Spatial Analyst Tools
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| Spatial Analyst Tools |
The ArcGIS Spatial Analyst extension provides a rich set of spatial analysis and modeling tools for both raster (cell-based) and feature (vector) data.
Spatial Analyst Tools consist of a set of tools, and it will be explained by explaining all the tools as follows:
Conditional Toolset:
Conditional tools allow you to control the output values based on the conditions placed on the input values. Conditions that can be applied are of two types, either they are queries about attributes or a condition that depends on the position of the conditional in the list. Attribute query tools clearly select all cells evaluated as True.
These cells can keep their original value, set to another value, or set to NoData. Cells evaluated as False can be set to a different set of values than if True. For example, if the value in the input raster is greater than ten, return one; Otherwise, return 100:
Performs a conditional if/else evaluation on each of the input cells of an input raster.
The value from a position raster is used to determine from which raster in a list of input rasters the output cell value will be obtained.
Set Null sets identified cell locations to NoData based on a specified criteria. It returns NoData if a conditional evaluation is true, and returns the value specified by another raster if it is false.
Density Toolset:
Using the Density tools, you can calculate the density of the input features within a neighborhood around each output point cell. By calculating the density, you are in a sense spreading the values (for the input) over the surface. The amount is distributed at each sample location (line or point) throughout the study area,
And the density value is calculated for each cell in the output raster. For density maps, a circular search area is applied that specifies the distance to search for sample sites (a line or point) or to spread the values around each site and calculate the density value:
Calculates a magnitude-per-unit area from point or polyline features using a kernel function to fit a smoothly tapered surface to each point or polyline.
Calculates a magnitude-per-unit area from polyline features that fall within a radius around each cell.
Calculates a magnitude-per-unit area from point features that fall within a neighborhood around each cell.
Distance Toolset:
The distance tools allow you to perform an analysis that is either a straight line (Euclidean) or a weighted distance. Distance can be weighted by a simple cost (friction) surface, or by ways that take into account vertical and horizontal constraints on movement, and the two main ways to perform distance analysis using the ArcGIS Spatial Analyst extension are Euclidean distance and cost-weighted distance tools. The Euclidean distance tool measures the distance of a straight line from each cell to the nearest source; The source identifies the things of importance,
Such as wells, roads or school. The distance from the center of the cell to the center of the cell is measured. Not only can you specify the distance between each cell and the nearest source, you can also calculate the orientation for each cell using the Euclidean orientation and determine the closest source using the Euclidean assignment. Euclidean distance equates to distance as a cost factor, which is the cost of traveling through any given cell. For example, the mountain climb to the destination may be shorter, but it is faster to get around it. The cost allocator selects the nearest (or least expensive) source cell based on the accrued travel cost. The cost return link tool provides a roadmap that defines the path to take from any cell, along the least expensive path,
Back to the nearest source, in addition to a single cost variable, vertical and horizontal constraints on movement can be incorporated into your analysis using the Path Distance Tools, Path Distance Customization, and Path Distance Backlink:
Once you have done the cost distance analysis, and generated the distance and direction bitmaps, you can calculate the least expensive (or shortest) path from the chosen destination to your source location using cost path and cost path as multiline tools. The cost path travels from the destination to the source in what is guaranteed to be the cheapest path relative to the cost units specified by the original cost raster. With two cost raster data instead of a linear path, you can use the Corridor tool to select a group of cells that do not exceed the specified cost:
Calculates the sum of accumulative costs for two input accumulative cost rasters.
Calculates, for each cell, its least-cost source based on the least accumulative cost over a cost surface.
Defines the neighbor that is the next cell on the least accumulative cost path to the least-cost source.
Produces the least-cost connectivity network between two or more input regions.
Calculates the least accumulative cost distance for each cell from or to the least-cost source over a cost surface.
Calculates the least-cost path from a source to a destination.
Calculates the least-cost path from a source to a destination as a line feature.
Calculates, for each cell, the nearest source based on Euclidean distance.
Calculates, for each cell, the direction, in degrees, to the neighboring cell along the shortest path back to the closest source while avoiding barriers.
Calculates, for each cell, the direction, in degrees, to the nearest source.
Calculates, for each cell, the Euclidean distance to the closest source.
Calculates, for each cell, the least accumulative cost distance from or to the least-cost source, while accounting for surface distance along with horizontal and vertical cost factors.
Calculates the least-cost source for each cell based on the least accumulative cost over a cost surface, while accounting for surface distance along with horizontal and vertical cost factors.
Defines the neighbor that is the next cell on the least accumulative cost path to the least-cost source, while accounting for surface distance along with horizontal and vertical cost factors.
Extraction Toolset:
Extraction tools allow you to extract a subset of cells from a raster either by cell attributes or their spatial location. You can also get cell values for specific locations as an attribute in a point feature class or as a table.
Tools that extract cell values based on their attributes or location into a new raster include: Extracting cells by attribute value (extracting by attributes) is accomplished by a where condition. For example, your analysis might require extracting cells more than 100 m in height from an elevation dot line. Extracting cells by their spatial geometry requires that cell groups meet the criteria for falling into or out of a specific geometry (extract by circle, extraction by polygon,
Extraction by rectangle) Extracting cells by specific locations requires specifying those locations either by the locations of the x,y points (extract by points) or by the selected cells with a bitmap mask (extract by mask). Tools that allow you to specify the locations for which cell values are extracted to an attribute or regular table include the following:
The cell values defined by the point feature class can be recorded as an attribute of the new Extract Values to Points class. This will extract values from only one raster input. The cell values defined by the point feature class can be appended to the attribute table of that feature class (extracting multiple values to points). Cell values can also be selected from multiple bitmaps. Cell values for specific locations (raster and feature) can be recorded in a table (sample):
Extracts the cells of a raster based on a logical query.
Extracts the cells of a raster based on a circle by specifying the circle's center and radius.
Extracts the cells of a raster that correspond to the areas defined by a mask.
Extracts the cells of a raster based on a set of coordinate points.
Extracts the cells of a raster based on a polygon by specifying the polygon's vertices.
Extracts the cells of a raster based on a rectangle by specifying the rectangle's extent.
Extract Multi Values to Points
Extracts cell values at locations specified in a point feature class from one or more rasters and records the values to the attribute table of the point feature class.
Extracts the cell values of a raster based on a set of point features and records the values in the attribute table of an output feature class.
Creates a table that shows the values of cells from a raster, or set of rasters, for defined locations. The locations are defined by raster cells or by a set of points.
The input rasters can be two-dimensional or multidimensional. The structure of the output table changes when the input rasters are multidimensional.
Generalization Toolset:
Generalization analysis tools are used either to clean up small erroneous data in a raster or to generalize the data to get rid of unnecessary details for a more general analysis There are many common sources of erroneous data, such as the following: May contain many small areas of cells that are categorized wrong, and images scanned on paper maps may contain unnecessary lines or text,
There may be problems converting raster data with different formats, resolutions, or projections. Generalization tools help you identify these regions and automate the assignment of more reliable values to the cells that make up the regions. Generalizing tools fall into several general categories: those that generalize to areas (Expand and Shrink, as well as Nibble and Thin) and those that smooth out the edges of a region.
(Boundary Clean and Majority Filter) Those that identify unique regions that consist of regions. (area group) The one that changes the accuracy of the data. (Aggregation):
Generates a reduced-resolution version of a raster. Each output cell contains the Sum, Minimum, Maximum, Mean, or Median of the input cells that are encompassed by the extent of that cell.
Smooths the boundary between zones by expanding and shrinking it.
Expands specified zones of a raster by a specified number of cells.
Replaces cells in a raster based on the majority of their contiguous neighboring cells.
Replaces cells of a raster corresponding to a mask with the values of the nearest neighbors.
For each cell in the output, the identity of the connected region to which that cell belongs is recorded. A unique number is assigned to each region.
Shrinks the selected zones by a specified number of cells by replacing them with the value of the cell that is most frequent in its neighborhood.
Thins rasterized linear features by reducing the number of cells representing the width of the features.
Groundwater Toolset:
Groundwater instruments can be used to perform rudimentary modeling of fluorescence and dispersion of components in groundwater flow. The following topics provide background information on the theoretical aspects of the tools as well as some examples of their implementation:
Calculates the groundwater seepage velocity vector (direction and magnitude) for steady flow in an aquifer.
Calculates the groundwater seepage velocity vector (direction and magnitude) for steady flow in an aquifer.
Calculates the path of a particle through a velocity field, returning an ASCII file of particle tracking data and, optionally, a feature class of track information.
Calculates the time-dependent, two-dimensional concentration distribution in mass per volume of a solute introduced instantaneously and at a discrete point into a vertically mixed aquifer.
Hydrology Toolset:
Hydrology tools are used to model the flow of water through a surface, and information about the shape of the Earth's surface is useful for many areas, such as regional planning, agriculture, and forestry. These fields require an understanding of how water flows through an area and how changes in that area can affect that flow. When modeling the flow of water, you may want to know where the water is coming from and where it is heading. The following topics explain how hydrological functions can be used to help model the movement of water across the surface, key concepts and terms related to drainage systems and surface processes, how tools can be used to extract hydrological information from a digital elevation model (DEM), and sample hydrological applications:
Creates a raster delineating all drainage basins.
Fills sinks in a surface raster to remove small imperfections in the data.
Creates a raster of accumulated flow into each cell. A weight factor can optionally be applied.
Creates a raster of flow direction from each cell to its downslope neighbor, or neighbors, using D8, Multiple Flow Direction (MFD) or D-Infinity (DINF) methods.
Computes, for each cell, the horizontal or vertical component of downslope distance, following the flow path(s), to cell(s) on a stream into which they flow. In case of multiple flow paths, minimum, weighted mean, or maximum flow distance can be computed.
If an optional flow direction raster is provided, the down slope direction(s) will be limited to those defined by the input flow direction raster.
Calculates the upstream or downstream distance, or weighted distance, along the flow path for each cell.
Creates a raster identifying all sinks or areas of internal drainage.
Snaps pour points to the cell of highest flow accumulation within a specified distance.
Assigns unique values to sections of a raster linear network between intersections.
Assigns a numeric order to segments of a raster representing branches of a linear network.
Converts a raster representing a linear network to features representing the linear network.
Determines the contributing area above a set of cells in a raster.
Interpolation Toolset:
Interpolation tools create a continuous surface (or prediction) from the point values taken, and it is usually difficult or expensive to visit each site in the study area to measure the height, concentration, or magnitude of a phenomenon. Instead of that,
You can measure the phenomenon at strategically dispersed sample sites, and the expected values can be assigned to all other sites. Entry points can be randomly spaced, uniformly spaced, or based on a sampling scheme. A continuous surface representation of a raster data set represents some measure, such as height, concentration, or magnitude (for example, height, acidity, or noise level).
Surface interpolation tools make predictions from sample measurements for all locations in the output raster dataset, whether or not an in-situ measurement is performed.
There are a variety of ways to derive a prediction for each location; Each method is referred to as a model. With each model, there are different assumptions for the data,
And certain models are more applicable to specific data - for example, one model may explain local variance better than another. Each model produces predictions using different calculations:
Interpolates a raster surface from points using an inverse distance weighted (IDW) technique.
Interpolates a raster surface from points using kriging.
Interpolates a raster surface from points using a natural neighbor technique.
Interpolates a raster surface from points using a two-dimensional minimum curvature spline technique.
The resulting smooth surface passes exactly through the input points.
Interpolates a raster surface, using barriers, from points using a minimum curvature spline technique. The barriers are entered as either polygon or polyline features.
Interpolates a hydrologically correct raster surface from point, line, and polygon data.
Interpolates a hydrologically correct raster surface from point, line, and polygon data using parameters specified in a file.
Interpolates a raster surface from points using a trend technique.
Local Toolset:
- Local tools are those in which the value at each cell location on the resulting raster is a function of the values from all the inputs at that location. To perform the calculation, the local tool only needs, for both the input raster, the value at that location, plus (in some cases) a comparison value. Once the result is generated, the calculation is made for the location of the next cell,
- The process is repeated until all cells have been processed. With the local tools, you can combine the input raster, calculate a statistic on it, or evaluate a criterion for each cell in the output raster based on the values of each cell from multiple input raster:
Calculates a per-cell statistic from multiple rasters.
The available statistics are Majority, Maximum, Mean, Median, Minimum, Minority, Range, Standard deviation, Sum, and Variety.
Combines multiple rasters so that a unique output value is assigned to each unique combination of input values.
Evaluates on a cell-by-cell basis the number of times the values in a set of rasters are equal to another raster.
Evaluates on a cell-by-cell basis the number of times a set of rasters is greater than another raster.
Determines on a cell-by-cell basis the position of the raster with the maximum value in a set of rasters.
Evaluates on a cell-by-cell basis the number of times a set of rasters is less than another raster.
Determines on a cell-by-cell basis the position of the raster with the minimum value in a set of rasters.
Determines the value in an argument list that is at a certain level of popularity on a cell-by-cell basis. The particular level of popularity (the number of occurrences of each value) is specified by the first argument.
The values from the set of input rasters are ranked on a cell-by-cell basis, and which of these gets returned is determined by the value of the rank input raster.
Map Algebra Toolset:
- Algebra map is Iran's method for spatial analysis by creating expressions in an algebraic language.
With a raster calculator, you can easily create and run algebra map expressions that set a raster:
Builds and executes a single Map Algebra expression using Python syntax in a calculator-like interface.
Go to Spatial Analyst Tools Part 2
- The same topic is available in Arabic from here:
Watch this video from the YouTube channel.
In the same way, as described through this site. Watch the video first, then you can search for any tool by writing its name in the search, the language of the video is Arabic, but English subtitles and any language in the world are available. Good luck and God bless you.
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