Temporal remote sensing of thermal diffusion waves in bare soil subsurface at multi-spatial scales
Bibliographic record
Abstract
There have been several attempts to characterize the soil subsurface such as, locating existing interfaces, buried structures and/or moisture dynamics using remotely sensed data. The aim of this research was to investigate the influence of subsurface soil properties on surface temperature dynamics that could be detected remotely. Achieving this goal requires investigating systematically the problems created by assumptions in the ID model of heat conduction applied to soil profiles at different spatial scales. Investigation at micro scale was conducted by applying a continuous heating test to three samples obtained from Dara Plain, west Gulf of Suez, the Eastern Egyptian Desert, representing the surface crusts formed in Dara plain and Dara dry valley, as well as the hardpan found deep in Dara Plain soil profiles. The results demonstrated that at scales of a few centimeters, the spatial distribution of solid and void phases influenced only the soil bulk thermal properties, but there was no influence on the dynamics of the surface temperature change. This explained the success of fitting the same ID model (R 2=0.99), originally developed to model surface temperature increase of homogenous materials under continuous heating, to observed surface temperature of two soil crusts with different spatial structure as indicated by computed tomography. At the soil profile scale, the surface temperature of a group of synthetic soil profiles with subsurface layers was recorded using a thermal video camera, during a simulated diurnal cycle in the laboratory, while the subsurface thermal property, namely thermal 'inertia' was measured at different depths using heat pulse probes. Results indicated that the presence of subsurface thermal mismatches changed the magnitude and phase of maximum surface temperature with comparison to a dry homogenous sand profile. The increase or decrease in maximum surface temperature depends on the ratio of thermal inertia around mismatch surfaces, as well as direction of thermal gradient field during heating or cooling. Average values of thermal inertia ratios were calculated from heat pulse probe measurements and were used to reconstruct the first harmonic of surface temperature using a theoretical thermal wave model. The model produced delays in timing of the maximum temperature similar to experimental data. Finally, at close-range sensing scale, around 75 m2, principle component analysis was applied to images of infra-red temperatures captured every 1/2 hr during a complete diurnal cycle, for a vineyard in southern Ontario. The results indicate that 45%, 82% and 66% of the variation in surface temperature temporal dynamics during heating, cooling and diurnal cycle, respectively, were attributed to intrinsic subsurface thermal inertia, while 55%, 17% and 34% of surface dynamics were attributed to surface transient effects such as delays induced by orientation of soil surface to solar position. This research concluded that surface conditions, such as microtopography, in an open field situation can interfere with remotely-captured temperature signals related to subsurface characteristics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".