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Functionality: elaborate workflow for spatial typology datasets
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florisvdh committed Jul 30, 2019
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Expand Up @@ -244,9 +244,10 @@ Depending on the purpose, the type-attribute is to be derived from one or more o

Moreover, it is brought in consistency, and restricted to the type codes from the datasource `types`.

Also, main types need to be linked to their corresponding _subtypes_ in order to be picked up when selections are defined at the subtype level (needed when no subtype information exists for a given spatial object).
A processed layer `habitatmap_stdized` is constructed to standardise the format of `habitatmap`:

Further, extra attributes are needed in most applications -- especially when using the `habitatmap` dataset: the rank and the associated areal proportion of each row.
- main types need to be linked to their corresponding _subtypes_ in order to be picked up when selections are defined at the subtype level (needed when no subtype information exists for a given spatial object).
- extra attributes are needed in most applications: the rank and the associated areal proportion of each row.

Ideally, an intermediate spatial layer is generated that combines the above layers and integrates their information.

Expand All @@ -255,12 +256,15 @@ Ideally, an intermediate spatial layer is generated that combines the above laye

_**Needed functions: in package n2khab:**_

Both functions take into account type code consistency and link subtypes to main types. Both functions generate a data set consisting of both a spatial object and a long / tidy dataframe (tibble), including areal proportions.
The functions take into account type code consistency and link subtypes to main types. Most functions return a data set consisting of both a spatial object and a long / tidy dataframe (tibble), including areal proportions.

- `write_habitatmap_terr(threshold_pct, outputdir)`
- this function reads and integrates `habitatmap` and `habitatdune`
- `write_habitatmap_integrated(threshold_pct, outputdir)`
- incorporates `write_habitatmap_terr()` but inserts the spatial units from `habitatstreams` and `watersurfaces` while retaining useful (type) attributes, ideally including those from `mhq_lentic_locs` and `mhq_lotic_locs`
- `read_habitatmap_stdized(path, file)`
- returns spatial object and long (tidy) tibble based on `habitatmap`
- `read_habitatmap_terr(path, file)`
- returns `habitatmap_terr`: this integrates the terrestrial locations of `habitatmap_stdized` (but excluding those with very low certainty of containing habitat or RIB), `habitatdune` and `mhq_terrestrial_locs` and adds further interpretation (especially: translating some main type codes into a specific subtype).
- `expand_types()`: takes a type column in a dataframe and expands it, based on relationships between main types and subtypes, in order to optimize joins with `habitatmap_terr`.
- `read_habitatmap_integrated(path, file)`
- returns `habitatmap_integrated`: based on `habitatmap_terr`; inserts the spatial units from `habitatstreams` and `watersurfaces_interpr` while retaining useful (type) attributes, ideally including those from `mhq_lentic_locs` and `mhq_lotic_locs`

_**Dedicated writing workflow (scripts/Rmarkdown): in repo n2khab-preprocessing**_

Expand Down Expand Up @@ -413,8 +417,6 @@ _**Needed functions: in package n2khab:**_
- this holds the names, corresponding to codes in other textual data sources (`types`, `env_pressures` etc.), supporting multiple languages.
- `read_GRTSmh(path, file)`
- if this is not feasible within R, an open GIS-backend needs to be called by R
- `read_habitatmap(path, file)`
- returns spatial object and long (tidy) tibble
- `read_habitatdune(path, file)`
- `read_habitatstreams(path, file)`
- `read_sac(path, file)`
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