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This item rearrange_points (Optional) Determines whether to rearrange points in the LAS files. REARRANGE_POINTS —The order of the points in the LAS files will remain the same. MAINTAIN_POINTS —The points in the LAS files will be rearranged. This is the default. Boolean in the help, seems to be the wrong way round.
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08-26-2016
12:14 AM
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But, how do you know where in the raster image (pixel position, row & col) these control points are located?
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08-26-2016
12:04 AM
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Well a dataset covering the entire USA would look a little funny using the Hawaii projection (centred on 157degW). Isn't the whole of eastern USA rather distorted?
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08-25-2016
09:23 AM
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Although it has little relevance to this debate, I thought I would have a look at the 2 projections. Centred on Hawaii, I think that this is where we are talking about. Both frames are exactly the same scale and are centred on the same point. Note that Web Mercator the scale is smaller. It really is a bad projection to use for almost anywhere!!!!
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08-25-2016
06:23 AM
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Are you sure that you need a Make Query table tool here. Wouldn't a simple join do what you need?
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08-25-2016
03:14 AM
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Do something like this : # name has a "time stamp"
import datetime
Now = datetime.datetime.now()
DateTimeStamp = "_{:%Y%m%d_%H%M}".format(Now)
outFile = "FileBasename" + DateTimeStamp + ".ext"
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08-25-2016
02:36 AM
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You could use a bit of python to get the ID (your identifer or OID@) My dummy table of data. flds = ["ID", "Station", "ChloroVal", "SelFlag"]
# read the data into a dict containing a list
data_dict = {}
with arcpy.da.SearchCursor(tbl, flds) as inCur:
for row in inCur:
ID = row[0]
station = row[1]
val = row[2]
data = [val, ID]
if station in data_dict:
data_dict[station].append(data)
else:
data_dict[station] = [data] data_dict looks like this : {u'B1': [[5.4, 1], [3.4, 2], [6.4, 3], [5.0, 4]], u'B2': [[3.2, 5], [5.2, 6], [5.0, 7], [7.0, 8]]} then you read through this dict and sort each list. # process the dict to get the ID where Val is max, just sort each one
for k, v in data_dict.items():
v = sorted(v)
data_dict[k] = v The sorted list looks like this : {u'B1': [[3.4, 2], [5.0, 4], [5.4, 1], [6.4, 3]], u'B2': [[3.2, 5], [5.0, 7], [5.2, 6], [7.0, 8]]} now all you need is the ID associated with the last member of the list. updateList = []
for k, v in data_dict.items():
# pick the last one in each list
updateList.append(v[-1][1]) Then with updateList, open up an update cursor and set the selectFlag.
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08-24-2016
01:16 AM
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But still... I think it is unwise to be using a select or unique classify on a attribute which is double. There must be a better way to identify the row you need.
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08-23-2016
12:56 PM
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That's what NA is about, not so. As long as you have a network to analyse of course (often the most difficult bit). That's an allocation problem. What is Network analyst
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08-23-2016
12:51 PM
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By the way, thanks xander_bakker for giving us some nice pictures of the various "interpolations"
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08-23-2016
12:32 PM
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What is the "truth". Interpolation is interpolation. "Estimating", "predicting", values which are not actually there in your original data but putting some mathematical function through the input points to create a continuous surface raster output. Lots of stuff in the middle. IDW, NN, Splines, even Kriging
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08-23-2016
12:30 PM
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I think that the only thing I could add to that very detailed account is that if you add another layer to an existing mxd / map service and republish, just make sure it gets added at the bottom of the toc. You have to move it down because the default is to add it at the top. Otherwise all the layer pointers to your layers / feature items etc will get highly messed up in your map services.
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08-23-2016
12:24 PM
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That's a really old style aerial photo. Don't see many of them around these days. Xander is absolutely correct, there is no one click solution to get these geo-referenced easily. But have you considered using more modern sources of aerial imagery. Or do these photos have some sort of historical interest?
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08-23-2016
07:18 AM
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The main reason for the fgdb is because its faster. That's why most of the data gets copied across. Editable layers (feature access) have to be in the enterprise SDE. And we try to group all these into one service for publishing, then use the individual items inside the various WebMap/Apps. But, yes, it can become messy. There is lots of room for improvement in Portal. It would be nice to be able to share just the WebMap/App to a certain group without exposing the underlying feature layers as well.
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08-23-2016
07:07 AM
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