title: Determining estuarine seagrass density measures from low altitude multispectral imagery flown by remotely piloted aircraft

authors: Martin, Ross David

subjects: Seagrass

abstract: Seagrass is the subject of significant conservation research. Seagrass is ecologically important and of significant value to human interests. Many seagrass species are thought to be in decline.  Degradation of seagrass populations are linked to anthropogenic environmental issues. Effective management requires robust monitoring that is affordable at large scale. Remote sensing methods using satellite and aircraft imagery enable mapping of seagrass populations at landscape scale. 
Aerial monitoring of a seagrass population can require imagery of high spatial and/or spectral resolution for successful feature extraction across all levels of seagrass density. Remotely piloted aircraft (RPA) can operate close to the ground under precise flight control enabling repeated surveys in high detail with accurate revisit-positioning.
This study evaluates a method for assessing intertidal estuarine seagrass (Zostera muelleri) presence/absence and coverage density using multispectral imagery collected by a remotely piloted aircraft (RPA) flying at 30 m above the estuary surface (2.7 cm ground sampling distance). The research was conducted at Wharekawa Harbour on the eastern coast of the Coromandel Peninsula, North Island, New Zealand.
Differential drainage of residual ebb waters from the surface of an estuary at low tide creates a mosaic of drying sediment, draining surface and static shallow pooling that has potential to interfere with spectral observations. The field surveys demonstrated that despite minor shifts in the spectral coordinates of seagrass and other surface material, there was no apparent difference in image classification outcome from the time of bulk tidal water clearance to the time of returning tidal flood.
For the survey specification tested, classification accuracy increased with decreasing segmentation scale. Pixel-based image analysis (PBIA) achieved higher classification accuracy than object-based image analysis (OBIA) assessed at a range of segmentation scales. Contaminating objects such as shells and detritus can become aggregated within polygon objects when OBIA is applied but remain as isolated objects under PBIA at this image resolution. There was clear separability of spectra for seagrass and sediment, but shell and detritus confounded the classification of seagrass density in some situations.  High density seagrass was distinct from sediment, but classification error arose for sparse seagrass.
Three classifiers (linear discriminant analysis, support vector machine and random forest) and three feature selection options (no selection, collinearity reduction and recursive feature elimination) were assessed for effect on classification performance. The random forest classifier yielded the highest classification accuracy, with no accuracy benefit gained from collinearity reduction or recursive feature elimination. Spectral vegetation indices and texture layers substantially improved classification accuracy. Object geometry made a negligible contribution to classification accuracy using mean-shift segmentation at this image-scale.
The method achieved classification of seagrass density with up to 84% accuracy on a three-tier end-member class scale (low, medium, and high density) when using training data formed using visual interpretation of ground reference photography, and up to 93% accuracy using precisely measured seagrass leaf-area. Visual interpretation agreed with precisely measured seagrass leaf area 88% of the time with some misattribution at mid-density. Visual interpretation was substantially faster to apply than measuring the leaf area. A decile class scale for seagrass density correlated with actual leaf area measures more than the three-tier scale, however, was less accurate for absolute class attribution.
The research demonstrates that seagrass feature extraction from RPA-flown imagery is a feasible and repeatable option for seagrass population monitoring and environmental reporting. Further calibration is required for whole- and multi-estuary application.

text: Determining estuarine seagrass density measures from low altitude multispectral imagery flown by remotely piloted aircraft Seagrass is the subject of significant conservation research. Seagrass is ecologically important and of significant value to human interests. Many seagrass species are thought to be in decline.  Degradation of seagrass populations are linked to anthropogenic environmental issues. Effective management requires robust monitoring that is affordable at large scale. Remote sensing methods using satellite and aircraft imagery enable mapping of seagrass populations at landscape scale. 
Aerial monitoring of a seagrass population can require imagery of high spatial and/or spectral resolution for successful feature extraction across all levels of seagrass density. Remotely piloted aircraft (RPA) can operate close to the ground under precise flight control enabling repeated surveys in high detail with accurate revisit-positioning.
This study evaluates a method for assessing intertidal estuarine seagrass (Zostera muelleri) presence/absence and coverage density using multispectral imagery collected by a remotely piloted aircraft (RPA) flying at 30 m above the estuary surface (2.7 cm ground sampling distance). The research was conducted at Wharekawa Harbour on the eastern coast of the Coromandel Peninsula, North Island, New Zealand.
Differential drainage of residual ebb waters from the surface of an estuary at low tide creates a mosaic of drying sediment, draining surface and static shallow pooling that has potential to interfere with spectral observations. The field surveys demonstrated that despite minor shifts in the spectral coordinates of seagrass and other surface material, there was no apparent difference in image classification outcome from the time of bulk tidal water clearance to the time of returning tidal flood.
For the survey specification tested, classification accuracy increased with decreasing segmentation scale. Pixel-based image analysis (PBIA) achieved higher classification accuracy than object-based image analysis (OBIA) assessed at a range of segmentation scales. Contaminating objects such as shells and detritus can become aggregated within polygon objects when OBIA is applied but remain as isolated objects under PBIA at this image resolution. There was clear separability of spectra for seagrass and sediment, but shell and detritus confounded the classification of seagrass density in some situations.  High density seagrass was distinct from sediment, but classification error arose for sparse seagrass.
Three classifiers (linear discriminant analysis, support vector machine and random forest) and three feature selection options (no selection, collinearity reduction and recursive feature elimination) were assessed for effect on classification performance. The random forest classifier yielded the highest classification accuracy, with no accuracy benefit gained from collinearity reduction or recursive feature elimination. Spectral vegetation indices and texture layers substantially improved classification accuracy. Object geometry made a negligible contribution to classification accuracy using mean-shift segmentation at this image-scale.
The method achieved classification of seagrass density with up to 84% accuracy on a three-tier end-member class scale (low, medium, and high density) when using training data formed using visual interpretation of ground reference photography, and up to 93% accuracy using precisely measured seagrass leaf-area. Visual interpretation agreed with precisely measured seagrass leaf area 88% of the time with some misattribution at mid-density. Visual interpretation was substantially faster to apply than measuring the leaf area. A decile class scale for seagrass density correlated with actual leaf area measures more than the three-tier scale, however, was less accurate for absolute class attribution.
The research demonstrates that seagrass feature extraction from RPA-flown imagery is a feasible and repeatable option for seagrass population monitoring and environmental reporting. Further calibration is required for whole- and multi-estuary application.

year: 2020

title: Digital competencies of high school mathematics teachers in Pakistan

authors: Jafri, Mairaj

abstract: The dynamic demands of the contemporary educational landscape, which includes a variety of digital tools and resources, require teachers to develop digital competencies. This need is particularly pertinent for mathematics teachers in developing countries like Pakistan, where there is a requirement to bridge the digital divide and equip teachers with the knowledge and skills to integrate digital resources into their teaching practices. Prior research has acknowledged the importance of integrating digital resources in education; however, there is limited research on the challenges and opportunities that high school mathematics teachers encounter when using digital resources in resource-constrained environments like Pakistan.
This study aimed to investigate the digital competencies of high school mathematics teachers in Pakistan, focusing on their knowledge, beliefs, practices, and experiences in integrating digital resources into mathematics teaching and learning. To achieve this aim, the study adapted the “Digital Competencies for Teaching Mathematics with Technology” (DCTMT) framework. Employing a mixed-methods explanatory sequential design, the study was divided into two phases for data collection. In Phase 1, quantitative data were collected through an online survey, which received a total of 306 responses. I analysed the survey data using descriptive (Mean, Mode, Median, and Standard Deviation) and inferential (intra- and inter-construct Spearman’s rho (⍴) correlation tests) statistics. To further understand and explain important quantitative results, semi-structured interviews were conducted in Phase 2 with six (Phase 1) teachers. I analysed the qualitative data using pre-identified themes and sub-themes based on the constructs of the DCTMT framework.
The results of both phases indicated that teachers held firm beliefs about various aspects of mathematics education. Teachers expressed strong beliefs about pedagogical practices and held positive beliefs about the importance of digital resources for teaching and learning mathematics. Correlations were observed between beliefs, teachers' reported ability to create videos, knowledge of dynamic graphing software (DGS) and equation editors, and participation in professional training. The findings revealed that most teachers possessed some level of digital competency. Teachers predominantly relied on videos and graphics, indicating potential bias and a gap in their professional development and training. They lacked access to (particularly at school) and possessed a weak knowledge of mathematics-specific digital resources like Dynamic Graphing Software (DGS). Other factors, such as lack of resources, inadequate formal training, and limited professional development opportunities, hindered their ability to integrate digital resources into their teaching and learning of mathematics. However, the results indicated that teachers could overcome some of these challenges through resilience and self-learning initiatives.
The study findings suggest that equipping teachers with appropriate resources and targeted professional development could enhance their digital competencies. This would consequently promote equitable and diverse use of digital resources in mathematics education. Within the confines of resource-constrained environments, these findings support for nurturing teachers' resilience and cultivating a self-learning attitude among them. Teachers who equip themselves with digital skills receive training and have the confidence to integrate digital resources to develop digital competencies, irrespective of resource constraints.
This thesis contributes to the understanding of high school mathematics teachers' digital competencies in Pakistan and indicates the opportunities and obstacles they encounter while using digital resources. This research inquiry provides empirical evidence for the modified DCTMT framework and reveals significant interconnections between the five constructs of the framework. The study reveals critical insights into the intricate relationship between beliefs, access to resources, and competencies in utilizing digital tools for mathematics education. This thesis establishes a compelling link between training, self-learning, teachers' resilience, and their digital competencies, highlighting the dynamic interplay that shapes mathematics teachers' digital competencies. This thesis offers implications for teachers’ professional development, curriculum design, and policy formulation. It emphasizes the importance of supporting teachers with the resources and knowledge to integrate digital resources and enhance mathematics education in resource-constrained contexts.

text: Digital competencies of high school mathematics teachers in Pakistan The dynamic demands of the contemporary educational landscape, which includes a variety of digital tools and resources, require teachers to develop digital competencies. This need is particularly pertinent for mathematics teachers in developing countries like Pakistan, where there is a requirement to bridge the digital divide and equip teachers with the knowledge and skills to integrate digital resources into their teaching practices. Prior research has acknowledged the importance of integrating digital resources in education; however, there is limited research on the challenges and opportunities that high school mathematics teachers encounter when using digital resources in resource-constrained environments like Pakistan.
This study aimed to investigate the digital competencies of high school mathematics teachers in Pakistan, focusing on their knowledge, beliefs, practices, and experiences in integrating digital resources into mathematics teaching and learning. To achieve this aim, the study adapted the “Digital Competencies for Teaching Mathematics with Technology” (DCTMT) framework. Employing a mixed-methods explanatory sequential design, the study was divided into two phases for data collection. In Phase 1, quantitative data were collected through an online survey, which received a total of 306 responses. I analysed the survey data using descriptive (Mean, Mode, Median, and Standard Deviation) and inferential (intra- and inter-construct Spearman’s rho (⍴) correlation tests) statistics. To further understand and explain important quantitative results, semi-structured interviews were conducted in Phase 2 with six (Phase 1) teachers. I analysed the qualitative data using pre-identified themes and sub-themes based on the constructs of the DCTMT framework.
The results of both phases indicated that teachers held firm beliefs about various aspects of mathematics education. Teachers expressed strong beliefs about pedagogical practices and held positive beliefs about the importance of digital resources for teaching and learning mathematics. Correlations were observed between beliefs, teachers' reported ability to create videos, knowledge of dynamic graphing software (DGS) and equation editors, and participation in professional training. The findings revealed that most teachers possessed some level of digital competency. Teachers predominantly relied on videos and graphics, indicating potential bias and a gap in their professional development and training. They lacked access to (particularly at school) and possessed a weak knowledge of mathematics-specific digital resources like Dynamic Graphing Software (DGS). Other factors, such as lack of resources, inadequate formal training, and limited professional development opportunities, hindered their ability to integrate digital resources into their teaching and learning of mathematics. However, the results indicated that teachers could overcome some of these challenges through resilience and self-learning initiatives.
The study findings suggest that equipping teachers with appropriate resources and targeted professional development could enhance their digital competencies. This would consequently promote equitable and diverse use of digital resources in mathematics education. Within the confines of resource-constrained environments, these findings support for nurturing teachers' resilience and cultivating a self-learning attitude among them. Teachers who equip themselves with digital skills receive training and have the confidence to integrate digital resources to develop digital competencies, irrespective of resource constraints.
This thesis contributes to the understanding of high school mathematics teachers' digital competencies in Pakistan and indicates the opportunities and obstacles they encounter while using digital resources. This research inquiry provides empirical evidence for the modified DCTMT framework and reveals significant interconnections between the five constructs of the framework. The study reveals critical insights into the intricate relationship between beliefs, access to resources, and competencies in utilizing digital tools for mathematics education. This thesis establishes a compelling link between training, self-learning, teachers' resilience, and their digital competencies, highlighting the dynamic interplay that shapes mathematics teachers' digital competencies. This thesis offers implications for teachers’ professional development, curriculum design, and policy formulation. It emphasizes the importance of supporting teachers with the resources and knowledge to integrate digital resources and enhance mathematics education in resource-constrained contexts.

year: 2024-07-15

title: Rising demand for health care: The sustainability of community general practice in the Waikato

authors: Amey, Janet Heather

subjects: General practice

abstract: Community general practice is the cornerstone of New Zealand’s health system, providing first contact health care, care coordination and acting as gatekeeper to expensive hospital services. An ageing population now brings increasing demand for the care provided in general practice, with chronic conditions a major contributing factor. This rising demand, alongside limited workforce capacity will seriously test general practice sustainability. 

These evolving and multifaceted challenges are within the context of long-standing health access and outcome inequalities, particularly for Māori (and more recently the Pacific population) compared with Pākehā. The pursuit of equity is inherent in all health sector strategies, but any meaningful improvement will necessitate wide-ranging reform of current planning, funding and service delivery pathways across traditional sector boundaries.

The sustainability of general practice is about the sustainability and efficiency of the entire health system. To better measure the contribution of general practice care to the system, and improve demand projections, an expanded service use measure was developed, combining services of a general practice nature from Emergency Department and Accident & Medical settings with services delivered in community general practice.

Drawing on approaches from demography, epidemiology and health services research, linked demographic and health administrative data were used to undertake a retrospective, observational study of service use for 235,666 people enrolled with the Pinnacle Midlands Health Network in 2013/14. Using the new expanded measure, service use levels at a locality level were established by age, gender, ethnic group, chronic condition status, practice funding model, high needs status, income and geography of residence.

Significant variation was found in annual average consults (1.0 to 13.4 consults in 2013/14). Statistical analysis identified age, chronic conditions and gender as the key demand drivers responsible for such variation, with regional level results masking significant spatial variation. Where the cost of care was lower, people used a higher level of services in the enrolled practice setting and a lower level outside of it, suggesting the importance of affordable care. Māori and Pacific used significantly fewer services than Pākehā although there was substantial sub-regional variation. Using the expanded measure, the vast majority of care was delivered in the enrolled setting, including for those with chronic conditions.

Demand projections, based on the expanded measure of general practice, out to 2038 show the uneven geography of future demand due to disordered cohort flows and sub-regional population contexts. Overall, demand for services is projected to rise by 34 per cent to almost two million consults across the Waikato District Health Board catchment, with this driven predominantly by services for those aged 65+ years (or 45+ years in Hamilton City, Waikato and Waipa Districts).

Models of care are being transformed as general practices and Primary Health Organisations look to the future. Reorganisation of work roles, improved use of health information and use of emerging health technologies will be required to re-configure general practice in preparation for an ageing future, and to eliminate recalcitrant health inequalities. Real and inclusive collaboration across traditional system boundaries is perhaps the greatest challenge to general practice sustainability.

text: Rising demand for health care: The sustainability of community general practice in the Waikato Community general practice is the cornerstone of New Zealand’s health system, providing first contact health care, care coordination and acting as gatekeeper to expensive hospital services. An ageing population now brings increasing demand for the care provided in general practice, with chronic conditions a major contributing factor. This rising demand, alongside limited workforce capacity will seriously test general practice sustainability. 

These evolving and multifaceted challenges are within the context of long-standing health access and outcome inequalities, particularly for Māori (and more recently the Pacific population) compared with Pākehā. The pursuit of equity is inherent in all health sector strategies, but any meaningful improvement will necessitate wide-ranging reform of current planning, funding and service delivery pathways across traditional sector boundaries.

The sustainability of general practice is about the sustainability and efficiency of the entire health system. To better measure the contribution of general practice care to the system, and improve demand projections, an expanded service use measure was developed, combining services of a general practice nature from Emergency Department and Accident & Medical settings with services delivered in community general practice.

Drawing on approaches from demography, epidemiology and health services research, linked demographic and health administrative data were used to undertake a retrospective, observational study of service use for 235,666 people enrolled with the Pinnacle Midlands Health Network in 2013/14. Using the new expanded measure, service use levels at a locality level were established by age, gender, ethnic group, chronic condition status, practice funding model, high needs status, income and geography of residence.

Significant variation was found in annual average consults (1.0 to 13.4 consults in 2013/14). Statistical analysis identified age, chronic conditions and gender as the key demand drivers responsible for such variation, with regional level results masking significant spatial variation. Where the cost of care was lower, people used a higher level of services in the enrolled practice setting and a lower level outside of it, suggesting the importance of affordable care. Māori and Pacific used significantly fewer services than Pākehā although there was substantial sub-regional variation. Using the expanded measure, the vast majority of care was delivered in the enrolled setting, including for those with chronic conditions.

Demand projections, based on the expanded measure of general practice, out to 2038 show the uneven geography of future demand due to disordered cohort flows and sub-regional population contexts. Overall, demand for services is projected to rise by 34 per cent to almost two million consults across the Waikato District Health Board catchment, with this driven predominantly by services for those aged 65+ years (or 45+ years in Hamilton City, Waikato and Waipa Districts).

Models of care are being transformed as general practices and Primary Health Organisations look to the future. Reorganisation of work roles, improved use of health information and use of emerging health technologies will be required to re-configure general practice in preparation for an ageing future, and to eliminate recalcitrant health inequalities. Real and inclusive collaboration across traditional system boundaries is perhaps the greatest challenge to general practice sustainability.

year: 2018