scholarly journals A Non-Invasive Millimetre-Wave Radar Sensor for Automated Behavioural Tracking in Precision Farming—Application to Sheep Husbandry

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8140
Author(s):  
Alexandre Dore ◽  
Cristian Pasquaretta ◽  
Dominique Henry ◽  
Edmond Ricard ◽  
Jean-François Bompa ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Tracking System ◽  
Genetic Selection ◽  
Radar Data ◽  
Precision Farming ◽  
Video Tracking ◽  
Millimetre Wave ◽  
Electromagnetic Power ◽  
Wave Radar

The automated quantification of the behaviour of freely moving animals is increasingly needed in applied ethology. State-of-the-art approaches often require tags to identify animals, high computational power for data collection and processing, and are sensitive to environmental conditions, which limits their large-scale utilization, for instance in genetic selection programs of animal breeding. Here we introduce a new automated tracking system based on millimetre-wave radars for real time robust and high precision monitoring of untagged animals. In contrast to conventional video tracking systems, radar tracking requires low processing power, is independent on light variations and has more accurate estimations of animal positions due to a lower misdetection rate. To validate our approach, we monitored the movements of 58 sheep in a standard indoor behavioural test used for assessing social motivation. We derived new estimators from the radar data that can be used to improve the behavioural phenotyping of the sheep. We then showed how radars can be used for movement tracking at larger spatial scales, in the field, by adjusting operating frequency and radiated electromagnetic power. Millimetre-wave radars thus hold considerable promises precision farming through high-throughput recording of the behaviour of untagged animals in different types of environments.

scholarly journals A non-invasive radar system for automated behavioural tracking: application to sheep

2020 ◽  
Author(s):  
Alexandre Dore ◽  
Cristian Pasquaretta ◽  
Dominique henry ◽  
Edmond Ricard ◽  
Jean-François Bompard ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Tracking System ◽  
Genetic Selection ◽  
Radar Data ◽  
Millimetre Wave ◽  
Non Invasive ◽  
Electromagnetic Power ◽  
Automated Quantification ◽  
Behavioural Phenotyping

AbstractAutomated quantification of the behaviour of freely moving animals is increasingly needed in ethology, ecology, genetics and evolution. State-of-the-art approaches often require tags to identify animals, high computational power for data collection and processing, and are sensitive to environmental conditions, which limits their large-scale utilisation. Here we introduce a new automated tracking system based on millimetre-wave radars for real time robust and high precision monitoring of untagged animals. To validate our system, we tracked 64 sheep in a standard indoor behavioural test used for genetic selection. First, we show that the proposed radar application is faster and more accurate than conventional video and infrared tracking systems. Next, we illustrate how new behavioural estimators can be derived from the radar data to assess personality traits in sheep for behavioural phenotyping. Finally, we demonstrate that radars can be used for movement tracking at larger spatial scales, in the field, by adjusting operating frequency and radiated electromagnetic power. Millimetre-wave radars thus hold considerable promises for high-throughput recording of the behaviour of animals with various sizes and locomotor modes, in different types of environments.

scholarly journals Parameterization of the Spatial Variability of Rain for Large-Scale Models and Remote Sensing

2015 ◽  
Vol 54 (10) ◽  
pp. 2027-2046 ◽  
Author(s):  
Z. J. Lebo ◽  
C. R. Williams ◽  
G. Feingold ◽  
V. E. Larson
Keyword(s):  
Spatial Variability ◽  
Large Scale ◽  
Rain Rate ◽  
Numerical Models ◽  
Spatial Scales ◽  
Warm Pool ◽  
Radar Data ◽  
Model Output ◽  
Wide Range ◽  
Averaged Model

AbstractThe spatial variability of rain rate R is evaluated by using both radar observations and cloud-resolving model output, focusing on the Tropical Warm Pool–International Cloud Experiment (TWP-ICE) period. In general, the model-predicted rain-rate probability distributions agree well with those estimated from the radar data across a wide range of spatial scales. The spatial variability in R, which is defined according to the standard deviation of R (for R greater than a predefined threshold Rmin) σ(R), is found to vary according to both the average of R over a given footprint μ(R) and the footprint size or averaging scale Δ. There is good agreement between area-averaged model output and radar data at a height of 2.5 km. The model output at the surface is used to construct a scale-dependent parameterization of σ(R) as a function of μ(R) and Δ that can be readily implemented into large-scale numerical models. The variability in both the rainwater mixing ratio qr and R as a function of height is also explored. From the statistical analysis, a scale- and height-dependent formulation for the spatial variability of both qr and R is provided for the analyzed tropical scenario. Last, it is shown how this parameterization can be used to assist in constraining parameters that are often used to describe the surface rain-rate distribution.

Land Subsidence Detection by PSInSARTM Based on TerraSAR-X Images

2011 ◽  
Vol 301-303 ◽  
pp. 641-645 ◽  
Author(s):  
Hong Liang Jia ◽  
Bing Yu ◽  
Rui Zhang ◽  
Ming Zhi Sang
Keyword(s):  
High Resolution ◽  
Land Subsidence ◽  
Large Scale ◽  
Radar Data ◽  
Short Wave ◽  
Persistent Scatterer ◽  
Wave Radar ◽  
Land Deformation ◽  
Tianjin City ◽  
Large Scale Land

Land subsidence in urban area is becoming a severe geological hazard disturbing the urban construction and development. Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR) technique has demonstrated a good capability of monitoring the large scale land deformation. High resolution and short wave radar data can help to improve the precision of deformation detection based on PSInSAR. In this paper, 15 scenes of TerraSAR-X SAR data are used to derive the estimation of the subsidence rate in the Wuqing district, Tianjin city in China. The combination of TIN and nearest-connection method (NCM) are first used to establish the differential network model. The results show that high resolution TX image can dramatically increase the valid PSs and improve investigation reliability, especially in linear man-made constructs.

The spatial correlation between track roughness and ground-penetrating radar inferred ballast degradation

2018 ◽  
Vol 232 (7) ◽  
pp. 1917-1931
Author(s):  
Kirk M Scanlan ◽  
Michael T Hendry ◽  
C Derek Martin ◽  
Douglas R Schmitt
Keyword(s):  
Ground Penetrating Radar ◽  
Large Scale ◽  
Spatial Scales ◽  
Radar Data ◽  
Detection Tool ◽  
Heavy Haul ◽  
Surface Measurements ◽  
Radar Measurements ◽  
Ground Penetrating ◽  
Heavy Haul Railway

Ballast degradation is considered to be a primary factor that contributes to the development of track roughness, and as such it is important to develop efficient techniques to assess the condition of the ballast. Ground-penetrating radar is one method that has been applied in a variety of railway foundation studies including those attempting to non-destructively assess ballast degradation. However, there has yet to be a large-scale study that attempts to correlate the ground-penetrating radar-based estimates of ballast degradation with the observed track roughness. This study investigates this correlation along a 335 km-long heavy-haul railway subdivision in Alberta, Canada. Track roughness is quantified from repeated track alignment and surface measurements spanning 15 months prior to the ground-penetrating radar data acquisition. Three sets of 400 MHz ground-penetrating radar measurements were performed in August 2012, one along each ballast shoulder and one along the track centreline. The results of this study reveal that significant correlations between the observed track roughness and the ground-penetrating radar-based interpretation of ballast degradation are rare and only exist when the data are compared at very small spatial scales. The absence of significant correlations between track roughness and the estimates of ballast degradation is primarily interpreted as being the result of ambiguous ground-penetrating radar data caused by local-scale variations in the track foundation unrelated to ballast degradation. To address these issues, potential improvements in the application of ground-penetrating radar as a ballast degradation detection tool are proposed.

scholarly journals Analysis of 220 Years of Floodplain Population Dynamics in the US at Different Spatial Scales

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 141
Author(s):  
Firoza Akhter ◽  
Maurizio Mazzoleni ◽  
Luigia Brandimarte
Keyword(s):  
Population Dynamics ◽  
Large Scale ◽  
Spatial Scales ◽  
National Level ◽  
State Level ◽  
Economic Activities ◽  
Protection Measures ◽  
Management Planning ◽  
The Us ◽  
Over Time

In this study, we explore the long-term trends of floodplain population dynamics at different spatial scales in the contiguous United States (U.S.). We exploit different types of datasets from 1790–2010—i.e., decadal spatial distribution for the population density in the US, global floodplains dataset, large-scale data of flood occurrence and damage, and structural and nonstructural flood protection measures for the US. At the national level, we found that the population initially settled down within the floodplains and then spread across its territory over time. At the state level, we observed that flood damages and national protection measures might have contributed to a learning effect, which in turn, shaped the floodplain population dynamics over time. Finally, at the county level, other socio-economic factors such as local flood insurances, economic activities, and socio-political context may predominantly influence the dynamics. Our study shows that different influencing factors affect floodplain population dynamics at different spatial scales. These facts are crucial for a reliable development and implementation of flood risk management planning.

scholarly journals Insectivorous songbirds as early indicators of future defoliation by spruce budworm

2021 ◽  
Author(s):  
Marion Germain ◽  
Daniel Kneeshaw ◽  
Louis De Grandpré ◽  
Mélanie Desrochers ◽  
Patrick M. A. James ◽  
...  
Keyword(s):  
Large Scale ◽  
Spatial Scales ◽  
Spruce Budworm ◽  
Detection Methods ◽  
Maximum Probability ◽  
Point Count ◽  
Probability Of Presence ◽  
Time Lagged ◽  
One Year ◽  
Local Sampling

Abstract Context Although the spatiotemporal dynamics of spruce budworm outbreaks have been intensively studied, forecasting outbreaks remains challenging. During outbreaks, budworm-linked warblers (Tennessee, Cape May, and bay-breasted warbler) show a strong positive response to increases in spruce budworm, but little is known about the relative timing of these responses. Objectives We hypothesized that these warblers could be used as sentinels of future defoliation of budworm host trees. We examined the timing and magnitude of the relationships between defoliation by spruce budworm and changes in the probability of presence of warblers to determine whether they responded to budworm infestation before local defoliation being observed by standard detection methods. Methods We modelled this relationship using large-scale point count surveys of songbirds and maps of cumulative time-lagged defoliation over multiple spatial scales (2–30 km radius around sampling points) in Quebec, Canada. Results All three warbler species responded positively to defoliation at each spatial scale considered, but the timing of their response differed. Maximum probability of presence of Tennessee and Cape May warbler coincided with observations of local defoliation, or provided a one year warning, making them of little use to guide early interventions. In contrast, the probability of presence of bay-breasted warbler consistently increased 3–4 years before defoliation was detectable. Conclusions Early detection is a critical step in the management of spruce budworm outbreaks and rapid increases in the probability of presence of bay-breasted warbler could be used to identify future epicenters and target ground-based local sampling of spruce budworm.

Do elite soccer players cover longer distance when losing? Differences between attackers and defenders

2020 ◽  
pp. 174795412098227
Author(s):  
Carlos Lago-Peñas ◽  
Anton Kalén ◽  
Miguel Lorenzo-Martinez ◽  
Roberto López-Del Campo ◽  
Ricardo Resta ◽  
...  
Keyword(s):  
New York ◽  
High Speed ◽  
Large Scale ◽  
Tracking System ◽  
Soccer Players ◽  
Running Performance ◽  
Situational Variables ◽  
Total Distance ◽  
Professional Soccer ◽  
Score Line

This study aimed to evaluate the effects playing position, match location (home or away), quality of opposition (strong or weak), effective playing time (total time minus stoppages), and score-line on physical match performance in professional soccer players using a large-scale analysis. A total of 10,739 individual match observations of outfield players competing in the Spanish La Liga during the 2018–2019 season were recorded using a computerized tracking system (TRACAB, Chyronhego, New York, USA). The players were classified into five positions (central defenders, players = 94; external defenders, players = 82; central midfielders, players = 101; external midfielders, players = 72; and forwards, players = 67) and the following match running performance categories were considered: total distance covered, low-speed running (LSR) distance (0–14 km · h−1), medium-speed running (MSR) distance (14–21 km · h−1), high-speed running (HSR) distance (>21 km · h−1), very HSR (VHSR) distance (21–24 km · h−1), sprint distance (>24 km · h−1) Overall, match running performance was highly dependent on situational variables, especially the score-line condition (winning, drawing, losing). Moreover, the score-line affected players running performance differently depending on their playing position. Losing status increased the total distance and the distance covered at MSR, HSR, VHSR and Sprint by defenders, while attacking players showed the opposite trend. These findings may help coaches and managers to better understand the effects of situational variables on physical performance in La Liga and could be used to develop a model for predicting the physical activity profile in competition.

scholarly journals Mapping High Spatiotemporal-Resolution Soil Moisture by Upscaling Sparse Ground-Based Observations Using a Bayesian Linear Regression Method for Comparison with Microwave Remotely Sensed Soil Moisture Products

2021 ◽  
Vol 13 (2) ◽  
pp. 228
Author(s):  
Jian Kang ◽  
Rui Jin ◽  
Xin Li ◽  
Yang Zhang
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Spatial Scales ◽  
Microwave Remote Sensing ◽  
In Situ Measurements ◽  
Spatial Density ◽  
Linear Regression Method ◽  
Spatiotemporal Resolution ◽  
Pixel Scale

In recent decades, microwave remote sensing (RS) has been used to measure soil moisture (SM). Long-term and large-scale RS SM datasets derived from various microwave sensors have been used in environmental fields. Understanding the accuracies of RS SM products is essential for their proper applications. However, due to the mismatched spatial scale between the ground-based and RS observations, the truth at the pixel scale may not be accurately represented by ground-based observations, especially when the spatial density of in situ measurements is low. Because ground-based observations are often sparsely distributed, temporal upscaling was adopted to transform a few in situ measurements into SM values at a pixel scale of 1 km by introducing the temperature vegetation dryness index (TVDI) related to SM. The upscaled SM showed high consistency with in situ SM observations and could accurately capture rainfall events. The upscaled SM was considered as the reference data to evaluate RS SM products at different spatial scales. In regard to the validation results, in addition to the correlation coefficient (R) of the Soil Moisture Active Passive (SMAP) SM being slightly lower than that of the Climate Change Initiative (CCI) SM, SMAP had the best performance in terms of the root-mean-square error (RMSE), unbiased RMSE and bias, followed by the CCI. The Soil Moisture and Ocean Salinity (SMOS) products were in worse agreement with the upscaled SM and were inferior to the R value of the X-band SM of the Advanced Microwave Scanning Radiometer 2 (AMSR2). In conclusion, in the study area, the SMAP and CCI SM are more reliable, although both products were underestimated by 0.060 cm3 cm−3 and 0.077 cm3 cm−3, respectively. If the biases are corrected, then the improved SMAP with an RMSE of 0.043 cm3 cm−3 and the CCI with an RMSE of 0.039 cm3 cm−3 will hopefully reach the application requirement for an accuracy with an RMSE less than 0.040 cm3 cm−3.

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