Smap Soil Classification (Soil Order) Aug 2021

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1522
148
Added
25 Aug 2021

This dataset was first added to LRIS Portal on 25 Aug 2021.

This layer is a "dissolved" representation of the NZSC soil order for S-map previously available as a lookup table. Refer to document Smap Data Dictionary Dissolved Layers.pdf at lris.scinfo.org.nz/document/22129-smap-data-dictio...

Layer ID 105956
Data type Vector polygon
Feature count 172807
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Soil Drainage Aug 2021

Licence

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

You may not use this work for commercial purposes.

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992
80
Added
25 Aug 2021

This dataset was first added to LRIS Portal on 25 Aug 2021.

This layer is a "dissolved" representation of the soil drainage attribute for S-map previously available as a lookup table. Refer to document Smap Data Dictionary Dissolved Layers.pdf at lris.scinfo.org.nz/document/22129-smap-data-dictio...

Layer ID 105955
Data type Vector polygon
Feature count 132587
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Soil Texture Aug 2021

Licence

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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550
27
Added
25 Aug 2021

This dataset was first added to LRIS Portal on 25 Aug 2021.

This layer is a "dissolved" representation of the soil texture attribute for S-map previously available as a lookup table. Refer to document Smap Data Dictionary Dissolved Layers.pdf at lris.scinfo.org.nz/document/22129-smap-data-dictio...

Layer ID 105954
Data type Vector polygon
Feature count 80517
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Soil Depth Aug 2021

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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599
19
Added
25 Aug 2021

This dataset was first added to LRIS Portal on 25 Aug 2021.

This layer is a "dissolved" representation of the soil depth attribute for S-map soils previously available as a lookup table. Refer to document Smap Data Dictionary Dissolved Layers.pdf at lris.scinfo.org.nz/document/22129-smap-data-dictio...

Layer ID 105953
Data type Vector polygon
Feature count 64599
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Gorse Density 2013

450
1
Updated
16 Jul 2021

This dataset was last updated on LRIS Portal on 16 Jul 2021.

Gorse density has been classified within 4 ha (200 x 200 m) tiles as either absent (transparent), low density (< 1 plant/ha = yellow), moderate density (<10 plants/ha = orange) or high density (>10 plants/ha = red).

Layer ID 105686
Data type Vector polygon
Feature count 5961
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)

Gorse Density 2020

442
3
Added
13 Jul 2021

This dataset was first added to LRIS Portal on 13 Jul 2021.

Gorse density has been classified within 4 ha (200 x 200 m) tiles as either absent (transparent), low density (< 1 plant/ha = yellow), moderate density (<10 plants/ha = orange) or high density (>10 plants/ha = red).

Layer ID 105678
Data type Vector polygon
Feature count 5961
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)

Desert Road Gorse (Ulex europaeus) 2020

394
2
Added
05 Jul 2021

This dataset was first added to LRIS Portal on 05 Jul 2021.

This raw aerial photography covers 23,000 ha of the Desert Road stretch of SH 1 running through the Central Plateau is provided to members of the Desert Rd Invasive Legume Control Group so that they can locate plants and prioritize areas where ground control is required. Gorse competes with native vegetation and can produce seed that remains viable in the soil for decades.

Estimated image resolution = 0.28 m

Layer ID 105648
Data type Image/Raster
Resolution 0.180m
Services Catalog Service (CS-W)

New Zealand Rabbit Proneness

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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567
8
Added
16 Jun 2021

This dataset was first added to LRIS Portal on 16 Jun 2021.

Rabbit numbers counted by pest destruction boards to measure the affect of control operations are used to assess the relationship between recorded elements of land resources (parent material, soils, vegetation, slope, erosion) and rabbit populations. The results of the study clearly confirm the often observed concentration of high rabbit populations on the brown-grey earth soils and a corresponding reduction in rabbit numbers with increased rainfall and pasture improvement.

This analysis uses the NZLRI/FSL soils data to assign rabbit proneness.
This analysis precedes the illegal release of rabbit haemorragic disease (RHD) in 1997 and does not factor in any interactions between environment and RHD in terms of assigning rabbit proneness.

Layer ID 105591
Data type Vector polygon
Feature count 12642
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

North Island National Pasture Productivity

Licence

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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You must not release derivatives of this work.

829
24
Updated
27 Jul 2021

This dataset was last updated on LRIS Portal on 27 Jul 2021.

The New Zealand National Pasture Productivity map is a multi-temporal approach to estimating pasture (dry matter) yield in New Zealand's grassland area. The approach uses a model generated from collected historical records of pasture yield in 21 locations around New Zealand.It was hypothesised that yield of a paddock planted with pasture species would correlate with some average of normalised difference vegetation index (NDVI) observed at that location. The temporal median of NDVI of vegetated images across New Zealand's grasslands was obtained by calculating the median NDVI of all observations for each pixel where vegetation (NDVI > 0) was observed. Paddock polygons were manually created to surround each of the locations where yields had been obtained, and the spatial means within these polygons of the median NDVIs were plotted against the measured yields. A linear relationship between these quantities was created, which was applied to paddock polygons at a national scale. The uncertainty of the model is +/- 2.2 t/ha/yr for a 70% confidence interval.The data presented in this geodatabase is a segmentation of New Zealand grasslands using an automated multi-temporal approach presented by North, Pairman, and Belliss (2019). The parameters of this segmentation process were selected to achieve minimal missed boundaries between true paddock units. As a side-effect, some boundaries were created between sub-paddock areas with differing spectral response, such as in areas of strip grazing, areas divided by ridges or gullies, and areas with different management patterns. While these artefacts may improve the spatial accuracy of the pasture yield, the result is not intended to provide a one-to-one mapping between true paddock areas and their average pasture yield.The model was applied to each of these polygons. Because the data used to develop the initial model had generally high yields, the model has only been applied to polygons representative of higher-producing grasslands. Where median NDVI for a polygon was outside the domain of the assessed polygons, the model was deemed unfit to estimate pasture yield. Polygons with low median NDVI therefore have an assigned yield of zero.A full list of attribute definitions can be found in the attached PDF.The data used to generate the model has been derived from various published sources, in combination with Sentinel-2 imagery. Complete sets of Sentinel-2 for five passes covering mainland New Zealand were assembled and cloud-cleared in an automated manner using TMASK techinques. The resulting valid data was used to create medians of vegetated images on a per-pixel basis.The segmentation of New Zealand grasslands was derived by initially taking selected Sentinel-2 passes which gave suitable coverage of New Zealand's agricultural land, and applying the automated multi-temporal approach to boundary delineation. Around 200 passes from January - November 2018 were used to achieve the segmentation. These polygons were overlaid with the union of polygons from LCDB v5.0 (lris.scinfo.org.nz/layer/104400-lcdb-v50-land-cove...) which were either High-Producing or Low-Producing Grassland in both 2012 and 2018, and had not changed class between those dates.

Layer ID 105112
Data type Vector multipolygon
Feature count 6893470
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

South Island National Pasture Productivity

Licence

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

You may not use this work for commercial purposes.

You must attribute the creator in your own works.

You must not release derivatives of this work.

834
23
Updated
26 Jul 2021

This dataset was last updated on LRIS Portal on 26 Jul 2021.

The New Zealand National Pasture Productivity map is a multi-temporal approach to estimating pasture (dry matter) yield in New Zealand's grassland area. The approach uses a model generated from collected historical records of pasture yield in 21 locations around New Zealand.It was hypothesised that yield of a paddock planted with pasture species would correlate with some average of normalised difference vegetation index (NDVI) observed at that location. The temporal median of NDVI of vegetated images across New Zealand's grasslands was obtained by calculating the median NDVI of all observations for each pixel where vegetation (NDVI > 0) was observed. Paddock polygons were manually created to surround each of the locations where yields had been obtained, and the spatial means within these polygons of the median NDVIs were plotted against the measured yields. A linear relationship between these quantities was created, which was applied to paddock polygons at a national scale. The uncertainty of the model is +/- 2.2 t/ha/yr for a 70% confidence interval.The data presented in this geodatabase is a segmentation of New Zealand grasslands using an automated multi-temporal approach presented by North, Pairman, and Belliss (2019). The parameters of this segmentation process were selected to achieve minimal missed boundaries between true paddock units. As a side-effect, some boundaries were created between sub-paddock areas with differing spectral response, such as in areas of strip grazing, areas divided by ridges or gullies, and areas with different management patterns. While these artefacts may improve the spatial accuracy of the pasture yield, the result is not intended to provide a one-to-one mapping between true paddock areas and their average pasture yield.The model was applied to each of these polygons. Because the data used to develop the initial model had generally high yields, the model has only been applied to polygons representative of higher-producing grasslands. Where median NDVI for a polygon was outside the domain of the assessed polygons, the model was deemed unfit to estimate pasture yield. Polygons with low median NDVI therefore have an assigned yield of zero.A full list of attribute definitions can be found in the attached PDF.The data used to generate the model has been derived from various published sources, in combination with Sentinel-2 imagery. Complete sets of Sentinel-2 for five passes covering mainland New Zealand were assembled and cloud-cleared in an automated manner using TMASK techinques. The resulting valid data was used to create medians of vegetated images on a per-pixel basis.The segmentation of New Zealand grasslands was derived by initially taking selected Sentinel-2 passes which gave suitable coverage of New Zealand's agricultural land, and applying the automated multi-temporal approach to boundary delineation. Around 200 passes from January - November 2018 were used to achieve the segmentation. These polygons were overlaid with the union of polygons from LCDB v5.0 (lris.scinfo.org.nz/layer/104400-lcdb-v50-land-cove...) which were either High-Producing or Low-Producing Grassland in both 2012 and 2018, and had not changed class between those dates.

Layer ID 105111
Data type Vector multipolygon
Feature count 4013090
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed
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