Simple Map Viewer is a configurable app template with a straightforward and simple user experience for exploring a web map. Use CasesDisplays a map with a legend and description within a sliding drawer pane. This is a good general-purpose map app when simple navigation tools are needed.Configurable OptionsSimple Map Viewer presents content from a web map and can be configured using the following options:Provide a title and description.Choose the color of the theme, text, and legend header.Enable and customize the ability for feature and location search.Enable tools for finding current location and zooming to the default home extentSupported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsThis application has no data requirements.Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a map and choose to create a web appOn the Content page, click Create - App - From Template Click the Download button to access the source code. Do this if you want to host the app on your own server and optionally customize it to add features or change styling.

Retirement Notice: This item is in mature support as of February 2023 and will be retired in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.This layer displays change in pixels of the Sentinel-2 10m Land Use/Land Cover product developed by Esri, Impact Observatory, and Microsoft. Available years to compare with 2021 are 2018, 2019 and 2020. By default, the layer shows all comparisons together, in effect showing what changed 2018-2021. But the layer may be changed to show one of three specific pairs of years, 2018-2021, 2019-2021, or 2020-2021.Showing just one pair of years in ArcGIS Online Map Viewer To show just one pair of years in ArcGIS Online Map viewer, create a filter. 1. Click the filter button. 2. Next, click add expression. 3. In the expression dialogue, specify a pair of years with the ProductName attribute. Use the following example in your expression dialogue to show only places that changed between 2020 and 2021:ProductNameis2020-2021 By default, places that do not change appear as a transparent symbol in ArcGIS Pro. But in ArcGIS Online Map Viewer, a transparent symbol may need to be set for these places after a filter is chosen. To do this: 4. Click the styles button.5. Under unique values click style options. 6. Click the symbol next to No Change at the bottom of the legend. 7. Click the slider next to "enable fill" to turn the symbol off. Showing just one pair of years in ArcGIS Pro To show just one pair of years in ArcGIS Pro, choose one of the layer's processing templates to single out a particular pair of years. The processing template applies a definition query that works in ArcGIS Pro. 1. To choose a processing template, right click the layer in the table of contents for ArcGIS Pro and choose properties. 2. In the dialogue that comes up, choose the tab that says processing templates. 3. On the right where it says processing template, choose the pair of years you would like to display. The processing template will stay applied for any analysis you may want to perform as well. How the change layer was created, combining LULC classes from two yearsImpact Observatory, Esri, and Microsoft used artificial intelligence to classify the world in 10 Land Use/Land Cover (LULC) classes for the years 2017-2021. Mosaics serve the following sets of change rasters in a single global layer: Change between 2018 and 2021Change between 2019 and 2021Change between 2020 and 2021To make this change layer, Esri used an arithmetic operation combining the cells from a source year and 2021 to make a change index value. ((from year * 16) + to year) In the example of the change between 2020 and 2021, the from year (2020) was multiplied by 16, then added to the to year (2021). Then the combined number is served as an index in an 8 bit unsigned mosaic with an attribute table which describes what changed or did not change in that timeframe. Variable mapped: Change in land cover between 2018, 2019, or 2020 and 2021 Data Projection: Universal Transverse Mercator (UTM)Mosaic Projection: WGS84Extent: GlobalSource imagery: Sentinel-2Cell Size: 10m (0.00008983152098239751 degrees)Type: ThematicSource: Esri Inc.Publication date: January 2022 What can you do with this layer?Global LULC maps provide information on conservation planning, food security, and hydrologic modeling, among other things. This dataset can be used to visualize land cover anywhere on Earth. This layer can also be used in analyses that require land cover input. For example, the Zonal Statistics tools allow a user to understand the composition of a specified area by reporting the total estimates for each of the classes. Land Cover processingThis map was produced by a deep learning model trained using over 5 billion hand-labeled Sentinel-2 pixels, sampled from over 20,000 sites distributed across all major biomes of the world. The underlying deep learning model uses 6 bands of Sentinel-2 surface reflectance data: visible blue, green, red, near infrared, and two shortwave infrared bands. To create the final map, the model is run on multiple dates of imagery throughout the year, and the outputs are composited into a final representative map. Processing platformSentinel-2 L2A/B data was accessed via Microsoft’s Planetary Computer and scaled using Microsoft Azure Batch. Class definitions1. WaterAreas where water was predominantly present throughout the year; may not cover areas with sporadic or ephemeral water; contains little to no sparse vegetation, no rock outcrop nor built up features like docks; examples: rivers, ponds, lakes, oceans, flooded salt plains.2. TreesAny significant clustering of tall (~15-m or higher) dense vegetation, typically with a closed or dense canopy; examples: wooded vegetation, clusters of dense tall vegetation within savannas, plantations, swamp or mangroves (dense/tall vegetation with ephemeral water or canopy too thick to detect water underneath).4. Flooded vegetationAreas of any type of vegetation with obvious intermixing of water throughout a majority of the year; seasonally flooded area that is a mix of grass/shrub/trees/bare ground; examples: flooded mangroves, emergent vegetation, rice paddies and other heavily irrigated and inundated agriculture.5. CropsHuman planted/plotted cereals, grasses, and crops not at tree height; examples: corn, wheat, soy, fallow plots of structured land.7. Built AreaHuman made structures; major road and rail networks; large homogenous impervious surfaces including parking structures, office buildings and residential housing; examples: houses, dense villages / towns / cities, paved roads, asphalt.8. Bare groundAreas of rock or soil with very sparse to no vegetation for the entire year; large areas of sand and deserts with no to little vegetation; examples: exposed rock or soil, desert and sand dunes, dry salt flats/pans, dried lake beds, mines.9. Snow/IceLarge homogenous areas of permanent snow or ice, typically only in mountain areas or highest latitudes; examples: glaciers, permanent snowpack, snow fields. 10. CloudsNo land cover information due to persistent cloud cover.11. Rangeland Open areas covered in homogenous grasses with little to no taller vegetation; wild cereals and grasses with no obvious human plotting (i.e., not a plotted field); examples: natural meadows and fields with sparse to no tree cover, open savanna with few to no trees, parks/golf courses/lawns, pastures. Mix of small clusters of plants or single plants dispersed on a landscape that shows exposed soil or rock; scrub-filled clearings within dense forests that are clearly not taller than trees; examples: moderate to sparse cover of bushes, shrubs and tufts of grass, savannas with very sparse grasses, trees or other plants.CitationKarra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021.AcknowledgementsTraining data for this project makes use of the National Geographic Society Dynamic World training dataset, produced for the Dynamic World Project by National Geographic Society in partnership with Google and the World Resources Institute.For questions please email environment@esri.com

This Land Cover-Land Use Tile Cache may be used for fast display in ArcGIS Online, ArcGIS Desktop, and other applications that can consume tile services.The statewide dataset contains a combination of land cover mapping from 2016 aerial imagery and land use derived from standardized assessor parcel information for Massachusetts. The data layer is the result of a cooperative project between MassGIS and the National Oceanic and Atmospheric Administration’s (NOAA) Office of Coastal Management (OCM). Funding was provided by the Mass. Executive Office of Energy and Environmental Affairs.

This land cover/land use dataset does not conform to the classification schemes or polygon delineation of previous land use data from MassGIS (1951-1999; 2005).In this hosted tile cache layer, all impervious polygons are symbolized by their generalized use code; all non-impervious land cover polygons are symbolized by their land cover category. The idea behind this method is to use both cover and use codes to provide a truer picture of how land is being used: parcel use codes may indicate allowed or assessed, not actual use; land cover alone (especially impervious) does not indicate actual use.

See the full datalayer description for more details.Also available are a Map Service and a Feature Service. They provide attribute query, although they will not display as quickly as the tile cache at smaller (zoomed out) scales.Add the Land Cover-Land Use Legend Map Service to an ArcGIS Online map along with this tile service to have a legend appear.

When using apps or web maps from MassGIS in ArcGIS Online, this map may be added as a basemap from the Basemap Gallery (based on the MassGIS Basemap tile layer).This general-reference map for the Commonwealth of Massachusetts uses MassGIS data and includes a topographic base featuring water bodies, rivers and streams, open space areas and hillshade; many "detailed features" including roads, points of interest, place names, and more; and 2D building structure outlines. The three "layers" in this map are also cached separately and may be added to maps individually as needed:Building Structures (2D)Detailed FeaturesTopographic Base>> See a map legend and read more about this map. The tile layer in this basemap is refreshed regularly.

Coral reefs are one of the most diverse and ecologically important areas of the world. However, many reefs, are threatened by ocean temperatures that are increasingly becoming warmer than the coral animals' natural tolerance. According to NOAA, when water is too warm, corals will expel the algae (zooxanthellae) living in their tissues causing the coral to turn completely white. This is called coral bleaching. When a coral bleaches, it is not dead. Corals can survive a bleaching event, but they are under more stress and are subject to mortality.The NOAA Coral Reef Watch program uses satellite data to provide current reef environmental conditions to quickly identify areas at risk for coral bleaching. The station data displayed in this map are derived from satellite based measurements of ocean temperature. These "virtual stations" are not actual buoys or in situ stations transmitting data, rather a spatial analyses for reef locations around the world are derived from 5 km resolution raster data. There are 213 points for the virtual stations around the world along with polygons describing the major tropical coral reef systems. Each station has several variables: Alert Level: an index of the likelihood of coral bleaching, scaled from 0 (no heat stress) to 4 (coral mortality likely) based on the attributes belowSea surface temperature: average temperature of the ocean surface derived from satellite measurementsTemperature anomaly: a comparison of the current surface temperature to the 1981-2010 historical averageHotspots: number of degrees above the coral's threshold toleranceDegree Heating Weeks: accumulated thermal stress experienced by coralsMaintenanceService data is maintained by the Overwrite Feature Service script running as a Scheduled Notebook TaskSee Sample OverwriteFS NotebookRevisionsJan 25, 2024: Updated Legend text for Area Layer, adding clarityJul 28, 2023: Applied updated Symbology and Popups from Coral Reef Bleaching Stations Web Map

【Courtesy of the C. V. Starr East Asian Library University of California, Berkeley】 Japanese date Keiō 2 [1866]. In color. Folded. Title from: Kyōto zu sōmokuroku /Ōtsuka Takashi. p.66. Wood block print. In Japanese. Relief shown pictorially. Includes distance charts, text, and legend. Local Note EAST; F 55: Title added by hand :Kyō saiken ezu. Monted cover title is missing Subject

【Courtesy of the C. V. Starr East Asian Library University of California, Berkeley】 1 map : hand col. ; 61 x 109 cm., folded to 17 x 15 cm., in envelope 31 x 21 cm. Wood block print. In Japanese. Covers Matsumae to Tsushima, Iojima, Ryukyu, and Hachijojima. Title added by hand. Shows distance of sea routes. Includes legend. East Asian Library call number Ca_21.

【Courtesy of the C. V. Starr East Asian Library University of California, Berkeley】 Japanese date Keiō 3 [1867]. In color. Folded. Mounted cover title. Wood block print. In Japanese. Title added by hand. Includes kokudaka and crests of daimyo and legend. Okuyama Seiei kōzu. Orientation varies.