North Island National Pasture Productivity

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Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International

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837
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

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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.

848
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

Basic Ecosystems

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Creative Commons Attribution-Noncommercial-No Derivative Works 3.0

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5184
396
Added
01 May 2018

This dataset was first added to LRIS Portal on 01 May 2018.

This layer was derived from three existing data layers: the Land Cover Database 2 (LCDB2) (MfE 2002); the Land Use Map (LUM) from the Land Use Carbon Analysis System (MfE 2008; Dymond et al. 2012); and EcoSat Forests (Shepherd et al. 2002). Indigenous forest classes from EcoSat Forests were combined with classes from LCDB2 to form basic ecosystems classes. Where indigenous forest was mapped by LCDB2, the type of forest was determined from the EcoSat Forests layer. The eight forest types of EcoSat Forests were reduced to three basic types: beech forest; podocarp-broadleaved forest; and mixed beech and podocarp-broadleaved forest. To produce a recent 2008 layer the LUM was used to update indigenous and exotic forest changes since 2002. The mapping was performed using 15 m pixels, which is equivalent to a mapping scale of approximately 1:50 000.

Layer ID 95415
Data type Image/Raster
Resolution 25.000m
Services Catalog Service (CS-W), data.govt.nz Atom Feed

Nitrate Leaching

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Creative Commons Attribution-Noncommercial-No Derivative Works 3.0

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2674
56
Added
24 Apr 2018

This dataset was first added to LRIS Portal on 24 Apr 2018.

Nitrogen leaching was estimated using OVERSEER farm nutrient budgeting software version 5.4 (Ministry of Agriculture and Forestry et al., 2011) with a modifier to account for OVERSEER version 6. OVERSEER was run for the 100 combinations of soils and climate from level II of LENZ (Leathwick et al., 2003). Stocking rate were set to the carrying capacity of the land according to the New Zealand Land Resource Inventory (Landcare Research, 2011b), and annual leaching rate per stock unit calculated. The nitrogen leaching rates per stock unit were then combined with the map of animal numbers to produce a map of nitrogen leaching for all of New Zealand.

(Currently unavailable for download - 18/10/2018)

Layer ID 95392
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

GHG Fluxes (Greenhouse Gases)

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Creative Commons Attribution-Noncommercial-No Derivative Works 3.0

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1900
37
Updated
26 Apr 2018

This dataset was last updated on LRIS Portal on 26 Apr 2018.

The current New Zealand greenhouse gas inventory derives implied emission factors that vary between animal types (Ministry for the Environment, 2010). The spatial distribution of animal numbers (dairy, sheep, beef, and deer) was modelled using a land-use map derived from AgriBase (AgriQuality New Zealand, 2003) and the land cover database (LCDB4.1, Manaaki Whenua, 2015). The number of animals were scaled using statistics of livestock numbers at the regional level (Agricultural Production Census (APS), Statistics New Zealand, 2017) and spatially distributed the animals using the potential carrying capacity from fundamental soil layers (Landcare Research, 2011a). N.B. Deer numbers were missing from the APS data for 2015-16 for the Taranaki region which results in reduced GHG values for the region. New Zealand-specific emissions factors were then applied using the IPCC (Intergovernmental Panel on Climate Change) methodology for the agriculture sector for methane and nitrous oxide emissions (Ministry for the Environment, 2010).
Units: tonnes of CO2 equivalent/ha/year

(Currently unavailable for download 18/10/2018)

Layer ID 95391
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Sediment Lost

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Creative Commons Attribution-Noncommercial-No Derivative Works 3.0

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2231
51
Added
23 Apr 2018

This dataset was first added to LRIS Portal on 23 Apr 2018.

This layer depicts estimated sediment/soil loss across New Zealand and was created using the NZeem erosion model. Erosion control is defined as the prevention of soil loss by an ecosystem. NZeem has been calibrated from sediment discharges measured in New Zealand rivers (Dymond et al., 2010). This model estimates the long-term mean erosion rate from all sources of erosion, both mass-movement and surficial, and accounts for all sizes of rainfall events. The model was run on the national datasets of rainfall, erosion terrains, and land cover to produce a national 1:50,000 scale map of long-term mean erosion rates. Dymond et al. (2010) assessed the accuracy of the model by comparing predictions of specific sediment discharge (assuming sediment delivery ratio of 1 everywhere) with available measurements and obtained a model efficiency of 0.64.

Layer ID 95388
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Sediment Retained

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Creative Commons Attribution-Noncommercial-No Derivative Works 3.0

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1744
31
Added
23 Apr 2018

This dataset was first added to LRIS Portal on 23 Apr 2018.

This layer depicts estimated sediment/soil retention across New Zealand and was created using the NZeem erosion model. Sediment retained is defined as the difference between soil loss with and without tree cover (sediment loss avoided). Erosion control is defined as the prevention of soil loss by an ecosystem. NZeem has been calibrated from sediment discharges measured in New Zealand rivers (Dymond et al., 2010). This model estimates the long-term mean erosion rate from all sources of erosion, both mass-movement and surficial, and accounts for all sizes of rainfall events. The model was run on the national datasets of rainfall, erosion terrains, and land cover to produce a national 1:50,000 scale map of long-term mean erosion rates. Dymond et al. (2010) assessed the accuracy of the model by comparing predictions of specific sediment discharge (assuming sediment delivery ratio of 1 everywhere) with available measurements and obtained a model efficiency of 0.64.

Layer ID 95387
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Water Yield

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Creative Commons Attribution-Noncommercial-No Derivative Works 3.0

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2643
57
Updated
03 May 2018

This dataset was last updated on LRIS Portal on 03 May 2018.

This layer represents the net supply of water remaining after evapo-transpiration losses (mm/yr) as an indicator of water- flow regulation. Although this is a simplified view and does not consider low flows or flood flows, it permits national assessment with the use of a nationally applicable water-balance model (similar to the tier 1 approach in Kareiva et al. (2011)). WATYIELD (Fahey et al., 2010) models daily water transfers of rainfall, interception, evapotranspiration, and drainage associated with a soil profile. Input data to the model are daily rainfall and daily potential evapotranspiration (PET). Parameters required for the model included the fraction of intercepted rainfall, vegetation factors for transpiration, and total and readily available water holding capacity of the soil.

Layer ID 95385
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Kaikoura - After Earthquake (23rd November, 2016)

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Creative Commons Attribution 3.0 New Zealand

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5801
56
Added
29 Nov 2016

This dataset was first added to LRIS Portal on 29 Nov 2016.

This image comes from the European Space Agency’s Copernicus Programme taken on 23 November at 11:16 NZDT .

This image comes from the European Space Agency’s Copernicus Programme. Copernicus’ six Sentinel satellites collect comprehensive pictures of our land, ocean, emergency response, atmosphere, security and climate change to understand the health of our planet.

Sentinel-2 is a wide-swath, high-resolution, multi-spectral imaging mission. Its optical instrument samples in 13 spectral bands: four bands at 10 metres, six bands at 20 metres and three bands at 60 metres spatial resolution. The imagery you see on this site is derived from the four bands with a spatial resolution of 10m.

There is an on-line viewer for this and the post-earthquake image at imagery.landcareresearch.co.nz/.

In accordances with licensing please credit ESA by acknowledging "Imagery Copernicus Sentinel data, November 2016".

Layer ID 48497
Data type Image/Raster
Resolution 10.000m
Services Catalog Service (CS-W), data.govt.nz Atom Feed

Kaikoura - Before Earthquake (10th February 2016)

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Creative Commons Attribution 3.0 New Zealand

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4633
46
Added
28 Nov 2016

This dataset was first added to LRIS Portal on 28 Nov 2016.

This image comes from the European Space Agency’s Copernicus Programme taken on 10 February at 11:25 NZDT. This before image was chosen to have a similar sun angle to the after image (lris.scinfo.org.nz/layer/497-kaikoura-after-earthq... ), thus minimising differences due to illumination.

Copernicus’ six Sentinel satellites collect comprehensive pictures of our land, ocean, emergency response, atmosphere, security and climate change to understand the health of our planet. Sentinel-2 is a wide-swath, high-resolution, multi-spectral imaging mission. Its optical instrument samples in 13 spectral bands: four bands at 10 metres, six bands at 20 metres and three bands at 60 metres spatial resolution. The imagery you see on this site is derived from the four bands with a spatial resolution of 10m.

There is an on-line viewer for this and the post-earthquake image at imagery.landcareresearch.co.nz/.

In accordances with licensing please credit ESA by acknowledging "Imagery Copernicus Sentinel data, February 2016".

Layer ID 48496
Data type Image/Raster
Resolution 10.000m
Services Catalog Service (CS-W), data.govt.nz Atom Feed
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