Set of functions in WPS web services, allowing access to the documentation of GIS layers (model, alias, relationships, list values) from the Bordeaux Métropole GIS database.

This dictionary is accessible via an interface on ‘http://data.bordeaux-metropole.fr/dicopub/#/dico’

Webservice WPS

Operation

WPS is a real-time access service. For more details, refer to the FAQ.

WebService URL:

https://data.bordeaux-metropole.fr/wps?key=[VOTRECLE]&SERVICE=WPS&VERSION=1.0.0&REQUEST=EXECUTE&IDENTIFIER=[NOMCOUCHE]

Replace [yourcle] with the software key that was provided to you by Bordeaux Métropole. To order one (valid for WMS, WFS, WPS and CUB APIs), click here If you would like to see more information about OGC web services click on this link

Layer Name

Name of the layer to provide to your client:

Layer name| Description

—|— dico_domains | domains are super-categories of themes.Themes are logical groupings of layers. This function allows you to list the available domains and the themes contained dico_themes | themes are logical groupings of layers. This function allows you to list the available themes and the layers contained

dico_layers | this function allows you to list the available layers and their attributes

dico_propagation | this function allows to list the propagation of layers

dico_search

| this function allows you to search the dictionary

** **

This dictionary is accessible via an interface on ‘http://data.bordeaux-metropole.fr/dicopub/#/dico’

Webservice WPS

Operation

WPS is a real-time access service. For more details, refer to the FAQ.

WebService URL:

https://data.bordeaux-metropole.fr/wps?key=[VOTRECLE]&SERVICE=WPS&VERSION=1.0.0&REQUEST=EXECUTE&IDENTIFIER=[NOMCOUCHE] Replace [yourcle] with the software key that was provided to you by Bordeaux Métropole.To order one (valid for WMS, WFS, WPS and CUB APIs), click here

If you would like to see more information about OGC web services click on this link

Layer Name

Name of the layer to provide to your client:

Layer name| Description —|— dico_domains | domains are super-categories of themes. Themes are logical groupings of layers.This function allows you to list the available domains and the themes contained

dico_themes | themes are logical groupings of layers.This function allows you to list the available themes and the layers contained

dico_layers

| this function allows you to list the available layers and their attributes

dico_propagation | this function allows to list the propagation of layers

dico_search | this function allows you to search the dictionary

**

**

Learn state-of-the-art skills to build compelling, useful, and fun Web GIS apps easily, with no programming experience required.Building on the foundation of the previous three editions, Getting to Know Web GIS, fourth edition,features the latest advances in Esri’s entire Web GIS platform, from the cloud server side to the client side.Discover and apply what’s new in ArcGIS Online, ArcGIS Enterprise, Map Viewer, Esri StoryMaps, Web AppBuilder, ArcGIS Survey123, and more.Learn about recent Web GIS products such as ArcGIS Experience Builder, ArcGIS Indoors, and ArcGIS QuickCapture. Understand updates in mobile GIS such as ArcGIS Collector and AuGeo, and then build your own web apps.Further your knowledge and skills with detailed sections and chapters on ArcGIS Dashboards, ArcGIS Analytics for the Internet of Things, online spatial analysis, image services, 3D web scenes, ArcGIS API for JavaScript, and best practices in Web GIS.Each chapter is written for immediate productivity with a good balance of principles and hands-on exercises and includes:A conceptual discussion section to give you the big picture and principles,A detailed tutorial section with step-by-step instructions,A Q/A section to answer common questions,An assignment section to reinforce your comprehension, andA list of resources with more information.Ideal for classroom lab work and on-the-job training for GIS students, instructors, GIS analysts, managers, web developers, and other professionals, Getting to Know Web GIS, fourth edition, uses a holistic approach to systematically teach the breadth of the Esri Geospatial Cloud.AUDIENCEProfessional and scholarly. College/higher education. General/trade.AUTHOR BIOPinde Fu leads the ArcGIS Platform Engineering team at Esri Professional Services and teaches at universities including Harvard University Extension School. His specialties include web and mobile GIS technologies and applications in various industries. Several of his projects have won specialachievement awards. Fu is the lead author of Web GIS: Principles and Applications (Esri Press, 2010).Pub Date: Print: 7/21/2020 Digital: 6/16/2020 Format: Trade paperISBN: Print: 9781589485921 Digital: 9781589485938 Trim: 7.5 x 9 in.Price: Print: $94.99 USD Digital: $94.99 USD Pages: 490TABLE OF CONTENTSPrefaceForeword1 Get started with Web GIS2 Hosted feature layers and storytelling with GIS3 Web AppBuilder for ArcGIS and ArcGIS Experience Builder4 Mobile GIS5 Tile layers and on-premises Web GIS6 Spatial temporal data and real-time GIS7 3D web scenes8 Spatial analysis and geoprocessing9 Image service and online raster analysis10 Web GIS programming with ArcGIS API for JavaScriptPinde Fu | Interview with Esri Press | 2020-07-10 | 15:56 | Link.

This is a collection of all GPS- and computer-generated geospatial data specific to the Alpine Treeline Warming Experiment (ATWE), located on Niwot Ridge, Colorado, USA. The experiment ran between 2008 and 2016, and consisted of three sites spread across an elevation gradient. Geospatial data for all three experimental sites and cone/seed collection locations are included in this package. ––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––––– Geospatial files include cone collection, experimental site, seed trap, and other GPS location/terrain data. File types include ESRI shapefiles, ESRI grid files or Arc/Info binary grids, TIFFs (.tif), and keyhole markup language (.kml) files. Trimble-imported data include plain text files (.txt), Trimble COR (CorelDRAW) files, and Trimble SSF (Standard Storage Format) files. Microsoft Excel (.xlsx) and comma-separated values (.csv) files corresponding to the attribute tables of many files within this package are also included. A complete list of files can be found in this document in the “Data File Organization” section in the included Data User's Guide. Maps are also included in this data package for reference and use. These maps are separated into two categories, 2021 maps and legacy maps, which were made in 2010. Each 2021 map has one copy in portable network graphics (.png) format, and the other in .pdf format. All legacy maps are in .pdf format. .png image files can be opened with any compatible programs, such as Preview (Mac OS) and Photos (Windows). All GIS files were imported into geopackages (.gpkg) using QGIS, and double-checked for compatibility and data/attribute integrity using ESRI ArcGIS Pro. Note that files packaged within geopackages will open in ArcGIS Pro with “main.” preceding each file name, and an extra column named “geom” defining geometry type in the attribute table. The contents of each geospatial file remain intact, unless otherwise stated in “niwot_geospatial_data_list_07012021.pdf/.xlsx”. This list of files can be found as an .xlsx and a .pdf in this archive. As an open-source file format, files within gpkgs (TIFF, shapefiles, ESRI grid or “Arc/Info Binary”) can be read using both QGIS and ArcGIS Pro, and any other geospatial softwares. Text and .csv files can be read using TextEdit/Notepad/any simple text-editing software; .csv’s can also be opened using Microsoft Excel and R. .kml files can be opened using Google Maps or Google Earth, and Trimble files are most compatible with Trimble’s GPS Pathfinder Office software. .xlsx files can be opened using Microsoft Excel. PDFs can be opened using Adobe Acrobat Reader, and any other compatible programs. A selection of original shapefiles within this archive were generated using ArcMap with associated FGDC-standardized metadata (xml file format). We are including these original files because they contain metadata only accessible using ESRI programs at this time, and so that the relationship between shapefiles and xml files is maintained. Individual xml files can be opened (without a GIS-specific program) using TextEdit or Notepad. Since ESRI’s compatibility with FGDC metadata has changed since the generation of these files, many shapefiles will require upgrading to be compatible with ESRI’s latest versions of geospatial software. These details are also noted in the “niwot_geospatial_data_list_07012021” file.

This dataset contains a GIS database of Aids to Navigation in the Gulf of Mexico and coastal waters of Alabama, Florida, Louisiana, Mississippi and Texas. These data were compiled on 1999-10-21. The term "Aids to Navigation" (ATONS or AIDS) refers to a device outside of a vessel used to assist mariners in determining their position or safe course, or to warn them of obstructions. AIDS to navigation include lighthouses, lights, buoy, sound signals, landmarks, RACONs, radio beacons, LORAN, and omega. These include AIDS which are installed and maintained by the Coast Guard as well as privately installed and maintained aids (permit required). This does not include unofficial AIDS (illegal) such as stakes, PVC pipes, and such placed without permission. Each USCG District Headquarters is responsible for updating their database on an "as needed" basis. When existing AIDS are destroyed or relocated and new AIDS are installed the database is updated. Each AID is assigned an official "light listing number". The light list is a document listing the current status of ATONS and it is published and distributed on a regular basis. Interim changes to the light list are published in local Notices to Mariners which are the official means which navigators are supposed to keep their charts current. In addition, the USCG broadcasts Notices to Mariners on the marine band radio as soon as changes of the status of individual AIDS are reported. The light list number and local Notices to Mariners reports are suggested ways to keep the database current on a regular or even "real time" basis. However, annual (or more frequent) updates of the entire dataset may be obtained from each USCG District Headquarters. Geographic Information System (GIS) software is required to display the data in this NCEI accession.

Snapshot img

What is the GIS In Utility Industry Market Size?

The GIS market in the utility industry size is forecast to increase by USD 3.55 billion at a CAGR of 19.8% between 2023 and 2028. Market expansion hinges on various factors, such as the rising adoption of Geographic Information System (GIS) solutions in the utility sector, the convergence of GIS with Building Information Modeling, and the fusion of Augmented Reality with GIS technology. These elements collectively drive market growth, reflecting advancements in spatial data analytics and technological convergence. The increased adoption of GIS solutions in the utility industry underscores the importance of geospatial data in optimizing infrastructure management. Simultaneously, the integration of GIS with BIM signifies the synergy between spatial and building information for enhanced project planning and management. Additionally, the integration of AR with GIS technology highlights the potential for interactive and interactive visualization experiences in spatial data analysis. Thus, the interplay of these factors delineates the landscape for the anticipated expansion of the market catering to GIS and related technologies.

What will be the size of Market during the forecast period?

Request Free GIS In Utility Industry Market Sample

Market Segmentation

The market research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019 - 2023 for the following segments.

Product

  Software
  Data
  Services


Deployment

  On-premises
  Cloud


Geography

  North America

    Canada
    US


  Europe

    Germany
    France


  APAC

    China
    India
    Japan


  Middle East and Africa



  South America

    Brazil

Which is the largest segment driving market growth?

The software segment is estimated to witness significant growth during the forecast period. In the utility industry, the spatial context of geographic information systems (GIS) plays a pivotal role in site selection, land acquisition, planning, designing, visualizing, building, and project management. Utilities, including electricity, gas, water, and telecommunications providers, leverage GIS software to efficiently manage their assets and infrastructure. This technology enables the collection, management, analysis, and visualization of geospatial data, derived from satellite imaging, aerial photography, remote sensors, and artificial intelligence. Geospatial AI, sensor technology, and digital reality solutions are integral components of GIS, enhancing capabilities for smart city planning, urban planning, water management, mapping systems, grid modernization, transportation, and green buildings.

Get a glance at the market share of various regions. Download the PDF Sample

The software segment was valued at USD 541.50 million in 2018. Moreover, the geospatial industry continues to evolve, with startups and software solutions driving innovation in hardware, smart city planning, land use management, smart infrastructure planning, and smart utilities. GIS solutions facilitate 4D visualization, enabling stakeholders to overcome geospatial data barriers and make informed decisions. The utility industry's reliance on GIS extends to building information modeling, augmented reality, and smart urban planning, ultimately contributing to the growth of the geospatial technology market.

Which region is leading the market?

For more insights on the market share of various regions, Request Free Sample

North America is estimated to contribute 37% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.

How do company ranking index and market positioning come to your aid?

Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.

AABSyS IT Pvt. Ltd. - The company offers GIS solutions such as remote sensing and computer aided design and drafting solutions for electric and gas utility.

Technavio provides the ranking index for the top 20 companies along with insights on the market positioning of:

AABSyS IT Pvt. Ltd.
Autodesk Inc.
Avineon Inc.
Bentley Systems Inc.
Blue Marble Geographics
Cadcorp Ltd.
Caliper Corp.
Environmental Systems Research Institute Inc.
General Electric Co.
Hexagon AB
Mapbox Inc.
Maxar Technologies Inc.
Mobile GIS Services Ltd.
NV5 Global Inc.
Orbital Insight Inc.
Pitney Bowes Inc.
Schneider Electric SE
SuperMap Software Co. Ltd.
Trimble Inc.
VertiGIS Ltd.

Explore our company rankings and market positioning. Request Free Sample

How can Technavio assist you in ma

DNRGPS is an update to the popular DNRGarmin application. DNRGPS and its predecessor were built to transfer data between Garmin handheld GPS receivers and GIS software.

DNRGPS was released as Open Source software with the intention that the GPS user community will become stewards of the application, initiating future modifications and enhancements.

DNRGPS does not require installation. Simply run the application .exe

See the DNRGPS application documentation for more details.

Compatible with: Windows XP, Windows 7, Windows 8, and Windows 10, ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

Limited Compatibility: Interactions with ArcMap layer files and ArcMap graphics are no longer supported. Instead use shapefile or geodatabase.

Prerequisite: .NET 4 Framework

DNR Data and Software License Agreement

Subscribe to the DNRGPS announcement list to be notified of upgrades or updates.

Debris Basins are key components of the Los Angeles County Flood Control District's (LACFCD) flood control system. Typically located at the mouths of canyons, debris basins capture sediment, gravel, boulders, and vegetative debris that are washed out of the canyons during storms, protection lower lying communities from possible flooding and property damage. Due to the transitory changes in capacity and sediment, the DPW only provides point locations of its debris basins data. More information on dams and debris basins are available from the Los Angeles County Department of Pubic Works' Sediment Management website.Download Data:Debris BasinsDamsUsing GIS Data on this siteGIS data downloaded from this site generally requires GIS software to view. Click here for a list of GIS Data Viewers

The term Aids to Navigation (ATONS or AIDS) refers to a device outside of a vessel used to assist mariners in determining their position or safe course, or to warn them of obstructions. AIDS to navigation include lighthouses, lights, buoy, sound signals, landmarks, racons, radio beacons, LORAN, and omega. These include AIDS which are installed and maintained by the Coast Guard as well as privately installed and maintained aids (permit required). This does not include unofficial AIDS (illegal) such as stakes, PVC pipes, and such placed without permission.

This data set is not certified for navigation and is not intended to be used for navigation purposes.

Each USCG District Headquarters is responsible for updating their database on an 'as needed' basis. When existing AIDS are destroyed or relocated and new AIDS are installed the database is updated. Each AID is assigned an official 'light listing number'. The light list is a document listing the current status of ATONS and it is published and distributed on a regular basis. Interim changes to the light list are published in local Notices to Mariners which are the official means which navigators are supposed to keep their charts current. In addition, the USCG broadcasts Notices to Mariners on the marine band radio as soon as changes of the status of individual AIDS are reported. The light list number and local Notices to Mariners reports are suggested ways to keep the database current on a regular or even 'real time' basis. However, annual (or more frequent) updates of the entire dataset may be obtained from each USCG District Headquarters.

Geographic Information System (GIS) software is required to display the data in this NODC accession.

File List bathymetry_30s.7z (MD5: dd855211bbcdee7d6862414da23d6da2) biogeo01_07_30s.7z (MD5: 396525db0abd9de2ede3d8fdeb15e8ee) biogeo08_17_30s.7z (MD5: 96c2417eed84e85f9896536b934c53e1) Monthly_Variables_30s.7z (MD5: 89016a8d17e8d8a1dddef0a121a83f5d)

     Additional high resolution raster files:

Sea_Ice_30s.7z (MD5: 547d355294c530f63b9b0a73dedd2f3a)

     Low resolution MARSPEC data files:

MARSPEC_2o5m.7z (MD5: 923c97d185adb0c72f158a84e2981391) MARSPEC_5m.7z (MD5: 95f7c3739c4f2889c2eff18afeffa489) MARSPEC_10m.7z (MD5: d91f3127f46f7004d116f14328bf4b71) Description Ecological niche models are widely used in terrestrial studies to address critical ecological and evolutionary questions related to past and future climate change, local adaptation and speciation, the discovery of rare endemics, and biological invasions. However the application of niche models to similar questions in marine ecosystems has lagged behind, in part due to the lack of a centralized high-resolution spatial data set representing both benthic and pelagic marine environments. Here we describe the creation of MARSPEC, a high-resolution GIS database of ocean climate layers intended for marine ecological niche modeling and other applications in marine spatial ecology. MARSPEC combines information related to topographic complexity of the seafloor with bioclimatic measures of sea surface temperature and salinity for the world ocean. We derived seven geophysical variables from a high-resolution raster grid representing depth of the seafloor (bathymetry) to characterize six facets of topographic complexity (east-west and north-south components of aspect, slope, concavity of the seafloor, and plan and profile curvature) and distance from shore. We further derived 10 bioclimatic variables describing the annual mean, range, variance and extreme values for temperature and salinity from long-term monthly climatological means obtained from remotely sensed and in situ oceanographic observations. All variables were clipped to a common land mask, interpolated to a nominal 1-km (30 arc-second) grid, and converted to an ESRI raster grid file format compatible with popular GIS programs. MARSPEC is a 10-fold improvement in spatial resolution over the next-best data set (Bio-ORACLE) and is the only high-resolution global marine data set to combine variables from the benthic and pelagic environments into a single database. Additionally, we provide the monthly climatological layers used to derive the bioclimatic variables, allowing users to calculate equivalent MARSPEC variables from anomaly data for past and future climate scenarios. A detailed description of GIS processing steps required to calculate the MARSPEC variables can be found in the metadata.

      Key words: climate change; ecological niche modeling; GIS; marine spatial ecology; ocean climate; salinity; sea surface temperature; species distribution modeling.

This resource contains the test data for the GeoServer OGC Web Services tutorials for various GIS applications including ArcGIS Pro, ArcMap, ArcGIS Story Maps, and QGIS. The contents of the data include a polygon shapefile, a polyline shapefile, a point shapefile, and a raster dataset; all of which pertain to the state of Utah, USA. The polygon shapefile is of every county in the state of Utah. The polyline is of every trail in the state of Utah. The point shapefile is the current list of GNIS place names in the state of Utah. The raster dataset covers a region in the center of the state of Utah. All datasets are projected to NAD 1983 Zone 12N.

Mapping of deicing material storage facilities in the Lake Champlain Basin was conducted during the late fall and winter of 2022-23. 126 towns were initially selected for mapping (some divisions within the GIS towns data are unincorporated “gores”). Using the list of towns, town clerk contact information was obtained from the Vermont Secretary of State’s website, which maintains a database of contact information for each town.Each town was contacted to request information about their deicing material storage locations and methods. Email and telephone scripts were developed to briefly introduce the project and ask questions about the address of any deicing material storage locations in the town, type of materials stored at each site, duration of time each site has been used, whether materials on site are covered, and the type of surface the materials are stored on, if any. Data were entered into a geospatial database application (Fulcrum). Information was gathered there and exported as ArcGIS file geodatabases and Comma Separated Values (CSV) files for use in Microsoft Excel. Data were collected for 118 towns out of the original 126 on the list (92%). Forty-three (43) towns reported that they are storing multiple materials types at their facilities. Four (4) towns have multiple sites where they store material (Dorset, Pawlet, Morristown, and Castleton). Of these, three (3) store multiple materials at one or both of their sites (Pawlet, Morristown, and Castleton). Where towns have multiple materials or locations, the record information from the overall town identifier is linked to the material stored using a unique ‘one-to-many’ identifier. Locations of deicing material facilities, as shown in the database, were based on the addresses or location descriptions provided by town staff members and was verified only using the most recent aerial imagery (typically later than 2018 for all towns). Locations have not been field verified, nor have site conditions and infrastructure or other information provided by town staff.Dataset instructions:The dataset for Deicing Material Storage Facilities contains two layers – the ‘parent’ records titled ‘salt_storage’ and the ‘child’ records titled ‘salt_storage_record’ with attributes for each salt storage site. This represents a ‘one-to-many’ data structure. To see the attributes for each salt storage site, the user needs to Relate the data. The relationship can be accomplished in GIS software. The Relate needs to be built on the following fields:‘salt_storage’: ‘fulcrum_id’‘salt_storage_record: ‘fulcrum_parent_id’This will create a one-to-many relationship between the geographic locations and the attributes for each salt storage site.

This physical structures points feature class represents current wastewater information in the City of Los Angeles. The maintenance hole structure is used to provide access to the sewer from the surface. The Mapping and Land Records Division of the Bureau of Engineering, Department of Public Works provides the most rigorous geographic information of the sanitary sewer system using a geometric network model, to ensure that its sewers reflect current ground conditions. The sanitary sewer system, pump plants, wyes, maintenance holes, and other structures represent the sewer infrastructure in the City of Los Angeles. Wye and sewer information is available on NavigateLA, a website hosted by the Bureau of Engineering, Department of Public Works.Associated information about the wastewater Physical_structure is entered into attributes. Principal attributes include:JUNCTION_SUBTYPE: junction subtype is the principal field that describes various types of points as either Diversion Structure, Drop or Drop Trap, Flush, Junction Chamber, Junction Structure, Maintenance, Offset, Other Structure, Siphon, Special Shallow, Special Structure, Terminal, Transition, Trap, Valve Vault, Weir. For a complete list of attribute values, please refer to (TBA Wastewater data dictionary). Wastewater Physical Structures points layer was created in geographical information systems (GIS) software to display the location of wastewater structures. The structures points layer is a feature class in the LACityWastewaterData.gdb Geodatabase dataset. The layer consists of spatial data as a points feature class and attribute data for the features. The points are entered manually based on wastewater sewer maps and BOE standard plans, and information about the points is entered into attributes. The physical structures points data layer differs from non-structures points data layer, such that physical structures points are maintenance holes. Reference the JUNCTION_SUBTYPE and MH_TYPE field for the type of structure. The STRUCTURE_ID field value is the unique ID. The wastewater structures points are inherited from a sewer spatial database originally created by the City's Wastewater program. The database was known as SIMMS, Sewer Inventory and Maintenance Management System. Structures information should only be added to the Wastewater Structures layer if documentation exists, such as a wastewater map approved by the City Engineer. Sewers plans and specifications proposed under private development are reviewed and approved by Bureau of Engineering. The Department of Public Works, Bureau of Engineering's, Brown Book (current as of 2010) outlines standard specifications for public works construction. For more information on sewer materials and structures, look at the Bureau of Engineering Manual, Part F, Sewer Design section, and a copy can be viewed at http://eng.lacity.org/techdocs/sewer-ma/f400.pdf. For more information on maintenance holes, a copy can be viewed at http://boemaps.eng.ci.la.ca.us/reports/pdf/s140-0_std_pl.pdf.List of Fields:SERVICEID: User-defined unique feature number that is automatically generated.OBJECTID: Internal feature number.FACILITY_NO: This field is currently not being edited.ENG_DIST: LA City Engineering District. The boundaries are displayed in the Engineering Districts index map. Values: • W - West LA Engineering District. • H - Harbor Engineering District. • C - Central Engineering District. • V - Valley Engineering District.CNCL_DIST: LA City Council District. Values: • (numbers 1-15) - Current City Council Member for that District can be found on the mapping website http://navigatela.lacity.org/index.cfm, click Council Districts layer name, under Boundaries layer group.CRTN_DT: Creation date of the point feature.MDIST: This value is the maintenance district identifier. Bureau of Sanitation needs to provide BOE with updated definitions. This field is currently not being edited.LAT: The value is the latitude coordinate of the point.USER_ID: The name of the user carrying out the edits of the structure data.LON: The value is the longitude coordinate of the point.NAME: This field is currently not being edited.VDATUM: This is the year of the standard plan, which contains the information the user enters into pipe data.MHMATERIAL: The value is the material that the structure is made from. This information is not specified on the standard plan. Values: • UNK - Unknown. • RCP - Reinforced Concrete Pipe. • CSP - Corrugated Steel Pipe. • CIPC - Cast in place concrete. • C - Concrete. • BRK - Brick. • PRC - Precast Reinforced Concrete. • B - Brick. • CON - Concrete. • VCP - Vitrified Clay Pipe. • O - Other. • P - Plastic.BLKNO: The value is the block number of the street on which the physical structure is located.STREET2: The value is the cross street name on which the physical structure hole is located, if applicable.COVERDIAM: The value diameter of the physical structure cover expressed in feet.BARRELDIAM: The value diameter of the inside of the physical structure expressed in feet.STATUS: This value is the active or inactive status of the structure. Values: • ABAN - Proposed Inactive. • PROP_ACT - Proposed Active. • INACT - Inactive. • ACT - Active. • ABAN - Abandoned.SEQ: The value is the sequence number of the maintenance hole.SHAPE: Feature geometry.STREET1: The value is the street name on which the physical structure is located.MH_BASE: The value is the non-structure base, used by Bureau of Sanitation to describe the direction of flow at the intersection of a pipe and a non-structure. Values: • F - F. • B - B. • G - G. • H - H. • Q - Q.MH_TYPE: The value signifies the maintenance hole type or other structure type. Values: • DMH - Drop Maintenance Hole. • CFS - Confluence Structure. • DMT - Drop trap Maintenance Hole. • ABN - Abandoned. • BPS - Bypass Structure. • DI - Diversion Structure. • SH - Shallow Maintenance Hole. • OMH - Offset Maintenance Hole. • RV - Relief Valve. • SIP - Siphon. • VV - Valve vault. • LH - Lamp Hole. • FL - Flush Station. • GV - Gate Valve. • TRP - Trap maintenance hole. This type of structure is used to prevent sewer gases from flowing upstream in the sewer line. • HD - Transition. • TRS - Transition structure. • FT - Flush Tank. • WMH - Weir maintenance hole. This type of structure is used to gauge sewer flows. Automatic recording devices may be installed for flow measurement. • INA - Inactive. • MH - Maintenance Hole. • OTH - Other structure. • FS - Flush Station. • WW - Wet well. • JT - Junction Chamber Trap. • JC - Junction Chamber. • PMH - Pressure Maintenance Hole. • PS - Pump Station. • FMH - Flush Maintenance Hole. • TMH - Terminal maintenance hole. • GS - Gauging Structure. • JS - Junction Structure.LID_ELEV: The value is the lid elevation of the structure, in decimal feet.BASIN: The value is basin number.OWNER: This value is the agency or municipality that constructed the physical structure. Values: • CTY - City of LA. • FED - Federal Facilities. • OUTLA - Adjoining cities. • COSA - LA County Sanitation. • PVT - Private.COMMENTS: This attribute contains comments of structures and structure status.MH_DEPTH: The value is the depth of the physical structure expressed in decimal feet.JUNCTION_SUBTYPE: The value is the type of physical structure. Values: • 1 - Maintenance. • 4 - Offset. • 15 - Valve Vault. • 6 - Diversion Structure. • 8 - Flush. • 9 - Junction Chamber. • 5 - Trap. • 7 - Special Shallow. • 3 - Terminal. • 10 - Siphon. • 13 - Junction Structure. • 16 - Transition. • 2 - Drop or Drop Trap. • 11 - Weir. • 12 - Special Structure. • 14 - Other Structure.LAST_UPDATE: Date of last update of the point feature.YEAR_INST: This is the year of the structure installation.ROUTE: The value is the sewer maintenance route number.ADDRESS: This field is currently not being edited.ENABLED: Internal feature number.STRUCTURE_ID: The value is the ID of the structure. It could be either the value from the UP_STRUCT or DN_STRUCT fields. This point is the structure that may be a maintenance hole, junction, siphon, etc. The field STRUCTURE_ID is a key attribute to relate the physical structures feature class to the UP_MH field or the DN_MH field in pipe lines feature class.ASSETID: User-defined unique feature number that is automatically generated.

Tool and data set of road networks for 80 of the most populated urban areas in the world. The data consist of a graph edge list for each city and two corresponding GIS shapefiles (i.e., links and nodes).Make your own data with our ArcGIS, QGIS, and python tools available at: http://csun.uic.edu/codes/GISF2E.htmlPlease cite: Karduni,A., Kermanshah, A., and Derrible, S., 2016, "A protocol to convert spatial polyline data to network formats and applications to world urban road networks", Scientific Data, 3:160046, Available at http://www.nature.com/articles/sdata201646

OUTDATED. See the current data at https://data.cityofchicago.org/d/fwns-qqic -- To view or use these files, compression software and special GIS software, such as ESRI ArcGIS, is required. To download, right-click the "Download" link above and choose "Save link as." This version of the data was posted 8/8/2012 and stayed live until 7/16/2015, when it was replaced with the list of aldermen inaugurated 5/18/2015, after allowing time for most office space arrangements to be finalized.

Abstract

The dataset is a geodatabase focusing on the distribution of freshwater fish species in Northern Greece. The study area encompasses various lakes and rivers within the regions of Thrace, Eastern, Central, and Western Macedonia, and Epirus. It classifies fish species into three categories based on their conservation status according to the IUCN Red List: Critically Endangered, Endangered, and Vulnerable. The data analysis reveals that the study area is characterized by high fish diversity, particularly in certain ecosystems such as the Evros River, Strymonas River, Aliakmonas River, Axios River, Volvi Lake, Nestos River, and Prespa Lake. These ecosystems serve as important habitats for various fish species. Mapping of the dataset shows the geographic distribution of threatened fish species, indicating that Northern Greece is a hotspot for species facing extinction risks. Overall, the dataset provides valuable insights for researchers, policymakers, and conservationists in understanding the status of fish fauna in Northern Greece and developing strategies for the protection and preservation of these important ecosystems.

Methods

Data Collection: The dataset was collected through a combination of field surveys, literature reviews, and the compilation of existing data from various reliable sources. Here's an overview of how the dataset was collected and processed:

• Freshwater Fishes and Lampreys of Greece: An Annotated Checklist
• The Red Book of Endangered Animals of Greece
• The "Red List of Threatened Species"
• The study "Monitoring and Evaluation of the Conservation Status of Fish Fauna Species of Community Interest in Greece"
• The international online fish database FishBase

Data Digitization and Georeferencing: To create a comprehensive database, we digitized and georeferenced the collected data from various sources. This involved converting information from papers, reports, and surveys into digital formats and associating them with specific geographic coordinates. Georeferencing allowed us to map the distribution of fish species within the study area accurately.

Data Integration: The digitized and georeferenced data were then integrated into a unified geodatabase. The geodatabase is a central repository that contains both spatial and descriptive data, facilitating further analysis and interpretation of the dataset.

Data Analysis: We analyzed the collected data to assess the distribution of fish species in Northern Greece, evaluate their conservation status according to the IUCN Red List categories, and identify the threats they face in their respective ecosystems. The analysis involved spatial mapping to visualize the distribution patterns of threatened fish species.

Data Validation: To ensure the accuracy and reliability of the dataset, we cross-referenced the information from different sources and validated it against known facts about the species and their habitats. This process helped to eliminate any discrepancies or errors in the dataset.

Interpretation and Findings: Finally, we interpreted the analyzed data and derived key findings about the diversity and conservation status of freshwater fish species in Northern Greece. The results were presented in the research paper, along with maps and visualizations to communicate the spatial patterns effectively.

Overall, the dataset represents a comprehensive and well-processed collection of information about fish fauna in the study area. It combines both spatial and descriptive data, providing valuable insights for understanding the distribution and conservation needs of freshwater fish populations in Northern Greece.

Usage notes

The data included with the submission is stored in a geodatabase format, specifically an ESRI Geodatabase (.gdb). A geodatabase is a container that can hold various types of geospatial data, including feature classes, attribute tables, and raster datasets. It provides a structured and organized way to store and manage geographic information.

To open and work with the geodatabase, you will need GIS software that supports ESRI Geodatabase formats. The primary software for accessing and manipulating ESRI Geodatabases is ESRI ArcGIS, which is a proprietary GIS software suite. However, there are open-source alternatives available that can also work with Geodatabase files.

Open-source software such as QGIS has support for reading and interacting with Geodatabase files. By using QGIS, you can access the data stored in the geodatabase and perform various geospatial analyses and visualizations. QGIS is a powerful and widely used open-source Geographic Information System that provides similar functionality to ESRI ArcGIS.

For tabular data within the geodatabase, you can export the tables as CSV files and open them with software like Microsoft Excel or the open-source alternative, LibreOffice Calc, for further analysis and manipulation.

Overall, the data provided in the submission is in a geodatabase format, and you can use ESRI ArcGIS or open-source alternatives like QGIS to access and work with the geospatial data it contains.

The web-posted Alaska Shore Station Database is a compilation of hundreds of intertidal sites that were visited and evaluated throughout the coastal waters of Alaska. At each station attempts are made to document all observed species and their assemblages, geomorphic features, measurements of beach length and slope, and gather photographic examples. This online database has been designed to integrate with the spatially explicit, Alaska ShoreZone web enabled GIS platform. The end result is a user friendly and accessible version of the Shore Station database with a queryable display of station locations, downloadable species lists and photos.

This dataset is of simplified geometries from COD live services deployed August 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx

This dataset includes buildings and districts in Chicago which are listed on the National Register of Historic Places (NRHP) or designated as National Historic Landmarks (NHL). The NRHP is the official list of the Nation's historic places worthy of preservation; NHLs are nationally significant historic places designated by the Secretary of the Interior because they possess exceptional value or quality in illustrating or interpreting the heritage of the United States. The NRHP and NHL programs are federally-established and are administered by the National Park Service (www.nps/gov/nr) and the Illinois Historic Preservation Agency (IHPA, www.illinoishistory.gov/). This dataset is provided by the City of Chicago based on NRHP and NHL nominations provided by IHPA. To view or use these shapefiles, compression software and special GIS software, such as ESRI ArcGIS or QGIS, is required. To download this file, right-click the "Download" link above and choose "Save link as." Time Period: Data is current as of June 2012. Update Frequency: Data is updated as needed.

This dataset is of simplified geometries from COD live services deployed June 2019. Simplification methods applied from ESRI libraries using Python, Node.js and Mapshaper.js and based on adapted procedures for best outcomes preserving shape, topology and attributes. These data are not a substitute for the original COD data sets used in GIS applications. No warranties of any kind are made for any purpose and this dataset is offered as-is. Versions of topojson, kml and csv are also available. For a list of other simplified CODs see the address list: https://github.com/UGA-ITOSHumanitarianGIS/mapservicedoc/raw/master/Data/AWSDeploymentURLlist.xlsx