Wrap all functionalities as DEM methods (GlacioHack#478)

doc/source/api.md

@@ -11,21 +11,38 @@ documentation.
 .. currentmodule:: xdem
 ```
 
-## DEM
-
 ```{eval-rst}
 .. minigallery:: xdem.DEM
       :add-heading:
 ```
 
-### Opening a DEM
+## DEM
+
+```{important}
+A {class}`~xdem.DEM` inherits all raster methods and attributes from the {class}`~geoutils.Raster` object of GeoUtils.
+Below, we only repeat the core attributes and methods of GeoUtils, see
+[the Raster API in GeoUtils](https://geoutils.readthedocs.io/en/latest/api.html#raster) for the full list.
+```
+
+### Opening or saving a DEM
 
 ```{eval-rst}
 .. autosummary::
     :toctree: gen_modules/
 
     DEM
     DEM.info
+    DEM.save
+```
+
+### Plotting a DEM
+
+```{eval-rst}
+.. autosummary::
+    :toctree: gen_modules/
+
+    DEM
+    DEM.plot
 ```
 
 ### Create from an array
@@ -41,27 +58,40 @@ documentation.
 
 ### Unique attributes
 
-```{note}
-A {class}`~xdem.DEM` inherits four unique attributes from {class}`~geoutils.Raster`, see [the dedicated section of GeoUtils' API](https://geoutils.readthedocs.io/en/latest/api.html#unique-attributes).
+#### Inherited from {class}`~geoutils.Raster`
+
+```{eval-rst}
+.. autosummary::
+    :toctree: gen_modules/
+
+    DEM.data
+    DEM.crs
+    DEM.transform
+    DEM.nodata
 ```
 
+#### Specific to {class}`~xdem.DEM`
+
 ```{eval-rst}
 .. autosummary::
     :toctree: gen_modules/
 
     DEM.vcrs
 ```
 
-### Derived attributes
+### Georeferencing
+
+#### Inherited from {class}`~geoutils.Raster`
 
 ```{eval-rst}
 .. autosummary::
     :toctree: gen_modules/
 
-    DEM.ccrs
+    DEM.reproject
+    DEM.crop
 ```
 
-### Vertical referencing
+#### Vertical referencing for {class}`~xdem.DEM`
 
 ```{eval-rst}
 .. autosummary::
@@ -71,6 +101,53 @@ A {class}`~xdem.DEM` inherits four unique attributes from {class}`~geoutils.Rast
     DEM.to_vcrs
 ```
 
+### Raster-vector interface
+
+```{note}
+See the full list of vector methods in [GeoUtils' documentation](https://geoutils.readthedocs.io/en/latest/api.html#vector).
+```
+
+```{eval-rst}
+.. autosummary::
+    :toctree: gen_modules/
+
+    DEM.polygonize
+    DEM.proximity
+```
+
+### Coregistration
+
+```{tip}
+To build and pass your coregistration pipeline to {func}`~xdem.DEM.coregister_3d`, see the API of {ref}`api-geo-handle`.
+```
+
+```{eval-rst}
+.. autosummary::
+    :toctree: gen_modules/
+
+    DEM.coregister_3d
+```
+
+### Terrain attributes
+
+```{eval-rst}
+.. autosummary::
+    :toctree: gen_modules/
+
+    DEM.slope
+    DEM.aspect
+    DEM.hillshade
+    DEM.curvature
+    DEM.profile_curvature
+    DEM.planform_curvature
+    DEM.maximum_curvature
+    DEM.topographic_position_index
+    DEM.terrain_ruggedness_index
+    DEM.roughness
+    DEM.rugosity
+    DEM.fractal_roughness
+```
+
 ## dDEM
 
 ```{eval-rst}
@@ -113,6 +190,25 @@ A {class}`~xdem.DEM` inherits four unique attributes from {class}`~geoutils.Rast
     xdem.coreg.BlockwiseCoreg
 ```
 
+#### Fitting and applying transforms
+
+```{eval-rst}
+.. autosummary::
+    :toctree: gen_modules/
+
+    xdem.coreg.Coreg.fit
+    xdem.coreg.Coreg.apply
+```
+
+#### Other functionalities
+
+```{eval-rst}
+.. autosummary::
+    :toctree: gen_modules/
+
+    xdem.coreg.Coreg.residuals
+```
+
 ### Affine coregistration methods
 
 

doc/source/coregistration.md

@@ -23,6 +23,14 @@ Those transformations include for instance:
 - rotations, reflections,
 - scalings.
 
+## Quick use
+
+Coregistrations are defined using either a single method or pipeline of {class}`~xdem.coreg.Coreg` methods, that are listed below.
+
+Performing the coregistration on a pair of DEM is done either by using {func}`xdem.DEM.coregister_3d` from the DEM that will be aligned, or
+by specifying the {func}`xdem.coreg.Coreg.fit` and {func}`xdem.coreg.Coreg.apply` steps, which allows array inputs and
+to apply the same fitted transformation to several objects (e.g., horizontal shift of both a stereo DEM and its ortho-image).
+
 ## Introduction
 
 Coregistration of a DEM is performed when it needs to be compared to a reference, but the DEM does not align with the reference perfectly.

doc/source/dem_class.md

@@ -0,0 +1,166 @@
+---
+file_format: mystnb
+jupytext:
+  formats: md:myst
+  text_representation:
+    extension: .md
+    format_name: myst
+kernelspec:
+  display_name: xdem-env
+  language: python
+  name: xdem
+---
+(dem-class)=
+
+# The digital elevation model ({class}`~xdem.DEM`)
+
+Below, a summary of the {class}`~xdem.DEM` object and its methods.
+
+(dem-obj-def)=
+
+## Object definition and attributes
+
+A {class}`~xdem.DEM` is a {class}`~geoutils.Raster` with an additional georeferenced vertical dimension stored in the attribute {attr}`~xdem.DEM.vcrs`.
+It inherits the **four main attributes** of {class}`~geoutils.Raster` which are {attr}`~xdem.DEM.data`,
+{attr}`~xdem.DEM.transform`, {attr}`~xdem.DEM.crs` and {attr}`~xdem.DEM.nodata`.
+
+Many other useful raster attributes and methods are available through the {class}`~geoutils.Raster` object, such as
+{attr}`~geoutils.Raster.bounds`, {attr}`~geoutils.Raster.res`, {func}`~xdem.DEM.reproject` and {func}`~xdem.DEM.crop` .
+
+```{tip}
+The complete list of {class}`~geoutils.Raster` attributes and methods can be found in [GeoUtils' API](https://geoutils.readthedocs.io/en/stable/api.html#raster) and more info on rasters on [GeoUtils' Raster documentation page](https://geoutils.readthedocs.io/en/stable/raster_class.html).
+```
+
+## Open and save
+
+A {class}`~xdem.DEM` is opened by instantiating with either a {class}`str`, a {class}`pathlib.Path`, a {class}`rasterio.io.DatasetReader` or a
+{class}`rasterio.io.MemoryFile`, as for a {class}`~geoutils.Raster`.
+
+
+```{code-cell} ipython3
+import xdem
+
+# Instantiate a DEM from a filename on disk
+filename_dem = xdem.examples.get_path("longyearbyen_ref_dem")
+dem = xdem.DEM(filename_dem)
+dem
+```
+
+Detailed information on the {class}`~xdem.DEM` is printed using {func}`~geoutils.Raster.info`, along with basic statistics using `stats=True`:
+
+```{code-cell} ipython3
+# Print details of raster
+dem.info(stats=True)
+```
+
+```{important}
+The {class}`~xdem.DEM` data array remains implicitly unloaded until {attr}`~xdem.DEM.data` is called. For instance, here, calling {class}`~xdem.DEM.info()` with `stats=True` automatically loads the array in-memory.
+
+The georeferencing metadata ({attr}`~xdem.DEM.transform`, {attr}`~xdem.DEM.crs`, {attr}`~xdem.DEM.nodata`), however, is always loaded. This allows to pass it effortlessly to other objects requiring it for geospatial operations (reproject-match, rasterizing a vector, etc).
+```
+
+A {class}`~xdem.DEM` is saved to file by calling {func}`~xdem.DEM.save` with a {class}`str` or a {class}`pathlib.Path`.
+
+```{code-cell} ipython3
+# Save raster to disk
+dem.save("mydem.tif")
+```
+```{code-cell} ipython3
+:tags: [remove-cell]
+import os
+os.remove("mydem.tif")
+```
+
+## Plotting
+
+Plotting a DEM is done using {func}`~xdem.DEM.plot`, and can be done alongside a vector file.
+
+```{code-cell} ipython3
+# Open a vector file of glacier outlines near the DEM
+import geoutils as gu
+fn_glacier_outlines = xdem.examples.get_path("longyearbyen_glacier_outlines")
+vect_gla = gu.Vector(fn_glacier_outlines)
+
+# Plot the DEM and the vector file
+dem.plot(cmap="terrain", cbar_title="Elevation (m)")
+vect_gla.plot(dem)  # We pass the DEM as reference for the plot CRS/extent
+```
+
+## Vertical referencing
+
+The vertical reference of a {class}`~xdem.DEM` is stored in {attr}`~xdem.DEM.vcrs`, and derived either from its
+{attr}`~xdem.DEM.crs` (if 3D) or assessed from the DEM product name during instantiation.
+
+```{code-cell} ipython3
+# Check vertical CRS of dataset
+dem.vcrs
+```
+
+In this case, the DEM has no defined vertical CRS, which is quite common. To set the vertical CRS manually,
+use {class}`~xdem.DEM.set_vcrs`. Then, to transform into another vertical CRS, use {class}`~xdem.DEM.to_vcrs`.
+
+```{code-cell} ipython3
+# Define the vertical CRS as the 3D ellipsoid of the 2D CRS
+dem.set_vcrs("Ellipsoid")
+# Transform to the EGM96 geoid
+dem.to_vcrs("EGM96")
+```
+
+```{note}
+For more details on vertical referencing, see the {ref}`vertical-ref` page.
+```
+
+## Terrain attributes
+
+A wide range of terrain attributes can be derived from a {class}`~xdem.DEM`, with several methods and options available,
+by calling the function corresponding to the attribute name such as {func}`~xdem.DEM.slope`.
+
+```{code-cell} ipython3
+# Derive slope using the Zevenberg and Thorne (1987) method
+slope = dem.slope(method="ZevenbergThorne")
+slope.plot(cmap="Reds", cbar_title="Slope (degrees)")
+```
+
+```{note}
+For the full list of terrain attributes, see the {ref}`terrain-attributes` page.
+```
+
+## Coregistration
+
+3D coregistration is performed with {func}`~xdem.DEM.coregister_3d`, which aligns the
+{class}`~xdem.DEM` to another DEM using a pipeline defined with a {class}`~xdem.coreg.Coreg`
+object (defaults to horizontal and vertical shifts).
+
+```{code-cell} ipython3
+# Another DEM to-be-aligned to the first one
+filename_tba = xdem.examples.get_path("longyearbyen_tba_dem")
+dem_tba = xdem.DEM(filename_tba)
+
+# Coregister (horizontal and vertical shifts)
+dem_tba_coreg = dem_tba.coregister_3d(dem)
+
+# Plot the elevation change of the DEM due to coregistration
+dh_tba = dem_tba - dem_tba_coreg.reproject(dem_tba)
+dh_tba.plot(cmap="Spectral", cbar_title="Elevation change due to coreg (m)")
+```
+
+```{note}
+For more details on building coregistration pipelines and accessing metadata, see the {ref}`coregistration` page.
+```
+
+## Uncertainty analysis
+
+Estimation of DEM-related uncertainty can be performed with {func}`~xdem.DEM.estimate_uncertainty`, which estimates both
+**an error map** considering variable per-pixel errors and **the spatial correlation of errors**. The workflow relies
+on an independent elevation data object that is **assumed to have either much finer or similar precision**, and uses
+stable terrain as a proxy.
+
+```{code-cell} ipython3
+# Estimate elevation uncertainty assuming both DEMs have similar precision
+sig_dem, rho_sig = dem.estimate_uncertainty(dem_tba_coreg, precision_of_other="same")
+
+# The error map variability is estimated from slope and curvature by default
+sig_dem.plot(cmap="Purples", cbar_title=r"Error in elevation (1$\sigma$, m)")
+
+# The spatial correlation function represents how much errors are correlated at a certain distance
+rho_sig(1000)  # Correlation at 1 km

doc/source/elevation_objects.md

@@ -0,0 +1,12 @@
+(elevation-objects)=
+# Elevation data objects
+
+Elevation data objects of xDEM inherit their characteristics from raster and vector objects of
+our sister-package [GeoUtils](https://geoutils.readthedocs.io/en/stable/).
+
+```{toctree}
+:maxdepth: 2
+
+dem_class
+elevation_point_cloud
+```

doc/source/elevation_point_cloud.md

@@ -0,0 +1,17 @@
+---
+file_format: mystnb
+jupytext:
+  formats: md:myst
+  text_representation:
+    extension: .md
+    format_name: myst
+kernelspec:
+  display_name: xdem-env
+  language: python
+  name: xdem
+---
+(elevation-point-cloud)=
+
+# The elevation point cloud ({class}`~xdem.EPC`)
+
+In construction, planned for 2024.

doc/source/index.md

@@ -98,12 +98,13 @@ intro_accuracy_precision
 :caption: Features
 :maxdepth: 2
 
+elevation_objects
 vertical_ref
 terrain
 coregistration
 biascorr
 comparison
-spatialstats
+uncertainty
 ```
 
 ```{toctree}