LENZ - Winter solar radiation

3384
263
Added
28 May 2010

This dataset was first added to LRIS Portal on 28 May 2010.

Winter solar radiation data layer used in the creation of Land Environments of New Zealand (LENZ) classification. The classification layers have been made publicly available by the Ministry for the Environment (see data.mfe.govt.nz/layers/?q=LENZ for to access these layers).

Winter solar radiation reaches a minimum in June, the month when the sun is lowest in the sky and day lengths are at their shortest, hence the layer is the monthly average solar radiation layer calculated for the month of June. Estimates of winter solar radiation across New Zealand were derived from a surface fitted to monthly solar radiation estimates for 98 sites as described for mean annual solar radiation.

Data describing monthly humidity was used as a surrogate measure of cloudiness to improve the fit of the surface to the underlying data. This also increases the local accuracy of the surface predictions, as the number of meteorological stations used to fit the humidity surface is more than three times greater than the number of sites used to fit the solar radiation surface. For more details on the creation of these layers see the mean annual solar radiation layer.

The units for this layer are in MJ/m2/day, higher values signify areas that have higher levels of solar radiation. This layer has been multiplied by a factor of 10 (i.e. converted into an integer grid) to save space and make the grids more responsive. A value of 53 is actually 5.3 MJ/m2/day.

Additional details such as the climate station locations used in the creation of the layer and error maps are defined in the attached LENZ Technical Guide.

Layer ID 48096
Data type Grid
Resolution 25.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

NZEEM (Erosion Rates) North Island

3463
68
Added
02 Dec 2010

This dataset was first added to LRIS Portal on 02 Dec 2010.

Mean annual erosion rates (tonnes of soil/km2/yr) in the North Island of New Zealand under current landcover generated from EcoSat Woody (2001-2003).

This layer is not available for download on LRIS. If you are interested in downloading that layer, please contact John Dymond.

Reference: John R. Dymond, Harley D. Betts, Christina S. Schierlitz, An erosion model for evaluating regional land-use scenarios, Environmental Modelling and Software, Volume 25, Issue 3, March 2010, Pages 289-298, ISSN 1364-8152, DOI.

Layer ID 48178
Data type Grid
Resolution 15.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

Bannockburn Soil Map (SB222)

3268
19
Added
21 Jun 2013

This dataset was first added to LRIS Portal on 21 Jun 2013.

A downloadable TIFF image of the 1:15,000 scale SB222 soil map - Soils of the Bannockburn Valley, South Island, New Zealand by FG Beecroft. A full resolution PDF version is also available in the attachments section.

Note this is a more detailed soil map than the Grow Otago soils maps, but uses the old Genetic Soil Classification - soil naming conventions used in this map and the attached report may differ from those found in newer soils maps and databases.

Layer ID 48358
Data type Image/Raster
Resolution 3.000m
Services Catalog Service (CS-W), data.govt.nz Atom Feed

FSL Particle Size Classification

3062
215
Added
07 Jun 2010

This dataset was first added to LRIS Portal on 07 Jun 2010.

The New Zealand Fundamental Soil Layer originates from a relational join of features from two databases: the New Zealand Land Resource Inventory (NZLRI), and the National Soils Database (NSD). The NZLRI is a national polygon database of physical land resource information, including a soil unit. Soil is one in an inventory of five physical factors (including rock, slope, erosion, and vegetation) delineated by physiographic polygons at approximately 1:50,000 scale. The NSD is a point database of soil physical, chemical, and mineralogical characteristics for over 1500 soil profiles nationally. A relational join between the NZLRI dominant soil and derivative tables from the NSD was the means by which 14 important soil attributes were attached to the NZLRI polygons. Some if these attributes originate from exact matches with NSD records, while others derive from matches to similar soils or professional estimates. This layer contains the particle size classification attribute. Particle size class describes in broad terms the proportions of sand, silt and clay in the fine earth fraction of the soil except in the case of skeletal soils ( > 35% coarse fraction ) where it applies to the whole soil. The classes are described in Webb and Wilson (1995) and the user should also refer to the item grav_class for a description of the topsoil gravel content of soils. For the 2nd Edition Gisborne-East Coast mapping, particle size is recorded as undefined as soils were mapped directly to the New Zealand Soil Classification.

Layer ID 48112
Data type Vector polygon
Feature count 107298
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

The dataset contains polygons of soils of part Raglan County mapped at 1:63360. The attributes contain the soil series and the soil classification. No analytical properties of the soil are included.

Layer ID 48153
Data type Vector polygon
Feature count 1421
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Kaikoura - Before Earthquake (10th February 2016)

Licence

Creative Commons Attribution 3.0 New Zealand

You may use this work for commercial purposes.

You must attribute the creator in your own works.

3196
34
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

Soil Map of Piako County

3122
38
Added
29 Jun 2010

This dataset was first added to LRIS Portal on 29 Jun 2010.

The dataset contains polygons of soils of Piako County mapped at 1:63 360. The attributes contain the soil series and the soil classification. No analytical properties of the soil are included.

Layer ID 48129
Data type Vector polygon
Feature count 694
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Land Cover Database - LCDB v3.3 Change

Licence

Creative Commons Attribution 3.0 New Zealand

You may use this work for commercial purposes.

You must attribute the creator in your own works.

3001
90
Added
13 Nov 2013

This dataset was first added to LRIS Portal on 13 Nov 2013.

This data set (LCDB v3.3 Change) is a mask of non temporal changes made between LCDB v3.3 and the previous version (LCDB v3.0) and temporal change between the 2001 and 2008 timesteps. The non-temporal changes include errors in the earlier mappings and linework refinement, including reversal of over-smoothed hand-drawn linework in v3.0. Errors were identified from; a review of low producing grassland in the South Island, updates from MfE's Kyoto Land Use maps, checks of the dating of v3.0 mapped change, and feedback from users. An “EditDate” and “Authority” attribute are available in this layer indicating the date and source of the change for both non-temporal and temporal changes mapped. The Authority attribute indicates who (or who's dataset) identified the change. Note, where minor line-work improvements were applied using automated processes, the EditDate and Authorify have not been changed (but the “NonTemporal” attribute is still set true). This layer was produced with a tolerance of 50cm as a zero tolerance generates slivers too small for the portal software to project correctly. Funding is from the Ministry for Science and Innovation under contract CO9X1101, which was contributed to by the Ministry for the Environment. The Department of Conservation and individual regional councils and territorial authorities have made significant in kind contributions by checking the draft mapping for their areas of interest.

Layer ID 48404
Data type Vector multipolygon
Feature count 151874
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W), data.govt.nz Atom Feed

Mean April Soil Temperature (South Island)

3044
14
Added
14 Jun 2013

This dataset was first added to LRIS Portal on 14 Jun 2013.

Soil temperature surfaces for the South Island of New Zealand are based on analysis of a combination of monthly mean soil temperature data from the NIWA (National Institute of Water and Atmospheric Research)3 years data from 175 mini-data-loggers (1997-2000) laid out in a stratified sampling scheme at 7 climatically representative locations in the South Island. At each location a cluster of about 25 data loggers sampled a range of elevations between 100 and 1800 m. At each elevation grouping the 4 primary aspects (N, S, E, W) and a flat site were sampled at a depth of 30 cm. Multiple regression used site characteristics of latitude, Distance from coast, elevation, aspect, slope and forest/non-forest cover to predict topographic effects on soil temperatures.

Layer ID 48339
Data type Grid
Resolution 25.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

This layer provides a classification of New Zealand ecosystems according to tree and shrub composition. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relation ship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. The transformed environmental layers were then used to classify New Zealand into areas of similar biotic composition. The biotic data used for this model include all non-fern tree and shrub taxa from NVS recce data and estimated community compositions from pollen data.

Layer ID 48224
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed
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