MPI SLMACC Auger and Tacit Soil Observations

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.

573
8
Added
13 Jun 2017

This dataset was first added to LRIS Portal on 13 Jun 2017.

This dataset contains 500 augers observations of soil properties collected for a digital soil mapping and land use capability analysis in the Kaikohe to Paihia area. An additional 172 tacit points of estimated soil properties at sites where pedologists were confident they could predict likely soil distribution are also included.

These data were used in conjunction with elevation, slope and other spatial explicit covariate data to predict soil distributions continuously across 100 km2 of Northland hill country

The project report (11 Mb PDF) for this work is downloadable at www.mpi.govt.nz/dmsdocument/30615-use-of-modern-te...

Layer ID 48574
Data type Vector point
Feature count 672
Services Vector Query API, Web Feature Service (WFS), Catalog Service (CS-W)

MPI SLMACC Northland Soil Mapunit (version 11)

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.

704
10
Updated
27 Apr 2017

This dataset was last updated on LRIS Portal on 27 Apr 2017.

Soil map unit raster classification - generated from a Random Forest model based on soil auger data points and terrain and parent material co-variate layers. This model uses 16 soil map units which represent groupings of taxonomically similar soils at NZ Soil Classification sub-group to family level. Random Forest predicts classifications - the map units so defined will be assigned typical soil associations and properties

The project report (11 Mb PDF) for this work is downloadable at www.mpi.govt.nz/dmsdocument/30615-use-of-modern-te...

Layer ID 48559
Data type Multi-attribute Grid
Resolution 5.000m
Services Raster Query API

GDM - Trees and Shrubs - Underlying Data: vpdtran

2502
31
Added
07 Oct 2011

This dataset was first added to LRIS Portal on 07 Oct 2011.

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48262
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

GDM - Trees and Shrubs - Underlying Data: acidptran

1707
17
Added
07 Oct 2011

This dataset was first added to LRIS Portal on 07 Oct 2011.

This layer provides a transformation of environmental layer to best predict plant compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48250
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

GDM - Trees and Shrubs - Underlying Data: agetran

1943
18
Added
07 Oct 2011

This dataset was first added to LRIS Portal on 07 Oct 2011.

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48251
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48252
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

GDM - Trees and Shrubs - Underlying Data: discoasttran

1612
13
Added
07 Oct 2011

This dataset was first added to LRIS Portal on 07 Oct 2011.

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48253
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

GDM - Trees and Shrubs - Underlying Data: gdmxtran

1561
12
Added
07 Oct 2011

This dataset was first added to LRIS Portal on 07 Oct 2011.

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48254
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

GDM - Trees and Shrubs - Underlying Data: gdmytran

1498
12
Added
07 Oct 2011

This dataset was first added to LRIS Portal on 07 Oct 2011.

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48255
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed

GDM - Trees and Shrubs - Underlying Data: junestran

1806
16
Added
07 Oct 2011

This dataset was first added to LRIS Portal on 07 Oct 2011.

This layer provides a transformation of environmental layer to best predict tree and shrub compositional turnover. Generalized Dissimilarity Modelling was used to produce a model of biotic composition in relationship to environment and biogeography. This model was used to transform and scale environmental layers to predict community composition. These transformed environmental layers can be used to predict commmunity composition changes, and 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 48256
Data type Grid
Resolution 100.000m
Services Raster Query API, Catalog Service (CS-W), data.govt.nz Atom Feed
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