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Extract coordinates for series of georeferenced files in ArcGIS 10?

Extract coordinates for series of georeferenced files in ArcGIS 10?


I have a series of 1900 spatially continuous images that are georeferenced. Each image is a tif file paired with a tfw file.

These images are easily open and shown in ArcMap 10. However, I need a way to extract and tabulate all of their associated coordinates (in this case, the centerpoints of each image) into a spreadsheet.

How do I do this? Please note that I have no scripting abilities.

Thanks!


In arcmap 10.
I think I would use the footprint feature (in mosaic dataset) and
then generate the centroid of those polygons.
add an x and a y field to my attribute table,
calculate the geometry,
then export to dbf and convert to xls.
Also found in this answer are several resources for esri help.


Resource maintenance Update frequency unknown

ArcGIS coordinate system * Type Projected * Geographic coordinate reference GCS_North_American_1983 * Projection NAD_1983_UTM_Zone_15N * Coordinate reference details Projected coordinate system Well-known identifier 26915 X origin -10158462.226681 Y origin -9998099.9919429999 XY scale 6400 Z origin 0 Z scale 1 M origin 0 M scale 1 XY tolerance 0.02 Z tolerance 0.001 M tolerance 0.001 High precision true Latest well-known identifier 26915 Well-known text PROJCS["NAD_1983_UTM_Zone_15N",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-93.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26915]]
Reference system identifier * Value 26915 * Codespace EPSG * Version 8.2.6


Resource maintenance Update frequency unknown

ArcGIS coordinate system * Type Projected * Geographic coordinate reference GCS_North_American_1983 * Projection NAD_1983_UTM_Zone_15N * Coordinate reference details Projected coordinate system Well-known identifier 26915 X origin -10158462.226681 Y origin -9998099.9919429999 XY scale 6400 Z origin 0 Z scale 1 M origin 0 M scale 1 XY tolerance 0.02 Z tolerance 0.001 M tolerance 0.001 High precision true Latest well-known identifier 26915 Well-known text PROJCS["NAD_1983_UTM_Zone_15N",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-93.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26915]]
Reference system identifier * Value 26915 * Codespace EPSG * Version 8.2.6


Resource maintenance Update frequency unknown

ArcGIS coordinate system * Type Projected * Geographic coordinate reference GCS_North_American_1983 * Projection NAD_1983_UTM_Zone_15N * Coordinate reference details Projected coordinate system Well-known identifier 26915 X origin -10158462.216681 Y origin -9998099.9919429999 XY scale 6400 Z origin 0 Z scale 1 M origin 0 M scale 1 XY tolerance 0.02 Z tolerance 0.001 M tolerance 0.001 High precision true Latest well-known identifier 26915 Well-known text PROJCS["NAD_1983_UTM_Zone_15N",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-93.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26915]]
Reference system identifier * Value 26915 * Codespace EPSG * Version 8.2.6


Raster and world file import to ArcGis, What are the map units?

In short: I thought the map units would be in meter or km, but this doesn't seem right. Are they in decimal degrees? Can this be set as an option in ArcGis?

I'm cooperating with a researcher using ArcGIS to overlay some computer vision images on a map. I've created a world file to test the raster import in ArcGIS, but I seem to have gotten the scaling wrong.

I've created a jgw file to accompany a 1600x1600 pixel image which should cover an 8 by 8 meter square. I've managed to position and rotate it correctly, but the scaling is very much off.

Update: I tried, pretty much on random to downscale the image, and sent my colleague this file (Note that i miss-typed the number of decimals on line 1 and 4:

The resulting image looks like this, a lot closer to what I am looking for.

I've created the jgw file using a simple python script reading a csv file of the corner positions.


Segment Images

Segmentation is the process of partitioning an image into objects by grouping neighboring pixels with common values. The objects in the image ideally correspond to real-world features. Effective segmentation ensures that classification results are more accurate.

  1. Enable the Preview option in the Object Creation panel. A Preview Window appears with segments outlined in green.
  2. Under Segment Settings, select an Algorithm from the drop-down list provided. The following options are available:
    • Edge: Best for detecting edges of features where objects of interest have sharp edges. Set an appropriate Scale Level and Merge Level (see steps below) to effectively delineate features.
    • Intensity: Best for segmenting images with subtle gradients such as digital elevation models (DEMs) or images of electromagnetic fields. When selecting this method, don't perform any merging set the Merge Level to 0. Merging is used primarily to combine segments with similar spectral information. Elevation and other related attributes are not appropriate for merging.

See Watershed Algorithm Background for more detailed descriptions of each option.

Tip: For best segmentation results, select a combination of bands that have similar spectral ranges such as R, G, B, and NIR bands. You should not perform segmentation with a combination of custom bands (normalized difference or HSI color space) and visible/NIR bands. You can perform segmentation on the normalized difference or color space bands by themselves, but not in combination with visible and NIR bands.

  • Full Lambda Schedule: (default). Merges small segments within larger, textured areas such as trees or clouds, where over-segmentation may be a problem.
  • Fast Lambda: Merges adjacent segments with similar colors and border sizes.

See Merge Algorithms Background for more detailed descriptions of each option.


Gathering Data in the Field with the Collector for ArcGIS App

When I first started working with GIS, I often wondered, where did all of this spatial data come from? As I progressed through my initial undergrad coursework and internship experiences, the answers quickly revealed themselves. Some of the data is created by someone sitting at a desk. Other data is automatically generated as a subset or byproduct of another dataset. A large amount of data, however, is collected on-site, by people in the field.

When I began my first internship I was doing exactly that. Weather permitting, I would be out in the field collecting data with a high-tech, high-end Trimble GPS.

As many of us know, GIS does not typically have the capability or need to achieve survey-grade accuracy. For this reason, it has become an increasingly popular choice to skip purchasing a $10,000 GPS unit and instead purchase an Android tablet or iPad for $1000 or less. This trend has been on the rise ever since powerful tablets with an acceptable battery life for mobile data collection became an affordable option. Because of this, GIS software companies have developed native Android and iOS apps for mobile spatial data collection. There are several apps out there, including free and open source options. Data collection with these native apps can even be performed on a smart phone.

Two Options for Mobile Data Collection

This post will focus on ESRI’s Collector for ArcGIS app, as it will tie in with the article I wrote two weeks ago detailing how to create and host a dataset in ArcGIS Online tailored for mobile data collection.

Collector for ArcGIS

The Collector app is available on the Google Play store for Android and the App Store for iOS. After downloading the app, login to your organization’s account just as you would on ArcGIS Online. Any webmaps that exist in your organization’s ArcGIS Online account will be visible in the Collector’s main menu.

Collector for ArcGIS Main Menu

Select and open the map that you wish to collect data in. In this case, the Inventory map that was created in the previous blog post. The Collector’s map interface is relatively simple and its capabilities are intuitive and user friendly. Depending on your device, the layout may be slightly different, but the same functionality is present across all device types. Below is a screenshot of the initial Collector window, with a brief outline of what each button does.

  1. The maps button will return to the main menu.
  2. The find my location button will use your device’s built in GPS to find your location and display it on the map.
  3. The bookmarks button allows for saving of specific locations / map extents as bookmarks. This eliminates the guesswork if you need to quickly reference or jump between two areas.
  4. If you are collecting more than one type of feature, the Layers tool is useful for turning on and off datasets when one type may not be in use.
  5. The search tool works like a Google Maps search, allowing you to search for and zoom to any location on Earth. It can also be configured to search through attribute values for a feature layer in the map.
  6. The measurement tool allows you to measure distances and areas by drawing temporary lines and polygons on the map.
  7. The basemap tool allows you to select and change the basemap. Available basemaps include Topographic, Imagery (and an option to include labels), OpenStreetMap, ESRI Streets, Terrain, and the USGS National Map, among others. You can also create and load a custom basemap if, for example, you have higher resolution imagery available for your study area.
  8. Clicking on or dragging the plus sign to the left will allow for the creation of new features. Feature templates defined in ArcMap or ArcGIS Online will be visible here for any feature layer that is present in the webmap.

Once you’ve familiarized yourself with the tools available in the Collector, you can begin collecting data. Click on or pull the plus sign (point 8) to the left to see templates available for creation. On some versions of the Collector, the location of the feature will automatically be assigned your current location. If this doesn’t automatically begin, you can click the symbol that looks like a person with the find my location target next to it to use your location for the feature. You can also tap any location on the map to set the feature’s location to that point. The Collector also allows you to draw vertices for line and polygon feature layers this way. There is also the capability to “walk” a line or polygon feature, the Collector will drop a verticy at a predefined distance as you walk along a feature until you tell it to stop.

A Feature Collected in the Field

Next, you can begin assigning values to the attributes for that feature. Note that the domain value lists are present for the attributes that you configured to have them. This helps to greatly streamline a collection effort and can cut the time it takes to collect a single feature tremendously. Editing can be done in the field if any mistakes were made, and the progress of the inventory can be seen back at the office in real time as the collection effort occurs in the field.

In the next blog post, I will go further in how to utilize ArcGIS Online’s suite of tools to better represent, share, and understand the data that has been collected.


VPmap series

VPmap Series bridges the gap between scans of plans and maps and graphical information systems, such as GIS and FM.

Floor plans, paper maps, satellite images, and aerial photography are a major data source for GIS or Facility Management. Fully equipped, easy to use and independent from any target system, VPmap Series provides accurate integration, calibration and conversion of original documents with two solution alternatives: VPmap and VPmap pro.

Large format scanners deliver digital "raster" images in good quality. However, for capturing and transferring content information a specialized software is indispensable - the perfect solution is VPmap Series. Georeferencing, image correction, data reduction and interactive or automatic conversion of contours and shapes: with VPmap Series you can avoid the tedious procedures associated with traditional digitizing most elegantly and efficiently.

VPmap Series supports scan integration in all fields, such as building and room administration, infrastructure planning, cadastral records, land development, land survey, geology and many more. The smart technology of VPmap Series will reduce costs considerably and adds substantial value to existing documents.

VPmap and VPmap pro provide professional interactive tools to create and edit spatial data and attribute information from scanned maps for transfer into GIS. Simply convert raster maps into vector-based maps, utilize intelligent attribute-definition functions, and add individual attributes. The VPmap Series is targeted at GIS applications, mainly to transfer scanned maps into ArcGIS (ESRI), MapInfo, AutoCAD Civil/Map 3D etc. Thus, VPmap and VPmap pro contain GeoTIFF, Shapefile SHP, and MIF support for import and export explicitly to and from any common GIS platform.

With all VPmap Series products you can make your choice whether you want to run them inside your AutoCAD, BricsCAD, or ZWCAD, or if you prefer stand-alone operation. Floating license network operation is supported at no extra costs.

The state of the art integrated text recognition module (OCR) supports next to latin also greek and kyrilic characters. Optional an additional license for the 4 asian writings kanji, korean, and traditional and simplified chinese is available.

Available language versions:

See VPmap Series in Action:

Merging of two scanned maps

Quick Conversion for GIS:

A unique set of recognition features assists in digitizing scanned maps or aerial images. Even multicolored altitude lines will be converted easily into splines and polylines. Plus, with an exceptional algorithm, area objects turn into polygons or polylines. A single click is all you need to digitize buildings and properties in cadastral maps. Attribute assignment and automatic equalization in bordering outlines of traced objects are included. VPmap pro also includes automatic raster to vector conversion, especially for cadastral or contour maps. Save time and benefit from softelec's internationally reputed vectorization technology!

Raster Conversion:

VPmap Series imports almost any raster file format. Just scan your maps, or use satellite images as the first step to build up your geographical information system (GIS). Both products support easy, interactive tools to vectorize and recognize outlines and even reduce the color depth by intelligent color handling. In addition, VPmap pro offers functions for automatic vectorization and symbol recognition.

High Precision Georeferencing:

Exact and high-speed calibration is essential for digital map processing. VPmap Series offers multiple options for selecting the most suitable method: polynomial or triangular, full manual control or automatic input support, import coordinate values, assign point positions from a reference source or select a map projection.

Color Reduction:

Without any losses colors and color areas can be combined directly. Also, extract information from colors most rapidly: single colors or color patterns can be separated and exported individually.

Attribute Determination:

VPmap Series features sophisticated ways to simply recognize shape-based geometrical information and convert them to geographical attributes of entities. In addition you can define or import your own attribute tables and fill them interactively.

Geographical Information Query:

VPmap Series enables quick input of attribute-based queries. Results will be visually displayed in the image or drawing.

Export for GIS:

VPmap Series offers export to the most common GIS systems, like MapInfo, ArcGIS/ArcInfo, or AutoCAD Civil/Map 3D. Raster information will be exported as well as entities and their attributes.

One Product includes Two Licenses:

While the stand-alone installation provides fast execution of operations and easy handling, the installation with AutoCAD, AutoCAD Civil/Map 3D, BricsCAD, or ZWCAD gives the possibility to simultaneously running VPmap Series with other AutoCAD/BricsCAD/ZWCAD applications. VPmap Series provides these options in just one license - even running at the same time!


This tutorial will teach you to extract features from georeferenced maps and store them in a geodatabase for use in ArcGIS.

Here are the basic steps we will go through in this tutorial:

  1. Download the ArcMap project containing the georeferenced map and extract it a local drive.
  2. Create a new file geodatabase for storing the spatial data.
  3. Create new layers (feature classes) for each theme of data being created.
  4. Digitize features from the map using ArcGIS.
  • You have basic computer skills and understand Windows directory structures.
  • You have a good internet connection.
  • You have ArcGIS 10 working on your computer.

The map used in this exercise is scanned (and used with permission) from “Forward is the Motto of Today” Street Railways in Charlottesville, Virginia 1866 – 1936 which is a detailed history of Charlottesville streetcar system.

We will create three layers – routes, system features, and city limits – from the map. We will add name and type attributes to the system features and routes layers.


Positional Accuracy and Geographic Bias of Four Methods of Geocoding in Epidemiologic Research

We examined the geographic bias of four methods of geocoding addresses using ArcGIS, commercial firm, SAS/GIS, and aerial photography. We compared “point-in-polygon” (ArcGIS, commercial firm, and aerial photography) and the “look-up table” method (SAS/GIS) to allocate addresses to census geography, particularly as it relates to census-based poverty rates.

Methods

We randomly selected 299 addresses of children treated for asthma at an urban emergency department (1999–2001). The coordinates of the building address side door were obtained by constant offset based on ArcGIS and a commercial firm and true ground location based on aerial photography.

Results

Coordinates were available for 261 addresses across all methods. For 24% to 30% of geocoded road/door coordinates the positional error was 51 meters or greater, which was similar across geocoding methods. The mean bearing was −26.8 degrees for the vector of coordinates based on aerial photography and ArcGIS and 8.5 degrees for the vector based on aerial photography and the commercial firm (p < 0.0001). ArcGIS and the commercial firm performed very well relative to SAS/GIS in terms of allocation to census geography. For 20%, the door location based on aerial photography was assigned to a different block group compared to SAS/GIS. The block group poverty rate varied at least two standard deviations for 6% to 7% of addresses.

Conclusion

We found important differences in distance and bearing between geocoding relative to aerial photography. Allocation of locations based on aerial photography to census-based geographic areas could lead to substantial errors.