Lidar was captured for Wellington City Council by Aerial Surveys between 2019 and 2020. The dataset was generated by Aerial Surveys and their subcontractors. The survey area includes Wellington City and the surrounding area. Data management and distribution is by Land Information New Zealand Prepared DEM and DSM files are available through the LINZ Data Service: Wellington City, New Zealand 2019 Digital Elevation Model 2019-2020 Wellington City, New Zealand 2019 Digital Surface Model 2019-2020

This layer contains the DEM for LiDAR data in the Wellington Region including Wellington City as well as the surronding area captured in 2019. The DSM is available as layer Wellington City LiDAR 1m DSM (2019). The index tiles are available as layer Wellington City LiDAR Index Tiles (2019). The LAS point cloud and vendor project reports are available from OpenTopography. LiDAR was captured for Wellington City Council by Aerial Surveys from 20 March 2019 to 14 March 2020. These datasets were generated by Aerial Surveys and their subcontractors. Data management and distribution is by Land Information New Zealand. Data comprises: DEM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout DSM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout Point cloud: las tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout Pulse density specification is at a minimum of 16 pulses/square metre. Vertical datum is NZVD2016.

This layer contains the DEM for LiDAR data from the Wellington region captured in 2013. Note that this DEM is based on automated point cloud classification and contains some residual remnants of surface features. The DSM is available as layer Wellington LiDAR 1m DSM (2013). The index tiles are available as layer Wellington LiDAR Index Tiles (2013). The LAS point cloud is available from OpenTopography. Lidar was captured for Greater Wellington Regional Council by Aerial Surveys in 2013. The datasets were generated by Landcare Research. The survey area includes Wellington, Porirua, Lower Hutt, Upper Hutt, Wairarapa, and Kapiti. Data management and distribution is by Land Information New Zealand. Data comprises: •DEM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout •DSM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout •Point cloud: las tiles in NZTM2000 projection, tiled into a 1km x 1km tile layout Data was collected at >1 pulse/square metre pulse density. Attributes include: -Elevation -Intensity values -Return number -Adjusted GPS time -Classification Vertical datum is NZVD2016

Lidar of the entire Wellington region, captured for Greater Wellington Regional Council by Aerial Surveys in 2013. Further processing including automated classification and conversion to NZVD2016 was done by Landcare Research. Data management and distribution is by Land Information New Zealand. Prepared DEM and DSM files are available through the LINZ Data Service Wellington, New Zealand 2013-2014 DEM Wellington, New Zealand 2013-2014 DSM

NAME: Wellington region LiDAR DEM 1mABSTRACT : Lidar was captured for Greater Wellington Regional Council by Aerial Surveys in 2013SOURCE DATE: LiDAR Flown Feb 2013 SUPPLIER: NZ Aerial Surveys Ltd.CAPTURE METHOD: Using LiDAR and surface created with Kriging interpolation. Vertical datum is NZVD2016POSITIONAL ACCURACY: Generally +/- 1.05m but worse in dense bush areasCUSTODIAN/CONTACT: Greater Wellington regional Council GIS TeamUPDATE FREQUENCY: As requested, within WAGGIS regional maintenance programmeUSAGE: Attributes include -Elevation, intensity values, return number, classificationCOMPLETENESS: 100% Wellington regional areaKEYWORDS: Landcover, topography, DEM

Lidar was collected for GNS Science by NZ Aerial Mapping in September 2010, under survey name Tararua LiDAR, and includes approximately 8 km of the Wellington Fault on the North Island, approximately 82 km northeast of Wellington. The polygon encloses an area of approximately 9 km². The dataset was generated by NZ Aerial Mapping (NZAM) and their subcontractors and processed into various digital map data products. Note: This dataset was converted to LAS from XYZ (ASCII) points and lacks typical lidar attibutes.

This lidar was collected for Isabelle Manighetti, Observatoire de la Cote d'Azur, GEOAZUR. The requested survey area is located approximately 39 km east of Wellington. The polygon encloses an area of approximately 128 km².

This layer contains the index tiles for LiDAR data from the Wellington region captured in 2013. The DEM is available as layer Wellington LiDAR 1m DEM (2013). The DSM is available as layer Wellington LiDAR 1m DSM (2013). The LAS point cloud is available from OpenTopography.

Lidar was captured for Greater Wellington Regional Council by Aerial Surveys in 2013. The datasets were generated by Landcare Research. The survey area includes Wellington, Porirua, Lower Hutt, Upper Hutt, Wairarapa, and Kapiti. Data management and distribution is by Land Information New Zealand.

Data comprises: •DEM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout •DSM: tif or asc tiles in NZTM2000 projection, tiled into a 1:1,000 tile layout •Point cloud: las tiles in NZTM2000 projection, tiled into a 1km x 1km tile layout

Data was collected at >1 pulse/square metre pulse density. Attributes include: -Elevation -Intensity values -Return number -Adjusted GPS time -Classification

Vertical datum is NZVD2016

Lidar of the entire Wellington region, captured for Greater Wellington Regional Council by Aerial Surveys in 2013. Further processing including automated classification and conversion to NZVD2016 was done by Landcare Research. Data management and distribution is by Land Information New Zealand. Prepared DEM and DSM files are available through the LINZ Data Service Wellington, New Zealand 2013-2014 DEM Wellington, New Zealand 2013-2014 DSM

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Vertical datum is NZVD2016. Area of 50k topo sheet BQ31 (Wellington).1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ. Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, based off data from WCC (2009 and 2020) and HCC (2016)Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m. Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

Lidar was collected for GNS Science by NZ Aerial Mapping in September 2010, under survey name Tararua LiDAR, and includes approximately 8 km of the Wellington Fault on the North Island, approximately 82 km northeast of Wellington. The polygon encloses an area of approximately 9 km2. The dataset was generated by NZ Aerial Mapping (NZAM) and their subcontractors and processed into various digital map data products. Note: This dataset was converted to LAS from XYZ (ASCII) points and lacks typical lidar attibutes.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ. Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, based off data from WCC (2009 and 2020), PCC (2015), HCC (2016), Masterton urban (2016) and KCDC (2017). Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m. Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ. Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, based off data from WCC (2009 and 2020), PCC (2015), HCC (2016), Masterton urban (2016) and KCDC (2017). Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m. Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Area of 50k topo sheet BP32 (Paraparaumu).Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ.Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, for this sheet based off data from PCC (2015), and KCDC (2017).Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m.Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ. Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, based off data from WCC (2009 and 2020), PCC (2015), HCC (2016), Masterton urban (2016) and KCDC (2017). Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m. Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

Tree cover data has been uploaded to the databse on 21st of March 2022.This tree cover feature class was produced for Wellington City and Suburbs; the study area can be seen in the accompanying tree canopy cover report (https://dx.doi.org/10.26021/11224). The tree cover feature class was produced using an object-based image analysis (OBIA) approach. OBIA is a semi-automated image classification method that can be used to identify trees based on aerial photography and LiDAR data. Following the OBIA, tree canopy cover was manually refined to correct errors in the tree cover classification. Boundary adjustmentfor tree crowns was also undertaken at a scale of no greater than 1:2,500. For the purpose of the OBIA, a tree was defined as an object having vegetation-like reflectance characteristics, exceeding 3.5 m in height and having a minimum diameter of 1. 5 m. Treefeatures comprise all tree and forest types. This includes, but is not limited to, park and reserve trees, street trees, trees on private property, orchards, remnant patches of native forest, hedgerows, and trees in commercially-managed, large-scale forestry plantations. The data on which the OBIA was performed included aerial photography and LiDAR data. Aerial photography was captured by AAM NZ Ltd. for the Wellington City Council during the summer of 2016-17. Images were acquired on 24, 27, 28 February and 5 March 2017. Imagery was supplied as 10 cm pixel resolution, 3-band (RGB) uncompressed GeoTIFF. The final spatial accuracy is ± 0.2 m at 90% confidence level. LiDAR data were captured for Wellington City Council by Aerial Surveys from 20 March 2019 to 14 March 2020. As a consequence of the range in time of acquisition for LiDAR data, the tree canopy cover assessment that was completed for this report should be considered accurate as at 20 March 2019. Both aerial imagery and LiDAR data were sourced from the LINZ Data Service and licensed by Wellington City Council, for re-use under CC BY 4.0.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ. Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, based off data from WCC (2009 and 2020), PCC (2015), HCC (2016), Masterton urban (2016) and KCDC (2017). Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m. Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020.Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ.Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, based off data from WCC (2009 and 2020) and HCC (2016).Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m.Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Area of 50k topo sheet BP31 (Porirua).Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ.Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM, for this sheet based off data from PCC (2015).Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m.Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.

1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Vertical datum is NZVD2016. Area of 50k topo sheet BP34 (Masterton).1m elevation contours based off a composite bare-earth LIDAR DEM of Wellington Region, New Zealand, 2020. Base DEM is the 2013 WAGGIS LIDAR regional DEM, reprocessed in 2017 by Landcare Research for LINZ. Additional, mainly later, DEMs have been mosaiced in to replace the regional DEM where possible, in this sheet based off data from Masterton urban (2016). Original region-wide 2013 LIDAR data captured at 1.3 points per square metre, to an accuracy of +/- 0.15m (1 sigma) in 2013-2014.Subsequent more localised LIDAR surveys have provided improved strike point densities and accuracies.Vertical datum is NZVD2016. Projection NZTM. Parent DEM cell size 1m. Contours have been smoothed by first applying focal statistics to the parent DEM (3x3 cell, mean), then generalising the resulting contours using the Douglas-Peucker method.