title: Extent of seagrass in Tauranga Harbour: a comparison of satellite automated classification versus manual delineation of aerial imagery

authors: Shao, Zhanchao

abstract: This report outlines a comprehensive analysis of seagrass extent in Tauranga Harbour, New Zealand, using advanced remote sensing techniques. It compares two key methods: satellite-based supervised classification using Random Forest, and manual delineation via aerial photography. The research focuses on mapping the spatial and temporal changes in seagrass habitats, particularly the native species Zostera muelleri, from 1959 to 2024. Complementary to the satellite-based classification method, an easy-to-use graphical user interface (GUI) was developed, enabling users to efficiently access satellite imagery and generate detailed habitat maps.
The supervised classification using Random Forest proved effective for detecting seagrass habitats, achieving high accuracy (0.92 for Sentinel-2 and 0.88 for Landsat imagery). Despite occasional misclassifications, particularly in areas with high chlorophyll concentrations (i.e., the Tauranga Harbour sub-estuaries), the method provided a more time-efficient and scalable alternative to manual delineation. Aerial photography and manual mapping served as an important comparison but are less efficient in capturing less visible seagrass areas in deeper water or fragmented meadows.

text: Extent of seagrass in Tauranga Harbour: a comparison of satellite automated classification versus manual delineation of aerial imagery This report outlines a comprehensive analysis of seagrass extent in Tauranga Harbour, New Zealand, using advanced remote sensing techniques. It compares two key methods: satellite-based supervised classification using Random Forest, and manual delineation via aerial photography. The research focuses on mapping the spatial and temporal changes in seagrass habitats, particularly the native species Zostera muelleri, from 1959 to 2024. Complementary to the satellite-based classification method, an easy-to-use graphical user interface (GUI) was developed, enabling users to efficiently access satellite imagery and generate detailed habitat maps.
The supervised classification using Random Forest proved effective for detecting seagrass habitats, achieving high accuracy (0.92 for Sentinel-2 and 0.88 for Landsat imagery). Despite occasional misclassifications, particularly in areas with high chlorophyll concentrations (i.e., the Tauranga Harbour sub-estuaries), the method provided a more time-efficient and scalable alternative to manual delineation. Aerial photography and manual mapping served as an important comparison but are less efficient in capturing less visible seagrass areas in deeper water or fragmented meadows.

year: 2024-11-28

title: Investigation of intermittency in magnetohydrodynamics and solar wind turbulence: scale-dependent kurtosis

authors: Wan, Minping

subjects: magnetohydrodynamics (MHD)

abstract: The behavior of scale-dependent (or filtered) kurtosis is studied in the solar wind using magnetic field measurements from the ACE and Cluster spacecraft at 1 AU. It is also analyzed numerically with high-resolution magnetohydrodynamic spectral simulations. In each case the filtered kurtosis increases with wavenumber, implying the presence of coherent structures at the smallest scales. This phase coupling is related to intermittency in solar wind turbulence and the emergence of non-Gaussian statistics. However, it is inhibited by the presence of upstream waves and other phase-randomizing structures, which act to reduce the growth of kurtosis.

text: Investigation of intermittency in magnetohydrodynamics and solar wind turbulence: scale-dependent kurtosis The behavior of scale-dependent (or filtered) kurtosis is studied in the solar wind using magnetic field measurements from the ACE and Cluster spacecraft at 1 AU. It is also analyzed numerically with high-resolution magnetohydrodynamic spectral simulations. In each case the filtered kurtosis increases with wavenumber, implying the presence of coherent structures at the smallest scales. This phase coupling is related to intermittency in solar wind turbulence and the emergence of non-Gaussian statistics. However, it is inhibited by the presence of upstream waves and other phase-randomizing structures, which act to reduce the growth of kurtosis.

year: 2012

title: Pōwhiri process in mental health research

authors: McClintock, Kahu

subjects: indigenous mental health research

abstract: Within the health research context, indigenous people globally have a commitment to provide their own solutions. Māori, the indigenous people of Aotearoa (New Zealand) value the traditional Pōwhiri process of engagement and participation in mental health research. The practices and protocols within the Pōwhiri process (use in the Doctorate of Philosophy (2010) and Auckland University) are premised on the notion of respect and positive relationships between the tangata whenua (hosts or research participants) and manuwhiri (guests or researchers). This paper briefly describes the Pōwhiri process, which may be a model applicable to research with other indigenous cultures.

text: Pōwhiri process in mental health research Within the health research context, indigenous people globally have a commitment to provide their own solutions. Māori, the indigenous people of Aotearoa (New Zealand) value the traditional Pōwhiri process of engagement and participation in mental health research. The practices and protocols within the Pōwhiri process (use in the Doctorate of Philosophy (2010) and Auckland University) are premised on the notion of respect and positive relationships between the tangata whenua (hosts or research participants) and manuwhiri (guests or researchers). This paper briefly describes the Pōwhiri process, which may be a model applicable to research with other indigenous cultures.

year: 2010