The point cloud layer contains the extents of mobile, terrestrial and airborne laser scanning completed to Main Roads specifications and standards for project planning, design, construction and asset management purposes.This data is used for road investigation, planning, design, construction and asset management.The data within these layers are continually maintained and edited on a daily basis.Data Dictionary: https://bit.ly/3v3V7sz

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. To acquire detailed surface elevation data for use in conservation planning, design, research, floodplain mapping, dam safety assessments, and hydrologic modeling. LAS and bare earth DEM data products are suitable for 1 foot contour generation. USGS LiDAR Base Specification 1.2, QL2. 19.6 cm NVA.This metadata record describes the hydro-flattened bare earth digital elevation model (DEM) derived from the classified LiDAR data for the 2017 Michigan LiDAR project covering approximately 907 square miles, in which its extents cover Oakland County.This data is for planning purposes only and should not be used for legal or cadastral purposes. Any conclusions drawn from analysis of this information are not the responsibility of Sanborn Map Company. Users should be aware that temporal changes may have occurred since this dataset was collected and some parts of this dataset may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. Contact: State of MichiganDue to the large size of the data, downloading the entire county may not be possible. It is recommended to use the live service directly within ArcMap or ArcGIS Pro. For further questions, contact the Oakland County Service Center at 248-858-8812, servicecenter@oakgov.com.

This web map shows Daily mean amount of cloud in Hong Kong.It is created by Hong Kong Observatory under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of CSDI Portal at https://portal.csdi.gov.hk.

Sentinel-2 Level-1C imagery with on-the-fly renderings for visualization. This imagery layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.Sentinel-2 imagery can be applied across a number of industries, scientific disciplines, and management practices. Some applications include, but are not limited to, land cover and environmental monitoring, climate change, deforestation, disaster and emergency management, national security, plant health and precision agriculture, forest monitoring, watershed analysis and runoff predictions, land-use planning, tracking urban expansion, highlighting burned areas and estimating fire severity.Geographic CoverageGlobalContinental land masses from 65.4° South to 72.1° North, with these special guidelines:All coastal waters up to 20 km from the shoreAll islands greater than 100 km2All EU islandsAll closed seas (e.g. Caspian Sea)The Mediterranean Sea Temporal CoverageThis layer includes a rolling collection of Sentinel-2 imagery acquired within the past 14 months.This layer is updated daily with new imagery.The revisit time for each point on Earth is every 5 days.The number of images available will vary depending on location. Product LevelThis service provides Level-1C Top of Atmosphere imagery.Alternatively, Sentinel-2 Level-2A is also available. Image Selection/FilteringThe most recent and cloud free images are displayed by default.Any image available within the past 14 months can be displayed via custom filtering.Filtering can be done based on attributes such as Acquisition Date, Estimated Cloud Cover, and Tile ID.Tile_ID is computed as [year][month][day]T[hours][minutes][seconds]_[UTMcode][latitudeband][square]_[sequence]. More… Visual RenderingDefault rendering is Natural Color (bands 4,3,2) with Dynamic Range Adjustment (DRA).The DRA version of each layer enables visualization of the full dynamic range of the images.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions created.Available renderings include: Agriculture with DRA, Bathymetric with DRA, Color-Infrared with DRA, Natural Color with DRA, Short-wave Infrared with DRA, Geology with DRA, NDMI Colorized, Normalized Difference Built-Up Index (NDBI), NDWI Raw, NDWI - with VRE Raw, NDVI – with VRE Raw (NDRE), NDVI - VRE only Raw, NDVI Raw, Normalized Burn Ratio, NDVI Colormap. Multispectral BandsBandDescriptionWavelength (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 - 2.28020Additional NotesOverviews exist with a spatial resolution of 150m and are updated every quarter based on the best and latest imagery available at that time.To work with source images at all scales, the ‘Lock Raster’ functionality is available. NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.This ArcGIS Server dynamic imagery layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image services API.Images can be exported up to a maximum of 4,000 columns x 4,000 rows per request. Data SourceSentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS, or alternatively access EarthExplorer or the Copernicus Data Space Ecosystem to download the scenes.For information on Sentinel-2 imagery, see Sentinel-2.

This layer displays a global map of land use/land cover (LULC) derived from ESA Sentinel-2 imagery at 10m resolution. Each year is generated with Impact Observatory’s deep learning AI land classification model, trained using billions of human-labeled image pixels from the National Geographic Society. The global maps are produced by applying this model to the Sentinel-2 Level-2A image collection on Microsoft’s Planetary Computer, processing over 400,000 Earth observations per year.The algorithm generates LULC predictions for nine classes, described in detail below. The year 2017 has a land cover class assigned for every pixel, but its class is based upon fewer images than the other years. The years 2018-2024 are based upon a more complete set of imagery. For this reason, the year 2017 may have less accurate land cover class assignments than the years 2018-2024. Key Properties Variable mapped: Land use/land cover in 2017, 2018, 2019, 2020, 2021, 2022, 2023, 2024Source Data Coordinate System: Universal Transverse Mercator (UTM) WGS84Service Coordinate System: Web Mercator Auxiliary Sphere WGS84 (EPSG:3857)Extent: GlobalSource imagery: Sentinel-2 L2ACell Size: 10-metersType: ThematicAttribution: Esri, Impact ObservatoryAnalysis: Optimized for analysisClass Definitions: ValueNameDescription1WaterAreas 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.2TreesAny significant clustering of tall (~15 feet 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).4Flooded 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.5CropsHuman planted/plotted cereals, grasses, and crops not at tree height; examples: corn, wheat, soy, fallow plots of structured land.7Built 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.8Bare 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.9Snow/IceLarge homogenous areas of permanent snow or ice, typically only in mountain areas or highest latitudes; examples: glaciers, permanent snowpack, snow fields.10CloudsNo land cover information due to persistent cloud cover.11RangelandOpen 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.NOTE: Land use focus does not provide the spatial detail of a land cover map. As such, for the built area classification, yards, parks, and groves will appear as built area rather than trees or rangeland classes.Usage Information and Best PracticesProcessing TemplatesThis layer includes a number of preconfigured processing templates (raster function templates) to provide on-the-fly data rendering and class isolation for visualization and analysis. Each processing template includes labels and descriptions to characterize the intended usage. This may include for visualization, for analysis, or for both visualization and analysis. VisualizationThe default rendering on this layer displays all classes.There are a number of on-the-fly renderings/processing templates designed specifically for data visualization.By default, the most recent year is displayed. To discover and isolate specific years for visualization in Map Viewer, try using the Image Collection Explorer. AnalysisIn order to leverage the optimization for analysis, the capability must be enabled by your ArcGIS organization administrator. More information on enabling this feature can be found in the ‘Regional data hosting’ section of this help doc.Optimized for analysis means this layer does not have size constraints for analysis and it is recommended for multisource analysis with other layers optimized for analysis. See this group for a complete list of imagery layers optimized for analysis.Prior to running analysis, users should always provide some form of data selection with either a layer filter (e.g. for a specific date range, cloud cover percent, mission, etc.) or by selecting specific images. To discover and isolate specific images for analysis in Map Viewer, try using the Image Collection Explorer.Zonal Statistics is a common tool used for understanding the composition of a specified area by reporting the total estimates for each of the classes. GeneralIf you are new to Sentinel-2 LULC, the Sentinel-2 Land Cover Explorer provides a good introductory user experience for working with this imagery layer. For more information, see this Quick Start Guide.Global land use/land cover maps provide information on conservation planning, food security, and hydrologic modeling, among other things. This dataset can be used to visualize land use/land cover anywhere on Earth. Classification ProcessThese maps include Version 003 of the global Sentinel-2 land use/land cover data product. It is produced by a deep learning model trained using over five 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 L2A 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 for each year.The input Sentinel-2 L2A data was accessed via Microsoft’s Planetary Computer and scaled using Microsoft Azure Batch. 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.

Maps and Apps Gallery is a configurable group app template that can be used for displaying a collection of maps, applications, documents, and layers. Gallery contents are searchable and can be filtered using item tags. Private gallery content can be accessed by signing in to the app using your ArcGIS credentials.Use Casesbuilding a common operational picture organizing a series of maps & apps for a community eventConfigurable OptionsConfigure Maps and Apps Gallery to present content from any group in your organization and personalize the app by modifying the following options: Display a custom title and logo in the application headerUse a custom color schemeChoose between grid- and list-style layoutsEnable or disable the tag cloud which can be used to filter the items displayed in the galleryChoose to open maps and layers in ArcGIS Online, or to preview them in the app's viewerSupported DevicesThis application is responsively designed to support use in browsers on desktops, mobile phones, and tablets.Data RequirementsMaps and Apps Gallery will display all item types supported by ArcGIS Online and Portal, although sharing maps is preferable to sharing stand-alone layers.Get Started This application can be created in the following ways:Click the Create a Web App button on this pageShare a group 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.Learn MoreFor release notes and more information on configuring this app, see the Maps and Apps Gallery documentation.

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.

Beta Notice: This item is currently in beta and is intended for early access, testing, and feedback. It is not recommended for production use, as functionality and content are subject to change without notice.Sentinel-2, 10m Multispectral 13-band imagery, rendered on-the-fly. Available for visualization and analytics, this Imagery Layer pulls directly from the Sentinel-2 on AWS collection and is updated daily with new imagery.This imagery layer can be used for multiple purposes including but not limited to vegetation, plant health, land cover and environmental monitoring.Geographic CoverageGlobalContinental land masses from 65.4° South to 72.1° North, with these special guidelines:All coastal waters up to 20 km from the shoreAll islands greater than 100 km2All EU islandsAll closed seas (e.g. Caspian Sea)The Mediterranean SeaNote: Areas of interest going beyond the Mission baseline (as laid out in the Mission Requirements Document) will be assessed, and may be added to the baseline if sufficient resources are identified.Temporal CoverageThe revisit time for each point on Earth is every 5 days.This layer is updated daily with new imagery.This imagery layer is designed to include imagery collected within the past 14 months. Custom Image Services can be created for access to images older than 14 months.The number of images available will vary depending on location.Image Selection/FilteringThe most recent and cloud free image, for any location, is displayed by default.Any image available, within the past 14 months, can be displayed via custom filtering.Filtering can be done based on Acquisition Date, Estimated Cloud Cover, and Tile ID.Tile_ID is computed as [year][month][day]T[hours][minutes][seconds]_[UTMcode][latitudeband][square]_[sequence]. More…NOTE: Not using filters, and loading the entire archive, may affect performance.Analysis ReadyThis imagery layer is analysis ready with TOA correction applied.Visual RenderingDefault rendering is Color-Infrared (bands 8,4,3) with Dynamic Range Adjustment (DRA).This DRA version enables visualization of the full dynamic range of the images. The non-DRA version of this layer can be viewed by switching to the pre-defined Color Infrared raster function.Bands near-infrared, red, green with dynamic range adjustment applied. Healthy vegetation is bright red while stressed vegetation is dull red.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions created.Available renderings include: Agriculture with DRA, Bathymetric with DRA, Natural Color with DRA, Short-wave Infrared with DRA, Geology with DRA, NDMI Colorized, Normalized Difference Built-Up Index (NDBI), NDWI Raw, NDWI - with VRE Raw, NDVI – with VRE Raw (NDRE), NDVI - VRE only Raw, NDVI Raw, Normalized Burn Ratio, NDVI Colormap.Multispectral BandsBandDescriptionWavelength (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 - 2.28020Additional NotesOverviews exist with a spatial resolution of 150m and are updated every quarter based on the best and latest imagery available at that time.To work with source images at all scales, the ‘Lock Raster’ functionality is available.NOTE: ‘Lock Raster’ should only be used on the layer for short periods of time, as the imagery and associated record Object IDs may change daily.This ArcGIS Server dynamic imagery layer can be used in Web Maps and ArcGIS Desktop as well as Web and Mobile applications using the REST based Image services API.Images can be exported up to a maximum of 4,000 columns x 4,000 rows per request.Data SourceSentinel-2 imagery is the result of close collaboration between the (European Space Agency) ESA, the European Commission and USGS. Data is hosted by the Amazon Web Services as part of their Registry of Open Data. Users can access the imagery from Sentinel-2 on AWS , or alternatively access Sentinel2Look Viewer, EarthExplorer or the Copernicus Open Access Hub to download the scenes.For information on Sentinel-2 imagery, see Sentinel-2.

The Network Model digitally represents England’s Strategic Road Network. The model contains critical information about our road’s location, names, lanes and widths. The Network Model was derived from Ordnance Survey (OS) Highways data and enriched with internal datasets. It reflects National Highways roads that are open for traffic and have been validated against our Operational Highway Boundary (RedLine). To ensure the model remains accurate, we have implemented processes to track changes across the network. However, if you have noticed any inaccuracies in the data, please report it here. (https://survey123.arcgis.com/share/283607b463dc4db985f9bc28e9e90b9d?portalUrl=https://highways-england.cloud.esriuk.com/portal) This form is to be used to report data issues only. In this initial release, speed limit and smart motorway information has been removed pending data validation. For maintenance issues on the network please report here. (https://report.nationalhighways.co.uk/) For non-emergency incidents please contact our Customer Contact Centre on 0300 123 5000. The data is published under an Open Government Licence.

Virginia LiDARThe Virginia LiDAR Inventory Web Mapping Application provides access to LiDAR point cloud and individual project metadata collected in the Commonwealth of Virginia according to the USGS 3DEP specification. Data is obtained from NOAA and USGS data portals. LiDAR Point Clouds are compressed for file storage and transfer. Informational Access Type:1) LiDAR Project Metadata: To download individual LiDAR project Metadata, click on a LiDAR inventory polygon for link to the host FTP site. Once at the host site, locate appropriate directory and .zip file to receive project documentation and accompanying project files. For use within ArcGIS, the geospatial grid and inventory data powering the VGIN LiDAR download inventory services can be downloaded under conversion and analysis resources below.2) LiDAR Point Clouds (Single): To download individual tiles, zoom in on the map until the tile grid appears. The VGIN Composite Geocoding service is available to use when querying by physical address, feature, or community anchor institution name. Click a tile to identify grid information for individual LiDAR Point clouds. Columns note where the LiDAR is hosted and what format is available for download. In many instances, multiple results are returned due to multiple file formats and flight years. If LiDAR data is missing spatial reference information please refer to the metadata in step 1 above. Tile grids are stacked so you will need to scroll through selections:3) LiDAR Point Clouds (Bulk): To download multiple files in a single FTP directory folder, which can be a necessity in many instances, consider the use of a multi-file download manager plugin to use with your browser in conjunction with the URLs provided on the LiDAR inventory polygon. If LiDAR data is missing spatial reference information please refer to the metadata in step 1 above. For use within ArcGIS, the geospatial grid and inventory data powering the VGIN LiDAR Download Inventory Services can be downloaded under conversion and resources below.Conversion and Resources:Convert to LAS from USGS/NOAA hosted .LAZ filesDownload LiDAR Inventory Data Project FootprintsDownload LiDAR Inventory Tile GridContact:For questions about the data please contact USGS For questions about the application please contact vbmp@vdem.virginia.gov

The Download Tool is available through CT ECO, a partnership between UConn CLEAR and CT DEEP. The tool provides easy download access to aerial imagery and lidar elevation collected during multiple flights.

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This layer is a hydro-flattened bare earth digital elevation model (DEM) derived from the classified Lidar point cloud covering the state of Connecticut.

The 3D scene is shown in the UC 2020 Plenary demo, AI and Deep Learning.The video of the plenary demonstration is here.

Landsat 8's Operational Land Imager collects new imagery for a given location every 16 days. The Normalized Difference Moisture Index (NDMI) estimates levels of moisture in vegetation. Wetlands and other vegetated areas with high levels of moisture appear as blue whereas deserts appear as tan to brown. This map is updated on a daily basis, retaining the 4 most recent scenes for each path/row that have cloud coverage < 50%, plus the scene closest to the corresponding GLS 2000 scene. Over time the older or cloudier scenes will be removed from the service. Each scene has attributes such as the acquisition date and estimated cloud cover percentage, which can be seen by clicking on the image. By default the map shows the most recent scenes, but by enabling time animation on the imagery layer, it is possible to restrict the displayed scenes to specific date range. Filters can be set to restrict and order the scenes based on other attributes as well.At scales smaller than 1:1 Million, overviews with 300m resolution are shown. To work with an individual scene at all scales use the lock raster functionality - (Set display order to a list of images Web Maps). Note that ‘Lock Raster’ should not be used on the service except for short periods of time, since each day a new service is created the Object IDs will change.Important Note: This web map shows imagery from the Landsat 8 Views image service, which is a free service and doesn't need any subscription. Similar services exist for returning PanSharpened, Panchromatic, and Analytic (full bit depth) imagery. Landsat data can also be accessed at https://landsatlook.usgs.gov/For more information on Landsat 8 imagery, see https://landsat.usgs.gov/landsat8.php.

This image service is available through CTECO, a partnership between UConn CLEAR and CT DEEP. This layer is a hydro-flattened bare earth digital elevation model (DEM) derived from the classified Lidar point cloud covering the state of Connecticut.

Indonesia flight routes from Ministry of Transportation (Kementerian Perhubungan). Extracted from MoT ArcGIS REST Services: https://portal-gis.dephub.go.id/server/rest/services/Tematik_Perhubungan_KementerianLembaga/FeatureServer/3

Overlay zoning boundaries were compiled by the MVC or MassGIS depending on the date of edit for a particular overlay district. Each district is listed as an independent data layer that can be turned on or off on the map.The Chilmark parcel boundaries have been loaded in directly from the MassGIS ArcGIS OnLine cloud portal.

This dataset contains GIS layers that depict the known spatial distributions (i.e., ranges) and reported breeding areas of ribbon seals (Histriophoca fasciata). It was produced as part of a U.S. Endangered Species Act status review, which included delineating the species in question and assessing its risk of extinction within the foreseeable future throughout all or a significant portion of its range. Its boundaries are based on previously published range maps and/or descriptions of the species' distribution in published or unpublished accounts. All boundaries should be considered approximate.Metadata accessed here:https://inport.nmfs.noaa.gov/inport/item/28181Data hosted as an online resource can be accessed here:https://console.cloud.google.com/storage/browser/nmfs_odp_afsc/MML/PEP/Ribbon%20Seal%20Distribution

This dataset contains GIS layers that depict the known spatial distributions (i.e., ranges) of the two subspecies of bearded seals (Erignathus barbatus). It was produced as part of a U.S. Endangered Species Act status review, which included delineating the species in question and assessing its risk of extinction within the foreseeable future throughout all or a significant portion of its range. Its boundaries are based on previously published range maps and/or descriptions of the species' distribution in published or unpublished accounts. All boundaries should be considered approximate. The approximate North American boundary between the two sub-species was changed to 130W (from 112W), based a re-analysis of the genetic data.Metadata accessed here:https://inport.nmfs.noaa.gov/inport/item/28177Data hosted as an online resource can be accessed here:https://console.cloud.google.com/storage/browser/nmfs_odp_afsc/MML/PEP/Bearded%20Seal%20Distribution

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. Oakland County participated in the Southeast Michigan Regional Orthoimagery project encompassing approximately 5000 square miles, which includes an additional ½ mile buffer beyond the boundary of the seven county region. This extends approximately 500 feet into Canada. The orthoimagery is true color with a base pixel resolution of 6 inches for the County-only imagery. Orthoimagery tiles were delivered in Tiff format with Tiff world files representing ground dimensions of 2000' x 3000'. Tile naming convention includes the county code, the third and fourth digit of the lower left X and the first three digits of the lowerY coordinate and the year flown. For example 161 2005, tile name would be 1612932405). Countywide and community mosaics are saved in the MrSID format. Community MrSID files are compressed at 20 to 1 using the 6 inch pixel imagery and countywide MrSIDs are compressed at 50 to 1 using the 2 foot pixel imagery. All control was based on the following -Michigan State Plane (South) -Horizontal datum -North American Datum (NAD 83) international feet second-order class I. -Vertical datum - North American Vertical Datum 1988 (NAVD88) international feet, third-order class I. All imagery was taken in the spring of 2005. Acquisition was attempted when the ground was not obscured by haze, smoke, dust, clouds or cloud shadows, and snow or ice. Flights were scheduled when solar angle was at least 30 degrees or more above the horizon Orthoimagery complies with the American Society for Photogrammetry and Remote Sensing Accuracy Standards for Class 1 mapping requirements.