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James, Thanks for continuing to work with me on this. You raise an interesting question. I suppose I would think of it differently. Any time two tracks meet the input criteria (space distance, time distance, and the new "mininum time for converged tracks" parameter *), it's the converged tracks alone that interest us. Because every set of cotraveling (converged) tracks will have a segment before when they are converging, and a segment afterward when they are diverging. Both converging and diverging will always be present before and after the valid "cotraveling (converged) segment. It seems to me that they don't need to be characterized. Another way to put this might be: In the condition where the tracks meet the desired criteria, they are neither converging or diverging. I hope this helps. ( * I see this has been added to the module you sent me to test. I'm still working on that. See my other post reply about problems updating Pro for this task. Thanks.)
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01-29-2021
12:46 PM
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James - Sorry for the slow reply. I'm running 2.6.3. Jerry sent me the new gpkx file to try out. He said it must be run with Pro Intel 2.7. I would update Pro now, but I see "Checking for updates is blocked" on the Pro "About" screen. I googled for a solution but didn't find one. Seems to be set by administrator. I'm on my own laptop, so I ran Pro as administrator. But I see the same "updates blocked" message. I looked through my Portal Home Edition Licensing section and elsewhere but saw no way to change this, and no way to download a new copy of Pro. (I'm not an adept Poral administrator.) Can you point to a solution? Thanks.
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01-29-2021
12:32 PM
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Thanks for this clarification. "Convex hulls from the extent of the points" makes more sense than the "median location" we read in the documentation for this tool.
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01-29-2021
12:12 PM
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Thanks for this clarification. It appears, then, that the Pattern of Life demo simply omitted (or I missed it) a preparatory step - to run the event data first through the Find Meeting Places analytic.
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01-29-2021
12:08 PM
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Thanks, Dan. I am wondering what tool ever produces an irregular polygon of this type when generalizing or interpreting the area covered by a cluster of points. Can you say?
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01-08-2021
04:04 PM
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The Esri Defense and Intell Showcase gave an outstanding demo of the Find Meeting Locations tool used with other Pattern of Life tools. I'd like to understand the analytics and presentation. Like, why does the meeting locations output polygon layer look like this? The Pro 2.7 tool reference only says: The tool creates two output feature classes: an area feature class indicating the locations identified as potential meeting sites and a point dataset as the centroid of the unique meeting location. Not much to go on. There is slightly more info in this clip which I extracted from the Showcase video and posted on YouTube. At 2:57 in the video, the analyst says: "The blue polygon is going to be the median location, so this is going to be an inclusive area of where a lot of meetings are occurring as determined by the tool." What does this mean? Why was this analytic chosen? I see almost no ArcGIS references median location . Would it make more visual and logical sense to use one of the density tools that produces a typical ellipse for analysis like this? Otherwise, what is the meaning of pointy end shapes like this? How are we supposed to make use of it? Thanks.
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01-08-2021
02:49 PM
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The Pattern of Life Link Chart is innovative, because it uses co-location as a "relationship" value: The problem with this tool -- if I understand it right -- is that the analyst must already have a polygon layer of precisely-named locations to make this work. The linkage relies on a simple table join, which requires "location name" values to match precisely. I think this is what's demonstrated at the Esri Defense and Intell Showcase in this clip which I posted on YouTube. At 7:55 in the video, the analyst specifies the names of the Key Fields for source and target layers. These are required for a simple table join by attribute - matching values in each table: I discussed this with @JamesJones4 at Esri. He indicated that analysts can "add notes" to a location layer (is there a tool for this?) to create that target entity key field for the table join. This seems impossible for the analyst who has lots of data or who does not know in advance which places are important. (This advance knowledge of barracks, guard shack, and mess hall in the Showcase demo seems to be an unlikely scenario for most analysts.) A better idea? The input data -- masses of it -- could be run through the Optimized Hot Spot tool to automatically generate the meeting places. (Or use the Find Meeting Places tool?) Use those uniquely identified polygons with a spatial join, not an attribute join as demonstrated, to enumerate all the players who are linked by location. Or, maybe I'm missing something. I hope so.
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01-08-2021
02:06 PM
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Because the Find Cotravelers tool shows lots of false hits of tracks that merely cross each other, we need more context to evaluate the results. Results look like this. Just the "cotraveled events" are shown: We need to see the entire track for each of the candidate cotraveler, so we can evaluate them: With a massive data set (I'm testing with AIS maritime tracking data from MarineCadastre.gov - 500K events off the coast of Miami.), we can't simply check by laying the results over the input data layer: The time-consuming workaround is this: Open the results table and note all of the "cotraveler" unique IDs. Do and Attribute Query of the input data set for the unique IDs. Export the selection to a new layer. Turn off the input layer. Symbolize the new layer by unique ID (to differentiate the tracks). Examine the tracks for true co-travelers, not mere crossing tracks.
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01-08-2021
01:27 PM
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I'm testing the Find Cotravelers tool with AIS maritime tracking data from MarineCadastre.gov - 500K events off the coast of Miami. The tool lets us set a time window and distance/proximity parameters. What's missing is a parameter for the minimum duration during which the distance/proximity conditions must be met. For example, "They must be moving close together in time and space for a minimum 60 minutes." Without this duration parameter, the tool also shows vessels that merely crossed paths within 100 meters and 10 minutes of each other [the tool defaults]. This can generate hundreds of false hits. Here is the results layer - supposedly co-travelers: This is the real picture: [I've discussed this with @JamesJones4 but wanted to document it here for others who run into this.]
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01-08-2021
01:05 PM
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I'm running the Find Cotravelers tool. I got the error below. Can't tell if the re was "empty output" because no events qualified, or because of the processing error. There is no Esri documentation for the Python ValueError: not enough values to unpack. And I don't have access to the .py file, of course. What should I do? Thanks. Warning empty output generated. Traceback (most recent call last): File "c:\program files\arcgis\pro\Resources\ArcToolbox\Scripts\intelMovementToolsClasses.py", line 183, in execute features, style = cotravelers.find_cotravelers()ValueError: not enough values to unpack (expected 2, got 1) Failed to execute (FindCotravelers). [I've discussed this with @JamesJones4 but wanted to document it here for others who run into this.]
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01-08-2021
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These are nice introductions to show the UI layout, what tools are available, and where to find them. It would be great to see a video for each of the major tools like Find Cotravelers, Find Meeting Places, Link Analysis, and Pattern of Life. With details about input data traps, how to optimize the parameters for different target types, and how to interpret results.
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01-08-2021
12:16 PM
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What is the best way to identify and remove unused images from our ArcGIS Online account? So we don't pay for unneeded storage. Thanks.
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10-16-2020
10:07 AM
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IDEA
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ISO 8601 is also the standard which is compatible with Pandas datetime objects, and in particular the Pandas read_csv() function.
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03-08-2019
10:06 AM
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ISO 8601 is also the standard which is compatible with Pandas datetime objects, and in particular the Pandas read_csv() function.
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03-08-2019
10:06 AM
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This is also the standard which is compatible with Pandas datetime objects, and in particular the Pandas read_csv function.
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03-08-2019
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Title | Kudos | Posted |
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2 | 01-08-2021 01:05 PM | |
1 | 01-08-2021 04:04 PM | |
2 | 01-08-2021 02:49 PM | |
2 | 01-08-2021 02:06 PM | |
2 | 01-08-2021 01:27 PM |
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