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

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.

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.Further metadata/references can be found here: http://gisweb.ciat.cgiar.org/RTBmaps/DataAvailability_RTBMaps.htmlDISCLAIMER, ACKNOWLEDGMENTS AND PERMISSIONS:This service is provided by Roots, Tubers and Bananas CGIAR Research Program as a public service. Use of this service to retrieve information constitutes your awareness and agreement to the following conditions of use.This online resource displays GIS data and query tools subject to continuous updates and adjustments. The GIS data has been taken from various, mostly public, sources and is supplied in good faith.RTBMaps GIS Data Disclaimer• The data used to show the Base Maps is supplied by ESRI.• The data used to show the photos over the map is supplied by Flickr.• The data used to show the videos over the map is supplied by Youtube.• The population map is supplied to us by CIESIN, Columbia University and CIAT.• The Accessibility map is provided by Global Environment Monitoring Unit - Joint Research Centre of the European Commission. Accessibility maps are made for a specific purpose and they cannot be used as a generic dataset to represent "the accessibility" for a given study area.• Harvested area and yield for banana, cassava, potato, sweet potato and yam for the year 200, is provided by EarthSat (University of Minnesota’s Institute on the Environment-Global Landscapes initiative and McGill University’s Land Use and the Global Environment lab). Dataset from Monfreda C., Ramankutty N., and Foley J.A. 2008.• Agroecology dataset: global edapho-climatic zones for cassava based on mean growing season, temperature, number of dry season months, daily temperature range and seasonality. Dataset from CIAT (Carter et al. 1992)• Demography indicators: Total and Rural Population from Center for International Earth Science Information Network (CIESIN) and CIAT 2004.• The FGGD prevalence of stunting map is a global raster datalayer with a resolution of 5 arc-minutes. The percentage of stunted children under five years old is reported according to the lowest available sub-national administrative units: all pixels within the unit boundaries will have the same value. Data have been compiled by FAO from different sources: Demographic and Health Surveys (DHS), UNICEF MICS, WHO Global Database on Child Growth and Malnutrition, and national surveys. Data provided by FAO – GIS Unit 2007.• Poverty dataset: Global poverty headcount and absolute number of poor. Number of people living on less than $1.25 or $2.00 per day. Dataset from IFPRI and CIATTHE RTBMAPS GROUP MAKES NO WARRANTIES OR GUARANTEES, EITHER EXPRESSED OR IMPLIED AS TO THE COMPLETENESS, ACCURACY, OR CORRECTNESS OF THE DATA PORTRAYED IN THIS PRODUCT NOR ACCEPTS ANY LIABILITY, ARISING FROM ANY INCORRECT, INCOMPLETE OR MISLEADING INFORMATION CONTAINED THEREIN. ALL INFORMATION, DATA AND DATABASES ARE PROVIDED "AS IS" WITH NO WARRANTY, EXPRESSED OR IMPLIED, INCLUDING BUT NOT LIMITED TO, FITNESS FOR A PARTICULAR PURPOSE. By accessing this website and/or data contained within the databases, you hereby release the RTB group and CGCenters, its employees, agents, contractors, sponsors and suppliers from any and all responsibility and liability associated with its use. In no event shall the RTB Group or its officers or employees be liable for any damages arising in any way out of the use of the website, or use of the information contained in the databases herein including, but not limited to the RTBMaps online Atlas product.APPLICATION DEVELOPMENT:• Desktop and web development - Ernesto Giron E. (GeoSpatial Consultant) e.giron.e@gmail.com• GIS Analyst - Elizabeth Barona. (Independent Consultant) barona.elizabeth@gmail.comCollaborators:Glenn Hyman, Bernardo Creamer, Jesus David Hoyos, Diana Carolina Giraldo Soroush Parsa, Jagath Shanthalal, Herlin Rodolfo Espinosa, Carlos Navarro, Jorge Cardona and Beatriz Vanessa Herrera at CIAT, Tunrayo Alabi and Joseph Rusike from IITA, Guy Hareau, Reinhard Simon, Henry Juarez, Ulrich Kleinwechter, Greg Forbes, Adam Sparks from CIP, and David Brown and Charles Staver from Bioversity International.Please note these services may be unavailable at times due to maintenance work.Please feel free to contact us with any questions or problems you may be having with RTBMaps.

Lands Department of Hong Kong SAR has released Location Search API which is available in Hong Kong Geodata Store (https://geodata.gov.hk/gs/). This API is very useful to Esri Users in Hong Kong as it saves vast amount of time to carry out data conversion to support location searching. The API is HTTP-based for application developers to find any locations in Hong Kong by addresses, building names, place names or facility names.

This code sample contains sample HTML and JavaScript files. Users can follow This Guidelines to use the Location Search API with ArcGIS API for JavaScript to build web mapping applications with ArcGIS API for JavaScript.

The Department of Information Technology and Telecommunications, GIS Unit, has created a series of Map Tile Services for use in public web mapping & desktop applications. The link below describes the Basemap, Labels, & Aerial Photographic map services, as well as, how to utilize them in popular JavaScript web mapping libraries and desktop GIS applications. A showcase application, NYC Then&Now (https://maps.nyc.gov/then&now/) is also included on this page.

The web service publishing DMP 1G data is designed for a displaying of the detailed elevation model via a web interface in 3D, in Web Mercator coordinate reference system. Service provides data in a specialized data format LERC (https://github.com/Esri/lerc), that enables efficient data compression with regard to fast data transmission and displaying data in 3D applications. For the displaying data it is possible to use existing Esri application such as Scene Viewer (https://www.esri.com/software/scene-viewer), ArcGIS Pro (http://www.esri.com/en/software/arcgis-pro), or ArcGIS Earth (http://www.esri.com/software/arcgis-earth).The service can also be used for displaying the elevation model in 3D in a proper web application using a library ArcGiS API for JavaScript 4.x or native applications using ArcGIS Runtime SDK.

Author: Megan Banaski (mbanaski@esri.com) and Max Ozenberger (mozenberger@esri.com)Last Updated: 1/1/2024Intended Environment: WebPurpose:Exercise A1: Review HTML, CSS, and JavaScript This lab is part of GitHub repository that contains short labs that step you through the process of developing a web application with ArcGIS API for JavaScript.The labs start from ground-zero and work through the accessing different aspects of the API and how to begin to build an application and add functionality.Requirements: Here are the resources you will use for the labs.ArcGIS for Developers - Account, Documentation, Samples, Apps, DownloadsEsri Open Source Projects - More source codeA simple guide for setting up a local web server (optional)Help with HTML, CSS, and JavaScript

The datasets used for this manuscript were derived from multiple sources: Denver Public Health, Esri, Google, and SafeGraph. Any reuse or redistribution of the datasets are subjected to the restrictions of the data providers: Denver Public Health, Esri, Google, and SafeGraph and should consult relevant parties for permissions.1. COVID-19 case dataset were retrieved from Denver Public Health (Link: https://storymaps.arcgis.com/stories/50dbb5e7dfb6495292b71b7d8df56d0a )2. Point of Interests (POIs) data were retrieved from Esri and SafeGraph (Link: https://coronavirus-disasterresponse.hub.arcgis.com/datasets/6c8c635b1ea94001a52bf28179d1e32b/data?selectedAttribute=naics_code) and verified with Google Places Service (Link: https://developers.google.com/maps/documentation/javascript/reference/places-service)3. The activity risk information is accessible from Texas Medical Association (TMA) (Link: https://www.texmed.org/TexasMedicineDetail.aspx?id=54216 )The datasets for risk assessment and mapping are included in a geodatabase. Per SafeGraph data sharing guidelines, raw data cannot be shared publicly. To view the content of the geodatabase, users should have installed ArcGIS Pro 2.7. The geodatabase includes the following:1. POI. Major attributes are locations, name, and daily popularity.2. Denver neighborhood with weekly COVID-19 cases and computed regional risk levels.3. Simulated four travel logs with anchor points provided. Each is a separate point layer.

Important Note: This item is in mature support as of February 2025 and is no longer being updated. A new version of this item is available for your use.This web application highlights some of the capabilities for accessing Sentinel-2 imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Sentinel-2 images on a daily basis.Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Sentinel-2 Explorer app provides the power of Sentinel-2 satellites, which gather data beyond what the eye can see. Use this app to draw on Sentinel's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the Sentinel-2 archive to visualize how the Earth's surface has changed over the last fourteen monthsQuick access to the following band combinations and indices is provided:BandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Agriculture : Highlights vigorous vegetation in bright green, stressed vegetation dull green and bare areas brown; Bands 11, 8, 2Natural Color : Bands 4, 3, 2Color Infrared : Healthy vegetation is bright red while stressed vegetation is dull red; Bands 8, 4 ,3 SWIR (Short-wave Infrared) : Highlights rock formations; Bands 12, 11, 4Geology : Highlights geologic features; Bands 12, 11, 2Bathymetric : Highlights underwater features; Bands 4, 3, 1Vegetation Index : Normalized Difference Vegetation Index(NDVI) with Colormap ; (Band 8 - Band 4)/(Band 8 + Band 4)Moisture Index : Normalized Difference Moisture Index (NDMI); (Band 8 - Band 11)/(Band 8 + Band 11)Normalized Burn Ratio : (Band 8 - Band 12)/(Band 8 + Band 12)Built-Up Index : (Band 11 - Band 8)/(Band 11 + Band 8)NDVI Raw : Normalized Difference Vegetation Index(NDVI); (Band 8 - Band 4)/(Band 8 + Band 4)NDVI - VRE only Raw : NDVI with VRE bands only; (Band 6 - Band 5)/(Band 6 + Band 5)NDVI - VRE only Colorized : NDVI with VRE bands only with Colormap; (Band 6 - Band 5)/(Band 6 + Band 5)NDVI - with VRE Raw : Also known as NDRE. NDVI with VRE band 5 and NIR band 8; (Band 8 - Band 5)/(Band 8 + Band 5)NDVI - with VRE Colorized : Also known as NDRE with Colormap; (Band 8 - Band 5)/(Band 8 + Band 5)NDWI Raw : Normalized Difference Water index with Green band and NIR band; (Band 3 - Band 8)/(Band 3 + Band 8)NDWI - with VRE Raw : Normalized Difference Water index with VRE band 5 and Green band 3; (Band 3 - Band 5)/(Band 3 + Band 5)NDWI - with VRE Colorized : NDWI index with VRE band 5 and Green band 3 with Colormap; (Band 3 - Band 5)/(Band 3 + Band 5)Custom SAVI : (Soil Adjusted Veg. Index); Offset + Scale*(1.5*(Band 8 - Band 4)/(Band 8 + Band 4 + 0.5))Custom Water Index : Offset + Scale*(Band 3 - Band 12)/(Band 3 + Band 12)Custom Burn Index : Offset + Scale*(Band 8 - Band 13)/(Band 8 + Band 13)Urban Index : Offset + Scale*(Band 8 - Band 12)/(Band 8 + Band 12)Optionally, you can also choose the "Custom Bands" or "Custom Index" option to create your own band combinationsThe Time tool enables access to a temporal time slider and a temporal profile of different indices for a selected point. The Time tool is only accessible at larger zoom scales. It provides temporal profiles for indices like NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and Urban Index. The Identify tool enables access to information on the images, and can also provide a spectral profile for a selected point. The Bookmark tool will direct you to pre-selected interesting locations.NOTE: Using the Time tool to access imagery in the Sentinel-2 archive requires an ArcGIS account.The application is written using Web AppBuilder for ArcGIS accessing imagery layers using ArcGIS API for JavaScript.The following Imagery Layer are being accessed : Sentinel-2 - Provides access to 10, 20, and 60m 13-band multispectral imagery and a range of functions that provide different band combinations and indices.

An attempt to collect, format, analyse and disseminate surveyed marine biological data deriving from the Eastern Mediterranean and Black Sea region is currently under development at the Hellenic Center for Marine Research (HCMR, Greece). The effort has been supported by the MedOBIS project (Mediterranean Ocean Biogeographic Information System) and has been carried out in cooperation with the Aristotelian University of Thessaloniki (Greece), the National Institute of Oceanography (Israel) and the Institute of Biology of the Southern Seas (Ukraine).

    The aim is to develop a taxon-based biogeography database and online data server with a link to survey and provide satellite environmental data. Currently, the primary features of the MedOBIS application are its offline GIS data formatting capabilities and its online Java and JavaScript enabling data server with taxon-based search, mapping and data downloading capabilities. In its completion, the MedOBIS online marine biological data system (http://www.iobis.org/OBISWEB/ObisDynPage1.jsp?content=meta/42.html) will be a single source of biological and environmental data (raw and analysed) as well as an online GIS tool for access of historical and current data by marine researchers. It will function as the Eastern Mediterranean and Black Sea node of EurOBIS (the European node of the International OBIS initiative, part of the Census of Marine Life).

    INTRODUCTION

    The international and interdisciplinary nature of the biological degradation issue as well as the technological advances of the Internet capabilities allowed the development of a considerable number of interrelated online databases. The free dissemination of valuable historical and current biological, environmental and genetic information has contributed to the establishment of an interdisciplinary platform targeted towards information integration at regional and also at global scales and to the development of information-based management schemes about our common interest.

    The spatial component of these data has led to the integration of the information by means of the Geographic Information System (GIS) technology. The latter is widely used as the natural framework for spatial data handling (Wright & Bartlett 1999, Valavanis 2002). GIS serves as the basic technological infrastructure for several online marine biodiversity databases available on the Internet today. Developments like OBIS (Ocean Biogeographic Information System, "http://www.iobis.org/"), OBIS-SEAMAP (Spatial Ecological Analysis of Megavertebrate Populations, "http://seamap.env.duke.edu/") and FIGIS (FAO Fisheries Global Information System, http://www.fao.org/fishery/figis) facilitate the study of anthropogenic impacts on threatened species, enhance our ability to test biogeographic and biodiversity models, support modelling efforts to predict distribution changes in response to environmental change and develop a strong potential for the public outreach component. In addition, such online database systems provide a broader view of marine biodiversity problems and allow the development of management practices that are based on synthetic analysis of interdisciplinary data (Schalk 1998, Decker & O'Dor 2002, Tsontos & Kiefer 2002).

    Towards this end, a development of a new online marine biological information system is presented here in its initial phase. MedOBIS (Mediterranean Ocean Biogeographic Information System) intends to assemble, formulate and disseminate marine biological data for the Eastern Mediterranean and Black Sea regions focusing on the assurance and longevity of historical surveyed data, the assembly of current and new information and the dissemination of raw and integrated biological and environmental data and future products through the Internet.

    MedOBIS DESCRIPTION

    MedOBIS current development consists of four main phases (Fig. 1). The data assembly phase is based on the free contribution of biological data from various national and international scientific surveys in the region. The data formatting phase is based on a GIS (ESRI, 1994), under which the geographic location of data stations is used to convert station data and their attributes to GIS shapefiles. The data analysis phase is based on data integration through GIS and spatial analyses (e.g. species distribution maps, species-environment relations, etc). Finally, the dissemination phase is based on ALOV Map, a free portable Java application for publication of vector and raster maps to the Internet and interactive viewing on web browsers. It supports navigation and search capabilities and allows working with multiple layers, thematic maps, hyperlinked features and attributed data.

    During the on-going data assembly phase, a total number of 776 stations with surveyed benthic biological data was employed. These data include mainly benthic species abundance (for nearly 3000 benthic organisms), benthic substrate types and several environmental parameters. Currently, 100 stations have been assembled for the Ionian Sea, 570 stations for the Aegean Sea and 106 stations for the Black Sea. The temporal resolution of these data extends for the period 1937-2000 while most data cover the period 1986-1996. Additionally, monthly satellite images of sea surface temperature (SST) and chlorophyll (Chl-a) were assembled for the period 1998-2003. Satellite data were obtained from the Advanced Very High Resolution Radiometer (AVHRR SST) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS Chl-a). 

    During the data formatting phase, all assembled surveyed stations were converted to a GIS shapefile (Fig. 2). This GIS information layer includes the geographic coordinates of the stations as well as stations' identification number. Station data attributes were organised in an MS Access Database while satellite data were embedded in a GIS database as GIS regular grids. The MedOBIS data analysis phase is still at the initial stage. Several off line analytical published efforts (e.g. Arvanitidis et al. 2002, Valavanis et al. 2004a,b,c) will be included in the MedOBIS development, which mainly focus on species distribution maps, mapping of productive oceanic processes and species-environment interactions. 

    The MedOBIS dissemination phase ("http://www.medobis.org/") is based on ALOV Map ("http://www.alov.org/"), a joint project of ALOV Software and the Archaeological Computing Laboratory, University of Sydney, Australia. ALOV Map is a Java-based application for publication of GIS data on the Internet and interactive viewing on web browsers. ALOV Map is designed to display geographical information stored in shapefiles or in any SQL database or even in an XML (Extensible Markup Language) document serving as a database. MedOBIS uses ALOV Map's full capabilities and runs in a client-server mode (Fig. 3). ALOV Map is connected to an MS Access database via a servlet container. This architecture was needed to connect the biological data with the spatial data and facilitate search options, such as, which species are found at which stations. Additionally, a JavaScript code is invoked, which searches the data, pops up a window with the results and then shows the relevant stations on the map.

    To provide a taxon-based search capability to the MedOBIS development, the sampling data as well as the relevant spatial data are stored in the database, so taxonomic data can be linked with the geographical data by SQL (Structured Query Language) queries. To reference each species to its location on the map, the database queries are stored and added to the applet as individual layers. A search function written in JavaScript searches the attribute data of that layer, displays the results in a separate window and marks the matching stations on the map (Fig. 4). Finally, selecting several stations by drawing a zooming rectangle on the map provides a list with predefined themes from which the user may select more information (Fig. 5). 

    CURRENT LIMITATIONS AND FUTURE PLANS

    A disadvantage of embedding information from the database as a layer is the relatively long download time due to the current MedOBIS-ALOV Map client-server architecture. An appropriate solution would be a direct search on the server side, which will allow partial data downloading to the client side. This work will be embedded in the MedOBIS application in the future (client-side architecture), when the size of assembled data becomes relatively 'heavy' for the current client-server architecture. This is an on-going process, since the MedOBIS initiative has been endorsed by the "Excellence of the Institute of Marine Biology of Crete (IMBC) in Marine Biodiversity", a Hellenic National Project that has been evaluated and approved by European experts. As more data will be assembled in time-series databases, an additional future work will include the development of MedOBIS data analysis phase, which is planned to include GIS modelling/mapping of species-environment interactions.

    Size reference: 2953 species; 776 stations

    [Source: The information provided in the summary was extracted from the MarBEF Data System at "http://www.marbef.org/data/eurobisproviders.php"]

Important Note: This item is in mature support as of February 2024 and is no longer being updated. A new version of this item is available for your use.This web application highlights some of the capabilities for accessing Landsat imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Landsat images on a daily basis.Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Landsat Explorer app provides the power of Landsat satellites, which gather data beyond what the eye can see. Use this app to draw on Landsat's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the entire Landsat archive to visualize how the Earth's surface has changed over the last forty years.Quick access to the following band combinations and indices is provided:Agriculture : Highlights agriculture in bright green; Bands 6, 5, 2Natural Color : Sharpened with 15m panchromatic band; Bands 4, 3, 2 +8Color Infrared : Healthy vegetation is bright red; Bands 5, 4 ,3 SWIR (Short Wave Infrared) : Highlights rock formations; Bands 7, 6, 4Geology : Highlights geologic features; Bands 7, 6, 2Bathymetric : Highlights underwater features; Bands 4, 3, 1Panchromatic : Panchromatic images at 15m; Band 8Vegetation Index : Normalized Difference Vegetation Index(NDVI); (Band 5 - Band 4)/(Band 5 + Band 4)Moisture Index : Normalized Difference Moisture Index (NDMI); (Band 5 - Band 6)/(Band 5 + Band 6)SAVI : Soil Adjusted Veg. Index); Offset + Scale*(1.5*(Band 5 - Band 4)/(Band 5 + Band 4 + 0.5))Water Index : Offset + Scale*(Band 3 - Band 6)/(Band 3 + Band 6)Burn Index : Offset + Scale*(Band 5 - Band 7)/(Band 5 + Band 7)Urban Index : Offset + Scale*(Band 5 - Band 6)/(Band 5 + Band 6)Optionally, you can also choose the "Custom Bands" or "Custom Index" option to create your own band combinationsThe Time tool enables access to a temporal time slider and a temporal profile of different indices for a selected point. The Time tool is only accessible at larger zoom scales. It provides temporal profiles for NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and Urban Index. The Identify tool enables access to information on the images, and can also provide a spectral profile for a selected point. The Stories tool will direct you to pre-selected interesting locations.The application is written using Web AppBuilder for ArcGIS accessing imagery layers using ArcGIS API for JavaScript.The following Imagery Layers are being accessed : Multispectral Landsat - Provides access to 30m 8-band multispectral imagery and a range of functions that provide different band combinations and indices.Pansharpened Landsat - Provides access to 15m 4-band (Red, Green, Blue and NIR) panchromatic-sharpened imagery.Panchromatic Landsat - Provides access to 15m panchromatic imagery. These imagery layers can be accessed through the public group Landsat Community on ArcGIS Online.

Based on the World Ocean Atlas' global ocean variable measurements we classified the oceanic water bodies into 37 volumetric regions, called ecological marine units. These volumetric region units can be used to support climate change impact studies, conservation priority setting, and marine spatial planning. Read more about how these regions were created in the research article A Three-Dimensional Mapping of the Ocean based on Environmental Data, which appeared in March 2017 in the Oceanography journal.This application visualizes ecological marine units using voxel scene layers. You can read more about voxel layers in the ArcGIS Pro documentation. This application was built using ArcGIS API for JavaScript (read more about web voxel layers). The original netCDF dataset can be found here. The code for the application is available on GitHub.Related work:Ecological Marine Units Explorer - a web application that visualizes the ocean as a 3D grid.Esri's website on Ecological Marine Units.

This web application highlights some of the capabilities for accessing Landsat imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Landsat images on a daily basis.

Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Landsat Explorer app provides the power of Landsat satellites, which gather data beyond what the eye can see. Use this app to draw on Landsat's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the entire Landsat archive to visualize how the Earth's surface has changed over the last forty years.

Quick access to the following band combinations and indices is provided:

• Agriculture : Highlights agriculture in bright green; Bands 6, 5, 2
• Natural Color : Sharpened with 15m panchromatic band; Bands 4, 3, 2 +8
• Color Infrared : Healthy vegetation is bright red; Bands 5, 4 ,3
• SWIR (Short Wave Infrared) : Highlights rock formations; Bands 7, 6, 4
• Geology : Highlights geologic features; Bands 7, 6, 2
• Bathymetric : Highlights underwater features; Bands 4, 3, 1
• Panchromatic : Panchromatic images at 15m; Band 8
• Vegetation Index : Normalized Difference Vegetation Index(NDVI); (Band 5 - Band 4)/(Band 5 + Band 4)
• Moisture Index : Normalized Difference Moisture Index (NDMI); (Band 5 - Band 6)/(Band 5 + Band 6)
• SAVI : Soil Adjusted Veg. Index); Offset + Scale*(1.5*(Band 5 - Band 4)/(Band 5 + Band 4 + 0.5))
• Water Index : Offset + Scale*(Band 3 - Band 6)/(Band 3 + Band 6)
• Burn Index : Offset + Scale*(Band 5 - Band 7)/(Band 5 + Band 7)
• Urban Index : Offset + Scale*(Band 5 - Band 6)/(Band 5 + Band 6)

This web application highlights some of the capabilities for accessing Sentinel-2 imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Sentinel-2 images on a daily basis.Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Sentinel-2 Explorer app provides the power of Sentinel-2 satellites, which gather data beyond what the eye can see. Use this app to draw on Sentinel's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the Sentinel-2 archive to visualize how the Earth's surface has changed over the last fourteen monthsQuick access to the following band combinations and indices is provided:BandDescriptionWavelength (µm)Resolution (m)1Coastal aerosol0.433 - 0.453602Blue0.458 - 0.523103Green0.543 - 0.578104Red0.650 - 0.680105Vegetation Red Edge0.698 - 0.713206Vegetation Red Edge0.733 - 0.748207Vegetation Red Edge0.773 - 0.793208NIR0.785 - 0.900108ANarrow NIR0.855 - 0.875209Water vapour0.935 - 0.9556010SWIR – Cirrus1.365 - 1.3856011SWIR-11.565 - 1.6552012SWIR-22.100 - 2.28020Agriculture : Highlights vigorous vegetation in bright green, stressed vegetation dull green and bare areas brown; Bands 11, 8, 2Natural Color : Bands 4, 3, 2Color Infrared : Healthy vegetation is bright red while stressed vegetation is dull red; Bands 8, 4 ,3 SWIR (Short-wave Infrared) : Highlights rock formations; Bands 12, 11, 4Geology : Highlights geologic features; Bands 12, 11, 2Bathymetric : Highlights underwater features; Bands 4, 3, 1Vegetation Index : Normalized Difference Vegetation Index(NDVI) with Colormap ; (Band 8 - Band 4)/(Band 8 + Band 4)Moisture Index : Normalized Difference Moisture Index (NDMI); (Band 8 - Band 11)/(Band 8 + Band 11)Normalized Burn Ratio : (Band 8 - Band 12)/(Band 8 + Band 12)Built-Up Index : (Band 11 - Band 8)/(Band 11 + Band 8)NDVI Raw : Normalized Difference Vegetation Index(NDVI); (Band 8 - Band 4)/(Band 8 + Band 4)NDVI - VRE only Raw : NDVI with VRE bands only; (Band 6 - Band 5)/(Band 6 + Band 5)NDVI - VRE only Colorized : NDVI with VRE bands only with Colormap; (Band 6 - Band 5)/(Band 6 + Band 5)NDVI - with VRE Raw : Also known as NDRE. NDVI with VRE band 5 and NIR band 8; (Band 8 - Band 5)/(Band 8 + Band 5)NDVI - with VRE Colorized : Also known as NDRE with Colormap; (Band 8 - Band 5)/(Band 8 + Band 5)NDWI Raw : Normalized Difference Water index with Green band and NIR band; (Band 3 - Band 8)/(Band 3 + Band 8)NDWI - with VRE Raw : Normalized Difference Water index with VRE band 5 and Green band 3; (Band 3 - Band 5)/(Band 3 + Band 5)NDWI - with VRE Colorized : NDWI index with VRE band 5 and Green band 3 with Colormap; (Band 3 - Band 5)/(Band 3 + Band 5)Custom SAVI : (Soil Adjusted Veg. Index); Offset + Scale*(1.5*(Band 8 - Band 4)/(Band 8 + Band 4 + 0.5))Custom Water Index : Offset + Scale*(Band 3 - Band 12)/(Band 3 + Band 12)Custom Burn Index : Offset + Scale*(Band 8 - Band 13)/(Band 8 + Band 13)Urban Index : Offset + Scale*(Band 8 - Band 12)/(Band 8 + Band 12)Optionally, you can also choose the "Custom Bands" or "Custom Index" option to create your own band combinationsThe Time tool enables access to a temporal time slider and a temporal profile of different indices for a selected point. The Time tool is only accessible at larger zoom scales. It provides temporal profiles for indices like NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and Urban Index. The Identify tool enables access to information on the images, and can also provide a spectral profile for a selected point. The Bookmark tool will direct you to pre-selected interesting locations.NOTE: Using the Time tool to access imagery in the Sentinel-2 archive requires an ArcGIS account.The application is written using Web AppBuilder for ArcGIS accessing imagery layers using ArcGIS API for JavaScript.The following Imagery Layer are being accessed : Sentinel-2 - Provides access to 10, 20, and 60m 13-band multispectral imagery and a range of functions that provide different band combinations and indices.

The U.S. Vessel Traffic application is a web-based visualization and data-access utility created by Esri. Explore U.S. maritime activity, look for patterns, and download manageable subsets of this massive data set. Vessel traffic data are an invaluable resource made available to our community by the US Coast Guard, NOAA and BOEM through Marine Cadastre. This information can help marine spatial planners better understand users of ocean space and identify potential space-use conflicts. To download this data for your own analysis, explore the Download Options, navigate to a NOAA Electronic Navigation Chart area of interest, and make your selection. This data was sourced from the Automatic Identification System (AIS) provided by USCG, NOAA, and BOEM through Marine Cadastre and aggregated for visualization and sharing in ArcGIS Pro. This application was built with the ArcGIS API for JavaScript. Access this data as an ArcGIS Online collection here. Learn more about AIS tracking here. Find more ocean and maritime resources in Living Atlas. Inquiries can be sent to Keith VanGraafeiland.

Web-palvelu, joka julkaisee DMR 4G -dataa, joka on suunniteltu näyttämään yksityiskohtainen korkeusmalli verkkoympäristössä 3D: ssä, S-JTSK-koordinaattijärjestelmässä Křovákin näkökulmasta. Palvelun tarjoamat tiedot ovat erikoistuneessa muodossa LERC (https://github.com/Esri/lerc), mikä mahdollistaa tehokkaan pakkaamisen nopeaan tiedonsiirtoon ja renderointiin 3D-sovelluksissa. Palvelun lähdetiedot sijaitsevat koordinaattijärjestelmässä S-JTSK/Krovak East North (EPSG 5514). Olemassa olevia Esri-sovelluksia, kuten Scene Viewer (https://www.esri.com/software/scene-viewer), ArcGIS Pro (http://www.esri.com/en/software/arcgis-pro) tai ArcGIS Earth (http://www.esri.com/en/software/arcgis-pro), voidaan käyttää korkeusmallin näyttämiseen 3D-muodossa omissa verkkosovelluksissasi käyttämällä ArcGIS API JavaScript 4.x -kirjastoa tai natiivisovelluksia ArcGIS Runtime SDK: n avulla.

Burn severity datasets for wildfires in British Columbia (BC) that occurred between 1985 and 2019 were created based on methodology and JavaScript code developed by Parks et al. (2018) with minor modifications to account for BC's growing season: pre- and post-fire scene selection dates were changed to June 1-Sept 30. Floating point geoTIFFs were created in Google Earth Engine’s code development environment using JavaScript; all other processing was completed using ArcGIS 10.6 & Python 2.7.

Only wildfires >25ha are included in this repository. Fire perimeters from BC's Wildfire Perimeters - Historical spatial dataset were used to determine wildfire extents. Fire numbers correspond to the [FIRE_NUMBER] field within this dataset.

Please be aware that no field verification has been performed on this data.

Burn Severity Metrics

• dnbr – differenced normalized burn ratio
• rbr – relativized burn ratio
• rdnbr – relativized differenced normalized burn ratio

Each metric has also been run with an offset (see “_w_offset” directories), which includes pixels from a 180m buffer outside the mapped fire perimeter. This offset may help assess unburned areas within the fire perimeter as long as the cover types outside the perimeter are similar to the cover types within the perimeter.

Available Datasets

There are 5 raster and/or vector datasets available for each fire:

1. Floating point geoTIF as exported from Google Earth Engine (GEE)

o

o ex. C10006_1985_dnbr.tif

2. Integer geoTIF

o Created from the floating point geoTIF

o

o ex. C10006_1985_dnbr_int.tif

3. Integer geoTIF clipped to mapped fire perimeter

o Fire perimeter from the BC Wildfire Perimeter - Historical spatial dataset , with any internal holes removed, is used to clip the integer geoTIF

o

o ex. C10006_1985_dnbr_masked.tif

4. Reclassed clipped geoTIF

o Clipped geoTIF is reclassed using the thresholds in Table 1 below (from Parks et al. 2018).

o

o ex. C10006_1985_dnbr_reclass.tif

Table 1: Burn severity thresholds from Parks et al.

5. Reclassed burn severity shapefile

o Reclassed geoTIF is converted into a polygon shapefile and the classification is converted to text (Low, Moderate, High); no smoothing is applied

o

o ex. C10006_1985_dnbr_reclass_poly.shp

Known Issues

A small number of fires failed during the Google Earth Engine processing (see Table 2). These fires have no burn severity classification available.

Table 2. Fires without burn severity information available

The High Tide Flooding App allows quick visualization and understanding of U.S. high tide flooding probability scenarios through 2100. Users can quickly assess how many flooding days are expected to occur within coastal communities each year for the different flooding scenarios ranging from low to extreme. The application also allows sharing of a location and impact year so you can share links with colleagues or quickly compare outlooks.Coastal planners and state and local municipal leaders, regional planning councils and alike need this information to better understand potential impacts to help plan accordingly. Increasing this understanding can help impact policy and protect the investments of citizens.This data was sourced from NOAA Technical Report NOS CO-OPS 086: Patterns and Projections of High Tide Flooding Along the U.S. Coastline Using a Common Impact Threshold and aggregated for visualization and sharing in ArcGIS Pro. This application was built with the ArcGIS API for JavaScript. You can find the supporting layer in the Living Atlas of the World.

Webová služba publikující data DMP 1G, určená pro zobrazení podrobného výškového modelu v prostředí webu ve 3D, v souřadnicovém systému Web Mercator. Data jsou službou poskytována ve specializovaném formátu LERC (https://github.com/Esri/lerc), který umožňuje jejich efektivní kompresi s ohledem na rychlý přenos a vykreslení dat ve 3D aplikacích. Zdrojová data pro službu jsou umístěna v souřadnicovém systému WGS 84 / Pseudo-Mercator (EPSG 3857 alias 900913). Pro zobrazení dat lze využít stávající Esri aplikace, jako Scene Viewer (https://www.esri.com/software/scene-viewer), ArcGIS Pro (http://www.esri.com/en/software/arcgis-pro), nebo ArcGIS Earth (http://www.esri.com/software/arcgis-earth).Službu lze využít i pro zobrazení výškového modelu ve 3D ve vlastních webových aplikacích, využitím knihovny ArcGIS API for JavaScript 4.x, nebo nativních aplikacích, využitím ArcGIS Runtime SDK.

This open source ArcGIS JavaScript application lets you load and interact with a WMS with multiple dimensions (time + 1 other). The application retrieves the layers unique time slices and other dimensions slices from the WMS and then displays both of those dimensions on a slider. If there are more than just one time and one other dimension, you can choose which combination of 2 dimensions to use. When you select a specific dimension, the application updates the layer to draw/display that dimension.As of ArcGIS for Server 10.2.1, Esri supports multi-dimensional WMS services. This application allows you to view the Multi-Dimensional WMS service. Since this application is using WMS, the application supports WMS services coming from servers over than Esri. For example this application works with THREDDS WMS services such as this one. View it live The source code for this application may be found at:https://github.com/Esri/WMSMultiDimensionalEsriViewer