North Island National Pasture Productivity

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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272
3
Added
24 Nov 2020

This dataset was first added to LRIS Portal on 24 Nov 2020.

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

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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.

242
10
Added
24 Nov 2020

This dataset was first added to LRIS Portal on 24 Nov 2020.

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

Smap Predicted Carbon August 2020

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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You must not release derivatives of this work.

575
35
Added
20 Sep 2020

This dataset was first added to LRIS Portal on 20 Sep 2020.

Spatial surface estimates of soil carbon stock (units tonnes per hectare) for the 0–30cm layer, over the land surface of New Zealand, based on a generalised linear regression model using environmental classification, national soil layer, and climate layers as explanatory variables, with a correction for spatial auto correlation of data samples. Estimates are made on a grid where each grid cell has dimensions 1,000 m x 1,000 m (100 ha). The value at each grid cell is our best estimate of the mean soil carbon stock across the area occupied by each grid cell.
A number of data layers were acquired to act as explanatory layers for the prediction of soil carbon. Soil data includes the MfE Historic Soils Database (under an agreement with MfE), the NSD (LandcareResearch New Zealand 2012), the SINDI soil quality dataset (Landcare Research New Zealand 2012), and the LMI soils dataset (under an agreement with Plant and Food Research 2011).Additional explanatory data layers were obtained from the LENZ data set (Landcare Research New Zealand), including the LENZ climate layers (e.g. mean annual rainfall) as well as environmental classification layers (LENZ level 1, 2, 3, and 4), from the Koordinates data portal (Koordinates 2012). In addition, the natural potential vegetation layer (Leathwick 2001) is used as an indicator of vegetation prior to agricultural development. These layers were augmented by explanatory layers acquired from the LRIS portal (Landcare Research 2012), consisting of national maps of basic soil properties (soil order, exchangeable calcium, acid soluble phosphorus, rock class, mid-estimate of surface outcrops, annual water deficit). Additional 0–30cm carbon stock data was obtained by using SINDI data (derived from 0–10cm depth samples) along with NSD data and a regression model to infer 0–30cm soil carbon stocks (tonnes/ha) at the centre of each pixel.
This data is owned by the Ministry of Primary Industries (MPI)).

Layer ID 105005
Data type Grid
Resolution 1000.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Predicted pH August 2020

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

You may not use this work for commercial purposes.

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You must not release derivatives of this work.

1069
42
Added
15 Sep 2020

This dataset was first added to LRIS Portal on 15 Sep 2020.

Estimates of soil pH, as measured in a 1:5 water solution, for the 0 – 7.5 cm depth interval. The values of this layer represent estimates for the centre of a 100 m x 100 m (1 ha) grid covering all of New Zealand, with the exception of areas that do not have soils. The layer was generated using a 3 dimensional quantile regression forest model, that leverages a range of spatial predictors, including land use, topography and climate layers.

More detailed information about the model used is provided in the publication: National Scale 3D Mapping of Soil pH Using a Data Augmentation Approach, Remote Sens. 2020, 12(18), 2872; doi.org/10.3390/rs12182872

Layer ID 104963
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Soil Drainage Aug 2020

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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You must not release derivatives of this work.

2410
269
Added
24 Aug 2020

This dataset was first added to LRIS Portal on 24 Aug 2020.

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 104903
Data type Vector polygon
Feature count 131599
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Polygons August 2020

Online
Only
Licence

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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You must not release derivatives of this work.

324
0
Added
18 Aug 2020

This dataset was first added to LRIS Portal on 18 Aug 2020.

This layer shows the coverage of S-map polygons, labelled with their Soil mapunit – a unique identifier of one or more polygons with the same soil information.
The S-map primary map layer of soil classes (i.e. delineated areas that are labelled with the soil family names) is no longer freely available to commercial users. Access to this data and associated soil attribute data for commercial use is by negotiation - contact Graeme Anderson (andersong@landcareresearch.co.nz).

ACCESS to publicly available S-map data is now at
S-map Soil Depth
S-map Soil Drainage
S-map Soil Texture
S-map NZ Soil Classification

Layer ID 104867
Data type Vector polygon
Feature count 339450
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Soil Classification (Soil Order) Aug 2020

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

You may not use this work for commercial purposes.

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You must not release derivatives of this work.

2522
258
Added
18 Aug 2020

This dataset was first added to LRIS Portal on 18 Aug 2020.

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 104865
Data type Vector polygon
Feature count 171858
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Soil Depth Aug 2020

Licence

Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

You may not use this work for commercial purposes.

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You must not release derivatives of this work.

1433
62
Added
18 Aug 2020

This dataset was first added to LRIS Portal on 18 Aug 2020.

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 104864
Data type Vector polygon
Feature count 63821
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Smap Soil Texture Aug 2020

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.

313
62
Added
18 Aug 2020

This dataset was first added to LRIS Portal on 18 Aug 2020.

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 104862
Data type Vector polygon
Feature count 79620
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

LCDB_v5.0 - Land Cover Database version 5.0, Chatham Islands

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Creative Commons Attribution 4.0 International

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728
39
Updated
29 Jan 2020

This dataset was last updated on LRIS Portal on 29 Jan 2020.

The New Zealand Land Cover Database (LCDB) is a multi-temporal, thematic classification of New Zealand's land cover. It identifies 33 mainland land cover classes (35 classes once the offshore Chatham Islands are included). The classification was revised between versions 1, 2, and 3 but has been consistent thereafter, and always with backward compatibility maintained. Land cover features are described by a polygon boundary, a land cover code, and a land cover name at each nominal time step; summer 1996/97, summer 2001/02, summer 2008/09, summer 2012/13, and summer 2018/19. The data set is designed to complement in theme, scale and accuracy, New Zealand’s 1:50,000 topographic database (www.linz.govt.nz/land/maps/topographic-maps/topo50...). LCDB is suitable for use in national and regional environment monitoring, forest and shrubland inventory, biodiversity assessment, trend analysis and infrastructure planning. The classification used in LCDBv5.0 is presented in the document 'LCDBClassesAtVersion5.pdf' and a table correlating LCDB classes over all versions is presented in the document 'LCDBClassCorrelations.pdf'. Both of these are among the accessory documents to this dataset in the LRIS portal (lris.scinfo.org.nz/). LCDB version 5.0 was released in January 2020 and includes corrections to all time steps 1997/97, 2001/02, 2008/09, 2012/13 and 2018/19 for both the New Zealand mainland and Chatham Islands. A description of work undertaken for this release (including that of all earlier releases) is presented in the Lineage section. Of particular note at version 5.0 is the addition to LCDB, of attributes designed to readily identify and monitor wetlands over time and a similar capability to manage significant coastal changes. “EditAuthority” and "EditDate" are attributes, maintained since version 3.0 to indicate authorship and nominal date of polygon mapping, edit or change. Errors in the data due to misclassification (rather than land cover change) or poor delineation can be reported to Landcare Research for inclusion in the next release using the online feedback facility in lris.scinfo.org.nz/.

Layer ID 104442
Data type Vector polygon
Feature count 2333
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)
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