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0

Use ST_Line_Interpolate_Point union them first to create a single complete without gaps line .


6

The Geometry.within() method only accepts other Geometry objects -- in your case, it has to be a Polygon. It doesn't know what to do with a feature class, so I would suggest dissolving that feature class into one containing a single polygon, and then access the Geometry object with this: urban_area_geom = [r[0] for r in ...


0

I would suggest managing your data as 3 separate layers and setting their order in Leaflet via MapBox.js. You would essentially have one base layer from MapBox Studio that is just background data like imagery or topography. Next you would have your CartoDB layer. Lastly would be a layer of labels, roads and places from MapBox Studio. I have done this ...


0

You can use the Join attributes by location tool from the toolbar (Vector > Data Management Tools > Join attributes by location). Select the Keep all records option to make sure the output layer receives all attributes related to each specific point: Hope this helps!


0

One solution is to make the landmine points transparent. Another is to add the place name labels as a new layer - This assumes you can find a place name layer and reuse it. If you have a map option that hides everything except placenames and another map option that shows a base map without labels, then you could draw the base, then add the landmines, then ...


2

Are there any parameters on the cities you want? GeoNames might be a good resource. Under their tools page there is a GeoNames csv file to shapefile converter. It might take a little bit of work and sifting through the data to get exactly what you want.


11

Populated Places 1:10m (Natural Earth) Shapefile 7343 Cities Download from http://www.naturalearthdata.com/downloads/10m-cultural-vectors/ (Populated Places) Terms of Use http://www.naturalearthdata.com/about/terms-of-use/ No permission is needed to use Natural Earth. Crediting the authors is unnecessary. However, if you wish to cite the map ...


2

Must it be a shapefile? Google Maps offer something like you asked as a kml file (kmz in fact, which is just a zip containing a kml), at https://www.google.com/maps/d/viewer?mid=zMlf_4RO8x7E.kllT447wz1Ws&msa=0&ie=UTF8&t=m&ll=8.407168,165.9375&spn=130.849955,280.898438&z=2&source=embed


3

Buffer (without dissolving) all lines a (very) small distance. Spatially Join your points to your buffers with a one-to-one join_operation with an intersect match_option. In the resulting feature class, there will be an attribute Join_Count of how many buffers matched each point. Any point at an intersection would intersect two buffers, while points ...


2

This is a bit more complex, you will need to create two temporary 'unselect' feature classes. Use the tool Feature Vertices to Points with the 'BOTH_ENDS' specified to create points where you don't want selection. Do this for the blue and the red lines then merge. Use Select by Location to select the points within a small tolerance from the blue lines (how ...


4

I think this is a great question and one with more relevance as we start using different technologies to store spatial data such as PostGIS. There are two issues involved here, from what I can think about: 1) Scale: I used to teach cartography students that a City from the view of "The Country" is a point, but as you zoom in to the scale of a "region", ...


1

If your data density is so low that it is non-contiguous, the obvious alternative, which is frequency hotspot analysis using raster surfaces, won't be so good either. Also raster surfaces are not good near coastlines due to weighting issues (some cells have large chunks of sea, then you have to fiddle with weighted corrections - which requires dense ...


0

If you are trying to randomize your original points, you may want to take a look at the Point Randomizer script rather than using the buffer method. It is possible (with a Spatial or 3D Analyst extensions, or an Advanced license) to use the Create Random Points tool and constrain the points to fall on lines. You could take your buffers and intersect them ...


0

Another approach would be to use the Field Calculator. Here is the code that you will need for the Field Calculator: from random import randint,choice def RandMove(old_pnt,min_shift,max_shift): neg = [-1,1] #get the first point from the geometry object old_x = old_pnt.firstPoint.x old_y = old_pnt.firstPoint.y #calculate new coordinates new_x ...


5

You can manipulate individual point geometry using an Update Cursor. Accessing the SHAPE@XY token is by far the most efficient cursor-based approach. However, if you have a polygon of your area of interest, using a random point generator will likely be more efficient. In this example, I use a minimum and maximum threshold to set the limits for a random ...


1

First you need a line identifier. A buffer will probably do what you need, with dissolve. Then you can spatially join the buffer polys back to the points and transfer the buffer fid across. Then you need to sequence them in some way. The points all seem to go NE-SW, so perhaps ordering on the Y coord will get you a sequence. Apply this as an index to the ...


-1

we have once Geoprocessing tool Point to Line in arcgis use once i think this is useful to you http://resources.arcgis.com/en/help/main/10.1/index.html#//00170000003s000000


7

One approach is to convert this to raster and then extract contours Another is to find the buffer for each point;Dissolve those buffers to get a narrow polygon;Find the center line of each dissolved polygon.


2

Normalizing the data leads me to some missing ideas/points. Also, I think Excel can do everything you want for the "database" you contemplate. Hint: Use sheets, or multiple files and use variations of Lookup functions. Save into the useful file(s) for imports/lookups from QGIS I envision these discrete tables [or excel sheets], to start off your data ...


0

Ok, I had a look at shapefile.py and was able to arrive at this solution: from struct import unpack points = [] msacur.execute("SELECT ID, Shape FROM site_locations") # Field Shape contains binary data in GeomSHP format - to be converted rows = msacur.fetchall() for row in rows: # Find out the shape type shapeType = unpack("<i", ...


3

I would take DenaliHardtail's suggestion of using polygons to represent accurate sizes of the plots. This layer could have a table with Grave_ID, Grave_Type, Grave_Capacity, and Grave_Occupancy_Number. Then you could have a point layer with points overlying the corresponding grave polygons. Columns for the point layer table could be Person-ID, First_Name, ...


4

I would create a polygon for the grave since the grave itself is a plot of land and have a one to many relationship for the people; one grave can have zero (unoccupied, available, or for sale ?) or many people. You could also use a point instead of the polygon. Polygons would make better presentations for sales and maintenance.


20

I would go the complicated way: Two Tables in a 1:n relation one table with the point location of the graves another table with the Grave-ID and person data You can build a relation between the two tables so that selecting a grave will select all person records in the person-table. The idea of having tables with fields like Person1, Person2... is ...


1

I will calculate the intersection of two paths, one starting at Point A using the bearing from Point A to Point B, and the other path starting at 89.99999N, 179.99999E bearing 180 degrees. That will give me the approximate point on the 180.


0

It seems you've a problem with the coordinate system. Now you've the same CS for both layers but probably one of them has the wrong one. You should try to check this first, then, if this is the error, you need to define the right projection before reproject for the system you want. If this is not the error, as the shift position is consistent, you can fix ...



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