Thresholding in qgis

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Evaluates the extreme either maximum or minimum upslope value from an input grid based on the D8 flow model. This is intended initially for use in stream raster generation to identify a threshold of the slope times area product that results in an optimum according to drop analysis stream network. If the optional outlet point shapefile is used, only the outlet cells and the cells upslope by the D8 flow model of them are in the domain to be evaluated. By default, the tool checks for edge contamination. This is defined as the possibility that a result may be underestimated due to grid cells outside of the domain not being counted. This is the desired effect and indicates that the result for these grid cells is unknown due to it being dependent on terrain outside of the domain of data available. Edge contamination checking may be turned off in cases where you know this is not an issue or want to ignore these problems, if for example, the DEM has been clipped along a watershed outline. A point shape file defining outlets of interest. If this input file is used, only the area upslope of these outlets will be evaluated by the tool. A flag to indicate whether the maximum or minimum upslope value is to be calculated. This grid indicates likely stream source grid cells. In parallel flow systems L is proportional to A y about 1. This method tries to identify the transition between these two paradigms by using an exponent y somewhere in between y about 1. The output file is a new outlets shapefile where each point has been moved to coincide with the stream raster grid, if possible. This input paramater is the maximum number of grid cells that the points in the input outlet shapefile will be moved before they are saved to the output outlet shapefile. Creates an indicator grid 1, 0 of upward curved grid cells according to the Peuker and Douglas algorithm. With this tool, the DEM is first smoothed by a kernel with weights at the center, sides, and diagonals. The Peuker and Douglas method also explained in Band,is then used to identify upwardly curving grid cells. This technique flags the entire grid, then examines in a single pass each quadrant of 4 grid cells, and unflags the highest. This proto-channel network generally lacks connectivity and requires thinning, issues that were discussed in detail by Band The center weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. The side weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. The diagonal weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. This tool is intended for use as part of the slope-area stream raster delineation method. The slope exponent m parameter which will be used in the formula: Sm Anthat is used to create the slope-area grid. The area exponent n parameter which will be used in the formula: Sm Anthat is used to create the slope-area grid. The standard use is to use an accumulated source area grid to as the input grid to generate a stream raster grid as the output. The threshold logic is:. A common use of this input is to use a D-Infinity contributing area grid as the mask so that the delineated stream network is constrained to areas where D-infinity contributing area is available, replicating the functionality of an edge contamination mask. This function is designed to aid in the determination of a geomorphologically objective threshold to be used to delineate streams. Drop Analysis attempts to select the right threshold automatically by evaluating a stream network for a range of thresholds and examining the constant drop property of the resulting Strahler streams. Basically it asks the question: Is the mean stream drop for first order streams statistically different from the mean stream drop for higher order streams, using a T-test. Stream drop is the difference in elevation from the beginning to the end of a stream defined as the sequence of links of the same stream order. This function can be used in the development of stream network rasters, where the exact watershed characteristic s that were accumulated in the accumulated stream source grid vary based on the method being used to determine the stream network raster. For the science behind using this to determine a stream delineation threshold, see Tarboton et al. This parameter is the lowest end of the range searched for possible threshold values using drop analysis.

Vector topology cleaning


Take my QGIS courses! Visit my company website. This tutorial is now obsolete. Heatmaps are one of the best visualization tools for dense point data. Heatmaps are used to easily identify find clusters where there is a high concentration of activity. They are also useful for doing cluster analysis or hotspot analysis. We will work with a dataset of crime locations in Surrey, UK for the year and find crime hotspots in the county. This work is licensed under a Creative Commons Attribution 4. Subscribe to my mailing list Get occasional emails when I post new material or announce training events. For convenience, you may directly download a copy of the dataset from the link below: surrey-street. Browse to the surrey-street. Your filename maybe different if you downloaded a fresh copy of the dataset. Select CSV comma separated values as the file format. You will see the Longitude and Latitude columns automatically selected as X and Y fields. Make sure you check the Use spatial index option as that will speed up your operations on this layer. Click OK. You may see some errors. You can ignore those for the purpose of this tutorials. Click Close. As our data is in EPSG, you can ignore the warning. If you liked tutorials on this site and do check out spatialthoughts.

The interaction of the lower and upper thresholds on the output values for Rescale by Function


Take my QGIS courses! Visit my company website. GIS Workflows typically involve many steps - with each step generating intermediate output that is used by the next step. If you change the input data or want to tweak a parameter, you will need to run through the entire process again manually. Fortunately, QGIS has a graphical modeler built-in that can help you define your workflow and run it with a single invocation. You can also run these workflows as a batch over a large number of inputs. This tutorial shows how to build a model to extract areas for a particular class from a classified land use raster. As of 31 DecemberGLCF has shut down its services and the files needed for this tutorial are no longer accessible. You may directly download an archival copy of both the datasets from the links below if you wish to work on this tutorial:. The following steps outline the process to code the above process into a model and run it on the downloaded datasets. If you do not see this algorithm or any of the subsequent algorithms mentioned in thi tutorial, you may be using the Simplified Interface of the Processing Toolbox. The boxes can be moved and arranged by clicking on it and dragging it while holding the left mouse button. You can also use the scroll-wheel to zoom in and out in the model canvas. Models can be a great timesaver and allow you to write your workflow once and run it multiple times. You can even share your model with other users. The model files are saved in the. You can send the. The models directory location will depend on the platform as follows: Replace username with your login name. This work is licensed under a Creative Commons Attribution 4. Subscribe to my mailing list Get occasional emails when I post new material or announce training events.

Binary Thresholding function


Evaluates the extreme either maximum or minimum upslope value from an input grid based on the D8 flow model. This is intended initially for use in stream raster generation to identify a threshold of the slope times area product that results in an optimum according to drop analysis stream network. If the optional outlet point shapefile is used, only the outlet cells and the cells upslope by the D8 flow model of them are in the domain to be evaluated. By default, the tool checks for edge contamination. This is defined as the possibility that a result may be underestimated due to grid cells outside of the domain not being counted. This is the desired effect and indicates that the result for these grid cells is unknown due to it being dependent on terrain outside of the domain of data available. Edge contamination checking may be turned off in cases where you know this is not an issue or want to ignore these problems, if for example, the DEM has been clipped along a watershed outline. A point shape file defining outlets of interest. If this input file is used, only the area upslope of these outlets will be evaluated by the tool. A flag to indicate whether the maximum or minimum upslope value is to be calculated. This grid indicates likely stream source grid cells. In parallel flow systems L is proportional to A y about 1. This method tries to identify the transition between these two paradigms by using an exponent y somewhere in between y about 1. The output file is a new outlets shapefile where each point has been moved to coincide with the stream raster grid, if possible. This input paramater is the maximum number of grid cells that the points in the input outlet shapefile will be moved before they are saved to the output outlet shapefile. Creates an indicator grid 1, 0 of upward curved grid cells according to the Peuker and Douglas algorithm. With this tool, the DEM is first smoothed by a kernel with weights at the center, sides, and diagonals. The Peuker and Douglas method also explained in Band,is then used to identify upwardly curving grid cells. This technique flags the entire grid, then examines in a single pass each quadrant of 4 grid cells, and unflags the highest. This proto-channel network generally lacks connectivity and requires thinning, issues that were discussed in detail by Band The center weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. The side weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. The diagonal weight parameter used by a kernel to smooth the DEM before the tool identifies upwardly curved grid cells. This tool is intended for use as part of the slope-area stream raster delineation method. The slope exponent m parameter which will be used in the formula: Sm Anthat is used to create the slope-area grid. The area exponent n parameter which will be used in the formula: Sm Anthat is used to create the slope-area grid. The standard use is to use an accumulated source area grid to as the input grid to generate a stream raster grid as the output. The threshold logic is:. A common use of this input is to use a D-Infinity contributing area grid as the mask so that the delineated stream network is constrained to areas where D-infinity contributing area is available, replicating the functionality of an edge contamination mask. This function is designed to aid in the determination of a geomorphologically objective threshold to be used to delineate streams. Drop Analysis attempts to select the right threshold automatically by evaluating a stream network for a range of thresholds and examining the constant drop property of the resulting Strahler streams. Basically it asks the question: Is the mean stream drop for first order streams statistically different from the mean stream drop for higher order streams, using a T-test. Stream drop is the difference in elevation from the beginning to the end of a stream defined as the sequence of links of the same stream order. This function can be used in the development of stream network rasters, where the exact watershed characteristic s that were accumulated in the accumulated stream source grid vary based on the method being used to determine the stream network raster. For the science behind using this to determine a stream delineation threshold, see Tarboton et al. This parameter is the lowest end of the range searched for possible threshold values using drop analysis. This technique looks for the smallest threshold in the range where the absolute value of the t-statistic is less than 2. For the science behind the drop analysis see Tarboton et al. This parameter is the highest end of the range searched for possible threshold values using drop analysis.

Step 7. QGIS Interface for SWAT (QSWAT) Tutorial

The first model that we created in the previous chapter was a very simple one, with just one input and 3 algorithms. More complex models can be created, with different types of inputs and containing more step. For this chapter we will work with a model that creates a vector layer with watersheds, based on a DEM and a threshold value. That will be very useful for calculating several vector layers corresponding to different thresholds, without having to repeat each single step each time. This lesson does not contain instructions about how to create you model. You already know the necessary steps we saw them in a previous lesson and you have already seen the basic ideas about the modeler, so you should try it yourself. Remember: first add the inputs and then add the algorithms that use them to create the workflow. Open the modeler and then open the model file that you will find in the data folder. You should see something like this. This model contains all the steps needed to complete the calculation, but it just has one input: the DEM. That means that the threshold for channel definition use a fixed value, which makes the model not as useful as it could be. That is not a problem, since we can edit the model, and that is exactly what we will do. That will ask the user for a numerical input that we can use when such a value is needed in any of the algorithms included in our model. Click on the Number entry in the inputs tree, and you will see the corresponding dialog. Fill it with the values shown next. We have to link that input to the algorithm that uses it, in this case the Channel network one. To edit an algorithm that already exists in the modeler, just click on the pen icon on the corresponding box in the canvas. If you click on the Channel network algorithm, you will see something like this. The dialog is filled with the current values used by the algorithm. You can see that the threshold parameter has a fixed value of 1, this is also the default value of the algorithm, but any other value could be put in there. However, you might notice that the parameter is not entered in a common text box, but in an option menu. If you unfold it, you will see something like this. The input that we added is there and we can select it. Whenever an algorithm in a model requires a numerical value, you can hardcode it and directly type it, or you can use any of the available inputs and values remember that some algorithms generate single numerical values.

QGIS Raster Calculator for No Data Values and Thresholds (Version 3.x)



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