Efficient utilisation of aggregate resources is critical to supporting infrastructure development and reducing operational and transport costs related to extraction of raw materials. To understand the spatial distribution of future resources, aggregate opportunity in the Wellington Region has been mapped using modelling of geological, land use, infrastructure and cultural digital data to map where future resources could be located so they can be prioritised over less critical land uses to support our growing economy. Aggregate opportunity areas are places that have overlapping spatial data classes favourable for extractive activities. A spatial modelling approach has been used to identify places with opportunity for future hard rock, gravel and sand extraction. The resulting maps and their GIS based equivalent datasets of gravel and hard rock aggregate opportunity can be used to manage aggregate resources, generate targets for exploration activities and provide insight into future resources. Appendix to GNS Science report 2024/09 consisting of 29 PDF maps and GIS data files. (DOI: https://doi.org/10.21420/JW09-RF66) DOI: https://doi.org/10.21420/7hym-j851 Cite as: Hill, MP & Chilton, MO. 2024. Aggregate opportunity modelling for the Wellington Region of New Zealand [digital appendix]. Lower Hutt (NZ): GNS Science. https://doi.org/10.21420/7hym-j851

Efficient utilisation of aggregate resources is critical to supporting infrastructure development and reducing operational and transport costs related to extraction of raw materials. To understand the spatial distribution of future resources, aggregate opportunity in the southern Auckland area has been mapped using modelling of geological, land use, infrastructure and cultural digital data to map where future resources could be located so they can be prioritised over less critical land uses to support our growing economy. Aggregate opportunity areas are places that have overlapping spatial data classes favourable for extractive activities. A spatial modelling approach has been used to identify places with opportunity for future hard rock, gravel and sand extraction. The resulting maps and their GIS based equivalent datasets of gravel and hard rock aggregate opportunity can be used to manage aggregate resources, generate targets for exploration activities and provide insight into future resources. Appendix to GNS Science report 2024/12 consisting of 27 PDF maps and GIS data files. (DOI: https://doi.org/10.21420/J47S-NN09) DOI: https://doi.org/10.21420/acbq-rn69 Cite as: Hill, MP & Chilton, MO. 2024. Aggregate opportunity modelling for the southern Auckland area of New Zealand [digital appendix]. Lower Hutt (NZ): GNS Science. https://doi.org/10.21420/acbq-rn69

Efficient utilisation of aggregate resources is critical to supporting infrastructure development and reducing operational and transport costs related to extraction of raw materials. To understand the spatial distribution of future resources, aggregate opportunity in the Bay of Plenty area has been mapped using modelling of geological, land use, infrastructure and cultural digital data to map where future resources could be located so they can be prioritised over less critical land uses to support our growing economy. Aggregate opportunity areas are places that have overlapping spatial data classes favourable for extractive activities. A spatial modelling approach has been used to identify places with opportunity for future hard rock, gravel and sand extraction. The resulting maps and their GIS based equivalent datasets of gravel and hard rock aggregate opportunity can be used to manage aggregate resources, generate targets for exploration activities and provide insight into future resources. Appendix to GNS Science report 2024/10 consisting of 27 PDF maps and GIS data files. (DOI: https://doi.org/10.21420/W34K-RR18) DOI: https://doi.org/10.21420/hnhw-v111 Cite as: Hill, MP & Chilton, MO. 2024. Aggregate opportunity modelling for the Bay of Plenty area of New Zealand [digital appendix]. Lower Hutt (NZ): GNS Science. https://doi.org/10.21420/hnhw-v111

Efficient utilisation of aggregate resources is critical to supporting infrastructure development and reducing operational and transport costs related to extraction of raw materials. To understand the spatial distribution of future resources, aggregate opportunity in the Central Otago area has been mapped using modelling of geological, land use, infrastructure and cultural digital data to map where future resources could be located so they can be prioritised over less critical land uses to support our growing economy. Aggregate opportunity areas are places that have overlapping spatial data classes favourable for extractive activities. A spatial modelling approach has been used to identify places with opportunity for future hard rock, gravel and sand extraction. The resulting maps and their GIS based equivalent datasets of gravel and hard rock aggregate opportunity can be used to manage aggregate resources, generate targets for exploration activities and provide insight into future resources. Appendix to GNS Science report 2024/13 consisting of 27 PDF maps and GIS data files. (DOI: https://doi.org/10.21420/RFGE-SQ76) DOI: https://doi.org/10.21420/6ask-wg49 Cite as: Hill, MP & Chilton, MO. 2024. Aggregate opportunity modelling for the Central Otago area of New Zealand [digital appendix]. Lower Hutt (NZ): GNS Science. https://doi.org/10.21420/6ask-wg49

Efficient utilisation of aggregate resources is critical to supporting infrastructure development and reducing operational and transport costs related to extraction of raw materials. To understand the spatial distribution of future resources, aggregate opportunity in the northern Auckland area has been mapped using modelling of geological, land use, infrastructure and cultural digital data to map where future resources could be located so they can be prioritised over less critical land uses to support our growing economy. Aggregate opportunity areas are places that have overlapping spatial data classes favourable for extractive activities. A spatial modelling approach has been used to identify places with opportunity for future hard rock, gravel and sand extraction. The resulting maps and their GIS based equivalent datasets of gravel and hard rock aggregate opportunity can be used to manage aggregate resources, generate targets for exploration activities and provide insight into future resources. Appendix to GNS Science report 2024/11 consisting of 27 PDF maps and GIS data files. (DOI: https://doi.org/10.21420/DS28-ZG73) DOI: https://doi.org/10.21420/1zkf-sh56 Cite as: Hill, MP & Chilton, MO. 2024. Aggregate opportunity modelling for the northern Auckland area of New Zealand [digital appendix]. Lower Hutt (NZ): GNS Science. https://doi.org/10.21420/1zkf-sh56

GeoNet collects information about the intensity of shaking that people experienced during an earthquake. There have been a few different varieties of reports in the history of collecting this data. Today, GeoNet collects Felt Rapid reports based on a cartoon representation of shaking. After very large earthquakes we provide an additional long form survey, Felt Detailed, for those who would like to provide more information. The Felt Rapid API can be found here: https://api.geonet.org.nz/intensity?type=reported and more information on the Felt Reports can be found here on the GeoNet website: https://www.geonet.org.nz/data/types/felt. DOI: https://doi.org/10.21420/RS7F-VE53 Cite as: GNS Science. (2015). GeoNet Aotearoa New Zealand Felt Rapid Dataset [Data set]. GNS Science. https://doi.org/10.21420/RS7F-VE53

New Zealand network of tsunameters in the southwest Pacific. Tsunameters, devices or systems that detect tsunamis, often use Deep-ocean Assessment and Reporting of Tsunami (DART) real-time monitoring systems. Information about the DART network can be found here: https://www.geonet.org.nz/tsunami/dart Sensor and instrument metadata can be found at https://github.com/GeoNet/delta/blob/main/network/sites.csv DART Raw and Detided data is available via the Tilde API (https://tilde.geonet.org.nz/v3/api-docs/), the Tilde UI (https://tilde.geonet.org.nz/ui/data-exploration#/) and for data-tutorials see (https://github.com/GeoNet/data-tutorials/tree/main/Tilde). The detided constituents are generated by NIWA and can be found here: https://github.com/GeoNet/delta/blob/main/environment/constituents.csv. DART BPR data. The BPR records are available in Tilde (using "Method=raw"). This also includes Temperature (water-temperature) and Pressure (water-pressure) data. DART Trigger Catalogue. A catalogue of all of the auto-triggers on the DART network can also be found here: https://github.com/GeoNet/data/tree/main/dart-triggers DOI for DART Dataset: https://doi.org/10.21420/8TCZ-TV02 DOI for DART Network: https://doi.org/10.1029/2020EO144274 Cite Dataset as: GNS Science (2020). NZ Deep-ocean Assessment and Reporting of Tsunami (DART) Data set [Data set]. GNS Science. https://doi.org/10.21420/8TCZ-TV02 [last accessed on -insert date-]. Cite Network as: Fry, B., S.-J. McCurrach, K. Gledhill, W. Power, M. Williams, M. Angove, D. Arcas, and C. Moore (2020), Sensor network warns of stealth tsunamis, Eos, 101, https://doi.org/10.1029/2020EO144274. Published on 26 May 2020. The DART Sensor Network has been made possible by funding from MBIE (https://www.mbie.govt.nz/) and MFAT (https://www.mfat.govt.nz/), and carried out in partnership between NEMA (https://www.civildefence.govt.nz), GNS Science (https://www.gns.cri.nz/) and NIWA (https://niwa.co.nz/), with support from SAIC (https://www.saic.com/).

A list of known seismological events compiled from oral and written history, and since the 1930s, from instrumental readings. DOI: https://doi.org/10.21420/tap4-5s59 Cite as: GNS Science. (2022). New Zealand Earthquake Catalogue for the revision of the 2022 National Seismic Hazard Model (NSHM) [Data set]. GNS Science. https://doi.org/10.21420/tap4-5s59

The GeoNet earthquake catalogue contains the technical information of all known seismological events. The dataset includes information about the events source parameters such as hypocenter, magnitude, arrival time of seismic phases as well as velocity model used and uncertainties in the parameters. Since the 1930's, earthquakes in the catalogue have been determined by instrumental records. Prior to that, estimates were made from oral and written records. At present, a densified network of weak motion and strong motion sensors is used nationally to monitor events in regions that are affected by large seismic activity and volcanism. Around 20000 events are recorded every year in the catalogue. GeoNet observations and earthquake source parameters are currently used for rapid response, risk assessment and research purposes. Overview of access tools: https://www.geonet.org.nz/data/types/eq_catalogue This dataset is funded through https://www.geonet.org.nz/sponsors DOI: https://doi.org/10.21420/0S8P-TZ38 Cite as: GNS Science. (1970). New Zealand Earthquake Catalogue [Data set]. GNS Science, GeoNet. https://doi.org/10.21420/0S8P-TZ38