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Add attribute information from polyline to a point shapefile (QGIS or ArcGIS)

Add attribute information from polyline to a point shapefile (QGIS or ArcGIS)


Is it possible to add attribute information from a polyline to a point dataset. I have a network layer with information per street how many scooters went over this street. I also have a point dataset of people with information on the level of noise annoyance. I want to add the number of scooters passed by to be added in the attribute table of the point layer. Not all points are exactly on the lines of the streets, so maybe there is a functions which links the closest line with its attributes to the point layer.

Is this possible and if so, how do I manage this?

I have ArcGIS and QGIS software installed.


In ArcGIS, you can use "spatial join" tool or right click on the points > joins and relate > join > join based on location.

In QGIS, ther is a similar function (vector >data management tool > join attribute by location)


In ArcGIS Desktop, personally I would look into the "Near" tool http://help.arcgis.com/en/arcgisdesktop/10.0/help/index.html#//00080000001q000000

If you run this tool, you would end up with the ObjectID/FeatureID of the closest road segment for each observation point. So then you could just to a regular table join based on that new value joining it back to the roads and you could get any attribute information from the road segment that's closest to each point, including your noise observation levels.

The reason I suggest this for your problem is first, it will give you the nearest street segment for each point, even if the points are not right on the street. Second, it can give you the distance the point is from the closest spot on the road, so if you wanted to consider how far each noise observation is from the road affecting things, the near tool could help add that extra dimension to your analysis.


Depending on how many points you have, you can consider the Attribute Transfer Tool in ArcGIS: http://desktop.arcgis.com/en/arcmap/10.3/manage-data/editing-existing-features/transferring-attributes-between-features.htm

It is manual but it is easy to map fields between features and get correct results everytime.


Exporting attribute fields to CAD as text

This workflow demonstrates how to export feature attributes to a CAD file as text elements using a point feature class and reserved CAD fields CADType and TxtValue. A common application for this workflow is to generate CAD text at the centroid of polygon features such as states, counties, or parcels.

The point feature is derived from an existing linear feature. It is used to provide a coordinate location for each text element in the CAD file. The resulting output CAD file will contain a text entity positioned at each point feature location.


To represent the data it is needed to follow the next steps. The files used can be downloaded from here.

1. Save data in CSV format

If you have an Excel file, convert the sheet where the data is stored to .csv format (Comma-separated values).

2. Know the coordinate system of the data

It is necessary to know the coordinate system of the data, whether it is geographic or projected coordinates. You can find more information here.

3. Add the delimited text layer

To import the spreadsheet, use the icon "Add Delimited Text Layer" located on the left inferior corner of the screen.

4. Choose the East and North columns

Using the "Explore" button choose the CSV file that needs to be imported.

Then, where it says "Coordinate X" and "Coordinate Y" choose from the dropdown menu the name of the Excel columns that have the values indicated.

5. Especify the projection system

With the "Filter" option it is possible to search and choose an specific coordinate system. If the EPSG code is known, is easier to find it. After choosing it, make sure that the coordinate system selected shows in "selected CRS".

6. Save as an ESRI Shapefile

Until now, what we are seeing is just a temporary spatial representation of a table, which is seen in this way:

To save this representation as an ESRI shapefile, right click on the layer and choose "Save As. ". In the new window specify the name and the desired location to save the file. It is even possible to make changes in the projection system here.

Just click "Accept", and voilà!

Saul Montoya

Saul Montoya es Ingeniero Civil graduado de la Pontificia Universidad Católica del Perú en Lima con estudios de postgrado en Manejo e Ingeniería de Recursos Hídricos (Programa WAREM) de la Universidad de Stuttgart con mención en Ingeniería de Aguas Subterráneas y Hidroinformática.

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5.3. Planning before you begin¶

Before you can create a new vector layer (which will be stored in a shapefile), you need know what the geometry of that layer will be (point, polyline or polygon), and you need to know what the attributes of that layer will be. Let’s look at a few examples and it will become clearer how to go about doing this.

5.3.1. Example 1: Creating a tourism map¶

Imagine that you want to create a nice tourism map for your local area. Your vision of the final map is a 1:50 000 toposheet with markers overlaid for sites of interest to tourists. First, let’s think about the geometry. We know that we can represent a vector layer using point, polyline or polygon features. Which one makes the most sense for our tourism map? We could use points if we wanted to mark specific locations such as look out points, memorials, battle sites and so on. If we wanted to take tourists along a route, such as a scenic route through a mountain pass, it might make sense to use polylines. If we have whole areas that are of tourism interest, such as a nature reserve or a cultural village, polygons might make a good choice.

As you can see it’s often not easy to know what type of geometry you will need. One common approach to this problem is to make one layer for each geometry type you need. So, for example, if you look at digital data provided by the Chief Directorate: Surveys and Mapping, South Africa, they provide a river areas (polygons) layer and a rivers polyline layer. They use the river areas (polygons) to represent river stretches that are wide, and they use river polylines to represent narrow stretches of river. In Fig. 5.7 we can see how our tourism layers might look on a map if we used all three geometry types.

Fig. 5.7 A map with tourism layers. We have used three different geometry types for tourism data so that we can properly represent the different kinds of features needed for our visitors, giving them all the information they need. ¶

5.3.2. Example 2: Creating a map of pollution levels along a river¶

If you wanted to measure pollution levels along the course of a river you would typically travel along the river in a boat or walk along its banks. At regular intervals you would stop and take various measurements such as Dissolved Oxygen (DO) levels, Coliform Bacteria (CB) counts, Turbidity levels and pH. You would also need to make a map reading of your position or obtain your position using a GPS receiver.

To store the data collected from an exercise like this in a GIS Application, you would probably create a GIS layer with a point geometry. Using point geometry makes sense here because each sample taken represents the conditions at a very specific place.

For the attributes we would want a field for each thing that describes the sample site. So we may end up with an attribute table that looks something like table_river_attributes.

Table River Attributes 1: Drawing a table like this before you create your vector layer will let you decide what attribute fields (columns) you will need. Note that the geometry (positions where samples were taken) is not shown in the attribute table –– the GIS Application stores it separately!


Point clustering - basic configuration

This sample demonstrates how to enable point clustering on a GeoJSONLayer. Clustering is a method of reducing points in a FeatureLayer, CSVLayer, GeoJSONLayer, or OGCFeatureLayer by grouping them into clusters based on their spatial proximity to one another. Typically, clusters are proportionally sized based on the number of features within each cluster.

Clustering is configured in the featureReduction property of the layer. You can enable clustering with a default configuration with minimal code by setting the type to cluster .

The feature reduction property gives you control over many other cluster properties. The clusterRadius defines area of influence that determines each cluster's region for including features. You may also define popupTemplates and labels for clusters that summarize the features comprised by the cluster.

Suggestions for basic configuration

  • Turn off label deconfliction when labeling clusters with a count in the center of the cluster. If label placement is outside the cluster, keep label deconfliction enabled.
  • Increase the clusterMinSize to fit labels inside smaller clusters (16pt is a good starting point).
  • For larger layers, format the cluster count in the label with either a rounded value or a meaningful abbreviated value (e.g. 10k instead of 10000 ). See the Point clustering - generate suggested configuration for an example of this.

Point clustering only applies to layers with point geometries in a MapView containing either a SimpleRenderer, UniqueValueRenderer, or a ClassBreaksRenderer. It does not apply to layers with polyline and polygon geometries.

Clustering layers with spatial references other than Web Mercator and WGS-84 is experimental and may not work for every projection. Clustered layers that have spatial references other than Web Mercator or WGS-84 have the same limitations listed in the projection engine documentation.


Add attribute information from polyline to a point shapefile (QGIS or ArcGIS) - Geographic Information Systems

What are the major properties of the contour polylines that can be used in order to complete the task:

  1. In general the contours never intersect. There is an exception in the case where there are overheads in the data, but such a relief phenomenon cannot actually be represented correctly by contours, so we will ignore them in this article.
  2. A contour polygon is always constructed by two and only two contours. This rule is not valid in two cases:
    • On the boundaries of the contour dataset, but the polylines closing the contour polygon on the boundaries are not actually contours, so this should not influence the solution proposed.
    • For the highest contours representing ridges, and lowest contours representing depressions.

Source Data

  1. The closed contours are easy to handle. How however we handle contours that have gaps? Normally there are two reasons for the presence of gaps in the contour data:
    • Some data captured in CAD systems has gaps left there on purpose, to leave space for labels
    • If the contours were captured from separate map sheets and the edge matching between the data from the separate data sheets was not good or not performed at all.
  2. How to handle the contours that are going out of the study area?

STEP1: Cleaning gaps in contours. ET GeoWizards has a function called Clean Contour Gaps. It expects the user to provide (apart from the input dataset) two parameters:

  • A field representing the elevation value of the contours
  • Tolerance - the gaps smaller than this tolerance will be closed.
  1. Manually connecting with a new polyline the dangling nodes of the dataset created in STEP 2. For small datasets this might be the quickest solution, but we very seldom work with such small datasets.
  2. Creating a bounding rectangle of the dataset and adding it as a polyline to the dataset created in STEP 2
  3. Creating a Convex Hull of the dataset and adding in to the dataset created in STEP 2.

Depending on the dataset both methods 2. and 3. will automate the process, but most probably both will require some additional data processing to fix the topology errors.

STEP 3: Create Convex Hull of the data - Convex Hull function

STEP 4: Buffer the Convex Hull with a very small distance. This is to ensure that it will not touch the contour polylines which will cause splitting of the original contours during the cleaning process.

STEP 5: Convert the buffered Convex Hull to it's boundary polyline - Polygon To Polyline

STEP 6: Merge the contours created in STEP 2 and the boundary of the buffered Convex Hull created in STEP 5.

STEP 7: Clean the merged dataset - Clean Dangling Nodes function. Carefully select the dangle tolerance. If needed manually edit some of the contour ends to be as close as possible to the convex hull boundary. Evaluate the result of the function (The Export Nodes function can be used to find out whether there are still dangling nodes present).

Note that an automatic procedure might not be able to fix all topology problems. ET GeoTools offer a large variety of tools that will help you productively analyze and fix topology problems.

STEP 8: Build polygons from the dataset created in STEP 7 - Build Polygons function.

Polygons classified with the Max elevation:

Polygons labeled with their Min and Max elevations

How to get the attributes of the contour polyline and populate them to the appropriate polygons?

Each contour (see the exceptions above) will have an upper and lower polygon, so if we create two points per contour polyline - one on the left side and one on the right side very close to the original polyline, one of the points will be in the lower polygon and the other point in the upper polygon. We will use the contours created in STEP 3 to get the left and right points.

STEP 9: Create Left and Right points - ET Points Along Polylines function if used with "BOTH" option will create two point per polyline one on the left and one on the right side of the polyline, at a relative distance from the start of the polyline (0 to 1) and with a user defined offset from the polyline on the side selected by the user. The points will carry the attributes of the corresponding polylines.

STEP 10: Make sure to preserve in the point dataset only the elevation field. All the other fields can be deleted.

As a result of STEP 10 we will have a point dataset. Each point will have the elevation value of the corresponding contour. Each polygon created in STEP 8 will have inside:

  • Standard Polygon (between 2 contours) - 2 points with different elevation values (one from the lower and one from the upper contour).
  • Ridge and Depression polygons - only one point created from the Lower/Upper contour
  • Polygons on the boundary of the original dataset - only one point.

The last step is to transfer the attributes from the points to the polygons.

STEP 10: We use Spatial Join with the Aggregate option and tolerance of 0 (we want only the points contained by a polygon to be joined to the polygon) to join the points to the polygons. The function will transfer the attributes of the points to the polygons and will create two new fields - Min and Max elevations (depending on the name of the elevation field in the input dataset.


Creating a shapefile of pipes in a network out of a shapefile of existing paths with path contents (count and type of pipes)

As the title states, I am tasked with creating a shapefile of lines, representing pipes. I currently have a linear shapefile representing paths and their contents (count and types of pipes along the given path). The features representing pipes would then be overlapping one another whenever there is more than one pipe.

The first thing I need to do is split the paths, so that there are the appropriate number of features of each type one each (former) path. When there is 1 of type A and two of B in one path, 3 line features will be created. This is (I think) the easy part.

The hard part is dissolving the new pipes together. In my result, the pipes should be continuous from a central point to end point. So if there are 5 pipes coming from a central point, then one splits off from the rest, that one would overlap the other 4, but still be its own feature, until it diverges. In the paths shapefile in this example there would be three features, one path with 5 pipes from the central point, then another path feature with one pipe after it diverges, and another with 4 pipes where the remaining pipes continue.


Join polyline sidewalk data (Dual lines) to centerline (Single line)?

I'm in the process of amalgamating several sidewalk datasets which require updating. With that in mind, I got my hands on some external data that tracked a portion of my city's sidewalk infrastructure. I am hoping to pull the attribute data from it and into my city wide centerline.

So the first issue I see is that beyond street names, there is no common ID between the attributes. I attempted a buffered spatial join method but found that in doing so, many segments from the sidewalk data get removed in favor of a single one, relative to the centerline segment itself. There is also no correlation of where segments intersect or end between the two datasets (Ex: centerline can have 4 segments along a road whereas there are 10 segments of the sidewalks).

Secondly, the sidewalk data is represented by two lines on either side of the centerline, while the complete rest of my data is centerline based. So even if I can join the data successfully, I'm not sure how to accommodate data from two lines being accurately represented within one line.

Should I completely forgo the single line data and start from scratch with a dual line set? (We have some topological networks and other dual line type options. none of which relate to the centerline in any way either.)

Would greatly appreciate some thoughts on how best to tackle this set of pickles.


How to create topographic profiles in ArcGIS with x,y coordinates, and plot them with projected sample locations in Python

I have been getting a lot of zircon (U-Th)/He cooling data these past couple of weeks from my South Lunggar project, and placing that data in a proper structural context for interpretation. This involves drawing cross-sections and projecting my sample locations onto those cross-sections, which requires a topographic profile (drawn with no vertical exaggeration) that has proper geographic or projected coordinates. Though this is a task that most geologists (especially structure/tectonics types) will have to do at some point, there is not a lot of information out there for doing it with modern tools.

Getting a georeferenced topo profile is a bit of a pain. It should be easy to do it simply in Arc but it’s not. The point projection is less of a pain, although it still requires a bit of work. If anyone else knows a quicker way to do this, I’d love to know, so share away!

I am doing this in ArcGIS 10 this also requires XToolsPro, which does nominally cost money although without paying the program still works after the trial period, and I think works for most recent versions of Arc. I am also using Python (with matplotlib) to do the plotting. It could be done in MATLAB very easily, for those with a copy.

Part 1: Generate the topographic profile

Step 1: Make the line

Create a polyline shapefile in ArcToolbox

Edit the line in ArcMap and draw the line.

It’d probably be helpful to have the DEM loaded.

Step 2: Make a raster out of the line

In ArcToolbox, –> Conversion Tools –> To Raster –> Polyline to Raster

It seems reasonable to use the same cell size as your DEM but you probably don’t have to.

Step 3: Make points out of every cell in the raster

In ArcToolbox, –> Conversion Tools –> From Raster –> Raster to Point

Make sure you input the line raster, not the DEM.

Step 4: Get elevation values for the points (add to attribute table)

ArcToolbox –> Spatial Analyst Tools –> Extraction –> Extract Values to Points

Step 5: Get X,Y coordinates for the points (also add to attribute table)

XToolsPro –> Table Operations –> Add X,Y,Z coordinates

I like to add both UTM and Lon/Lat (WGS84) coordinates to my attribute table. This requires doing the operation twice, which is trivial. In any case, you need some sort of projected coordinate system so that you can plot the profile with meters on both axes, so UTM is good.

Step 6: Calculate the distance along the profile of every point

Open up the .dbf file (basically the attribute table) of the point shapefile in your favorite spreadsheet program, and find the distance from the start for each point using the Pythagorean theorem. To be safe, save this file as a new spreadsheet file instead of saving the .dbf.

To plot it with the code I will show below, export the file as a .csv and delete the header row, so that it is only columns of numbers.

Part 2: Project sample locations onto the cross-section

This assumes you have a spreadsheet that has all of your samples with some sort of X,Y,Z coordinates. If you only have X and Y, you can get Z with the values to points step outlined in Step 4 after you have made a shapefile out of the spreadsheet.

Step 1: Import sample data into ArcMap

In ArcMap, File –> Add data –> Add XY data

This will plot the points as ‘events’ without them having the proper attributes to continue, so you have to…

Step 2: Make the points into a shapefile

Right click on the sample file in the Table of Contents in ArcMap, and go to Data –> Export Data and make a shapefile out of it.

Step 3: Add UTM coordinates to shapefile (if they’re not there yet)

Step 4: Project points onto cross-section

This is basically finding the along-section distance of the points. It assumes that the points will project to the nearest point of the profile, not along strike (if your section line is not strike-normal).

First, find the best-fit line of the UTM Easting and Northing coordinates from your section line. I did this by plotting them in Excel and fitting a trendline. This line will have the form y = mx+b.

Then, open the .dbf file from your sample shapefile in Excel.

Now, project a sample from location (c,d) onto the cross-section, so that the projection is at (x,y):

Then, calculate the distance along the projection for that point using the Pythagorean theorem as in Step 6 above.

Finally, export the file as a .csv and delete the header row, if you have one.

Part 3: Plotting it all up

I have been using Python’s matplotlib to make these plots, as I’m slowly working towards moving to Python from MATLAB. Instead of step-by-step descriptions of how to do things, I am going to simply post a snippet of my code, which should be commented enough that any Python user should get the gist of it:


Add attribute information from polyline to a point shapefile (QGIS or ArcGIS) - Geographic Information Systems

tracklines_2010_072_FA.shp: Tracklines of swath bathymetry collected by the U.S. Geological Survey surrounding Muskeget Channel, MA, 2010 (Esri polyline shapefile, Geographic WGS 84) 1.0 vector digital data Open-File Report 2012-1258

Woods Hole Coastal and Marine Science Center, Woods Hole, MA

U.S. Geological Survey, Coastal and Marine Geology Program

http://pubs.usgs.gov/of/2012/1258/GIS_catalog/tracklines/swath_tracks.zip Elizabeth A. Pendleton Jane F. Denny William W. Danforth Wayne E. Baldwin

High-Resolution Swath Interferometric Data Collected within Muskeget Channel, Massachusetts 1.0 Open-File Report 2012-1258

This data set contains tracklines for just less than 227 km of swath bathymetric data collected by the U.S. Geological Survey in Woods Hole, MA during geophysical cruises offshore of Martha's Vineyard, MA in the vicinity of Muskeget Channel in 2010. The swath bathymetric data will be used to characterize the seafloor within the area and these data document those locations.

en 20101012 20101013 20101014 20101019 20101116 ground condition

None planned -70.498789 -70.400722 41.417017 41.293141 -70.498789 -70.400722 41.293141 41.417017 GeneralU.S. Geological SurveyUSGSWoods Hole Coastal and Marine Science CenterWHCMSCCoastal and Marine Geology ProgramCMGPtrackstracklinesswath bathymetrybathymetryEsri polyline shapefileSEA Ltd Swathplus interferometric sonarR/V RafaelWHCMSC field activity serial number 2010-072-FAISO 19115 Topic Categoryoceanslocation

USA 508-548-8700 x2259 508-457-2310 [email protected]

Microsoft Windows Vista Version 6.1 (Build 7601) Service Pack 1 ESRI ArcCatalog 9.3.1.1850

http://pubs.usgs.gov/of/2012/1258/GIS_catalog/tracklines/track_thumb.png
Woods Hole Coastal and Marine Science Center Swath interferometric trackline navigation surrounding Muskeget Channel, MA
PNG Poppe, L.J. McMullen, K.Y. Foster, D.S. Blackwood, D.S. Williams, S.J. Ackerman, S.D. Moser, M.S. Glomb, K.A.

Geological Interpretation of the Sea Floor Offshore of Edgartown, Massachusetts document Open-File Report 2009-1001

http://pubs.usgs.gov/of/2009/1001/ Denny, J.F. Danforth, W.W. Foster, D.S. Sherwood, C.R.

Geophysical Data Collected off the South Shore of Martha's Vineyard, Massachusetts document Open-File Report 2008-1288

http://pubs.usgs.gov/of/2008/1288/ Shapefile Any spurious navigation points were removed during processing. Swathplus navigation data from all non-transit bathymetric tracklines from cruise 2010-072-FA were used to generate this shapefile.

The navigation for these data was acquired with a Coda Octopus F180 Differential Global Positioning System + Wide Area Augmentation System (DGPS+WAAS) they are accurate to + or - 1 to 2 meters, horizontally. All DGPS data are referenced to WGS84, and vertical distance between the pole-mounted interferometric sonar head, 0.5m below the sea surface, and the DGPS antenna located on the same pole on the bow of the R/V Rafael, 2.5 m above the sea surface, are corrected.

Navigation was extracted from the bathymetric data (raw *SXR format) in SwathPlus (version: 3.7.10) using the 'output position file' function.

(508) 548-8700x2259 (508) 457-2310 [email protected]

Navigation output from Swathplus (version: 3.7.10) was concatenated together for all files within a survey and converted to comma-separated value text using AWK for input to ArcGIS (version 9.3.1). In ArcCatalog (9.3.1), navigation text was converted to a point feature class by right-clicking on the comma separated text file -- Create Feature Class -- from XY table and choosing UTM, Zone 19N, WGS 84 as the projection

(508) 548-8700x2259 (508) 457-2310 [email protected]

U.S. Geological Survey disc 20101012 20101013 20101014 20101019 20101116 ground condition Trackline acquisition at sea: These bathymetric data were collected with a SEA Ltd Swathplus interferometric sonar (234 kHz) mounted on the bow of the R/V Rafael of Woods Hole, MA. The data were acquired with SwathPlus Software (versions: 3.7.10). Tracklines are spaced 70 m apart. USGS

XTools Pro (version 7.1.0) was then used within ArcMap (version 9.3.1) to convert the navigation points to a trackline shapefile. The trackline shapefiles were edited to remove spurious fixes, and a length field was created and populated using 'Calculate Geometry', which can be accessed by right-clicking on the attribute field name in the table view. The calculation was based on UTM, Zone 19N, WGS84 in the units of meters.

(508) 548-8700 x2259 (508) 457-2310 [email protected]

The file was reprojected to GCS WGS 84 using ArcToolBox.

Additional fields were created for the trackline file in ArcMap (version 9.3.1) by selecting options on the attribute table, then 'Add field'. Survey_ID and VehicleID are used to determine which survey the lines are associated with and which vessel was used to collect the data.

(508) 548-8700x2259 (508) 457-2310 [email protected] Downloadable Data Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Shapefile ArcGIS 9.3.1 This WinZip (v 14.5) file contains a shapefile of bathymetric tracklines surrounding Muskeget Channel, MA, and the associated metadata. Use WinZip or pkUnzip 122 KB WinZip 2.245 http://pubs.usgs.gov/of/2012/1258/GIS_catalog/tracklines/swath_tracks.zip http://pubs.usgs.gov/of/2012/1258/html/ofr2012-1258_GIS_catalog.html Data can be downloaded via the World Wide Web (WWW) None This zip file contains data available in Environmental Systems Research Institute (Esri) polyline shapefile format. The user must have ArcGIS or ArcView 3.0 or greater software to read and process the data file. In lieu of ArcView or ArcGIS, the user may utilize another GIS application package capable of importing the data. A free data viewer, ArcExplorer, capable of displaying the data is available from Esri at www.esri.com. 20140107 Elizabeth Pendleton U.S. Geological Survey Geologist mailing and physical address 384 Woods Hole Rd. Woods Hole MA

[email protected] 20140130 ArcGIS Metadata 1.0 Elizabeth A. Pendleton U.S. Geological Survey Geologist (508) 548-8700x2259 (508) 457-2310 384 Woods Hole Rd. Woods Hole MA

1.0 U.S. Geological Survey, Coastal and Marine Geology Program Woods Hole Coastal and Marine Science Center, Woods Hole, MA U.S. Geological Survey

Open-File Report 2012-1258 High-Resolution Swath Interferometric Data Collected within Muskeget Channel, Massachusetts These data were collected under a collaboration between the Woods Hole Oceanographic Institution (WHOI) and the U.S. Geological Survey (USGS), Coastal and Marine Geology Program, Woods Hole Coastal and Marine Science Center (WHCMSC). The primary objective of this program was to collect baseline bathymetry for Muskeget Channel, Massachusetts and identify areas of morphologic change within and around the channel. Repeat surveys in select areas were collected one month apart to monitor change. These data were collected to support an assessment of the impact to sediment transport a tidal in-stream energy conversion facility would have within Muskeget Channel. Accurate data and maps of seafloor topography are important first steps in monitoring bedform migration, fish habitat, marine resources, and environmental changes due to natural or human impacts. The data include high resolution bathymetry, acoustic-backscatter intensity, sound velocity in water, and navigation data. These data were collected during two surveys between October 2010 and November 2011 onboard the R/V Rafael using an SEA Ltd SwathPlus interferometric sonar (234 kHz). More information about the cruise can be found on the Woods Hole Coastal and Marine Science Center Field Activity webpage: <http://woodshole.er.usgs.gov/operations/ia/public_ds_info.php?fa=2010-072-FA> This data set contains tracklines for just less than 227 km of swath bathymetric data collected by the U.S. Geological Survey in Woods Hole, MA during geophysical cruises offshore of Martha's Vineyard, MA in the vicinity of Muskeget Channel in 2010. The swath bathymetric data will be used to characterize the seafloor within the area and these data document those locations.

Elizabeth A. Pendleton U.S. Geological Survey Geologist 508-548-8700 x2259 508-457-2310 384 Woods Hole Road Woods Hole MA

US [email protected] http://pubs.usgs.gov/of/2012/1258/GIS_catalog/tracklines/track_thumb.png Woods Hole Coastal and Marine Science Center Swath interferometric trackline navigation surrounding Muskeget Channel, MA PNG

Chappaquiddick Island Mutton Shoal Vineyard Sound Shovelful Shoal Cape Poge United States Katama Bay Bass Ledge Edgartown Nantucket Sound Muskeget Channel Martha's Vineyard Muskeget Island Tuckernuck Island Wasque Shoal Massachusetts Norton Shoal Nantucket Island Wasque Point Hawes Shoal North America Atlantic Ocean General

location oceans ISO 19115 Topic Category WHCMSC SEA Ltd Swathplus interferometric sonar U.S. Geological Survey Coastal and Marine Geology Program swath bathymetry USGS CMGP R/V Rafael tracklines Esri polyline shapefile Woods Hole Coastal and Marine Science Center WHCMSC field activity serial number 2010-072-FA tracks bathymetry General Chappaquiddick Island WHCMSC Mutton Shoal SEA Ltd Swathplus interferometric sonar U.S. Geological Survey Vineyard Sound Shovelful Shoal Cape Poge Coastal and Marine Geology Program United States Katama Bay swath bathymetry Bass Ledge USGS Edgartown Nantucket Sound CMGP Muskeget Channel Martha's Vineyard R/V Rafael Muskeget Island Tuckernuck Island Wasque Shoal location tracklines Esri polyline shapefile Woods Hole Coastal and Marine Science Center Massachusetts oceans WHCMSC field activity serial number 2010-072-FA tracks Norton Shoal Nantucket Island bathymetry Wasque Point Hawes Shoal North America Atlantic Ocean Neither the U.S. Government, the Department of the Interior, nor the USGS, nor any of their employees, contractors, or subcontractors, make any warranty, express or implied, nor assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, nor represent that its use would not infringe on privately owned rights. The act of distribution shall not constitute any such warranty, and no responsibility is assumed by the USGS in the use of these data or related materials. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government. The Public domain data from the U.S. Government are freely redistributable with proper metadata and source attribution. Please recognize the U.S. Geological Survey as the originator of the dataset. Geophysical Data Collected off the South Shore of Martha's Vineyard, Massachusetts

Sherwood, C.R. Foster, D.S. U.S. Geological Survey Reston, VA Denny, J.F. Danforth, W.W.

McMullen, K.Y. Foster, D.S. Moser, M.S. Williams, S.J. Blackwood, D.S. U.S. Geological Survey Reston, VA Glomb, K.A. Poppe, L.J. Ackerman, S.D.

The file was reprojected to GCS WGS 84 using ArcToolBox. 2013-01-01

Navigation output from Swathplus (version: 3.7.10) was concatenated together for all files within a survey and converted to comma-separated value text using AWK for input to ArcGIS (version 9.3.1). In ArcCatalog (9.3.1), navigation text was converted to a point feature class by right-clicking on the comma separated text file -- Create Feature Class -- from XY table and choosing UTM, Zone 19N, WGS 84 as the projection 2013-01-01 Elizabeth A. Pendleton U.S. Geological Survey Geologist (508) 548-8700x2259 (508) 457-2310 384 Woods Hole Rd. Woods Hole MA

XTools Pro (version 7.1.0) was then used within ArcMap (version 9.3.1) to convert the navigation points to a trackline shapefile. The trackline shapefiles were edited to remove spurious fixes, and a length field was created and populated using 'Calculate Geometry', which can be accessed by right-clicking on the attribute field name in the table view. The calculation was based on UTM, Zone 19N, WGS84 in the units of meters. 2013-01-01 Elizabeth A. Pendleton U.S. Geological Survey Geologist (508) 548-8700 x2259 (508) 457-2310 384 Woods Hole Rd. Woods Hole MA

Additional fields were created for the trackline file in ArcMap (version 9.3.1) by selecting options on the attribute table, then 'Add field'. Survey_ID and VehicleID are used to determine which survey the lines are associated with and which vessel was used to collect the data. 2013-01-01


The default software associated to open shx file:

ArcGIS for Desktop Basic (ArcView)

Company or developer:
Esri

ArcGIS for Desktop Basic (formerly known as ArcView) is GIS (geographic information system) application used to visualizing, managing, creating, and analyzing geographic data.

ArcGIS for Desktop Basic is a part of the ArcGIS Desktop. ArcGIS for Desktop Basic supports creation of interactive maps, spatial analysis, GIS deployment, map viewing and navigation, map printing etc.


Watch the video: How to create new polyline in Arc Gis