators from a comprehensive understanding of nutrient stocks and flows. Increasing our understanding of stocks and flows could help in the identification of knowledge gaps as well as areas where increased efficiencies can be achieved at a national level. NUOnet could also be used to develop tools to derive cost-benefit curves associated with nutrient management improvement scenarios and assess local, regional and national impacts of off-site nutrient loss. Understanding how agricultural production impacts human health is a challenge, and the database could be used to link crop management strategies to crop chemical composition to human consumption patterns and ultimately to human health outcomes. A national database will also be very important for development and evaluation of new technologies such as real-time sensing or other proximal and remote sensing technologies that enable assessment of nutrient use efficiencies, particularly at the grower level. The database could also be used to develop analyses that will contribute to the recommendation of policies for resource allocations that will most effectively fulfill the goals of the Grand Challenge. Such a national database with contributions from peers across different national programs could also enhance collaborations between ARS, universities, and extension specialists, as well as with producers, industry, and other partners. See the NUOnet Home Page for more information about this database and strategic goals. Resources in this dataset:Resource Title: GRACEnet-NUOnet Data Dictionary. File Name: GRACEnet-NUOnet_DD.csvResource Title: NUOnet Data Entry Template. File Name: DET_NATRES_NUO.zipResource Description: A multi-tab worksheet for data entry. Users can customize fields to be mandatory, set minimum and maximum values, and run a validation on fields as specified by the user. https://gpsr.ars.usda.gov/html/NUOnet_DET/DET_NATRES_NUO.xlsm

The information in the abstract is translated from the archeological report: The report is a supplementary part 2, which continues a series of reports of the archaeological investigations carried out in connection with the proposed double-track between Motala and Mjölby in western Östergötland. For the antiquarian and archaeological context and on the overall problem areas, see the report "An archaeological line project in western Östergötland" (see SND 2000). The newly made archaeological work included field assessment of Landstorp (agrarian remains, graves and an old road) and in Russingtorp (settlement from Early Neolithic and Early Bronze Age) and in Skänninge town (Middle Ages). In Lycketorp a trial excavation was made at a possible settlement site and of hollow ways.

Purpose:

The information in the purpose is translated from the archeological report: The aim of the field evaluation was to assess the character, extent and scope of the settlement remains found, and to date these for an upcoming excavation. An additional objective was to determine whether unmarked or ploughed down graves could be found in the study area on the western side of the railroad.

The ZIP file consist of GIS files and an Access database with information about the excavations, findings and other metadata about the archaeological survey.

Full Landscape Project v3.4 (Please note that this file is large, ~600mb, and may take a long time to download on slower internet connections):File Geodatabase (NJ State Plane NAD 1983) download: Click hereLandscape Regions (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click hereAtlantic Coastal Habitat (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click hereDelaware Bay Habitat (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click hereMarine Habitat (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click herePiedmont Habitat (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click herePinelands Habitat (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click hereSkylands Habitat (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click hereStream Habitat (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click hereVernal Pools and Vernal Habitats (Landscape Project v3.4):File Geodatabase (NJ State Plane NAD 1983) download: Click hereArcGIS Online: Click hereLandscape Project data are easily accessible and can be integrated with the planning, protection and land management programs of non-government organizations and private landowners and at every level of government- federal, state, county and municipal. Landscape maps and overlays provide a basis for proactive planning, such as the development of local habitat protection ordinances, zoning to protect critical wildlife areas, management guidelines for imperiled species conservation on public and private lands, and land acquisition projects. Most importantly, the information that is readily available in the Landscape Project can be used for planning purposes before any actions such as proposed development, resource extraction (e.g. timber harvests) or conservation measures occur. The maps help increase predictability for local planners, environmental commissions, and developers and help facilitate local land use decisions that appropriately site and balance development and habitat protection. The Landscape Project maps allow the regulated public to anticipate potential environmental regulation in an area and provide some level of assurance regarding areas where endangered, threatened or species of special concern are not likely to occur, affording predictability to the application and development process. Thus, Landscape Project maps can be used proactively by regulators, planners and the regulated public in order to minimize conflict and protect species. This minimizes time and money spent attempting to resolve after-the-fact endangered and threatened species issues.

This dataset contains annual results from the City of Tempe’s Impact Report for fiscal year 2023-2024, produced by the Tempe Department of Health and Human Services and Tempe Community Council. It summarizes key outcomes from programs and services that address community needs such as homelessness, mental health, youth development, and support for vulnerable populations. The data reflects progress made through targeted investments and initiatives guided by the Social Determinants of Health model. It is used to measure results, guide future planning, and ensure resources are directed where they make the greatest impact.Data DictionaryAdditional Information:Source: Excel documentContact: Kimberly Van NimwegenContact E-Mail: Kimberley_VanNimwegen@tempe.govData Source Type: Excel / Table, ZoomGrantsPreparation Method: Data is collected from multiple programs and services. Staff and partners enter summarized results into a shared Excel file, or ZoomGrants database which is compiled into the annual dataset.Publish Frequency: AnnualPublish Method: Manual

A control section is a unique identifier for individual segments of a roadway. Historically control sections were only assigned to on-system, or state-maintained, highways, and were created as a highway referencing system for planning and maintenance projects, etc. However, this dataset also includes off-system, or non-state-maintained, roadways. Control Section numbers are assigned for the life of the roadway and generally do not change or move, regardless of improvements to the roadway. Currently, control sections are located geographically along roadway using linear referencing. The data was created by the TxDOT Transportation Planning and Programming Division's Data Management Section.This data contains measures. Measures are stored as M-values within each vertex along the line, in the same way that some datasets store z-values for the elevation, except that measures store the distance from the origin, or DFO, of the line. M-enabled networks serve as a framework for locating roadway assets along the network using linear referencing. This data set must be downloaded as a file geodatabase in order to keep M-values intact. If downloaded as a shapefile or added to a map from a connection to ArcGIS online, measures will not applied to the line.Update Frequency: 1 MonthsSource: Geospatial Roadway Inventory Database (GRID)Security Level: PublicOwned by TxDOT: TrueRelated LinksData Dictionary PDF [Generated 2025/05/21]

DownloadA daily extract of the NPDES Conveyance dataset is available for download as a zipped file geodatabase.BackgroundAs a government agency that owns and maintains separate storm sewer systems, the Maryland State Highway Administration (SHA) is mandated to file a National Pollutant Discharge Elimination System (NPDES) permit with the Maryland Department of the Environment (MDE). The permit requires the inventory, inspection, and maintenance of SHA stormwater infrastructure. SHA is responsible for maintaining storm drain infrastructure on more than 5,000 miles of roadway statewide. SHA has developed a program consisting of SHA personnel, data managers, and subject matter experts to support the permit requirements and maintain these roadways. The tasks involved in the SHA NPDES data collection program are often completed by engineering consultants for SHA.The data are organized into a series of drainage systems with stormwater management facilities that are interconnected, allowing for flow-tracing function through distinct systems. A drainage system is defined as a series of storm drain structures or point features (i.e., manholes, inlets, endwalls) that connect hydraulically through conveyance features such as pipes and / or ditches. Closed and open storm drain structures are connected by pipe and ditch conveyance to create the drainage system. Stormwater management facilities (SWMF), also known as stormwater best management practices (BMP) are inventoried with the storm drain system. A system can include both open and closed storm drain features.ConveyanceConveyance features to be identified and inventoried include actual, physical features (pipes and ditches) and database connectivity features (hydraulic connectors). Conveyance is represented as line features in the database. Although they do not physically exist, hydraulic connectors should be inventoried to facilitate connection of drainage systems through stormwater BMPs; this is the only case where a hydraulic connector is created. Not every pipe or ditch conveyance is inventoried, but generally all conveyances between structures are inventoried. Conveyance features will have an upstream and downstream structure. When contract plans are not available showing proper conveyance for a storm drain system, conveyance can be determined by looking at the pipe(s) direction inside of structures. Field crews are not required to open manhole lids, and conveyance can be assumed at the field crew’s discretion when plans are not available.Pipes, Cross Culverts, & Driveway CulvertsPipes connect structures together in a system to maintain conveyance. Pipes consist of closed storm drain pipes, cross culverts, and driveway culverts. Rules for collecting cross culvert and driveway culvert pipes are described below. The following are rules that should be followed when collecting pipes within the storm drain network:All pipes between closed storm drain structures are inventoried.Pipes less than five feet in height are inventoried within SHA ROW.Pipes that are greater than five feet in height are not inventoried if they do not connect to closed storm drain structures. Pipes that are greater than five feet in height and do connect to closed storm drain structures are inventoried with the storm drain network.Closed storm drain systems that outfall through a pipe or culvert that is greater than five feet in height are inventoried. Pipe size, shape, invert, and material are recorded for all pipes. Because field crews are not required to open grates or manhole lids, this attribute information is most often gathered from contract plans. Pipe sizes and material should be verified in the field by observation through inlet grates and at end structures (headwalls, end sections, outfalls, projection pipes). Field crews should become familiar with different pipe sizes and materials prior to conducting field inventory.Cross Culverts are pipes, boxes, or arches that convey water from one side of the ROW to the other side, usually under the roadway. Cross culverts are inventoried as pipes. Depending on the situation and culvert size, not all cross culverts will be inventoried. The following are rules that should be followed when collecting cross culverts:The culvert height is determined from contract plans when available. Otherwise care should be taken to measure and estimate the actual culvert height in the field. This may require estimating the depth of sedimentation at the culvert ends to determine the feet of buried culvert.Culverts that are less than five feet in height are inventoried.Culverts that are greater than five feet in height are not inventoried.A culvert that is greater than five feet in height that has a closed storm drain tying in is not inventoried. Instead, the most downstream structure in the closed storm drain system is inventoried as a pipe connection at the location the storm drain system connects to the culvert.Driveway Culverts and entrance culverts are pipes, possibly with an end structure, that conveys water under driveways, utility access roads, or stormwater BMP access roads. Not all driveway culverts will be inventoried within SHA ROW. The following are rules that should be followed when collection driveway culverts:Private driveway culverts and culverts at farm or other access points that do not require access permits should not be inventoried. Culverts under entrance drives that provide two-way or greater traffic such as multi-family residential, commercial, public, or industrial properties are inventoried. Culverts under SHA-owned stormwater maintenance access or other utility access roads should also be inventoried.If the private driveway or access drive culvert has a closed storm drain structure such as an inlet or riser on the upstream or downstream end of the pipe, then the culvert should be inventoried.If a driveway culvert is excluded from the inventory, other adjoining closed drain structures completing the system should be connected using a ditch. The ditch in this case should be drawn through the culverts as if the culvert does not exist.DitchesDitches and open conveyance are channels or flow paths that connect open structures (headwalls, end sections, endwalls, projection pipes, inlets with open backs) in a system to maintain the conveyance. Attributes collected for ditches include material (vegetative, concrete, riprap, etc.), bottom width, and side slope. Not all ditches or open channels within SHA ROW are to be inventoried in the geodatabase. Ditches to be inventoried are the following:Ditches or open conveyance between open structures.Ditches or open conveyance greater than two feet in bottom width.Ditches or open conveyance that flow into stormwater BMPs regardless of bottom width.Hydraulic ConnectorsHydraulic Connectors connect the outfalls into stormwater BMPs to the control structure of the stormwater BMP to maintain conveyance through the system. Hydraulic connectors are used to represent connectivity through a stormwater BMP from inflows to control structures. Inflow points and control structures for stormwater BMPs should be connected with a hydraulic connector, including infiltration trenches. If hydraulic connectors do not exist in the previous inventory, the current development should create them. The hydraulic connector line features are stored in the CONVEYANCE feature class and no additional attribute information is collected. The connector is use so that connectivity between structures is maintained through stormwater BMPs and network tracing can occur.SimplificationsThe simplification process flattens database tables that normalize attribute information, resulting in a dataset with all attributes but also many null fields when the attribute type is not relevant to the SWMFAC type. The simplified data are a snapshot in time of the production NPDES data, updated every night.PublishingThis service was last published by Elliott Plack on 9/6/2019 based on a materialized view created by John Shiu. The service was republished on 11/26/2016 due to a security requirement on the source dataset.

The Texas Department of Transportation (TxDOT) maintains a spatial dataset of roadway polylines for planning and asset inventory purposes, as well as for visualization and general mapping. This dataset covers the state of Texas and includes on-systems routes (those that TxDOT maintains), such as interstate highways, U.S. highways, state highways, and farm and ranch roads, as well as off-system routes, such as county roads and local streets. Route segments in this unsegmented version are not broken by functional classification the way the other version of TxDOT Roadways feature layer is. This data contains measures. Measures are stored as M-values within each vertex along the line, in the same way that some datasets store z-values for the elevation, except that measures store the distance from the origin, or DFO, along the line. M-enabled networks serve as frameworks for locating roadway assets along the network using linear referencing. This data set must be downloaded as a file geodatabase in order keep M-values intact. If downloaded as a shapefile or added to a map from a connection to ArcGIS online, measures will not be applied to the line.Update Frequency: 1 MonthsSource: Geospatial Roadway Inventory Database (GRID)Security Level: PublicOwned by TxDOT: TrueRelated LinksData Dictionary PDF [Generated 2025/05/21]