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Tassel counts provide valuable information related to flowering and yield prediction in maize, but are expensive and time-consuming to acquire via traditional manual approaches. High-resolution RGB imagery acquired by unmanned aerial vehicles (UAVs), coupled with advanced machine learning approaches, including deep learning (DL), provides a new capability for monitoring flowering. In this article, three state-of-the-art DL techniques, CenterNet based on point annotation, task-aware spatial disentanglement (TSD), and detecting objects with recursive feature pyramids and switchable atrous convolution (DetectoRS) based on bounding box annotation, are modified to improve their performance for this application and evaluated for tassel detection relative to Tasselnetv2+. The dataset for the experiments is comprised of RGB images of maize tassels from plant breeding experiments, which vary in size, complexity, and overlap. Results show that the point annotations are more accurate and simpler to acquire than the bounding boxes, and bounding box-based approaches are more sensitive to the size of the bounding boxes and background than point-based approaches. Overall, CenterNet has high accuracy in comparison to the other techniques, but DetectoRS can better detect early-stage tassels. The results for these experiments were more robust than Tasselnetv2+, which is sensitive to the number of tassels in the image.

In recent days, phenotyping of various crops is gaining widespread popularity due to its ability to recognize variations in the effects of different genotypes of a particular crop in terms of its growth, yield, biomass, and so on. Such an application requires extensive data collection and analysis with a high spatial and temporal resolution, which can be attained using multiple sensors onboard Unmanned Aerial Vehicles (UAVs). In this study, we focus on harnessing information from a variety of sensors, such as RGB cameras, LiDAR units, and push-broom hyperspectral sensors – Short-wave Infrared (SWIR) and Visible Near Infrared (VNIR). The major challenge that needs to be overcome in this regard is to ensure an accurate integration of information captured across several days from the different sensor modalities. Moreover, the payload constraint for UAVs restrain us from mounting all the sensors simultaneously during a single flight mission, thus entailing the need for data capture from different sensors mounted on separate platforms that are flown individually over the agricultural field of interest. The first step towards integration of different data modalities is the generation of georeferenced products from each of the flight missions, which is accomplished with the help of Global Navigation Satellite Systems (GNSS) and Inertial Navigation Systems (INS) mounted on the UAVs that are time-synchronized with the onboard LiDAR units, cameras and/or hyperspectral sensors. Furthermore, an accurate georeferencing is achieved by developing robust calibration approaches dedicated towards accurate estimation of mounting parameters of the involved sensors. Finally, the geometric and spectral characteristics, such as canopy cover and leaf count, derived from the different sensors are used to devise a model to analyze the phenotypic traits of crops. The preliminary results indicate that the proposed calibration techniques can attain an accuracy of upto 3 cm.

Physical inactivity is estimated to be the fourth leading cause of global mortality. Strategies to increase physical activity (PA) increasingly emphasize environmental and policy changes including the modification of neighborhood environments to promote walking and other forms of healthy activity. Open Streets (OS) initiatives, an important and growing strategy to modify neighborhood environments for PA, create temporary parks for recreational activity by closing streets to motor vehicle traffic, thereby offering health and community building benefits. We used the Stanford Neighborhood Discovery Tool (DT)—photo/voice software on a tablet—to train neighborhood residents to act as “citizen scientist” observers of the local built environment on a non-event day and during an OS initiative. The purposes of this project were as follows: (1) to assess adult residents’ perceptions of neighborhood characteristics of the OS initiative in three socioeconomically diverse sites and (2) to test the DT for use in three international urban settings with OS initiatives; Bogota, Colombia; San Francisco, USA; and Temuco, Chile, among a multigenerational, multiethnic sample of adults including, for the first time, a vulnerable population of homeless adults (Bogota). Using the DT, participants walked an OS route taking photos and recording reasons for the photos, then completed a 25-item demographic/environmental observation survey and a 16-item Reflection Survey on perceived environmental changes. A total of 18 themes were reported by participants with areas of overlapping themes (e.g., Community and Social Connectedness) and areas where a single site reported a theme (e.g., Social Isolation in Older Adults). Ten of the 18 themes were identified by at least two sites including “Bike Resources” and “Services”, indicating the value of programming at OS initiatives. The themes of “Festive Environment” and “Family Friendly Environment” reflect the quality of the overall environment for participants. Four themes (Community and Social Connectedness, Family Friendly Environment, PA, and Safety) were reported by all sites. Three of the four unifying themes were also ranked among the highest reported categories of “seemed better” on the Reflection Survey (Ease of Walking, Overall Safety of Neighborhood, and Friendliness of Environment), providing additional confirmation of the shared experience of social, health, and psychological benefits from OS initiatives. OS initiatives offer a global strategy for increasing neighborhood opportunities for PA and a potential site for training citizen scientists to document environmental influences on PA.

Community-based physical activity (PA) programs in Latin America have been recognized because of the use of available environmental resources to offer PA classes. Yet, the evaluation of programs focused on PA classes involving dancing in public spaces is limited. The aim of this study was to assess the physical activity levels, park use, and the contextual characteristics of public parks with and without the Recreovía in Bogotá in Colombia. Al Ritmo de las Comunidades is a natural experiment conducted in nine parks (3 parks implementing new Recreovías, 3 control parks and 3 parks with existing Recreovías) during 2013. We used the System for Observing Play and Recreation in Communities to evaluate park use (gender, age, and physical activity level) and target areas. A total of 4925 people were observed during 702 observation visits to parks. The percentage of women was higher in parks with Recreovía, compared to parks without Recreovía (53% vs. 40% vs. 33%; p < 0.001). Women using parks with Recreovía compared to women in parks without Recreovía were less likely to be sedentary (25% vs. 39%; p < 0.0001) and more likely to engage in moderate-to-vigorous activity (75% vs. 61%; p < 0.0001). Among men, the activity pattern was the opposite. The Recreovía is a promising strategy to promote park use and PA, especially among women who are less likely to meet PA recommendations during their leisure time. The provision of a cost-free community program may be an effective approach and a good investment for health.

Physical inactivity is estimated to be the fourth leading cause of global mortality. Strategies to increase physical activity (PA) increasingly emphasize environmental and policy changes including the modification of neighborhood environments to promote walking and other forms of healthy activity. Open Streets (OS) initiatives, an important and growing strategy to modify neighborhood environments for PA, create temporary parks for recreational activity by closing streets to motor vehicle traffic, thereby offering health and community building benefits. We used the Stanford Neighborhood Discovery Tool (DT)-photo/voice software on a tablet-to train neighborhood residents to act as "citizen scientist" observers of the local built environment on a non-event day and during an OS initiative. The purposes of this project were as follows: (1) to assess adult residents' perceptions of neighborhood characteristics of the OS initiative in three socioeconomically diverse sites and (2) to test the DT for use in three international urban settings with OS initiatives; Bogota, Colombia; San Francisco, USA; and Temuco, Chile, among a multigenerational, multiethnic sample of adults including, for the first time, a vulnerable population of homeless adults (Bogota). Using the DT, participants walked an OS route taking photos and recording reasons for the photos, then completed a 25-item demographic/environmental observation survey and a 16-item Reflection Survey on perceived environmental changes. A total of 18 themes were reported by participants with areas of overlapping themes (e.g., Community and Social Connectedness) and areas where a single site reported a theme (e.g., Social Isolation in Older Adults). Ten of the 18 themes were identified by at least two sites including "Bike Resources" and "Services", indicating the value of programming at OS initiatives. The themes of "Festive Environment" and "Family Friendly Environment" reflect the quality of the overall environment for participants. Four themes (Community and Social Connectedness, Family Friendly Environment, PA, and Safety) were reported by all sites. Three of the four unifying themes were also ranked among the highest reported categories of "seemed better" on the Reflection Survey (Ease of Walking, Overall Safety of Neighborhood, and Friendliness of Environment), providing additional confirmation of the shared experience of social, health, and psychological benefits from OS initiatives. OS initiatives offer a global strategy for increasing neighborhood opportunities for PA and a potential site for training citizen scientists to document environmental influences on PA.