Remote Sensing Studies for the Assessment of Geohazards: Toxic Algal Blooms in the Lower Great Lakes, and the Land Subsidence in the Nile Delta
Bibliographic record
Abstract
Remote sensing techniques provide valuable tools for assessing a wide variety of environmental phenomena. They have been used for monitoring and assessment of various types of geologic and environmental hazards occurring on land, in the air, or in oceans. I present results from two studies, the first of which examines the spatial and temporal distribution of algal blooms in the Great Lakes; the second measures subsidence in the Nile Delta.\nIn the first study, methodologies to investigate the extent and distribution (temporally and spatially) of algal blooms in Lake Erie and Lake Ontario are studied. Millions of people in the U.S and Canada rely on the Great Lakes for drinking water, food, work, and recreation. Toxic algal blooms present a hazard to the substantial number of communities that draw water from the Great Lakes. Visible and infra red MODIS satellite data are used to map the extent of algal blooms in these lakes. Existing algorithms to retrieve chlorophyll concentrations are successfully tested against in situ measurements from sampling cruises. Algorithms are developed to identify the potentially toxic cyanobacterial blooms.\nThe second study examines subsidence in the Nile Delta. The modern Nile Delta is the major agricultural production area for Egypt and was formed from sediments supplied by at least 10 distinct distributary channels throughout the Holocene. With an average elevation around a meter above sea level and with a predicted rise in sea level of 1.8-5.9 mm/year the subsidence of the northern 30 km of the delta is a topic of major concern to the Egyptian population and government. Ongoing subsidence rates in the northeastern Nile Delta were estimated using persistent scatterer radar interferometry techniques. The highest rates ( ~8 mm/yr; twice average Holocene rates) correlate with the distribution of the youngest deposition, with older depositional centers subsiding at slower rates of 2-6 mm/yr. Results are interpreted to indicate that: (1) modern subsidence in the Delta is heavily influenced by the compaction of the most recent sediments, and (2) the highly threatened areas are at the terminus of the Damietta, where the most recent deposition has occurred.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".