Access SLU/Skogsstyrelsen ditches

Introduction

Skogsstyrelsen (The Swedish Forest Agency) hosts a set of spatial datasets, both open source data and data that requires registering for accessing. The former includes a national ditch layer at 0.5 and 1 m spatial resolution developed by Sveriges Lantbruksuniversitet (Swedish University of Agricultural Sciences). This dataset is a key layer for modelling Swedish wetlands and this post is an instruction for how to retrieve it and get it into Karttur´s GeoImagine Framework.

For details on accessing the data from Skogsstyrelsen FTP site, including how to register a user, please see the previous post on Access SLU/Skogsstyrelsen soil moisture.

Prerequisites

You do not need any special installations to access and download data from Skogsstyrelsen, but it might facilitate to use an FTP-client, like FileZilla. If you want to organise the dataset for use with Karttur’s GeoImagine Framework, you must have installed the Framework.

Skogsstyrelsen ditch datasets

There are two separate datasets over ditches available from Skogsstyrelsen, a dataset at 1 m spatial resolution covering almost the entire Swedish landmass, and a 0.5 m dataset covering approximately half the country. The latter dataset is reported to have a higher accuracy (86 %) compared to the former (82 %).

Download ditch datasets

Get the ditch datasets with an FTP client as explained in the post on Access SLU/Skogsstyrelsen soil moisture. To use the prepared scripts and command files of this post, you need to save the downloaded data as follows:

Bounding boxes

The SLU ditch datasets are delivered as tiles. The Framework process BBoxTiledRawData can be used for retrieving the boundary polygons of tiled raw data. The output of the process is a vector file. The process does not interact with the Framework database but is merely an opportunity for visually inspecting raw data prior to further processing.

Framework process: BBoxTiledRawData

Json command file: 0122_BBoxTiledRawData_slu-diken

## Create vector bounding boxes the ditch tiles ##
0122_BBoxTiledRawData_slu-diken.json

The figure below shows the bounding boxes for the SLU ditch datasets.

Mosaic the raw ditches

Because the SLU ditch dataset is delivered as tiles, you need to create virtual mosaics prior to organising them for the Framework.

Framework process: MosaicAncillary

Json command file: 0125_MosaicAncillary_slu-diken.json

## Mosaic the raw ditch tile datasets ##
0125_MosaicAncillary_slu-diken.json

The virtual mosaics will just be used as an intermediate layer for creating the SWEREF tiles to be used for the actual processing later. The next step is to import and register (organise) the virtual mosaics.

Organize ditches

The layers with the SLU ditches are imported (organized) by using the virtual mosaics created in the previous section. In essence this equals importing a single, virtual layer rather than the original tiles.

Framework process: OrganizeProjSysData

Json command file: 0160_Organizeprojsys_slu-diken.json

## Import virtual mosaics of the ditch tile datasets ##
0160_Organizeprojsys_slu-diken.json

Tile ditches

The imported ditch datasets are virtual datasets that point towards the original GeoTiff tiles. Applying the process TileProjSysRegion will result in a new set of GeoTiff tiles, but this time fitted to the default tiling system as defined for the Framework projecting system SWEREF99, that was created in the post Default region Sweden.

Framework process: TileProjSysRegion

Json command file: 0180_Tileprojsysregion_slu-diken.json

## tile ditch datasets to sweref ##
0180_TileProjSysRegion_slu-diken.json

And with that you have now added the two ditch datasets as GeoTiff ready to use Karttur’s GeoImagine Framework.