Australasian Hydrographic Society New Zealand Region Annual Seminar

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Australasian Hydrographic Society New Zealand Region Annual Seminar LINZ Update New Zealand Hydrographic Authority

Overview Andrew: 2014-15 Survey Campaign Upcoming Survey Schedule LiDAR Trial Stuart: Ed: NZ Risk Assessment Pacific Regional Navigation Initiative NZ Bathymetry Investigation

2014-2015 Surveys Completed

Auckland Islands - NZ 2862 "Our seas and waterways - yet to be fully charted and explored"

Auckland Islands - NZ 2862 - RNZN Request - Increasing Tourism (Future Proof) - Scientific Research Station

Auckland Islands - NZ 2862

Geodetic Network

Upcoming Surveys HS49: Parengarenga Harbour HS46: Rangaunu & Doubtless Bay HS47: Whangaruru Harbour HS48: Hokianga Harbour

Charting Programme - Wellington NZ 463 Approaches to Wellington NZ 4633 Wellington Harbour NZ 4634 Entrance to Wellington Harbour.

Charting Programme - Tauranga NZ 5411 NZ 5412 NZ 5413 NZ 541

Charting Programme - Nelson NZ 6142 NZ 614 NZ 615

Charting Programme - Mercury Bay NZ 5312 NZ 5314 NZ 5315 NZ 5316 NZ 5318

LiDAR Analysis 4 Discrete Areas with recent overlapping MBES data Seamless Topo/Bathy surfaces Analysis run on Residuals between surfaces Where does LiDAR sit in relation to HYSPEC e.g object detection?

LiDAR Analysis Dataset Mean Δh (m) σh (m) % MB-1 target % MB-2 target detection met detection met Whitianga 5m 0.36 0.35 50 53 Motiti 2.5m 0.25 0.52 38 76 Motiti 5m (LADS Mk3 Only) 0.46 0.65 0 0 Great Mercury Island 2.5m 0.12 1.21 12 15 Bay of Islands 2.5m No MBES Overlap 43 45 Bay of Islands 5m -0.2 0.24 25 27

LiDAR Analysis - Object Detection Riegl & LADS Mk3 Combination. LADS Mk3 Only. Less than 9 Strikes within 2m bin 9 or more Strikes within 2m bin

LiDAR Analysis - MV Taioma LiDAR LD = 18.7m MBES LD = 17.7m

LiDAR Analysis - Wigmore Pass

LiDAR Analysis - Wigmore Pass

LiDAR Analysis - Wigmore Pass

LiDAR Analysis - Wigmore Pass

LiDAR Analysis Results Near MB-1 Depth Accuracy Object Detection Limitations Augmenting MBES not replacing it. Excellent reconnaissance tool Joining Land and Sea (JLAS) potential

NZ Hydrography Risk Assessment

NZ EEZ & Ross Sea Region

Where s the risk?

What s the risk?

What s the risk?

1994 Hydrographic Survey Full seafloor search not achieved

2013 Hydrographic Survey Full seafloor search achieved

6.1m rock identified Chart updated by Notice to Mariners

NZ Hydrography Risk Assessment Evidence led, risk based assessment To identify areas of risk and prioritise charting improvements Novel methodology Analytical GIS based risk model AIS vessel traffic data (SOLAS and Domestic) Data gathering Likelihood layers MetOcean conditions, type of navigation, AtoNs, bathymetry, hazards Consequence layers Environmental impact, cultural sensitivity, economic sensitivity Resultant risk presented as heat maps Complete by mid 2016

FLOW CHART OF HYDROGRAPHY RISK ASSESSMENT METHODOLOGY STEP 1 DATA GATHERING Task 1A PREPARATORY STEP Define scope of Geographic Areas being considered. Regional or Interisland. Define Boundaries and Constraints. Stakeholder Identification Stakeholder Questionnaire, Grouping and Consultation Visit Locations Collect Ship Movement Data (SOLAS and Local) From Ports, Agents or Officials. Obtain Satellite (or Local) AIS Data Ship Information Attached) Obtain Economic Information about Each Area GDP. Growth Volumes, Tourism Activity Data gathering Stakeholder Analysis Feedback Consultation Task 1B HAZARD IDENTIFICATION Traffic Analysis (Satellite Derived AIS Data) and Locally Acquired Information Identify Navigational Safety Hazards. Define Likelihood Criteria Evaluate Environmental and Cultural Impact and Significance of Area. Define Consequence Criteria STEP 2 RISK ASSESSMENT Task 2A RISK CRITERIA GIS Assessment of Traffic Frequency by Type and Size GIS Evaluation of Likelihood Criteria GIS Evaluation of Consequence Criteria Task 2B GIS RISK MODEL STEP 3 ECONOMIC ASSESSMENT Task 3A ECONOMIC ANALYSIS Review Areas of Economic Importance to Coastal Areas where shipping use is in evidence. Assess the Economic Impact of Shipping to the Local Economy Task 3B GIS COST BENEFIT MODEL Translate GIS Risk Model Output into likelihood data. Derive loss of life and pollution potential from vessel AIS record. Quantify Costs of Survey Quantify Benefits of Hydrographic Services. Derive Net Present Value Confirm Risk Reduction Available from Charting Upgrades Traffic Forecasting for Proposed Shipping Expansion or Developments Optional STEP 4 IHO Capacity Building Awareness and Assessment Raising Awareness Task 4A Raising Awareness Task 4B Technical Visit Detailed Hydrographic Assessment STEP5 IHO Capacity Building Analysis and Action Development of a national prioritised hydrographic survey and charting programme PHASE 1 of Development: Collection & circulation of nautical information, necessary to maintain existing charts and publications up to date

Risk Model Result Figure 38: Tongatapu Risk Model Results

Maritime Safety in the Pacific

Tokelau Samoa Pacific Regional Navigation Initiative Niue

NZ Bathymetry Investigation

A voyage under the sea Ed Griffin NZ Bathymetry Investigation Project Manager

Bathymetry: The last Frontier?

Eastern Passage Chalky Inlet

Mutlibeam identified June 2015

Why is bathymetry important? Safety of life at sea (SOLAS) Efficient navigation Scientific Research Location of natural resources Recreation (e.g. Fishing) Marine Geology

Focus for this project LINZ 10 YEAR VISION Foundational work Coordination/stewardship Benchmark/baseline

Internationally

Provision in NZ

Data collection Does your unit/group or organisation collect depth data via bathymetric or hydrographic surveys?

Standards and metadata Recognised survey metadata standards? Which hydrographic standards do your surveys comply with?

Data fit for purpose Does What the are bathymetry the main reasons data that why you the use data now is meet not fit your for requirements? purpose?

Key Points Internationally: Gaps in data Moving towards better data provision New Zealand: No national coordinated approach Opportunities for quick wins Joint commissioning Data quality control (metadata/standards) LINZ data discoverable/accessible Data from exploration surveys & research vessels Long term: national bathymetry model