Dynamics of Wetlands in Ifrane National Park, Morocco: An Approach Using Satellite Imagery and Spectral Indices
Bibliographic record
Abstract
Our study aims to analyze the spatiotemporal dynamics of six lakes in Ifrane National Park (Morocco) using remote sensing and satellite imagery over the period 2000–2024. Spectral indices such as NDWI, MNDWI, EWI, AWEI, and ANDWI were employed to extract water bodies from Landsat images, while the NDVI index was used to identify irrigated agricultural lands. Additionally, the SPEI and RDI indices were applied to assess the impact of climate fluctuations on the hydrological evolution of the lakes. The results reveal an alarming reduction in lake surface areas, with some lakes having completely dried up. This decline is correlated with decreased precipitation and the expansion of irrigated agricultural lands, highlighting the impact of human activities. The analysis of hydrological correlations between lakes demonstrates significant interactions, although some indices show disparities. The rapid expansion of agricultural land, particularly arboriculture, increases pressure on water resources. These changes threaten local biodiversity and heighten the socio-economic vulnerability of surrounding populations.
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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 | 0.002 | 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".