MAPPING AND MONITORING OF
WATER AND MARINE ENVIRONMENTS


 

Observing long-term change in New Zealand’s coasts and oceans:
satellite observation of water quality and productivity

by Matt Pinkerton, Simon Wood and Mark Gall, National Institute of Water and Atmospheric Research Ltd (NIWA), Wellington

Dr Matt Pinkerton will report on research applying ocean colour and sea-surface temperature satellite observations to monitor variability and long-term change in New Zealand waters over the last two decades. Satellite observations from MODIS-Aqua, SeaWiFS and AVHRR sensors were blended to produce a 20-year time series of the concentration of Chlorophyll-a, oceanic primary production and vertical particulate flux in New Zealand’s offshore waters. These measurements have been used to contextualize changes to marine food-webs, fisheries, seabirds and marine mammals.

Recent advances in processing methods mean that satellite observations are increasingly being used in New Zealand for coastal applications. This talk will report on the development of a range of moderate-resolution satellite products for New Zealand’s coastal zone which have been used to monitor water quality, detect coastal change and develop spatially-resolved approaches to manage human impacts on coastal ecosystems. In one application, a novel method was developed to detect the depletion of phytoplankton by cultured bivalves in a large mariculture farm. We anticipate the opportunities for using higher resolution satellite data in the New Zealand coastal zone and inland waters. This tal will also highlight approaches for bio-optical sampling to validate and locally-tune satellite observations of water quality around New Zealand.

 

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Dr Matt Pinkerton - Principal Scientist - Marine Ecology, NIWA

Dr Matt Pinkerton is a Principal Scientist at NIWA with 20+ years’ experience in ocean remote sensing. He leads the NIWA core project on ocean remote sensing and has led work delivering satellite information for regional councils, central government and industry.

He is also a member of the New Zealand advisory group on marine and coastal indicators and ex-associate editor for bio-optics in Continental Shelf Research.

 

How Earth observation imaging platforms can improve
maritime domain awareness systems

Paul Kennedy will be speaking about maritime domain awareness systems for all types of Earth Observation imaging platforms to improve the decision making and operational performance of business, government, and defence organizations worldwide. Paul will provide practical examples where this technology has been applied at great effect, with a primary focus on what the Canadian Space Agency have achieved with Polar Epsilon 1 (with RadarSat-2) in maritime domain awareness across 11-million square kilometres of marine environment, and what the future looks like with Polar Epsilon 2 (with RCM).

 

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Paul Kennedy - Vice President, Ground Systems, MDA Corporation

Paul Kennedy has over 25 years of experience in earth observation, geographic information systems, and marine science.

Paul’s group provides advanced ground system solutions, including near-real time maritime domain awareness systems, for all types of Earth Observation imaging platforms.

 

25 years of getting value from satellite observations

NIWA has been receiving, processing and archiving direct broadcast data from Polar Orbiting satellites for over 25 years, initially from satellites transmitting in the L-Band, and since 2007 from those that transmit in the X-Band. These data have been used extensively for research purposes (e.g. to develop climatologies of Sea Surface Temperature, Chlorophyll-a, cloud type, cloud cover, albedo etc.) and is a critical input to advanced numerical weather prediction models as implemented at NIWA and for the generation of products used directly by end users (e.g. to target pelagic fisheries). This talk will describe the reception and processing systems in place at NIWA, the products derived from these data – both the transparent and opaque parts of the spectrum, the challenge of the ill-posed nature of these data,  the synergy between models and the data, as well as some of the products being used by end users.

 

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Dr Michael Uddstrom - Principal Scientist - Environmental Forecasting, NIWA

Michael is NIWA’s Principal Scientist for Environmental Forecasting. He leads NIWA’s weather related hazards forecasting research effort, which is focussed on improving the accuracy of forecasts of weather, river-flood, flood inundation, sea-state, sea-level including storm surge, and rip current hazards as they affect New Zealand. In this role, he was also responsible for establishing NIWA’s operational forecasting system, EcoConnect, where the NWP components are local implementations of the Unified Model, including the New Zealand Convective Scale Model (NZCSM). NIWA has a long history with use of the Unified Model. In the mid 1990s it began using the UM for climate change simulations, and by 2000 had implemented and demonstrated its capabilities as a cycling, limited area data assimilating mesoscale model – the first successful implementation outside the Met Office.

Michael has more than 30 years experience in the development of satellite algorithms for application across a wide range of science problems - from fisheries analysis to numerical weather prediction, and was responsible for the development of the science and technology proposals that resulted in the acquisition of New Zealand’s first supercomputer in 1999, a Cray T3E 1200 and its successor in 2009/10, an IBM p575 system. He continues to be a champion for the development of High Performance Computing in New Zealand, and has recently been appointed as Platforms Manager for New Zealand’s National eScience Infrastructure, responsible for managing New Zealand’s supercomputers in Auckland, Wellington and Christchurch, a role he carries out in parallel with his NIWA responsibilities.

 

Aquatic Earth Observation: State-of-the-art, case studies, and looking forward

by Dr. Magnus Wettle (1), Dr. Thomas Heege (2), Kevin Mackay (3)
(1) EOMAP Australia, Sunshine Coast, QLD, Australia, (2) EOMAP Germany, Seefeld Castle, Bavaria, Germany,
(3) NIWA, Greta Point, Wellington, New Zealand

Aquatic earth observation, with significant applications in sectors such as navigation, defence, oil and gas, and environmental management, can be broadly divided into two areas: monitoring water quality (e.g. turbidity, sediment loads or chlorophyll-a concentrations in the water column) and mapping the seafloor (e.g. bathymetry, seafloor reflectance, and benthic habitats).

Monitoring water quality using remote sensing has traditionally been done using sensors - such as on the MODIS satellites – with relatively coarse spatial resolution but frequent re-visit times. Applications for this have typically been in open ocean waters, limited by the complexities of inland and coastal aquatic environments and the lack of suitable higher resolution sensors. Dr Magnus Wettle will present a selection of case studies with government agencies, environmental consultancies and industry, which illustrate the state-of-the-art operational monitoring of inland and near coastal water quality using the latest generation of higher resolution satellite sensors.

Detecting the seafloor using remote sensing, particularly estimating water depth, has been in development since the 1970s, but it is in the last decade that the required physics-based algorithms and processing work flows have become sufficiently robust to offer an operational service - applicable worldwide with known accuracies - without the requirement for a priori, in situ field data. Dr Wettle will present a selection of case studies with government agencies, research institutes, environmental consultancies and industry which illustrate the state-of-the-art in mapping water depth, seafloor colour, and benthic habitats, using earth-orbiting satellite sensor data. In particular, he will present two New Zealand-based aquattic earth observation projects: mapping the bathymetry and shallow seafloor habitats of Marlborough Sounds together with NIWA, and mapping the shallow water bathymetry of Tonga and surrounding areas together with LINZ. Both projects were done with very high spatial resolution (2m pixel) satellite imagery, and the Tonga project will be one of the largest satellite-derived bathymetry projects completed worldwide, to date, at this level of resolution.

Looking forward, the next generation of platforms and sensors together with advancements in big data and AI, will further drive potential applications and continue lowering costs to the end user. Unmanned aerial vehicles (UAVs), capable of carrying multi- and hyper-spectral sensors, offer an additional platform for sourcing remotely sensed aquatic data. The potential opportunities and pitfalls for these will be briefly addressed.

 

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Dr Magnus Wettle - Managing Director, EOMAP Australia

Dr. Magnus Wettle has more than 15 years experience in the fields of aquatic earth observation research and applied solutions. During his career at CSIRO, he co-developed the SAMBUCA software, which is used today by CSIRO for shallow water applications. While at Geoscience Australia, he led the implementation of new capabilities, including satellite-based bathymetry and offshore oil seep detection. As a Senior Research Fellow at the University of Queensland, he managed the delivery of multi-disciplinary, remote sensing-based solutions to the natural resource industry. He joined EOMAP in 2012.

 

Using Remotely Sensed Tools for Combined Drought Indicators to Enhance Drought Early Warning for Decision Support

The fact that droughts, unlike most hazards, typically evolve slowly, last for months or years, and can cover thousands of square miles across multiple geopolitical boundaries makes it a daunting task to track them over space and time. In-situ networks will always face the challenges of underfunding, ongoing maintenance and not enough spatial density or uniform coverage to thoroughly monitor our hydroclimatic system. In the United States and abroad, many partners are working together to develop more coordinated and comprehensive drought early warning and information systems based in part on remotely sensed inputs, which can help augment our in situ networks. These systems are often centered around approaches aimed at building local capacity and for informing decision makers in the areas of food and water security.

The NDMC works to reduce societal vulnerability to drought by helping decision makers at all levels to: implement drought early warning systems, understand and prevent drought impacts, and increase long-term resilience to drought through proactive planning. The NDMC is a national/international center founded in 1995 at the University of Nebraska-Lincoln. The NDMC conducts basic and applied research in the areas of development and maintenance of a number of operational drought-related decision support tools and databases, monitoring and early warning, education, outreach and other services in the United States and around the world.  

This presentation will describe in more detail the various combined drought indicator efforts that the NDMC and partners around the world have been involved in as we work to complement in-situ networks with the best that satellites and models can provide while utilizing the strengths of multiple indicators in order to customize early drought warning systems for specific needs. Special attention will be given to our current work with the United Nations, World Bank, USAID and other partners around the world.

 

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Dr Mark Svoboda - National Drought Mitigation Center/University of Nebraska-Lincoln Director, University of Nebraska - Lincoln

As the NDMC’s Director, Svoboda (a climatologist by training) administers and oversees the center’s staff and mission, which involves the research, operational, planning and education/outreach programs of the NDMC and NOAA’s Drought Risk Management Research Center.

Mark works closely with federal, tribal, state, basin, local and international officials and governments on drought monitoring early warning information systems, drought risk management planning and collaborative research. He provides expertise on a wide range of climate-water management issues and is responsible for assessing user product needs and responding to information and decision support requests.

Svoboda is involved with drought monitoring, assessment and prediction committees and activities at the state, regional, tribal, national and international levels. Mark Svoboda is the co-founder (1999), and served for 17 years as one of the principal authors of the weekly U.S. Drought Monitor. His work with the Core Team of the Western Governors’ Association led to the development of a report and recommendations on creating a National Integrated Drought Information System (NIDIS) for the United States, which was authorised by Congress into public law in 2006.

Mark Svoboda is currently a member of the World Meteorological Organization/Global Water Partnership Integrated Drought Management Programme’s Advisory Panel and also serves on the NIDIS Executive Council. Most recently, he was selected to serve as a member of the United Nations Convention to Combat Desertification (UNCCD) Bureau of the Committee on Science and Technology’s (CST) Science Policy Interface (SPI) team. Mark’s Bachelor’s, Master’s and Doctoral degrees were all obtained at the University of Nebraska-Lincoln.

 

Developing, validating, and using a Combined Drought Indicator: insights from co-development approaches in Tunisia

The development of environmental monitoring tools such as the Tunisian Combined Drought Indicator (CDI), and their ultimate integration into successful environmental management regimes, requires broad-based engagement, including with vulnerable populations, to inform and shape the monitoring outputs and technical development processes. Likewise, ensuring that decision support tools like the CDI reach the desired audiences requires strong institutional relationships, working partnership coalitions within and across government agencies and research, private sector, and civil society organisations. This presentation highlights how such wide-ranging engagement informed and laid the groundwork for the ongoing technical development, validation, and usage of the Tunisian CDI.

The agencies developing the Tunisian CDI initially focused primarily on rainfed agricultural conditions. As such, it currently incorporates the following data:

  • SPI (derived from the CHIRPS dataset)
  • NDVI (MODIS)
  • Root-zone soil moisture (LIS model)
  • Day/night land surface temperature fluxes (MODIS)
  • Longer term aims: replace temperature flux with ESI (Python DisALEXI model); incorporate observed precipitation data in SPI; develop CDI variants incorporating the surface water supply index and/or an appropriate groundwater drought index

The DGRE has included national and local government agencies, research institutes, and the national farmers’ union in validation processes including nationwide workshops. Given the widespread skepticism of remote sensing and modelled data identified during the initial engagements, the DGRE is undertaking this extensive validation effort to form the requisite expert networks to ensure confidence in CDI results amongst its user-base and so it has a strong operational base for ongoing CDI improvement and usage. In addition, they are undertaking concurrent technical validation efforts using historical observed climatic, hydrological, and agricultural data.

The DGRE has used the CDI to inform in-situ drought monitoring and drought declaration processes. The DGRE also plans to introduce the information into water allocation decision-making processes that determine inter-basin transfers and reservoir management. Other agencies intend to use the information in the near future for a variety of purposes including seasonal crop planning, crop yield estimation, and import/export forecasting.

The relevant learnings for development of remote sensing tools are universal in application:

  • The criticality of building and reinforcing expert networks within and beyond government to facilitate the development and uptake of remote sensing-based information products and political decision support tools;
  • The role of institutional settings in leveraging cross-agency functions and relationships
  • The primary importance of effective data sharing mechanisms and data accessibility
     

 

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Stephen Fragaszy - Policy analyst – Environmental limits – Water Directorate, Ministry for the Environment

Stephen Fragaszy is a policy analyst focused on water management at the New Zealand Ministry for the Environment. He particularly enjoys inter-disciplinary work that has social and natural science features. Prior to joining the Ministry, he consulted for organisations and companies including the US National Drought Mitigation Center, the International Center for Biosaline Agriculture, Oxford, FAO, and the US Department of Defense. Projects had research, stakeholder engagement, and institutional development and strategy components.

He has a history (NYU) and geography (Oxford) background. While living the good life, he has picked up smatterings of Arabic, French, and Spanish and joined the happy ranks of parenthood in recent years.

 

Nowcasting convective weather in New Zealand using neural networks

Convective weather, which produces thunderstorms, squalls, hail, heavy localised rainfall and tornadoes significantly impacts safety, efficiency and well being. It has small spatial scales (few kilometres), but is usually resolvable in geostationary satellite imagery. While great progress has been made forecasting at larger scales, analysis and forecasting of convective weather still relies heavily on human interpretation of satellite observations.

Machine learning has recently had great success in feature and pattern identification in a number of other fields, and now approaches or exceeds human skill. MetOcean Solutions and the Knowledge Engineering and Discovery Research Institute (Auckland Institute of Technology) have been founded by the Ministry of Business, Innovation and Employment to develop and apply novel machine learning approaches to data from the Himawari geostationary satellite which observes the hemisphere that includes New Zealand. The aim of the project is to develop a system which can match or exceed the ability of a human forecaster to look at satellite imagery and predict the likely convective weather events associated with it.

The project is still in its early stages and the presentation will go over the aims, challenges and data involved involved in the project. The direction of research taken by MetOcean Solutions for its neural network approach to the problem will also be outlined.

 

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Dr Sébastien Delaux - Modeller, MetOcean Solutions

Sébastien has a degree in mathematical and mechanical modelling and a PhD working on computational fluid dynamics. Sébastien has been working for MetOcean Solutions for almost 7 years. He was initially involved in the development of a ship motion numerical model, that of an Under Keel Clearance tool as well as numerous consultancy projects. For the last 2 years, Sébastien has been mostly working on MetOcean Solutions data infrastructure and is now spending most of his time working on a deep learning project aimed at nowcasting convective weather in New Zealand from satellite images.

 

Remote Sensing for Automated Lake Monitoring

Freshwater is essential to New Zealand’s economic, environmental, cultural and social well-being. The New Zealand government prescribes that overall freshwater quality within a region must be maintained or improved and it gives regional councils the authority and responsibility to manage and monitor the freshwaters of their jurisdictions. However, with 3820 lakes larger than 1 hectare in New Zealand and less than 2% of them monitored consistently, our knowledge of water quality states and trends is highly biased.

Satellite remote sensing can help to address this challenge by estimating important water quality attributes frequently and nationwide from space. Data from passive optical sensors have been used to infer chlorophyll a, suspended matter concentrations and water clarity, but the accuracy of these determinations is currently problematic for state and trend analysis. This is partly because the retrieval algorithms are tailored to a small number of study lakes and fail when applied across the diverse range of lake types found in New Zealand. We promote the measurement of water colour as a powerful and intuitive water quality attribute. Water colour is directly, albeit not simply, related to algae, tannin staining and suspended matter, it is meaningful to the general public as an aesthetic criterion of water quality and it can be measured reliably using a multitude of instruments ranging from satellite sensors to smartphone cameras.

In this presentation, we show measurement of lake water colour of 1486 lakes from four years of Landsat 8 OLI data. This unprecedented synoptic dataset provides a rich source of information to address fundamental environmental questions, and provides information for stakeholders to investigate lake-specific processes. We are working towards an automated data processing service from which subscribers can receive status updates of the colour of their lakes of interest about 6 to 20 times per year from Landsat 8 and more often from the Sentinel series of satellites.

 

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Dr Moritz Lehmann - Research Fellow, Environmental Research Institute, University of Waikato

Moritz holds a PhD from Dalhousie University in Halifax, Canada, and has been a Senior Research Fellow with the University of Waikato in Hamilton since December 2014. He is an interdisciplinary aquatic scientist with with a background in oceanography, marine biology, computer science, mathematics and statistics and has over ten years of experience in research and consulting. Moritz’ research interests include the remote sensing of water quality in inland and coastal waters, dynamic ecosystem modelling and statistical methods for environmental monitoring and prediction. In his current work, Moritz takes a New Zealand-wide approach to map water quality of over 3800 lakes using satellite remote sensing and a good deal of field work at fabulously beautiful sites.