Prediction of skin surface soil permeability by infrared thermography: a soil flume experiment

Lima, João L.M.P. de; Abrantes, João R.C.B.; Silva, Valdemir P.; Montenegro, Abelardo Antônio de Assunção

doi:10.1080/17686733.2014.945325

Cited by 10 publications

(6 citation statements)

References 17 publications

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“…TIR has similarly been used for the monitoring and estimation of soil surface characteristics such as microrelief and rill morphology [85], soil water repellency [86], soil surface macropores [87], skin surface soil permeability [88], and overland and rill flow velocities by using thermal tracers [89,90].…”

Section: Vegetation Monitoring and Precision Agriculturementioning

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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Section: Vegetation Monitoring and Precision Agriculturementioning

confidence: 99%

On the Use of Unmanned Aerial Systems for Environmental Monitoring

et al. 2018

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“…IRT was used similarly by previous authors, but rather than to assess the SST, it was used in laboratory experiments to estimate the soil surface microrelief and rill morphology [97], to map soil surface permeability and identify preferential flow [98], to map macroporosity at the soil surface [99], to assess cooling the soil surface with cold water for assessing soil water repellency [100]. This paper proposed a novel, scalable approach for applying IRT monitoring of SST in environmental applications.…”

Section: Discussionmentioning

confidence: 99%

Applying Infrared Thermography to Soil Surface Temperature Monitoring: Case Study of a High-Resolution 48 h Survey in a Vineyard (Anadia, Portugal)

Frodella

Lazzeri

Moretti

et al. 2020

Sensors

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The soil surface albedo decreases with an increasing biochar application rate as a power decay function, but the net impact of biochar application on soil temperature dynamics remains to be clarified. The objective of this study was to assess the potential of infrared thermography (IRT) sensing by monitoring soil surface temperature (SST) with a high spatiotemporal and thermal resolution in a scalable agricultural application. We monitored soil surface temperature (SST) variations over a 48 h period for three treatments in a vineyard: bare soil (plot S), 100% biochar cover (plot B), and biochar-amended topsoil (plot SB). The SST of all plots was monitored at 30 min intervals with a tripod-mounted IR thermal camera. The soil temperature at 10 cm depth in the S and SB plots was monitored continuously with a 5 min resolution probe. Plot B had greater daily SST variations, reached a higher daily temperature peak relative to the other plots, and showed a faster rate of T increase during the day. However, on both days, the SST of plot B dipped below that of the control treatment (plot S) and biochar-amended soil (plot SB) from about 18:00 onward and throughout the night. The diurnal patterns/variations in the IRT-measured SSTs were closely related to those in the soil temperature at a 10 cm depth, confirming that biochar-amended soils showed lower thermal inertia than the unamended soil. The experiment provided interesting insights into SST variations at a local scale. The case study may be further developed using fully automated SST monitoring protocols at a larger scale for a range of environmental and agricultural applications.

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“…The collected data suggest that thermal image data was not an accurate predictor of channel presence under study field conditions. It should be possible to use soil temperature to identify moist areas (Pfister et al, 2010) and controlled laboratory experiments have demonstrated a relationship between soil moisture and temperature (de Lima et al, 2014). Possible limitations of thermal imagery use in this study include the timing of the sample collection in relation to rain events (most sampling occurred during a dry period) and the differences in soil temperature caused by the variable presence of canopy cover shading direct sunlight.…”

Section: Thermal Datamentioning

confidence: 99%

“…Ground-based thermal imagery collection has been used successfully in the field to identify areas of saturated soil and water connectivity and dynamics in the landscape (Pfister et al, 2010). In addition, laboratory studies of soil temperature have been successfully able to predict different types of soil permeability (de Lima et al, 2014). Detection of moist soil using thermal imaging is possible because evaporative cooling effects causes a temperature change which can be detected at the soil surface.…”

Section: Introductionmentioning

confidence: 99%

LiDAR-based predictions of flow channels through riparian buffer zones

et al. 2015

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Riparian buffer zones (RBZs) are critical for protecting stream water quality. High Resolution Light Detection and Ranging (LiDAR) data provides a way to locate channels where water can flow through a RBZ and into a stream. The objectives of this study were to characterize flow channels through riparian buffer zones around Lake Issaqueena, SC, USA, using LiDAR topography models and to validate these predictions using field observations of channel presence, soil moisture content and soil temperature. A LiDAR derived digital elevation model (DEM) was utilized to define flow channels and determine forty sample locations. Analysis indicated channel locations and the presence of large forested buffers generally 10 m or greater in the study area. High flow accumulation channels can be accurately predicted by LiDAR data, but lower flow channels were less accurately estimated. Surface soil temperature measurements were relatively uniform showing no difference between predicted channel and control locations. Presented methodologies can serve as a template for future efforts to quantify riparian buffers and their effects on protecting water quality.

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Prediction of skin surface soil permeability by infrared thermography: a soil flume experiment

Cited by 10 publications

References 17 publications

On the Use of Unmanned Aerial Systems for Environmental Monitoring

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Applying Infrared Thermography to Soil Surface Temperature Monitoring: Case Study of a High-Resolution 48 h Survey in a Vineyard (Anadia, Portugal)

LiDAR-based predictions of flow channels through riparian buffer zones

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