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<div class="section" id="arcgis-raster-analytics-module">
<h1>arcgis.raster.analytics module<a class="headerlink" href="#arcgis-raster-analytics-module" title="Permalink to this headline">¶</a></h1>
<span class="target" id="module-arcgis.raster.analytics"></span><p>Functions for calling the Raster Analysis Tools. The RasterAnalysisTools service is used by ArcGIS Server to provide distributed raster analysis.</p>
<div class="section" id="get-datastores">
<h2>get_datastores<a class="headerlink" href="#get-datastores" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt id="arcgis.raster.analytics.get_datastores">
<code class="descclassname">arcgis.raster.analytics.</code><code class="descname">get_datastores</code><span class="sig-paren">(</span><em>gis=None</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.get_datastores" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns a helper object to manage raster analytics datastores in the GIS.
If a gis isn’t specified, returns datastore manager of arcgis.env.active_gis</p>
</dd></dl>
</div>
<div class="section" id="is-supported">
<h2>is_supported<a class="headerlink" href="#is-supported" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt id="arcgis.raster.analytics.is_supported">
<code class="descclassname">arcgis.raster.analytics.</code><code class="descname">is_supported</code><span class="sig-paren">(</span><em>gis=None</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.is_supported" title="Permalink to this definition">¶</a></dt>
<dd><p>Returns True if the GIS supports raster analytics. If a gis isn’t specified,
checks if arcgis.env.active_gis supports raster analytics</p>
</dd></dl>
</div>
<div class="section" id="generate-raster">
<h2>generate_raster<a class="headerlink" href="#generate-raster" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt id="arcgis.raster.analytics.generate_raster">
<code class="descclassname">arcgis.raster.analytics.</code><code class="descname">generate_raster</code><span class="sig-paren">(</span><em>raster_function</em>, <em>function_arguments=None</em>, <em>output_raster_properties=None</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.generate_raster" title="Permalink to this definition">¶</a></dt>
<dd><p>raster_function : Required, see <a class="reference external" href="http://resources.arcgis.com/en/help/rest/apiref/israsterfunctions.html">http://resources.arcgis.com/en/help/rest/apiref/israsterfunctions.html</a></p>
<p>function_arguments : Optional, for specifying input Raster alone, portal Item can be passed</p>
<p>output_raster_properties : Optional</p>
<dl class="docutils">
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Image Service is created by the method and used as the output raster. </span></dt>
<dd><p class="first">You can pass in an existing Image Service Item from your GIS to use that instead.</p>
<p>Alternatively, you can pass in the name of the output Image Service that should be created by this method to be
used as the output for the tool.</p>
<p class="last">A RuntimeError is raised if a service by that name already exists</p>
</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_raster : Image layer item</p>
</dd></dl>
</div>
<div class="section" id="interpolate-points">
<h2>interpolate_points<a class="headerlink" href="#interpolate-points" title="Permalink to this headline">¶</a></h2>
<dl class="function">
<dt id="arcgis.raster.analytics.interpolate_points">
<code class="descclassname">arcgis.raster.analytics.</code><code class="descname">interpolate_points</code><span class="sig-paren">(</span><em>input_point_features</em>, <em>interpolate_field</em>, <em>optimize_for='BALANCE'</em>, <em>transform_data=False</em>, <em>size_of_local_models=None</em>, <em>number_of_neighbors=None</em>, <em>output_cell_size=None</em>, <em>output_prediction_error=False</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.interpolate_points" title="Permalink to this definition">¶</a></dt>
<dd><p>This tool allows you to predict values at new locations based on measurements from a collection of points. The tool
takes point data with values at each point and returns a raster of predicted values:</p>
<ul class="simple">
<li><dl class="first docutils">
<dt>An air quality management district has sensors that measure pollution levels. Interpolate Points can be used to</dt>
<dd>predict pollution levels at locations that don’t have sensors, such as locations with at-risk populations-
schools or hospitals, for example.</dd>
</dl>
</li>
<li>Predict heavy metal concentrations in crops based on samples taken from individual plants.</li>
<li><dl class="first docutils">
<dt>Predict soil nutrient levels (nitrogen, phosphorus, potassium, and so on) and other indicators (such as electrical</dt>
<dd>conductivity) in order to study their relationships to crop yield and prescribe precise amounts of fertilizer
for each location in the field.</dd>
</dl>
</li>
<li><dl class="first docutils">
<dt>Meteorological applications include prediction of temperatures, rainfall, and associated variables (such as acid</dt>
<dd>rain).</dd>
</dl>
</li>
</ul>
<dl class="docutils">
<dt>input_point_features <span class="classifier-delimiter">:</span> <span class="classifier">Required point layer containing locations with known values</span></dt>
<dd>The point layer that contains the points where the values have been measured.</dd>
<dt>interpolate_field <span class="classifier-delimiter">:</span> <span class="classifier">Required string - field to interpolate</span></dt>
<dd>Choose the field whose values you wish to interpolate. The field must be numeric.</dd>
<dt>optimize_for <span class="classifier-delimiter">:</span> <span class="classifier">Optional string - Choose your preference for speed versus accuracy.</span></dt>
<dd>More accurate predictions take longer to calculate. This parameter alters the default values of several other
parameters of Interpolate Points in order to optimize speed of calculation, accuracy of results, or a balance of
the two. By default, the tool will optimize for balance.
One of the following: [‘SPEED’, ‘BALANCE’, ‘ACCURACY’]</dd>
<dt>transform_data <span class="classifier-delimiter">:</span> <span class="classifier">Optional bool - Choose whether to transform your data to the normal distribution.</span></dt>
<dd>Interpolation is most accurate for data that follows a normal (bell-shaped) distribution. If your data does not
appear to be normally distributed, you should perform a transformation.</dd>
<dt>size_of_local_models <span class="classifier-delimiter">:</span> <span class="classifier">Optional int - Size of local models</span></dt>
<dd>Interpolate Points works by building local interpolation models that are mixed together to create the final
prediction map. This parameter controls how many points will be contained in each local model. Smaller values
will make results more local and can reveal small-scale effects, but it may introduce some instability in the
calculations. Larger values will be more stable, but some local effects may be missed.
The value can range from 30 to 500, but typical values are between 50 and 200.</dd>
<dt>number_of_neighbors <span class="classifier-delimiter">:</span> <span class="classifier">Optional int - Number of Neighbors</span></dt>
<dd>Predictions are calculated based on neighboring points. This parameter controls how many points will be used in
the calculation. Using a larger number of neighbors will generally produce more accurate results, but the
results take longer to calculate.
This value can range from 1 to 64, but typical values are between 5 and 15.</dd>
<dt>output_cell_size <span class="classifier-delimiter">:</span> <span class="classifier">Optional LinearUnit - Output cell size</span></dt>
<dd>Enter the cell size and unit for the output rasters.
The available units are Feet, Miles, Meters, and Kilometers.</dd>
<dt>output_prediction_error <span class="classifier-delimiter">:</span> <span class="classifier">Optional bool - Output prediction error</span></dt>
<dd>Choose whether you want to create a raster of standard errors for the predicted values.
Standard errors are useful because they provide information about the reliability of the predicted values.
A simple rule of thumb is that the true value will fall within two standard errors of the predicted value 95
percent of the time. For example, suppose a new location gets a predicted value of 50 with a standard error of
5. This means that this tool’s best guess is that the true value at that location is 50, but it reasonably could
be as low as 40 or as high as 60. To calculate this range of reasonable values, multiply the standard error by
2, add this value to the predicted value to get the upper end of the range, and subtract it from the predicted
value to get the lower end of the range.</dd>
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Image Service is created by the method and used as the output raster.</span></dt>
<dd>You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>named tuple with name values being :</p>
<blockquote>
<div><ul class="simple">
<li>output_raster (the output_raster item description is updated with the process_info),</li>
<li>process_info (if run in a non-Jupyter environment, use process_info.data to get the HTML data) and</li>
<li>output_error_raster (if output_prediction_error is set to True).</li>
</ul>
</div></blockquote>
</dd></dl>
</div>
<div class="section" id="create-viewshed">
<h2>create_viewshed<a class="headerlink" href="#create-viewshed" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.create_viewshed">
<code class="descclassname">analytics.</code><code class="descname">create_viewshed</code><span class="sig-paren">(</span><em>input_elevation_surface</em>, <em>input_observer_features</em>, <em>optimize_for=None</em>, <em>maximum_viewing_distance=None</em>, <em>maximum_viewing_distance_field=None</em>, <em>minimum_viewing_distance=None</em>, <em>minimum_viewing_distance_field=None</em>, <em>viewing_distance_is_3d=None</em>, <em>observers_elevation=None</em>, <em>observers_elevation_field=None</em>, <em>observers_height=None</em>, <em>observers_height_field=None</em>, <em>target_height=None</em>, <em>target_height_field=None</em>, <em>above_ground_level_output_name=None</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.create_viewshed" title="Permalink to this definition">¶</a></dt>
<dd><p>Compute visibility for an input elevation raster using geodesic method.</p>
<p>input_elevation_surface : Required string</p>
<p>input_observer_features : Required FeatureSet</p>
<dl class="docutils">
<dt>optimize_for <span class="classifier-delimiter">:</span> <span class="classifier">Optional string</span></dt>
<dd>One of the following: [‘SPEED’, ‘ACCURACY’]</dd>
</dl>
<p>maximum_viewing_distance : Optional LinearUnit</p>
<p>maximum_viewing_distance_field : Optional string</p>
<p>minimum_viewing_distance : Optional LinearUnit</p>
<p>minimum_viewing_distance_field : Optional string</p>
<p>viewing_distance_is_3d : Optional bool</p>
<p>observers_elevation : Optional LinearUnit</p>
<p>observers_elevation_field : Optional string</p>
<p>observers_height : Optional LinearUnit</p>
<p>observers_height_field : Optional string</p>
<p>target_height : Optional LinearUnit</p>
<p>target_height_field : Optional string</p>
<p>above_ground_level_output_name : Optional string</p>
<dl class="docutils">
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Image Service is created by the method and used as the output raster.</span></dt>
<dd>You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<dl class="docutils">
<dt>dict with the following keys:</dt>
<dd>“output_raster” : layer
“output_above_ground_level_raster” : layer</dd>
</dl>
</dd></dl>
</div>
<div class="section" id="summarize-raster-within">
<h2>summarize_raster_within<a class="headerlink" href="#summarize-raster-within" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.summarize_raster_within">
<code class="descclassname">analytics.</code><code class="descname">summarize_raster_within</code><span class="sig-paren">(</span><em>input_zone_layer</em>, <em>input_raster_layer_to_summarize</em>, <em>zone_field='Value'</em>, <em>statistic_type='Mean'</em>, <em>ignore_missing_values=True</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.summarize_raster_within" title="Permalink to this definition">¶</a></dt>
<dd><dl class="docutils">
<dt>input_zone_layer <span class="classifier-delimiter">:</span> <span class="classifier">Required layer - area layer to summarize a raster layer within defined boundaries.</span></dt>
<dd>The layer that defines the boundaries of the areas, or zones, that will be summarized.
The layer can be a raster or feature data. For rasters, the zones are defined by all locations in the input that
have the same cell value. The areas do not have to be contiguous.</dd>
<dt>input_raster_layer_to_summarize <span class="classifier-delimiter">:</span> <span class="classifier">Required - raster layer to summarize.</span></dt>
<dd>The raster cells in this layer will be summarized by the areas (zones) that they fall within.</dd>
<dt>zone_field <span class="classifier-delimiter">:</span> <span class="classifier">Required string - field to define the boundaries. This is the attribute of the layer that will be used</span></dt>
<dd>to define the boundaries of the areas. For example, suppose the first input layer defines the management unit
boundaries, with attributes that define the region, the district, and the parcel ID of each unit. You also have
a raster layer defining a biodiversity index for each location. With the field you select, you can decide to
calculate the average biodiversity at local, district, or regional levels.</dd>
<dt>statistic_type <span class="classifier-delimiter">:</span> <span class="classifier">Optional string - statistic to calculate.</span></dt>
<dd>You can calculate statistics of any numerical attribute of the points, lines, or areas within the input area
layer. The available statistics types when the selected field is integer are
Mean, Maximum, Median, Minimum, Minority, Range, Standard deviation(STD), Sum, and Variety. If the field is
floating point, the options are Mean, Maximum, Minimum, Range, Standard deviation, and Sum.
One of the following:
[‘Mean’, ‘Majority’, ‘Maximum’, ‘Median’, ‘Minimum’, ‘Minority’, ‘Range’, ‘STD’, ‘SUM’, ‘Variety’]</dd>
<dt>ignore_missing_values <span class="classifier-delimiter">:</span> <span class="classifier">Optional bool.</span></dt>
<dd>If you choose to ignore missing values, only the cells that have a value in the layer to be summarized will be
used in determining the output value for that area. Otherwise, if there are missing values anywhere in an area,
it is deemed that there is insufficient information to perform statistical calculations for all the cells in
that zone, and that area will receive a null (NoData) value in the output.</dd>
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Image Service is created by the method and used as the output raster.</span></dt>
<dd>You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_raster : Image layer item</p>
</dd></dl>
</div>
<div class="section" id="calculate-density">
<h2>calculate_density<a class="headerlink" href="#calculate-density" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.calculate_density">
<code class="descclassname">analytics.</code><code class="descname">calculate_density</code><span class="sig-paren">(</span><em>input_point_or_line_features</em>, <em>count_field=None</em>, <em>search_distance=None</em>, <em>output_area_units=None</em>, <em>output_cell_size=None</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.calculate_density" title="Permalink to this definition">¶</a></dt>
<dd><p>Density analysis takes known quantities of some phenomenon and creates a density map by spreading
these quantities across the map. You can use this tool, for example, to show concentrations of
lightning strikes or tornadoes, access to health care facilities, and population densities.</p>
<p>This tool creates a density map from point or line features by spreading known quantities of some
phenomenon (represented as attributes of the points or lines) across the map. The result is a
layer of areas classified from least dense to most dense.</p>
<p>For point input, each point should represent the location of some event or incident, and the
result layer represents a count of the incident per unit area. A larger density value in a new
location means that there are more points near that location. In many cases, the result layer can
be interpreted as a risk surface for future events. For example, if the input points represent
locations of lightning strikes, the result layer can be interpreted as a risk surface for future
lightning strikes.</p>
<p>For line input, the line density surface represents the total amount of line that is near each
location. The units of the calculated density values are the length of line-per-unit area.
For example, if the lines represent rivers, the result layer will represent the total length
of rivers that are within the search radius. This result can be used to identify areas that are
hospitable to grazing animals.</p>
<p>Other use cases of this tool include the following:</p>
<ul class="simple">
<li>Creating crime density maps to help police departments properly allocate resources to high crime
areas.</li>
<li>Calculating densities of hospitals within a county. The result layer will show areas with
high and low accessibility to hospitals, and this information can be used to decide where
new hospitals should be built.</li>
<li>Identifying areas that are at high risk of forest fires based on historical locations of
forest fires.</li>
<li>Locating communities that are far from major highways in order to plan where new roads should
be constructed.</li>
</ul>
<dl class="docutils">
<dt>input_point_or_line_features <span class="classifier-delimiter">:</span> <span class="classifier">Required feature layer - The input point or line layer that will be used to calculate</span></dt>
<dd>the density layer.</dd>
<dt>count_field <span class="classifier-delimiter">:</span> <span class="classifier">Optional string - count field</span></dt>
<dd>Provide a field specifying the number of incidents at each location. For example, if you have points that
represent cities, you can use a field representing the population of the city as the count field, and the
resulting population density layer will calculate larger population densities near cities with
larger populations. If the default choice of None is used, then each location will be assumed to represent a
single count.</dd>
<dt>search_distance <span class="classifier-delimiter">:</span> <span class="classifier">Optional LinearUnit - Search distance</span></dt>
<dd>Enter a distance specifying how far to search to find point or line features when calculating density values.
For example, if you provide a search distance of 10,000 meters, the density of any location in the output layer
is calculated based on features that are within 10,000 meters of the location. Any location that does not have
any incidents within 10,000 meters will receive a density value of zero.
If no distance is provided, a default will be calculated that is based on the locations of the input features
and the values in the count field (if a count field is provided).</dd>
<dt>output_area_units <span class="classifier-delimiter">:</span> <span class="classifier">Optional string - Output area units</span></dt>
<dd>Specify the output area unit. Density is count divided by area, and this parameter specifies the unit of the
area in the density calculation. The available areal units are Square Miles and Square Kilometers.</dd>
<dt>output_cell_size <span class="classifier-delimiter">:</span> <span class="classifier">Optional LinearUnit - Output cell size</span></dt>
<dd>Enter the cell size and unit for the output rasters.</dd>
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Image Service is created by the method and used as the output raster.</span></dt>
<dd>You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_raster : Image layer item</p>
</dd></dl>
</div>
<div class="section" id="classify">
<h2>classify<a class="headerlink" href="#classify" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.classify">
<code class="descclassname">analytics.</code><code class="descname">classify</code><span class="sig-paren">(</span><em>input_raster</em>, <em>input_classifier_definition</em>, <em>additional_input_raster=None</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.classify" title="Permalink to this definition">¶</a></dt>
<dd><p>input_raster : Required string</p>
<p>input_classifier_definition : Required string</p>
<p>additional_input_raster : Optional string</p>
<dl class="docutils">
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Image Service is created by the method and used as the output raster.</span></dt>
<dd>You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_raster : Image layer item</p>
</dd></dl>
</div>
<div class="section" id="segment">
<h2>segment<a class="headerlink" href="#segment" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.segment">
<code class="descclassname">analytics.</code><code class="descname">segment</code><span class="sig-paren">(</span><em>input_raster, spectral_detail=15.5, spatial_detail=15, minimum_segment_size_in_pixels=20, band_indexes=[0, 1, 2], remove_tiling_artifacts=False, output_name=None, *, gis=None, **kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.segment" title="Permalink to this definition">¶</a></dt>
<dd><p>Groups together adjacent pixels having similar spectral and spatial characteristics into
segments, known as objects.</p>
<table border="1" class="docutils">
<colgroup>
<col width="31%" />
<col width="69%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><strong>Argument</strong></td>
<td><strong>Description</strong></td>
</tr>
<tr class="row-even"><td>input_raster</td>
<td>Required ImageryLayer object</td>
</tr>
<tr class="row-odd"><td>spectral_detail</td>
<td><p class="first">Optional float. Default is 15.5.
Set the level of importance given to the spectral differences of
features in your imagery. Valid values range from 1.0 to 20.0. A high
value is appropriate when you have features you want to classify
separately but have somewhat similar spectral characteristics.
Smaller values create spectrally smoother outputs.</p>
<p class="last">For example, setting a higher spectral detail value for a forested
scene, will preserve greater discrimination between the different tree
species, resulting in more segments.</p>
</td>
</tr>
<tr class="row-even"><td>spatial_detail</td>
<td><p class="first">Optional float. Default is 15.
Set the level of importance given to the proximity between features
in your imagery. Valid values range from 1 to 20. A high value is
appropriate for a scene where your features of interest are small
and clustered together. Smaller values create spatially smoother
outputs.</p>
<p class="last">For example, in an urban scene, you could classify an impervious
surface using a smaller spatial detail, or you could classify
buildings and roads as separate classes using a higher spatial detail.</p>
</td>
</tr>
<tr class="row-odd"><td>minimum_segment_size_in_pixels</td>
<td>Optional float. Default is 20.
Merge segments smaller than this size with their best fitting
neighbor segment. This is related to the minimum mapping unit for a
mapping project. Units are in pixels.</td>
</tr>
<tr class="row-even"><td>band_indexes</td>
<td>Optional List of integers. Default is [0,1,2]
Define which 3 bands are used in segmentation. Choose the bands that
visually discriminate your features of interest best.</td>
</tr>
<tr class="row-odd"><td>remove_tiling_artifacts</td>
<td>Optional Bool. Default is False.
If False, the tool will not run to remove tiling artifacts after
segmentation. The result may seem blocky at some tiling boundaries.</td>
</tr>
<tr class="row-even"><td>output_name</td>
<td>Optional String. If specified, an Imagery Layer of given name is
created. Else, an Image Service is created by the method and used
as the output raster. You can pass in an existing Image Service Item
from your GIS to use that instead. Alternatively, you can pass in
the name of the output Image Service that should be created by this
method to be used as the output for the tool. A RuntimeError is raised
if a service by that name already exists</td>
</tr>
<tr class="row-odd"><td>gis</td>
<td>Optional GIS object. If not speficied, the currently active connection
is used.</td>
</tr>
</tbody>
</table>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">output_raster : Imagery Layer item</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
<div class="section" id="train-classifier">
<h2>train_classifier<a class="headerlink" href="#train-classifier" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.train_classifier">
<code class="descclassname">analytics.</code><code class="descname">train_classifier</code><span class="sig-paren">(</span><em>input_raster</em>, <em>input_training_sample_json</em>, <em>classifier_parameters</em>, <em>segmented_raster=None</em>, <em>segment_attributes='COLOR;MEAN'</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.train_classifier" title="Permalink to this definition">¶</a></dt>
<dd><p>input_raster : Required string</p>
<p>input_training_sample_json : Required string</p>
<p>segmented_raster : Optional string</p>
<p>classifier_parameters : Required string</p>
<p>segment_attributes : Required string</p>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_classifier_definition</p>
</dd></dl>
</div>
<div class="section" id="convert-feature-to-raster">
<h2>convert_feature_to_raster<a class="headerlink" href="#convert-feature-to-raster" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.convert_feature_to_raster">
<code class="descclassname">analytics.</code><code class="descname">convert_feature_to_raster</code><span class="sig-paren">(</span><em>input_feature</em>, <em>output_cell_size</em>, <em>value_field=None</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.convert_feature_to_raster" title="Permalink to this definition">¶</a></dt>
<dd><p>Creates a new raster dataset from an existing feature dataset.
Any feature class containing point, line, or polygon features can be converted to a raster dataset.
The cell center is used to decide the value of the output raster pixel. The input field type determines
the type of output raster. If the field is integer, the output raster will be integer;
if it is floating point, the output will be floating point.</p>
<p>input_feature : Required. The input feature layer to convert to a raster dataset.</p>
<dl class="docutils">
<dt>output_cell_size <span class="classifier-delimiter">:</span> <span class="classifier">Required LinearUnit. The cell size and unit for the output rasters.</span></dt>
<dd>The available units are Feet, Miles, Meters, and Kilometers.
eg - {“distance”:60,”units”:meters}</dd>
</dl>
<p>value_field : Optional string. The field that will be used to assign values to the output raster.</p>
<dl class="docutils">
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. The name of the layer that will be created in My Content.</span></dt>
<dd>If not provided, an Image Service is created by the method and used as the output raster.
You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_raster : Image layer item</p>
</dd></dl>
</div>
<div class="section" id="convert-raster-to-feature">
<h2>convert_raster_to_feature<a class="headerlink" href="#convert-raster-to-feature" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.convert_raster_to_feature">
<code class="descclassname">analytics.</code><code class="descname">convert_raster_to_feature</code><span class="sig-paren">(</span><em>input_raster</em>, <em>field='Value'</em>, <em>output_type='Polygon'</em>, <em>simplify=True</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.convert_raster_to_feature" title="Permalink to this definition">¶</a></dt>
<dd><p>This service tool converts imagery data to feature class vector data.</p>
<p>input_raster : Required. The input raster that will be converted to a feature dataset.</p>
<dl class="docutils">
<dt>field <span class="classifier-delimiter">:</span> <span class="classifier">Optional string - field that specifies which value will be used for the conversion.</span></dt>
<dd>It can be any integer or a string field.
A field containing floating-point values can only be used if the output is to a point dataset.
Default is “Value”</dd>
<dt>output_type <span class="classifier-delimiter">:</span> <span class="classifier">Optional string</span></dt>
<dd>One of the following: [‘Point’, ‘Line’, ‘Polygon’]</dd>
<dt>simplify <span class="classifier-delimiter">:</span> <span class="classifier">Optional bool, This option that specifies how the features should be smoothed. It is </span></dt>
<dd>only available for line and polygon output.
True, then the features will be smoothed out. This is the default.
if False, then The features will follow exactly the cell boundaries of the raster dataset.</dd>
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Feature layer is created by the method and used as the output .</span></dt>
<dd>You can pass in an existing Feature Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Feature Service that should be created by this method
to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_features : Image layer item</p>
</dd></dl>
</div>
<div class="section" id="copy-raster">
<h2>copy_raster<a class="headerlink" href="#copy-raster" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.copy_raster">
<code class="descclassname">analytics.</code><code class="descname">copy_raster</code><span class="sig-paren">(</span><em>input_raster</em>, <em>output_cellsize=None</em>, <em>resampling_method='NEAREST'</em>, <em>clip_setting=None</em>, <em>output_name=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.copy_raster" title="Permalink to this definition">¶</a></dt>
<dd><p>input_raster : Required string</p>
<p>output_cellsize : Optional string</p>
<dl class="docutils">
<dt>resampling_method <span class="classifier-delimiter">:</span> <span class="classifier">Optional string</span></dt>
<dd>One of the following: [‘NEAREST’, ‘BILINEAR’, ‘CUBIC’, ‘MAJORITY’]</dd>
</dl>
<p>clip_setting : Optional string</p>
<dl class="docutils">
<dt>output_name <span class="classifier-delimiter">:</span> <span class="classifier">Optional. If not provided, an Image Service is created by the method and used as the output raster.</span></dt>
<dd>You can pass in an existing Image Service Item from your GIS to use that instead.
Alternatively, you can pass in the name of the output Image Service that should be created by this method to be used as the output for the tool.
A RuntimeError is raised if a service by that name already exists</dd>
</dl>
<p>gis: Optional, the GIS on which this tool runs. If not specified, the active GIS is used.</p>
<p>output_raster : Image layer item</p>
</dd></dl>
</div>
<div class="section" id="create-image-collection">
<h2>create_image_collection<a class="headerlink" href="#create-image-collection" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.create_image_collection">
<code class="descclassname">analytics.</code><code class="descname">create_image_collection</code><span class="sig-paren">(</span><em>image_collection</em>, <em>input_rasters</em>, <em>raster_type_name</em>, <em>raster_type_params=None</em>, <em>out_sr=None</em>, <em>context=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.create_image_collection" title="Permalink to this definition">¶</a></dt>
<dd><p>Create a collection of images that will participate in the ortho-mapping project.
Provides provision to use input rasters by reference
and to specify image collection properties through context parameter.</p>
<table border="1" class="docutils">
<colgroup>
<col width="11%" />
<col width="89%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><strong>Argument</strong></td>
<td><strong>Description</strong></td>
</tr>
<tr class="row-even"><td>image_collection</td>
<td><p class="first">Required, the name of the image collection to create.</p>
<p>The image collection can be an existing image service, in
which the function will create a mosaic dataset and the existing
hosted image service will then point to the new mosaic dataset.</p>
<p>If the image collection does not exist, a new multi-tenant
service will be created.</p>
<p class="last">This parameter can be the Item representing an existing image_collection
or it can be a string representing the name of the image_collection
(either existing or to be created.)</p>
</td>
</tr>
<tr class="row-odd"><td>input_rasters</td>
<td>Required, the list of input rasters to be added to
the image collection being created. This parameter can
be any one of the following:
- List of portal Items of the images
- An image service URL
- Shared data path (this path must be accessible by the server)
- Name of a folder on the portal</td>
</tr>
<tr class="row-even"><td>raster_type_name</td>
<td>Required, the name of the raster type to use for adding data to
the image collection.</td>
</tr>
<tr class="row-odd"><td>raster_type_params</td>
<td><p class="first">Optional, additional raster_type specific parameters.</p>
<p>The process of add rasters to the image collection can be
controlled by specifying additional raster type arguments.</p>
<p class="last">The raster type parameters argument is a dictionary.</p>
</td>
</tr>
<tr class="row-even"><td>out_sr</td>
<td><p class="first">Optional, additional parameters of the service.</p>
<p class="last">The following additional parameters can be specified:
- Spatial reference of the image_collection; The well-known ID of
the spatial reference or a spatial reference dictionary object for the
input geometries.
If the raster type name is set to “UAV/UAS”, the spatial reference of the
output image collection will be determined by the raster type parameters defined.</p>
</td>
</tr>
<tr class="row-odd"><td>context</td>
<td><dl class="first last docutils">
<dt>Optional, The context parameter is used to provide additional input parameters</dt>
<dd><p class="first">{“image_collection_properties”: {“imageCollectionType”:”Satellite”},”byref”:True}</p>
<p>use image_collection_properties key to set value for imageCollectionType.
Note: the “imageCollectionType” property is important for image collection that will later on be adjusted by orthomapping system service.
Based on the image collection type, the orthomapping system service will choose different algorithm for adjustment.
Therefore, if the image collection is created by reference, the requester should set this
property based on the type of images in the image collection using the following keywords.
If the imageCollectionType is not set, it defaults to “UAV/UAS”</p>
<p class="last">If byref is set to True, the data will not be uploaded. If it is not set, the default is False</p>
</dd>
</dl>
</td>
</tr>
<tr class="row-even"><td>gis</td>
<td>Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.</td>
</tr>
</tbody>
</table>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The imagery layer item</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
<div class="section" id="add-image">
<h2>add_image<a class="headerlink" href="#add-image" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.add_image">
<code class="descclassname">analytics.</code><code class="descname">add_image</code><span class="sig-paren">(</span><em>image_collection</em>, <em>input_rasters</em>, <em>raster_type_name=None</em>, <em>raster_type_params=None</em>, <em>context=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.add_image" title="Permalink to this definition">¶</a></dt>
<dd><p>Add a collection of images to an existing image_collection. Provides provision to use input rasters by reference
and to specify image collection properties through context parameter.</p>
<p>It can be used when new data is available to be included in the same
orthomapping project. When new data is added to the image collection
the entire image collection must be reset to the original state.</p>
<table border="1" class="docutils">
<colgroup>
<col width="11%" />
<col width="89%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><strong>Argument</strong></td>
<td><strong>Description</strong></td>
</tr>
<tr class="row-even"><td>input_rasters</td>
<td>Required, the list of input rasters to be added to
the image collection being created. This parameter can
be any one of the following:
- List of portal Items of the images
- An image service URL
- Shared data path (this path must be accessible by the server)
- Name of a folder on the portal</td>
</tr>
<tr class="row-odd"><td>image_collection</td>
<td><p class="first">Required, the item representing the image collection to add input_rasters to.</p>
<p class="last">The image collection must be an existing image collection.
This is the output image collection (mosaic dataset) item or url or uri</p>
</td>
</tr>
<tr class="row-even"><td>raster_type_name</td>
<td>Required, the name of the raster type to use for adding data to
the image collection.</td>
</tr>
<tr class="row-odd"><td>raster_type_params</td>
<td><p class="first">Optional, additional raster_type specific parameters.</p>
<p>The process of add rasters to the image collection can be
controlled by specifying additional raster type arguments.</p>
<p class="last">The raster type parameters argument is a dictionary.</p>
</td>
</tr>
<tr class="row-even"><td>context</td>
<td><dl class="first last docutils">
<dt>Optional, The context parameter is used to provide additional input parameters</dt>
<dd><p class="first">{“image_collection_properties”: {“imageCollectionType”:”Satellite”},”byref”:True}</p>
<p>use image_collection_properties key to set value for imageCollectionType.
Note: the “imageCollectionType” property is important for image collection that will later on be adjusted by orthomapping system service.
Based on the image collection type, the orthomapping system service will choose different algorithm for adjustment.
Therefore, if the image collection is created by reference, the requester should set this
property based on the type of images in the image collection using the following keywords.
If the imageCollectionType is not set, it defaults to “UAV/UAS”</p>
<p class="last">If byref is set to True, the data will not be uploaded. If it is not set, the default is False</p>
</dd>
</dl>
</td>
</tr>
<tr class="row-odd"><td>gis</td>
<td>Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.</td>
</tr>
</tbody>
</table>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The imagery layer item</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
<div class="section" id="delete-image">
<h2>delete_image<a class="headerlink" href="#delete-image" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.delete_image">
<code class="descclassname">analytics.</code><code class="descname">delete_image</code><span class="sig-paren">(</span><em>image_collection</em>, <em>where</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.delete_image" title="Permalink to this definition">¶</a></dt>
<dd><p>delete_image allows users to remove existing images from the image collection (mosaic dataset).
The function will only delete the raster item in the mosaic dataset and will not remove the
source image.</p>
<table border="1" class="docutils">
<colgroup>
<col width="17%" />
<col width="83%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><strong>Argument</strong></td>
<td><strong>Description</strong></td>
</tr>
<tr class="row-even"><td>image_collection</td>
<td>Required, the input image collection from which to delete images
This can be the ‘itemID’ of an exisiting portal item or a url
to an Image Service or a uri</td>
</tr>
<tr class="row-odd"><td>where</td>
<td>Required string, a SQL ‘where’ clause for selecting the images
to be deleted from the image collection</td>
</tr>
<tr class="row-even"><td>gis</td>
<td>Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.</td>
</tr>
</tbody>
</table>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">The imagery layer url</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
<div class="section" id="delete-image-collection">
<h2>delete_image_collection<a class="headerlink" href="#delete-image-collection" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.delete_image_collection">
<code class="descclassname">analytics.</code><code class="descname">delete_image_collection</code><span class="sig-paren">(</span><em>image_collection</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.delete_image_collection" title="Permalink to this definition">¶</a></dt>
<dd><p>Delete the image collection. This service tool will delete the image collection
image service, that is, the portal-hosted image layer item. It will not delete
the source images that the image collection references.</p>
<table border="1" class="docutils">
<colgroup>
<col width="17%" />
<col width="83%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><strong>Argument</strong></td>
<td><strong>Description</strong></td>
</tr>
<tr class="row-even"><td>image_collection</td>
<td><p class="first">Required, the input image collection to delete.</p>
<p>The image_collection can be a portal Item or an image service URL or a URI.</p>
<p class="last">The image_collection must exist.</p>
</td>
</tr>
<tr class="row-odd"><td>gis</td>
<td>Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.</td>
</tr>
</tbody>
</table>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Boolean value indicating whether the deletion was successful or not</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
<div class="section" id="list-datastore-content">
<h2>list_datastore_content<a class="headerlink" href="#list-datastore-content" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.list_datastore_content">
<code class="descclassname">analytics.</code><code class="descname">list_datastore_content</code><span class="sig-paren">(</span><em>datastore</em>, <em>filter=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.list_datastore_content" title="Permalink to this definition">¶</a></dt>
<dd><p>List the contents of the datastore registered with the server (fileShares, cloudStores, rasterStores).</p>
<table border="1" class="docutils">
<colgroup>
<col width="15%" />
<col width="85%" />
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><strong>Argument</strong></td>
<td><strong>Description</strong></td>
</tr>
<tr class="row-even"><td>datastore</td>
<td>Required. fileshare, rasterstore or cloudstore datastore from which the contents are to be listed.
It can be a string specifying the datastore path eg “/fileShares/SensorData”, “/cloudStores/testcloud”,
“/rasterStores/rasterstore”
or it can be a Datastore object containing a fileshare, rasterstore or a cloudstore path.
eg:
ds=analytics.get_datastores()
ds_items =ds.search()
ds_items[1]
ds_items[1] may be specified as input for datastore</td>
</tr>
<tr class="row-odd"><td>filter</td>
<td>Optional. To filter out the raster contents to be displayed</td>
</tr>
<tr class="row-even"><td>gis</td>
<td>Optional GIS. The GIS on which this tool runs. If not specified, the active GIS is used.</td>
</tr>
</tbody>
</table>
<table class="docutils field-list" frame="void" rules="none">
<col class="field-name" />
<col class="field-body" />
<tbody valign="top">
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">List of contents in the datastore</td>
</tr>
</tbody>
</table>
</dd></dl>
</div>
<div class="section" id="build-footprints">
<h2>build_footprints<a class="headerlink" href="#build-footprints" title="Permalink to this headline">¶</a></h2>
<dl class="method">
<dt id="arcgis.raster.analytics.build_footprints">
<code class="descclassname">analytics.</code><code class="descname">build_footprints</code><span class="sig-paren">(</span><em>image_collection</em>, <em>computation_method='RADIOMETRY'</em>, <em>value_range=None</em>, <em>context=None</em>, <em>*</em>, <em>gis=None</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="headerlink" href="#arcgis.raster.analytics.build_footprints" title="Permalink to this definition">¶</a></dt>
<dd><p>Computes the extent of every raster in a mosaic dataset.</p>
<dl class="docutils">