Detection of waste dumping locations in landfill using multi-temporal Landsat thermal images
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The disposal of solid waste in a conventional landfill is inevitably associated with potential adverse environmental impacts, resulting in the migration of landfill gas and offensive odors on the surrounding areas. In addition to the obnoxious fumes and hazardous leachate, heat generation is continuously observed within the landfill during the aerobic and anaerobic phases. Despite the negative impacts, such "heat generation" phenomenon can turn into valuable information to aid in detecting unauthorized landfill activities and tracing unrecorded dumping regions. The spatial distribution of waste buried under the ground can be approximated and revealed through measuring the ground surface heat flux. In this study, we demonstrate how to utilize thermal remote sensing techniques to measure the land surface temperature (LST), which can aid in outlining the waste dumping regions within a landfill. The Jeleeb Al-Shuyoukh landfill, located in Kuwait, was used to demonstrate the proposed method, where the record of the exact dumping location was missing during the Gulf war. Ten-year Landsat Thematic Mapper(TM)/Enhanced Thematic Mapper Plus (ETM+) images (1985-1994) were acquired and processed in order to compute the LST within the landfill. Through combining the multi-temporal LST contours and overlay analysis, the most probable dumping regions within the landfill were outlined. A probability map was created to indicate the possible location of waste dumping within the studied landfill. With reference to the 50 boreholes drilled by the Environmental Protection Authority of Kuwait, our results derived during the summer and winter seasons both yielded an overall accuracy of 72%.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 it