USING SATELLITE IMAGERY TO ESTIMATE THE RATE OF VEGETATION COVER IN THE WATERSHED OF CHOTT CHERGUI -WILAYA OF EL BAYADH (HIGH STEPPE PLAINS OF ALGERIA)
Bibliographic record
Abstract
Several factors influence the extent of water erosion: the length and the gradient of the slope, soil texture, the extent of vegetation cover. However it is the soil cover that remains the dominant issue on the effective response against erosion by protective the surface facing the erosive forces of raindrops and runoff. Our work aims to estimate the rate of vegetation recovery using satellite imagery in a semiarid region of the watershed of the Chott Chergui within the wilaya of El Bayadh. It is estimated the overall rate of recovery of vegetation on the site and its linking with the values of the normalized difference vegetation index (NDVI) corresponding to the image. The result has developed a map of three classes of vegetation cover, the first is completely denuded of vegetation, it is sandy areas, with rocky outcrops, or areas of buildings. The second vegetation with a less than 10 %, which corresponds to natural vegetation growing at altitudes moderately important to mountainsides. The third class has a recovery rate above 10% representing the agricultural parcels along the banks of the wadis, or reforested areas (that cover more than 30 %).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".