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2021 Annual progress update

The keystone technology for Forest Flows, SimSAR L- and P-Band synthetic aperture radar (SAR), has arrived in New Zealand from its USA partner Artemis, and is operational. SimSAR is a novel remote sensing technology and the keystone technology provides the programme with the ability to measure soil moisture from an aircraft at a fine spatial resolution (10-25 m) to a depth of 1.5 m. This technology provides New Zealand for the first time, the ability to map accurately spatially variation in soil moisture (thus, soil texture and depth) in planted forests, the ability to precisely scale up terrestrial measurements, and identify key hydrological fluxes in planted forests over time. As faras we are aware, New Zealand is the first in the world to use this technology independently outside the USA. Once the frequencies are approved by MBIE, we will start our remote sensing campaign mapping soil moisture at our primary research sites.

Key to measuring spatial and temporal variation across each of the five primary research sites is Scion’s wireless IOT sensor network, which measures tree growth and water use, and soil water fluxes in real time. Over the last year, the New Zealand R&D company INFACT, has designed wireless dataloggers, called Flowlab, to meet the specifications of the programme. We have successfully tested Flowlab prototypes in the field and now 220 Flowlab dataloggers can be manufactured by the New Zealand company Quick Circuit Ltd. Flowlab’s low cost, high reliability, and novel wireless meshed network makes it possible to collect and transmit data from the large number of plots per site. Once activated, 57,000 observations are collected from 200 instruments daily from each site daily. In total, 300,000+ daily observations will be collected from the five sites. Worldwide, there are no other dataloggers that could meet the programme’s specifications, nor operate in a difficult forest environment. The rollout of Flowlab dataloggers and activation of the IOT sensor networks is on track for Year 3.

To manage the 300,000+ daily observations, a big data pipeline was developed from scratch. A New Zealand first, Scion has developed the Forest Flows Big Data Kafka Pipeline that can not only seamlessly stream clean, summarise, and store big data arriving in real-time from the forest. The cloud storage of terrestrial data will make it easier for national and international collaborators to access and use the data, as well as facilitate collaboration.

Forest Flows Big Data Kafka Pipeline is seen as an exemplar for streaming and managing big data by the University of Waikato’s MBIE Time-Evolving Data Science/Artificial Intelligence for Advanced Open Environmental Science (TAIAO) data science programme. It also provides an example of sharing data between institutions for the pan-CRI National Environmental Data Centre initiative.

The development of the biophysical model, CABALA-W, for the programme has attracted interest in Australia. CABALA-W will be able to accurately predict tree water use, carbon sequestration, and thus water use efficiency of carbon forests. This ability is highly useful for Australia’s carbon forestry sector and Australia’s Carbon Credit Units scheme. The strong interest from Australia’s forest carbon sector is an indicator of the potential impact of Forest Flows on NZ’s ETS scheme.


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