title: Exploring interindividual running economy responses to advanced footwear technology shoes across a range of variables: A quantitative study

authors: Cumming, Christiaan

abstract: Abstract
In the past decade, the running landscape has changed due to advanced footwear technology (AFT) being imbedded in running shoes. While AFT shoes have been shown to improve running economy (RE) on average, little is known about the factors that explain the large interindividual variability in RE response. Therefore, this study aimed to investigate the interindividual variability in RE response to AFT and identify potential predictors of this variability using quantitative methods. This thesis considered participant characteristics, anthropometric measures, neuromuscular measures, and subjective perceptions as potential factors underpinning interindividual variability.
This thesis is separated into three chapters. Chapter One is a brief review on AFT, their components, and their influence on RE and performance, as well as the observed interindividual variability in AFT shoe responses and the factors proposed to mediate this variability. AFT shoes have been designed to improve RE and include thick lightweight resilient and compliant foams, stiff elements embedded in the foam, and curved shoe geometry. Research has explored how these components may contribute to RE improvements and has proposed various factors that may explain the interindividual variability, such as running speed, training level, sex, leg length, body mass, shoe size, and plantarflexion muscle-tendon unit properties. Comparing the characteristics of responders to non-responders and exploring relationships between these characteristics and RE responses can assist in identifying runners more likely to benefit from running in AFT.
Chapter Two presents an experimental study using a cross-sectional, repeated-measures design.  A heterogenous sample of sixty-four participants (32 males, 32 females) of varying running levels, experience, age, and anthropometric characteristics completed two laboratory sessions between two and seven days apart. The first included baseline information and participant characteristics for anthropometric, neuromuscular measures, and maximal oxygen uptake. The second session served as the experimental phase, during which RE variables were evaluated in the two different shoe conditions: Salomon S/Lab Phantasm 2 (AFT) and Salomon Aero Glide 2 (CONTROL). RE was measured over four 6-minute trials in an AFT and a CONTROL shoe, allocated in a randomised, crossover order. Descriptive statistics (means ± SD), inferential comparisons (paired samples t-tests, Chi square, and Fishers exact), and Pearson’s correlation coefficients were calculated to compare between responders and non-responders to AFT shoes and explain AFT shoe response. The mean improvement in RE (expressed in terms of oxygen consumption) was 4.13 ± 1.6% when wearing AFT compared to CONTROL shoes, with individual responses ranging from -2.62% to 11.01%. From all the variables collected, only gastrocnemius medialis (GM) stiffness normalised to leg length was significantly different (p = 0.046) between groups, with responders exhibiting greater GM stiffness (329.8 ± 36.6 N/m²) compared to non-responders (296.4 ± 47.3 N/m²). No other between-group differences were statistically significant. Two variables were significantly and moderately correlated to RE response, where greater navicular drop (r = 0.31, p = 0.012) and greater GM stiffness (normalised to leg length) (r = 0.35, p = 0.005) were linked to greater RE benefits from running in AFT shoes. Additionally greater gear ratio (r = 0.26, p = 0.040) and lower standing plantarflexion isometric strength (normalised to body weight) (r = -0.26, p = 0.041) displayed significant and small correlations with improvements in RE when running in AFT shoes. A multiple linear regression including standing plantarflexion isometric strength, navicular drop, gear ratio, and GM stiffness (normalised to leg length) explained 27% of the variance in our AFT RE responses (R² = 0.2731, adjusted R² = 0.223), with GM stiffness being the most important factor (B = 0.014, p = 0.015). 
Lastly, Chapter Three summarises the findings, strengths, limitations, and recommendations for future research. This research provides further insight into interindividual variability in RE responses to AFT, showing not all runners benefit equally from AFT shoes. Therefore, runners should be aware that they may not improve their RE via AFT, however, individuals with greater GM stiffness, navicular drop, and static ankle gear ratio, and with lower standing plantarflexion isometric strength may benefit to a greater extent from AFT shoe wear. These factors may help guide more personalised footwear selection and prescription. Future research should investigate whether training interventions that modify these characteristics can enhance responses to AFT footwear and examine how other biomechanical variables, such as foot strike patterns or flight times, may interact with RE responses.

text: Exploring interindividual running economy responses to advanced footwear technology shoes across a range of variables: A quantitative study Abstract
In the past decade, the running landscape has changed due to advanced footwear technology (AFT) being imbedded in running shoes. While AFT shoes have been shown to improve running economy (RE) on average, little is known about the factors that explain the large interindividual variability in RE response. Therefore, this study aimed to investigate the interindividual variability in RE response to AFT and identify potential predictors of this variability using quantitative methods. This thesis considered participant characteristics, anthropometric measures, neuromuscular measures, and subjective perceptions as potential factors underpinning interindividual variability.
This thesis is separated into three chapters. Chapter One is a brief review on AFT, their components, and their influence on RE and performance, as well as the observed interindividual variability in AFT shoe responses and the factors proposed to mediate this variability. AFT shoes have been designed to improve RE and include thick lightweight resilient and compliant foams, stiff elements embedded in the foam, and curved shoe geometry. Research has explored how these components may contribute to RE improvements and has proposed various factors that may explain the interindividual variability, such as running speed, training level, sex, leg length, body mass, shoe size, and plantarflexion muscle-tendon unit properties. Comparing the characteristics of responders to non-responders and exploring relationships between these characteristics and RE responses can assist in identifying runners more likely to benefit from running in AFT.
Chapter Two presents an experimental study using a cross-sectional, repeated-measures design.  A heterogenous sample of sixty-four participants (32 males, 32 females) of varying running levels, experience, age, and anthropometric characteristics completed two laboratory sessions between two and seven days apart. The first included baseline information and participant characteristics for anthropometric, neuromuscular measures, and maximal oxygen uptake. The second session served as the experimental phase, during which RE variables were evaluated in the two different shoe conditions: Salomon S/Lab Phantasm 2 (AFT) and Salomon Aero Glide 2 (CONTROL). RE was measured over four 6-minute trials in an AFT and a CONTROL shoe, allocated in a randomised, crossover order. Descriptive statistics (means ± SD), inferential comparisons (paired samples t-tests, Chi square, and Fishers exact), and Pearson’s correlation coefficients were calculated to compare between responders and non-responders to AFT shoes and explain AFT shoe response. The mean improvement in RE (expressed in terms of oxygen consumption) was 4.13 ± 1.6% when wearing AFT compared to CONTROL shoes, with individual responses ranging from -2.62% to 11.01%. From all the variables collected, only gastrocnemius medialis (GM) stiffness normalised to leg length was significantly different (p = 0.046) between groups, with responders exhibiting greater GM stiffness (329.8 ± 36.6 N/m²) compared to non-responders (296.4 ± 47.3 N/m²). No other between-group differences were statistically significant. Two variables were significantly and moderately correlated to RE response, where greater navicular drop (r = 0.31, p = 0.012) and greater GM stiffness (normalised to leg length) (r = 0.35, p = 0.005) were linked to greater RE benefits from running in AFT shoes. Additionally greater gear ratio (r = 0.26, p = 0.040) and lower standing plantarflexion isometric strength (normalised to body weight) (r = -0.26, p = 0.041) displayed significant and small correlations with improvements in RE when running in AFT shoes. A multiple linear regression including standing plantarflexion isometric strength, navicular drop, gear ratio, and GM stiffness (normalised to leg length) explained 27% of the variance in our AFT RE responses (R² = 0.2731, adjusted R² = 0.223), with GM stiffness being the most important factor (B = 0.014, p = 0.015). 
Lastly, Chapter Three summarises the findings, strengths, limitations, and recommendations for future research. This research provides further insight into interindividual variability in RE responses to AFT, showing not all runners benefit equally from AFT shoes. Therefore, runners should be aware that they may not improve their RE via AFT, however, individuals with greater GM stiffness, navicular drop, and static ankle gear ratio, and with lower standing plantarflexion isometric strength may benefit to a greater extent from AFT shoe wear. These factors may help guide more personalised footwear selection and prescription. Future research should investigate whether training interventions that modify these characteristics can enhance responses to AFT footwear and examine how other biomechanical variables, such as foot strike patterns or flight times, may interact with RE responses.

year: 2025

title: Forest change mapping using remote sensing and Google Earth Engine

authors: Walawe Durage, Kalpanie Vimarshana Nandasena

subjects: Google Earth Engine

abstract: With advancements in data sources, software, and image analysis techniques, remote sensing has become an efficient method for forest classification. However, access to this technology has been limited for developing countries due to the high cost of high resolution images and analysis software. A potential solution is that NASA and the European Space Agency provide free access to mid-low resolution satellite images. In addition, Google Earth Engine (GEE), a free cloud-based geospatial analysis platform, has allowed researchers from developing countries to conduct research without relying on costly remote sensing software. This study evaluates the suitability of the freely available images and the GEE platform for different forest management applications in Sri Lanka. The research focused on three different scenarios in vegetation mapping: identifying home gardens, monitoring invasive pines, and forest cover mapping in a tropical montane region.
Home garden is an agroforestry class seen in tropical countries often overshadowed by global land cover classifications. This study used a random forest classification algorithm to classify the home garden, utilizing terrain data and Sentinel-2A images as the dataset. The results confirmed that the red band of Sentinel-2 and textural metrics derived from grey-level co-occurrence matrix analysis are effective in identifying home gardens from other forestry classes.
Monitoring the spread of invasive pines is important for forest management in Sri Lanka. This study used Landsat satellite images for the years 2000 and 2021 to detect the exotic Pinus caribaea species invasion of native habitats. By using an image difference technique, this research identified that the extent of these invasive pines had an overall decline over the past 21 years. Further, results showed that broadleaved forests and grasslands located within 100m of the pine plantations’ borders were susceptible to invasion.

In tropical regions, analysing forests can be difficult due to cloud cover. This research also focused on methods to enhance classification accuracy using multiple data sources: Sentinel-1, Sentinel-2, PALSAR-2, and elevation. Six different methods were tested. It was found that combining radar data with optical and topographical data improved vegetation classification accuracy. In addition, feature importance analysis using the random forest algorithm indicated that radar data plays a significant role in tropical land use classification.
The three case studies used in this research demonstrate that GEE and the freely available mid-low resolution satellite images make the application of remote sensing in Sri Lanka a viable solution for the monitoring and mapping of landcover.

text: Forest change mapping using remote sensing and Google Earth Engine With advancements in data sources, software, and image analysis techniques, remote sensing has become an efficient method for forest classification. However, access to this technology has been limited for developing countries due to the high cost of high resolution images and analysis software. A potential solution is that NASA and the European Space Agency provide free access to mid-low resolution satellite images. In addition, Google Earth Engine (GEE), a free cloud-based geospatial analysis platform, has allowed researchers from developing countries to conduct research without relying on costly remote sensing software. This study evaluates the suitability of the freely available images and the GEE platform for different forest management applications in Sri Lanka. The research focused on three different scenarios in vegetation mapping: identifying home gardens, monitoring invasive pines, and forest cover mapping in a tropical montane region.
Home garden is an agroforestry class seen in tropical countries often overshadowed by global land cover classifications. This study used a random forest classification algorithm to classify the home garden, utilizing terrain data and Sentinel-2A images as the dataset. The results confirmed that the red band of Sentinel-2 and textural metrics derived from grey-level co-occurrence matrix analysis are effective in identifying home gardens from other forestry classes.
Monitoring the spread of invasive pines is important for forest management in Sri Lanka. This study used Landsat satellite images for the years 2000 and 2021 to detect the exotic Pinus caribaea species invasion of native habitats. By using an image difference technique, this research identified that the extent of these invasive pines had an overall decline over the past 21 years. Further, results showed that broadleaved forests and grasslands located within 100m of the pine plantations’ borders were susceptible to invasion.

In tropical regions, analysing forests can be difficult due to cloud cover. This research also focused on methods to enhance classification accuracy using multiple data sources: Sentinel-1, Sentinel-2, PALSAR-2, and elevation. Six different methods were tested. It was found that combining radar data with optical and topographical data improved vegetation classification accuracy. In addition, feature importance analysis using the random forest algorithm indicated that radar data plays a significant role in tropical land use classification.
The three case studies used in this research demonstrate that GEE and the freely available mid-low resolution satellite images make the application of remote sensing in Sri Lanka a viable solution for the monitoring and mapping of landcover.

year: 2023

title: Current state of the Rotorua Lakes

authors: Hamilton, David P.

abstract: The Rotorua Te Arawa Lakes’ programme of restoration has arguably been the most ambitious and effective of any for a group of lakes around the world. It has been characterised by willingness to ‘try things’, to be guided closely by scientific input, and to
now have excellent structures for monitoring and implementation of actions. Still, major challenges remain. One of these is the potential for a sense of complacency, particularly when some lakes have responded extremely positively to in-lake treatments (e.g. Rotorua) or major one-off actions (e.g. Rotoiti). It is essential that these improvements in lake water quality, some of which may not be able to be maintained indefinitely in their current mode, not delay further catchment management actions.
Another challenge is exotic oxygen weeds, particularly where it is difficult to harvest large accumulations. The final challenge relates to climate. Recent years have been characterised by droughts and intense rainfall events that challenge land management practices. Further, surface water temperatures in the lakes in 2015 have been greater than at any time in the past. If these changes are symptomatic of a future climate, then there will need to be greater effort put into building resilience in the lakes and their catchments.

text: Current state of the Rotorua Lakes The Rotorua Te Arawa Lakes’ programme of restoration has arguably been the most ambitious and effective of any for a group of lakes around the world. It has been characterised by willingness to ‘try things’, to be guided closely by scientific input, and to
now have excellent structures for monitoring and implementation of actions. Still, major challenges remain. One of these is the potential for a sense of complacency, particularly when some lakes have responded extremely positively to in-lake treatments (e.g. Rotorua) or major one-off actions (e.g. Rotoiti). It is essential that these improvements in lake water quality, some of which may not be able to be maintained indefinitely in their current mode, not delay further catchment management actions.
Another challenge is exotic oxygen weeds, particularly where it is difficult to harvest large accumulations. The final challenge relates to climate. Recent years have been characterised by droughts and intense rainfall events that challenge land management practices. Further, surface water temperatures in the lakes in 2015 have been greater than at any time in the past. If these changes are symptomatic of a future climate, then there will need to be greater effort put into building resilience in the lakes and their catchments.

year: 2015