Meet Earth EngineGoogle Earth Engine combines a multi-petabyte catalog of satellite imagery and geospatial datasets with planetary-scale analysis capabilities and makes it available for scientists, researchers, and developers to detect changes, map trends, and quantify differences on the Earth's surface.SATELLITE IMAGERY+YOUR ALGORITHMS+REAL WORLD APPLICATIONSLEARN MOREGLOBAL-SCALE INSIGHTExplore our interactive timelapse viewer to travel back in time and see how the world has changed over the past twenty-nine years. Timelapse is one example of how Earth Engine can help gain insight into petabyte-scale datasets.EXPLORE TIMELAPSEREADY-TO-USE DATASETSThe public data archive includes more than thirty years of historical imagery and scientific datasets, updated and expanded daily. It contains over twenty petabytes of geospatial data instantly available for analysis.EXPLORE DATASETSSIMPLE, YET POWERFUL APIThe Earth Engine API is available in Python and JavaScript, making it easy to harness the power of Google’s cloud for your own geospatial analysis.EXPLORE THE APIGoogle Earth Engine has made it possible for the first time in history to rapidly and accurately process vast amounts of satellite imagery, identifying where and when tree cover change has occurred at high resolution. Global Forest Watch would not exist without it. For those who care about the future of the planet Google Earth Engine is a great blessing!-Dr. Andrew Steer, President and CEO of the World Resources Institute.CONVENIENT TOOLSUse our web-based code editor for fast, interactive algorithm development with instant access to petabytes of data.LEARN ABOUT THE CODE EDITORSCIENTIFIC AND HUMANITARIAN IMPACTScientists and non-profits use Earth Engine for remote sensing research, predicting disease outbreaks, natural resource management, and more.SEE CASE STUDIESREADY TO BE PART OF THE SOLUTION?SIGN UP NOWTERMS OF SERVICE PRIVACY ABOUT GOOGLE

The Bikeshare dataset was compiled on June 30, 2025 and was updated September 17, 2025 from the Bureau of Transportation Statistics (BTS) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The bikeshare layer shows the location of all bikeshare docking stations, along with their address if known and the city and state it is located in. Prior to April 30, 2025, this bikeshare layer reflected the bikeshare stations available for the latest Intermodal Passenger Connectivity Database (IPCD) data collection along with intermodal passenger connectivity information. To provide this timelier snapshot of bikeshare stations, the Bureau of Transportation Statistics is no longer including connectivity information. To obtain the previously provided IPCD Bikeshare layer on NTAD for the latest only bikeshare year that included connectivity information, query the current IPCD layer on NTAD (https://doi.org/10.21949/1522239) using the query where the “BIKE_SHARE” field is equal to 1, signifying that bikeshare service is provided at that location. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529012

This dataset comes from the Annual Community Survey question related to satisfaction with the quality of the city’s online services. Respondents are asked to provide their level of satisfaction related to “Tempe's online services (registration, payment, etc.)” on a scale of 5 to 1, where 5 means "Very Satisfied" and 1 means "Very Dissatisfied" (without "don't know" as an option).The survey is mailed to a random sample of households in the City of Tempe and has a 95% confidence level.This page provides data for the Online Service Satisfaction performance measure. The performance measure dashboard is available at 2.05 Online Services Satisfaction Rate. Additional Information Source: Community Attitude Survey ( Vendor: ETC Institute)Contact: Wydale HolmesContact E-Mail: Wydale_Holmes@tempe.govData Source Type: Excel and PDFPreparation Method: Extracted from Annual Community Survey results  Publish Frequency: Annual  Publish Method: Manual  Data Dictionary

This resource was created by Esri Canada Education and Research. To browse our full collection of higher-education learning resources, please visit https://hed.esri.ca/resourcefinder/.This tutorial introduces you to using Python code in a Jupyter Notebook, an open source web application that enables you to create and share documents that contain rich text, equations and multimedia, alongside executable code and visualization of analysis outputs. The tutorial begins by stepping through the basics of setting up and being productive with Python notebooks. You will be introduced to ArcGIS Notebooks, which are Python Notebooks that are well-integrated within the ArcGIS platform. Finally, you will be guided through a series of ArcGIS Notebooks that illustrate how to create compelling notebooks for data science that integrate your own Python scripts using the ArcGIS API for Python and ArcPy in combination with thousands of open source Python libraries to enhance your analysis and visualization.To download the dataset Labs, click the Open button to the top right. This will automatically download a ZIP file containing all files and data required.You can also clone the tutorial documents and datasets for this GitHub repo: https://github.com/highered-esricanada/arcgis-notebooks-tutorial.git.Software & Solutions Used: Required: This tutorial was last tested on August 27th, 2024, using ArcGIS Pro 3.3. If you're using a different version of ArcGIS Pro, you may encounter different functionality and results.Recommended: ArcGIS Online subscription account with permissions to use advanced Notebooks and GeoEnrichmentOptional: Notebook Server for ArcGIS Enterprise 11.3+Time to Complete: 2 h (excludes processing time)File Size: 196 MBDate Created: January 2022Last Updated: August 27, 2024

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. Created for the January 2016 Map of the Month. Data researched by OC-GIS team and hosted in ArcGIS Online.

The Dams dataset is a representation of the National Inventory of Dams (NID), maintained and published by the U.S. Army Corps of Engineers, in cooperation with the Association of State Dam Safety Officials, the states, territories, and federal agencies. It is also part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The Dams dataset (NID) includes all known dams of the United States and its territories, that meet the federal definition of a dam. Dams where downstream flooding would likely result in loss of human life (high hazard potential). Dams where downstream flooding would likely result in disruption of access to critical facilities, damage to public and private facilities, and require difficult mitigation efforts (significant hazard potential). Dams that meet minimum height and reservoir size requirements, even though they do not pose the same level of life or economic risk as those above - these low hazard potential dams equal or exceed 25 feet in height and exceed 15 acre-feet in storage, or equal or exceed 50 acre-feet storage and exceed 6 feet in height. The database contains more than 70 data fields for each dam. This includes the dam's location, size, purpose, type, last inspection, and regulatory facts. The information is updated periodically by the state and federal agencies, reflected by the "Data Last Updated Date". For more information on dams, visit the NID web site at https://nid.sec.usace.army.mil/#. A data dictionary, or other source of attribute information, is accessible at https://doi.org/10.21949/1529016

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. Locations that offer multiple Winter Activities. Created for the January 2016 Map of the Month. Data researched by OC-GIS team and hosted in ArcGIS Online.

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. Created for the January 2016 Map of the Month. Data researched by Oakland County GIS team and hosted in ArcGIS Online.Wikipedia: Sledding

This data supports the 1.05 Feeling of Safety in Your Neighborhood and 2.06 Police Trust Score performance measures.This data is the result of a community survey of approximately 500 residents collected electronically and monthly by Zencity on behalf of Tempe Police Department. The scores are provided to TPD monthly in PDF form, and are then transferred to Excel for Open Data. The trust score is a 0 to 100 measure, and is a combination of two questions: How much do you agree with this statement? Trust-Respect: The police in my neighborhood treat people with respect. How much do you agree with this statement? Trust-Listen: The police in my neighborhood listen to and take into account the concerns of local residents.The safety score is a 0 to 100 measure, and scores residents' feelings of safety in their neighborhood.The performance measure pages are available at 1.05 Feeling of Safety in Your Neighborhood and 2.06 Police Trust Score.Additional InformationSource: ZencityContact (author): Carlena OroscoContact E-Mail (author): Carlena_Orosco@tempe.gov Contact (maintainer): Carlena OroscoContact E-Mail (maintainer): Carlena_Orosco@tempe.gov Data Source Type: Zencity REST APIPreparation Method: This data is from a citizen survey collected monthly by Zencity and provided in an automated survey feed to the City of Tempe.Publish Frequency: MonthlyPublish Method: Zencity REST API Automated Survey Feed Updates ArcGIS Online feature layer.Data Dictionary

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. Created for the January 2016 Map of the Month. Data researched by Oakland County GIS team and hosted in ArcGIS Online.Wikipedia: Toboggan

RTB Maps is a cloud-based electronic Atlas. We used ArGIS 10 for Desktop with Spatial Analysis Extension, ArcGIS 10 for Server on-premise, ArcGIS API for Javascript, IIS web services based on .NET, and ArcGIS Online combining data on the cloud with data and applications on our local server to develop an Atlas that brings together many of the map themes related to development of roots, tubers and banana crops. The Atlas is structured to allow our participating scientists to understand the distribution of the crops and observe the spatial distribution of many of the obstacles to production of these crops. The Atlas also includes an application to allow our partners to evaluate the importance of different factors when setting priorities for research and development. The application uses weighted overlay analysis within a multi-criteria decision analysis framework to rate the importance of factors when establishing geographic priorities for research and development. Datasets of crop distribution maps, agroecology maps, biotic and abiotic constraints to crop production, poverty maps and other demographic indicators are used as a key inputs to multi-objective criteria analysis www.rtb.cgiar.org/RTBMaps

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. Created for the January 2016 Map of the Month. Data researched by OC-GIS team and hosted in ArcGIS Online.

SafeGraph is just a data company. That's all we do.SafeGraph Places for ArcGIS is a subset of SafeGraph Places. SafeGraph Places is a points-of-interest (POI) dataset with business listing, building footprint, visitor insights, & foot-traffic data for every place people spend money in the U.S.The complete SafeGraph Places dataset has ~ 5.4 million points-of-interest in the USA and is updated monthly (to reflect store openings & closings).Here, for free on this listing, SafeGraph offers a subset of attributes from SafeGraph Places: POI business listing information and POI locations (building centroids).Columns in this dataset:safegraph_place_idparent_safegraph_place_idlocation_namesafegraph_brand_idsbrandstop_categorystreet_addresscitystatezip_codeNAICS codeGeometry Point data. Latitude and longitude of building centroid.For data definitions and complete documentation visit SafeGraph Developer and Data Scientist Docs.For statistics on the dataset, see SafeGraph Places Summary Statistics.Data is available as a hosted Feature Service to easily integrate with all ESRI products in the ArcGIS ecosystem.Want More? Want this POI data for use outside of ArcGIS Online? Want POI data for Canada? Want POI building footprints (Geometry)?Want more detailed category information (Core Places)?Want phone numbers or operating hours (Core Places)?Want POI visitor insights & foot-traffic data (Places Patterns)?To see more, preview & download all SafeGraph Places, Patterns, & Geometry data from SafeGraph’s Data Bar.Or drop us a line! Your data needs are our data delights. Contact: support-esri@safegraph.comView Terms of Use

A copy of located in editsde for backup purposes. The dataset includes approximate flood-hazard boundary areas prepared by both detailed and approximate methods. Study limits were defined using the highlighted drainage-problem areas shown on the city's zoning base maps as a guide. Floodplain studies completed and sealed in 2007 and 2008 . Shape files created April 2011. Shape files exported from Autodesk Map 3D 2006 and projected using ArcMap 10. Maintenance and frequency to be determined by City of Tucson, Planning and Development ServicesReplace feature class "dsdFHZStudy2007CrossSections" See feature class "cotFloodHazardsPurposeLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Dataset ClassificationLevel 0 - OpenKnown UsesThis layer is intended to be used in the Open Data portal and not for regular use in ArcGIS Online and ArcGIS Enterprise.Known ErrorsLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Data ContactLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.Update FrequencyLorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua.

The Maryland Department of Information Technology has identified a variety of authoritative State provided sources containing State facilities and have compiled them into a single stacked point dataset. The dataset contains facilities for every Maryland State agency.This is a MD iMAP hosted service layer. Find more information at https://imap.maryland.gov.Feature Service Layer Link:https://mdgeodata.md.gov/imap/rest/services/Structure/MD_StateFacilities/FeatureServer/0

Polygon delineation of Maryland oyster harvest reserves created by MDNR, Fisheries Service. COMAR 08.02.04.13 is the source document for the features in this dataset.This is a MD iMAP hosted service. Find more information at https://imap.maryland.gov.Feature Service Link:https://mdgeodata.md.gov/imap/rest/services/Biota/MD_Shellfish/FeatureServer/0

[Metadata] NOAA Marine Protected Areas for Hawaii and vicinity, 2024 version. Downloaded from ArcGIS Online (https://noaa.maps.arcgis.com/home/item.html?id=eb2b36aecb004f14ac29cf0260624291#overview) by Hawaii Statewide GIS staff, Mar 14, 2025. Projected to Hawaii Statewide GIS standard projection (Nad 83 UTM Zone 4, HARN) and clipped to Hawaii and the Pacific. The MPA Inventory is a comprehensive catalog that provides detailed information for existing marine protected areas in the United States. The inventory provides geospatial boundary information (in polygon format) and classification attributes that seek to define the conservation objectives, protection level, governance and related management criteria for all sites in the database. The comprehensive inventory of federal, state and territorial MPA sites provides governments and stakeholders with access to information to make better decisions about the current and future use of place-based conservation. The information also will be used to inform the development of the national system of marine protected areas as required by Executive Order 13158. For more information, visit the NOAA MPA Inventory webpage (https://marineprotectedareas.noaa.gov/dataanalysis/mpainventory/) or email mpainventory@noaa.gov. Also see Hawaii Statewide GIS Metadata Summary at https://files.hawaii.gov/dbedt/op/gis/data/MPA_noaa_inventory.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

[Metadata] Description: TMK Plats for the State of Hawaii. Created May, 2018. Sources: City and County of Honolulu: 4/20/18; County of Maui: 4/24/18; County of Hawaii: 5/1/18; County of Kauai: 5/4/18.Please note - if you are using the State's ArcGIS Online data or the State's web services, or are downloading data from the State's geoportal, the data is served and exported in WGS84, although associated metadata may reference the coordinate system in which the data is stored natively (UTM Zone 4, NAD 83 HARN).For more information, please refer to metadata at https://files.hawaii.gov/dbedt/op/gis/data/tmk_zone_section_plat.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, Hi. 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

Displacement risk indicator showing how many households within the specified groups are facing severely housing cost burden (contributing more than 50% of monthly income toward housing costs).

Notice: The U.S. Census Bureau is delaying the release of the 2016-2020 ACS 5-year data until March 2022. For more information, please read the Census Bureau statement regarding this matter. -----------------------------------------This layer shows poverty status by age group. This layer is Census data from Esri's Living Atlas and is clipped to only show Tempe census tracts. This layer is symbolized to show the percentage of the population whose income falls below the Federal poverty line. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right (in ArcGIS Online).Data is from US Census American Community Survey (ACS) 5-year estimates. Vintage: 2015-2019 ACS Table(s): B17020 (Not all lines of these ACS tables are available in this feature layer.) Data downloaded from: Census Bureau's API for American Community Survey Date of Census update: December 10, 2020 National Figures: data.census.gov Additional Census data notes and data processing notes are available at the Esri Living Atlas Layer: https://tempegov.maps.arcgis.com/home/item.html?id=0e468b75bca545ee8dc4b039cbb5aff6 (Esri's Living Atlas always shows latest data)