Use of Miniature Thermal Cameras for Detection of Physiological Stress in Conifers

Śmigaj, Magdalena; Gaulton, Rachel; Suárez, Juan Carlos Pinilla; Barr, SL

doi:10.3390/rs9090957

Cited by 40 publications

(32 citation statements)

References 47 publications

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“…Apart from errors associated with the LST retrieval and the UAV-thermal sensor itself, there are also errors related to the underlying structure from motion process used to construct the ortho-rectified UAV-based thermal maps. Studies have already reported that the SfM process struggles to stitch thermal images into an accurate orthomosaic [49,73], since these contain reduced information compared to RGB images, rendering the detection of common feature points more challenging. SfM is based on both the images position and also the capacity to match pixels for georeferencing and correcting image distortion.…”

Section: Discussionmentioning

confidence: 99%

Capturing the Diurnal Cycle of Land Surface Temperature Using an Unmanned Aerial Vehicle

et al. 2018

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Characterizing the land surface temperature (LST) and its diurnal cycle is important in understanding a range of surface properties, including soil moisture status, evaporative response, vegetation stress and ground heat flux. While remote-sensing platforms present a number of options to retrieve this variable, there are inevitable compromises between the resolvable spatial and temporal resolution. For instance, the spatial resolution of geostationary satellites, which can provide sub-hourly LST, is often too coarse (3 km) for many applications. On the other hand, higher-resolution polar orbiting satellites are generally infrequent in time, with return intervals on the order of weeks, limiting their capacity to capture surface dynamics. With recent developments in the application of unmanned aerial vehicles (UAVs), there is now the opportunity to collect LST measurements on demand and at ultra-high spatial resolution. Here, we detail the collection and analysis of a UAV-based LST dataset, with the purpose of examining the diurnal surface temperature response: something that has not been possible from traditional satellite platforms at these scales. Two separate campaigns were conducted over a bare desert surface in combination with either Rhodes grass or a recently harvested maize field. In both cases, thermal imagery was collected between 0800 and 1700 local solar time. The UAV-based diurnal cycle was consistent with ground-based measurements, with a mean correlation coefficient and root mean square error (RMSE) of 0.99 and 0.68 °C, respectively. LST retrieved over the grass surface presented the best results, with an RMSE of 0.45 °C compared to 0.67 °C for the single desert site and 1.28 °C for the recently harvested maize surface. Even considering the orders of magnitude difference in scale, an exploratory analysis comparing retrievals of the UAV-based diurnal cycle with METEOSAT geostationary data yielded pleasing results (R = 0.98; RMSE = 1.23 °C). Overall, our analysis revealed a diurnal range over the desert and maize surfaces of ~20 °C and ~17 °C respectively, while the grass showed a reduced amplitude of ~12 °C. Considerable heterogeneity was observed over the grass surface at the peak of the diurnal cycle, which was likely indicative of the varying crop water status. To our knowledge, this study presents the first spatially varying analysis of the diurnal LST captured at ultra-high resolution, from any remote platform. Our findings highlight the considerable potential to utilize UAV-based retrievals to enhance investigations across multi-disciplinary studies in agriculture, hydrology and land-atmosphere investigations.

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Section: Discussionmentioning

confidence: 99%

Capturing the Diurnal Cycle of Land Surface Temperature Using an Unmanned Aerial Vehicle

et al. 2018

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“…Thus, the thermal image can be unreliable especially when the internal temperature of the camera is changing rapidly, such as during camera warmup period or during the flight when a gust of cool wind results in cooling of the camera. To overcome this challenge, the user may need to provide sufficient startup time before operation (preferably 30-60 min) [102,[143][144][145], shield the camera to minimize the change in the internal temperature of the camera [142], calibrate the camera [146][147][148][149][150][151][152][153], and perform frequent flat-field corrections.…”

Section: Thermalmentioning

confidence: 99%

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

Gautam

Pagay

2020

Agronomy

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With increasingly advanced remote sensing systems, more accurate retrievals of crop water status are being made at the individual crop level to aid in precision irrigation. This paper summarises the use of remote sensing for the estimation of water status in horticultural crops. The remote measurements of the water potential, soil moisture, evapotranspiration, canopy 3D structure, and vigour for water status estimation are presented in this comprehensive review. These parameters directly or indirectly provide estimates of crop water status, which is critically important for irrigation management in farms. The review is organised into four main sections: (i) remote sensing platforms; (ii) the remote sensor suite; (iii) techniques adopted for horticultural applications and indicators of water status; and, (iv) case studies of the use of remote sensing in horticultural crops. Finally, the authors' view is presented with regard to future prospects and research gaps in the estimation of the crop water status for precision irrigation.

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“…Key considerations relate to spatial resolution and thermal sensitivity, with the latter now achieving 40-50 mK. Thermal UAS remote sensing also requires consideration of radiometric calibration and accounting for vignetting and other systematic effects, as discussed by Smigaj et al [57]. With the aim to provide a description of the potential of a thermal camera mounted on a UAS, an example of a thermal image providing the surface temperature (in degrees Celsius) obtained over a vineyard of Aglianico is given in Figure 2.…”

Section: Sensorsmentioning

confidence: 99%

On the Use of Unmanned Aerial Systems for Environmental Monitoring

et al. 2018

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Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small-and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air-and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

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Use of Miniature Thermal Cameras for Detection of Physiological Stress in Conifers

Cited by 40 publications

References 47 publications

Capturing the Diurnal Cycle of Land Surface Temperature Using an Unmanned Aerial Vehicle

Capturing the Diurnal Cycle of Land Surface Temperature Using an Unmanned Aerial Vehicle

A Review of Current and Potential Applications of Remote Sensing to Study the Water Status of Horticultural Crops

On the Use of Unmanned Aerial Systems for Environmental Monitoring

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