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You should use the Table > Update Column command to calculate the population. Depending on how your population data is stored (point or polygon), how the dialog is filled out will differ: In the examples: CatchPopn is the attribute in the drivetime catchments table DTCatch that will receive the calculated population count PopnCol is the population count ...


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I was a bit surprised that no one had answered this question yet so I decided to look at how you would perform the task of extracting a watershed from a digitized point along a stream network in QGIS myself. I found that there are about five tools in QGIS for watershed extraction among the various toolboxes. Unfortunately, and perhaps a QGIS expert here can ...


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You could perform a watershed analysis yourself, but its a time consuming process. One good source of existing river catchment data is the HydroSHEDS project, which provides high resolution basins for much of the globe, including the UK.


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The trick is to Google "UK river catchment map". (Other combinations that include "watershed" don't work.) You will find River basin management plan documents. River basin district maps (downloadable files). An interactive map. Maps by the UK Environment Agency. Scottish river basin maps and data. A search involving "watershed" did turn up a historical ...


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If you don't find a map, SAGA GIS has a module called watershed basins that uses a dem and the channel network (your rivers). If you use a coarse dem this goes fast. http://www.saga-gis.org/saga_modules_doc/ta_channels/index.html


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I don't think there is a name for this exact technique, but hopefully some of what follows will provide some options: In general, there are many interpolation techniques for moving between a point representation and a continuous surface, such the TIN interpolation method underdark has illustrated. The continuous surface could then be classified by value to ...


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I am not sure that following the boundary will be more efficient than expanding the area. With raster data, you need to account for the number of times that you "go through" the entire image. With a region growing method, each pass will process an increasing number of pixels until you reach the boundary. If you look at the contour only, you might end up with ...


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Calculate the distance to all origin points, select the 90% nearest and then do a convex hull calculation to get the catchment area. Exact steps depend upon your software.


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ArcMap uses the D8 routing algorithm for determining flow directions between cells, with no convergence exponent since it is a single direction algorithm, while the default in SAGA GIS (I believe - at least it is in mine) is MFD with the convergence you specify. These methods differ and therefore will generate different catchment area results. You could ...


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If you're writing a tool it would be easier to modify the definition expression of a layer rather than to extract and load. This would be achievable in ArcPy but would be better suited to .net (VB or C#) In ArcObjects the definition query can be modified in ILayerDescription which can be accessed from IFeatureLayer. in VB: dim pLayerDesc as ...


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To make it where you can move a basin and have the polyline follow, you can set up a topology between the point and line layer. The rule most relevant to you is the Endpoint Must Be Covered By rule. This rule enforces that the endpoint of a line must be covered by a point feature in another feature class.


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This can be calculated quite easily using Voronoi Diagrams (also known as Theissen polygons) based on Euclidean Distance metrics (i.e. "As the crow flies") in GRASS, QGIS, or ArcGIS. In all three of these platforms, the linked tools take as input a point feature class and output a polygon feature class. If you are trying to calculate based on travel time ...


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I assume that there is only 1 pixel per polygon that has a maximum value. 1. Find Maximum Value ... use the shapefile to look at the Flow Accumulation Raster and identify the location of the maximum value in each basin. To solve this task (find the maximum pixel value in each polygon) you can use Zonal Statistics (Spatial Analyst). in_zone_data = ...


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I could see two ways of going about this problem. One is pretty straightforward. The other requires a great deal of supporting data. The straightforward algorithm would rely on convex hulls rather than voronoi polygons. Construct the convex hull of the vector endpoints and vertices for the street segments that fall inside your drive time cutoffs. Then, use ...



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