natt

# Náttúrufræðistofnun (NÍ) — Open data **Requires:** Tier 1 (maps) — rasterio/numpy for the WCS raster mask; `uv sync --group maps`. Náttúrufræðistofnun Íslands (Icelandic Institute of Natural History) publishes habitat-type, species-distribution, and geological data as open data. - Public download portal: https://www.natt.is/is/midlun/opin-gogn/nidurhal-gagna - Habitat-map viewer: http://vistgerdakort.ni.is/ - Map browser: https://kort.gis.is/mapview/ - Reference monograph (Fjölrit 54, 2018): http://utgafa.ni.is/fjolrit/Fjolrit_54.pdf - Change-log between 1st and 3rd edition: http://utgafa.ni.is/kort/lysigogn/vg25r_3utg_breytingar.pdf - License: "Gögnin eru öllum opin" — open, no use restrictions. ## OGC services NÍ runs a GeoServer at `https://gis.natt.is/geoserver/`. It hosts both NÍ's own layers and several layers federated from LMI / Hagstofan / Skógræktin. - WFS GetCapabilities: `https://gis.natt.is/geoserver/wfs?service=WFS&version=2.0.0&request=GetCapabilities` - WMS GetCapabilities: `https://gis.natt.is/geoserver/wms?service=WMS&version=1.3.0&request=GetCapabilities` - WCS GetCapabilities: `https://gis.natt.is/geoserver/wcs?service=WCS&version=2.0.1&request=GetCapabilities` - All layers are published in **EPSG:3057** (ISN93 / LCC Iceland). - WFS supports `outputFormat=application/json` (GeoJSON) and CQL filters via `CQL_FILTER=…`. - WCS spells the workspace separator `__`, WMS/WFS spell it `:`. The same coverage is `vistgerdir__ni_vg25r_3utg_lzw` (WCS) and `vistgerdir:ni_vg25r_3utg_lzw` (WMS). ## Vistgerðir á Íslandi (3. útgáfa, 1:25.000) — habitat types Habitat types ("vistgerðir") are NÍ's national EUNIS-aligned classification. There are 64 land-, 17 freshwater-, and 24 coastal-shore habitat types, documented in Fjölrit 54. **The 3rd edition is a raster.** The polygonised vector edition `LMI_vektor:vistgerd` was withdrawn in 2026 (see Caveats) — the surviving national-coverage publication is: | Service | Name | Notes | |---|---|---| | WCS coverage | `vistgerdir__ni_vg25r_3utg_lzw` | GeoTIFF, the fetchable one | | WMS layer | `vistgerdir:ni_vg25r_3utg_lzw` | styled `vistgerdir:vistgerdakort_3utg` | Grid (from `DescribeCoverage`): | property | value | |---|---| | CRS | EPSG:3057 (ISN93) | | resolution | 5 m | | size | 102928 × 72798 px (7.5 Gpx) | | envelope | `244069.5 311026.7 758709.5 675016.7` | | band 1 `GRAY_INDEX` | **habitat-type code** — the old `DN` values, unchanged | | band 2 | alpha; request `rangeSubset=GRAY_INDEX` to skip it | ### The legend *is* the `DN` → label inventory `GetLegendGraphic` in JSON returns the raster colormap — 73 entries, each with a `quantity` (the `DN`) and a `label` (the old `htxt` string, correct UTF-8). One request replaces streaming 24M vector rows: ```bash curl -sS "https://gis.natt.is/geoserver/wms?service=WMS&version=1.1.1\ &request=GetLegendGraphic&layer=vistgerdir:ni_vg25r_3utg_lzw\ &format=application/json" | jq -r ' .Legend[0].rules[0].symbolizers[0].Raster.colormap.entries[] | "\(.quantity)\t\(.label)"' | sort -n ``` `scripts/natt.py inventory` does exactly this and writes `data/raw/natt/vistgerdir/inventory.csv`. ### `DN` → habitat-type mapping (subset of interest) | DN | Code | Label | |---:|------|-------| | 1–5 | L1.1–L1.5 | Melavistir (gravel/sand barrens) | | 6–8 | L3.1–L3.3 | Skriðuvistir (scree) | | 9–10 | L4.1–L4.2 | Eyrar / aurar (river plains) | | 11–13 | L5.1–L5.3 | Mosavistir (moss) | | 14–17 | L6.1–L6.4 | Hraunavistir (lava fields) | | 18 | L2.1 | Moldavist (eroded soil) | | 19–25 | L7.* | Strandvistir (coastal terrestrial) | | 26–38 | L8.* | Mýrar / flóar (mires / fens) | | 39–45 | L9.* | Graslendi (grasslands) | | 46–55 | L10.* | Móar / kjarrlendi (heaths / scrub) | | 61–64 | L12.1–L12.4 | Hveravistir (geothermal) | | 95 | **L14.2** | **Tún og akurlendi** (cultivated hayfield + arable) | | 98 | V1 | Vötn (lakes) | | 99 | V2 | Ár (rivers) | | 108 | L13.1 | Jöklar og urðarjöklar (glaciers / rock glaciers) | | 122 | L1.6 | Landmelhólavist (inland dune) | | 130 | L8.7 | Rimamýravist (string fen) | | 150 | L14.1 | Þéttbýli og annað manngert land (urban / man-made) | | 152 | L11 | Birkiskógur (birch woodland) | | 153 | L14.3 | Skógrækt (forestry) | | 160 | L14.4 | Alaskalúpína (Alaska lupine — invasive) | | 161 | L14.5 | Uppgræðslur (revegetated land) | | 162 | L14.6 | Skógarkerfill ofl. þéttar tegundir (cow-parsley etc.) | | 175 | F | Fjöruvistir (intertidal) | | 176 | FX1.1 | Sjávarlón (coastal lagoons) | The `DN` values are **not** contiguous and not ordered by code — always take the full table from `natt.py inventory` rather than assuming a range. ### Fetching one habitat type Never ask for the whole 5 m grid in one request. `scaleFactor` downsamples server-side (nearest neighbour) and `subset` tiles it; both compose: ```bash # whole country at 1 km — 377 KB, <1 s. Good for probes and sanity checks. curl -sS "https://gis.natt.is/geoserver/wcs?service=WCS&version=2.0.1\ &request=GetCoverage&coverageId=vistgerdir__ni_vg25r_3utg_lzw\ &format=image/tiff&rangeSubset=GRAY_INDEX&scaleFactor=0.005" -o vg_1km.tif # one 100 km tile at 20 m — 26 MB, 30 s to a couple of minutes depending on # server load. scaleFactor = 5 / target_metres. curl -sS "https://gis.natt.is/geoserver/wcs?service=WCS&version=2.0.1\ &request=GetCoverage&coverageId=vistgerdir__ni_vg25r_3utg_lzw\ &format=image/tiff&rangeSubset=GRAY_INDEX&scaleFactor=0.25\ &subset=X(400000,500000)&subset=Y(350000,450000)" -o vg_tile.tif ``` Then mask band 1 to the code you want (`arr == 95`). `scripts/natt.py habitat --dn 95` does the whole tiled mosaic and writes an ISN93 uint8 mask GeoTIFF plus a sidecar with the area. Cost is server-bound and scales with output pixels — measured, national coverage: | `--res` | tiles | wall time | mask size | L14.2 area | |---:|---:|---|---:|---:| | 100 m | 4 | ~1 min | 0.2 MB | 1,807.5 km² | | 50 m (default) | 6 | ~2 min | 0.6 MB | 1,806.0 km² | | 20 m | 24 | ~30 min | 2.7 MB | 1,805.8 km² | Country-scale renders in this repo draw at 120–200 m/px, so even 100 m is sufficient for a map; 20 m is for detail work. **Native 5 m — only if you need patch-level geometry.** ~45 min end to end (582 of 1,924 tiles carry the class, found with a `scaleFactor` sampling pass first) versus ~2 min for the 50 m mask. Request `compression=Deflate` on GetCoverage — a tile drops ~18× (8.4 MB → 0.47 MB), which is what makes a native pass affordable at all. And gis.natt.is has returned a `502` partway through a long tile sequence, so cache per tile and retry before starting. **Regression check:** L14.2 (cultivated land) must come out at ≈1,806 km², matching the ~1,800 km² on the natt.is habitat page. The three resolutions agree to within 0.1%, and an independent native-5 m extract lands at exactly 1,806 km² (Guðröður / gudrodur, cross-check on PR #14) — the number is a property of the data, not of the sampling. ## Other vector layers in the WFS The WFS exposes ~150 layers. The most useful for nature/agriculture work: | Layer | What | |-------|------| | `vistgerdir:v_vg25v_fl_land` | **Geothermal (L12) habitat polygons only** — 360 rows | | `vistgerdir:v_vg25v_fl_vatn` | Freshwater habitat polygons (V1.1–V1.8), 54k rows | | `vistgerdir:v_vg25v_fl_fjorur` | Littoral-shore polygons (F1.*, F2.*, FX.*), 20k rows | | `ni:ni_vg25v_li` | Running-water lines (rivers) | | `ni:ni_vg25v_pt` | Cold/thermal-spring points | | `ni:vistgerdir_punktar` | Field-survey sample points (8k; all L-codes) | | `ni:Floraisl_dreifing` | Vascular-plant distribution (Flóra Íslands) | | `ni:Smadyr_dreifing` | Invertebrate distribution | | `ni:hvitabjorn_a_islandi` | Polar-bear sightings | | `land_og_skogur:natturulegt_birkilendi` | Natural birch woodland (Skógræktin) | | `land_og_skogur:raektad_skoglendi` | Cultivated forest (Skógræktin) | | `land_og_skogur:jardvegsrof` | Soil erosion | | `CORINE:clc18_is`, `clc12_is`, `clc06_is`, `clc00_is` | CORINE Land Cover for Iceland | The three `vistgerdir:v_vg25v_fl_*` layers share one schema — string codes, not `DN`: `id, vg1, vg1_texti, vg1_linkur, vg2 … vg5 (+_texti/_linkur), eunis_1, eunis_2, geom`. `vg1` is the top level (`L`/`V`/`F`), `vg2`–`vg5` drill down (`vg2='F2'`, `vg3='F2.3'`). Filter with CQL, e.g. `CQL_FILTER=vg3='F2.3'`. ## Caveats - **2026-08 — `LMI_vektor:vistgerd` was withdrawn.** The polygonised vector edition of the habitat map (schema `DN` int + `htxt` str, ~24M rows) is gone from gis.natt.is, gis.lmi.is and ogc.gis.is alike; all three answer `InvalidParameterValue: Feature type LMI_vektor:vistgerd unknown`. It is **not** coming back under a new vector name — use the WCS raster above. - **Trap: the new `vistgerdir:v_vg25v_fl_*` layers are NOT the replacement.** The naming is actively misleading: `v_vg25v_fl_land` sounds like the land habitat map but its capabilities title is *"Vistgerðir: Hverasvæði – Habitat types: Geothermal lands"* and every one of its 360 rows is `vg2='L12'`. Its siblings cover freshwater (`V*`) and littoral shores (`F*`). **The terrestrial habitats L1–L11, L13 and L14 — including L14.2 Tún og akurlendi — have no polygon layer on the WFS at all.** Always check `vg1`/`vg2` values with `count=1` before assuming a layer covers what its name suggests. - The text-based GeoServer responses (GML/CSV) come through as **cp1252-mojibake** for Icelandic characters. Always request `outputFormat=application/json` for clean UTF-8. The legend JSON is already correct UTF-8. - Edition 3 (2023) reshuffled L-codes vs edition 1 — see `vg25r_3utg_breytingar.pdf` before mixing data across editions. The raster's `DN` values match edition 3's vector `DN` exactly, so pre-2026 `DN`-based code in this repo ports unchanged. - WCS `scaleFactor` is served off pyramid overviews and is fast (a full-country 1 km read is <1 s); a full-resolution national fetch is 7.5 Gpx and must be tiled. `scripts/natt.py` tiles at 5000 output px per request.