# Landscape analysis

The `Landscape` class is the core code unit of PyLandStats and is used to compute the metrics over a given landscape raster. It can be instantiated as follows:

```{eval-rst}
.. automethod:: pylandstats.Landscape.__init__
```

## List of implemented metrics

The metrics of PyLandStats [are computed according to their definitions in FRAGSTATS](https://github.com/martibosch/pylandstats-notebooks/blob/main/notebooks/A01-fragstats-metrics-comparison.ipynb).

The notation for the metrics below is as follows:

- the letters with suffixes $a\_{i,j}, p\_{i,j}, h\_{i,j}$ respectively represent the area, perimeter, and distance to the nearest neighboring patch of the same class of the patch $j$ of class $i$.
- the letters with suffixes $e\_{i,k}, g\_{i,k}$ respectively represent the total edge between and number of pixel adjacencies between classes $i$ and $k$
- the capital letters $A, N, E$ respectively represent the total area, total number of patches and total edge of the landscape

Like FRAGSTATS, PyLandStats features six distribution-statistics metrics for each patch-level metric, which consist in a statistical aggregation of the values computed for each patch of a class or the whole landscape:

- the mean, which can be computed by adding a `_mn` suffix to the method name, e.g., `area_mn`
- the area-weighted mean, which can be computed by adding a `_am` suffix to the method name, e.g., `area_am`
- the median, which can be computed by adding a `_md` suffix to the method name, e.g., `area_md`
- the range, which can be computed by adding a `_ra` suffix to the method name, e.g., `area_ra`
- the standard deviation, which can be computed by adding a `_sd` suffix to the method name, e.g., `area_sd`
- the coefficient of variation, which can be computed by adding a `_cv` suffix to the method name, e.g., `area_cv`

note that the distribution-statistics metrics do not appear in the documentation below.

See the [FRAGSTATS documentation](https://www.umass.edu/landeco/research/fragstats/documents/fragstats_documents.html) for more information.

## Patch-level metrics

### Area, density, edge

```{eval-rst}
.. automethod:: pylandstats.Landscape.area
.. automethod:: pylandstats.Landscape.perimeter
```

### Shape

```{eval-rst}
.. automethod:: pylandstats.Landscape.perimeter_area_ratio
.. automethod:: pylandstats.Landscape.shape_index
.. automethod:: pylandstats.Landscape.fractal_dimension
```

### Core

```{eval-rst}
.. automethod:: pylandstats.Landscape.core_area
.. automethod:: pylandstats.Landscape.number_of_core_areas
.. automethod:: pylandstats.Landscape.core_area_index
```

### Aggregation

```{eval-rst}
.. automethod:: pylandstats.Landscape.euclidean_nearest_neighbor
```

## Class-level and landscape-level metrics

### Area, density, edge

```{eval-rst}
.. automethod:: pylandstats.Landscape.total_area
.. automethod:: pylandstats.Landscape.proportion_of_landscape
.. automethod:: pylandstats.Landscape.number_of_patches
.. automethod:: pylandstats.Landscape.patch_density
.. automethod:: pylandstats.Landscape.largest_patch_index
.. automethod:: pylandstats.Landscape.total_edge
.. automethod:: pylandstats.Landscape.edge_density
```

### Core

```{eval-rst}
.. automethod:: pylandstats.Landscape.total_core_area
.. automethod:: pylandstats.Landscape.core_area_proportion_of_landscape
.. automethod:: pylandstats.Landscape.number_of_disjunct_core_areas
.. automethod:: pylandstats.Landscape.disjunct_core_area_density
```

### Aggregation

```{eval-rst}
.. automethod:: pylandstats.Landscape.landscape_shape_index
.. automethod:: pylandstats.Landscape.effective_mesh_size
```

## Landscape-level metrics

### Diversity

```{eval-rst}
.. automethod:: pylandstats.Landscape.entropy
.. automethod:: pylandstats.Landscape.shannon_diversity_index
```

### Contagion, interspersion

```{eval-rst}
.. automethod:: pylandstats.Landscape.joint_entropy
.. automethod:: pylandstats.Landscape.conditional_entropy
.. automethod:: pylandstats.Landscape.mutual_information
.. automethod:: pylandstats.Landscape.relative_mutual_information
.. automethod:: pylandstats.Landscape.contagion
```

## Computing metrics data frames

```{eval-rst}
.. automethod:: pylandstats.Landscape.compute_patch_metrics_df
.. automethod:: pylandstats.Landscape.compute_class_metrics_df
.. automethod:: pylandstats.Landscape.compute_landscape_metrics_df
```

## Plotting landscape raster

```{eval-rst}
.. automethod:: pylandstats.Landscape.plot_landscape
```