The arrival of ArcGIS Pro has brought a challenge to ArcMap users. The new software is sufficiently different in architecture and layout that switching from the old to the new is not a simple process. In some ways, Pro is harder to learn for ArcMap users than for new GIS users, because some workflows have to be unlearned, or at least heavily modified. Current ArcMap users are pressed for time, trying to learn the new software while still completing their daily tasks, so a book that teaches Pro from the start is not an efficient method.Switching to ArcGIS Pro from ArcMap aims to quickly transition ArcMap users to ArcGIS Pro. Rather than teaching Pro from the start, as for a novice user, this book focuses on how Pro is different from ArcMap. Covering the most common and important workflows required for most GIS work, it leverages the user’s prior experience to enable a more rapid adjustment to Pro.AUDIENCEProfessional and scholarly; College/higher education; General/trade.AUTHOR BIOMaribeth H. Price, PhD, South Dakota School of Mines and Technology, has been using Esri products since 1991, teaching college GIS since 1995 and writing textbooks utilizing Esri’s software since 2001. She has extensive familiarity with both ArcMap/ArcCatalog and Pro, both as a user and in the classroom, as well as long experience writing about GIS concepts and developing software tutorials. She teaches GIS workshops, having offered more than 100 workshops to over 1,200 participants since 2000.Pub Date: Print: 2/14/2019 Digital: 1/28/2019 Format: PaperbackISBN: Print: 9781589485440 Digital: 9781589485457 Trim: 8 x 10 in.Price: Print: $49.99 USD Digital: $49.99 USD Pages: 172Table of ContentsPreface1 Contemplating the switch to ArcGIS ProBackgroundSystem requirementsLicensingCapabilities of ArcGIS ProWhen should I switch?Time to exploreObjective 1.1: Downloading the data for these exercisesObjective 1.2: Starting ArcGIS Pro, signing in, creating a project, and exploring the interfaceObjective 1.3: Accessing maps and data from ArcGIS OnlineObjective 1.4: Arranging the windows and panesObjective 1.5: Accessing the helpObjective 1.6: Importing a map document2 Unpacking the GUIBackgroundThe ribbon and tabsPanesViewsTime to exploreObjective 2.1: Getting familiar with the Contents paneObjective 2.2: Learning to work with objects and tabsObjective 2.3: Exploring the Catalog pane3 The projectBackgroundWhat is a project?Items stored in a projectPaths in projectsRenaming projectsTime to exploreObjective 3.1: Exploring different elements of a projectObjective 3.2: Accessing properties of projects, maps, and other items4 Navigating and exploring mapsBackgroundExploring maps2D and 3D navigationTime to exploreObjective 4.1: Learning to use the Map toolsObjective 4.2: Exploring 3D scenes and linking views5 Symbolizing mapsBackgroundAccessing the symbol settings for layersAccessing the labeling propertiesSymbolizing rastersTime to exploreObjective 5.1: Modifying single symbolsObjective 5.2: Creating maps from attributesObjective 5.3: Creating labelsObjective 5.4: Managing labelsObjective 5.5: Symbolizing rasters6 GeoprocessingBackgroundWhat’s differentAnalysis buttons and toolsTool licensingTime to exploreObjective 6.1: Getting familiar with the geoprocessing interfaceObjective 6.2: Performing interactive selectionsObjective 6.3: Performing selections based on attributesObjective 6.4: Performing selections based on locationObjective 6.5: Practicing geoprocessing7 TablesBackgroundGeneral table characteristicsJoining and relating tablesMaking chartsTime to exploreObjective 7.1: Managing table viewsObjective 7.2: Creating and managing properties of a chartObjective 7.3: Calculating statistics for tablesObjective 7.4: Calculating and editing in tables8 LayoutsBackgroundLayouts and map framesLayout editing proceduresImporting map documents and templatesTime to exploreObjective 8.1: Creating the maps for the layoutObjective 8.2: Setting up a layout page with map framesObjective 8.3: Setting map frame extent and scaleObjective 8.4: Formatting the map frameObjective 8.5: Creating and formatting map elementsObjective 8.6: Fine-tuning the legendObjective 8.7: Accessing and copying layouts9 Managing dataBackgroundData modelsManaging the geodatabase schemaCreating domainsManaging data from diverse sourcesProject longevityManaging shared data for work groupsTime to exploreObjective 9.1: Creating a project and exporting data to itObjective 9.2: Creating feature classesObjective 9.3: Creating and managing metadataObjective 9.4: Creating fields and domainsObjective 9.5: Modifying the table schemaObjective 9.6: Sharing data using ArcGIS Online10 EditingBackgroundBasic editing functionsCreating featuresModifying existing featuresCreating and editing annotationTime to exploreObjective 10.1: Understanding the editing tools in ArcGIS ProObjective 10.2: Creating pointsObjective 10.3: Creating linesObjective 10.4: Creating polygonsObjective 10.5: Modifying existing featuresObjective 10.6: Creating an annotation feature classObjective 10.7: Editing annotationObjective 10.8: Creating annotation features11 Moving forwardData sourcesIndex

SBAS (Sediment Budget Analysis System) for ArcGIS Desktop provides a framework for formulating, documenting, and calculating sediment budgets, including estimation of uncertainty. This Windows application (ESRI ArcMap Toolbox) allows users to define a conceptual budget visually by creating a series of cells and arrows that represent sources, sinks, and flux rates. It then calculates quantitative "micro" (local) and "macro" (regional) sediment budgets, using a pre-defined sediment-budget equation.

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

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

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

See the DNRGPS application documentation for more details.

Compatible with: Windows (XP, 7, 8, 10, and 11), ArcGIS shapefiles and file geodatabases, Google Earth, most hand-held Garmin GPSs, and other NMEA output GPSs

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

Prerequisite: .NET 4 Framework

DNR Data and Software License Agreement

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

Important Note: 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 ViewerTo 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:ProductNameis2020-2021By 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 ProTo 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 2022What 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

These estuarie polygon conservation features were derived by heads-up digitization using ArcGIS 10 and the Microsoft Bing(tm) Maps Aerial or ESRI World Imagery displayed as the reference imagery (ArcGIS Online Resource Center at http://resources.esri.com/arcgisonlineservices/).These DataSets projected to the Web Mercator projection. Problems with this data set are as follows not all of the caribbean has high quality of imagery so some of these areas were not able to be done. This dataset was complete on July 15 , 2011

These Lagoons polygon conservation features were derived by heads-up digitization using ArcGIS 10 and the Microsoft Bing(tm) Maps Aerial or ESRI World Imagery displayed as the reference imagery (ArcGIS Online Resource Center at http://resources.esri.com/arcgisonlineservices/).These DataSets projected to the Web Mercator projection. Problems with this data set are as follows not all of the caribbean has high quality of imagery so some of these areas were not able to be done. This dataset was complete on July 15 , 2011

SGID10.LOCATION.Buildings was derived from building footprints generated by Microsoft for all 50 States https://github.com/Microsoft/USBuildingFootprints In some cases the pixel prediction algorithm used by Microsoft identified and created building footprints where no buildings existed. To flag potential errors, building footprints within 750 meters of known populated areas (SGID10.DEMOGRAPHIC.PopBlockAreas2010_Approx) and within 500 meters of an address point (SGID10.LOCATION.AddressPoints) were selected and indentified as being a likely structure, footprints falling outside these areas were identified as possible buildings in the 'TYPE' field. In addition, attributes were added for address, city, county, and zip where possible.

Laatste update: 10 maart 2025Gebruikers die graag met Microsoft Excel werken kunnen met de ArcGIS for Excel Add-in hun feature layers aanmaken en bewerken vanuit Excel. Ook voor gebruikers die minder vaak met Excel werken kunnen met deze Add-In gebruik maken van nieuwe functionaliteiten. In dit artikel wordt besproken hoe de Add-in kan worden toegevoegd, hoe vanuit Excel een feature layer aangemaakt kan worden, hoe een bestaande feature layer bewerkt kan worden vanuit Excel en hoe aan de hand van functies coördinaten en adressen van punten berekend kunnen worden.