Dynamics of Land use Around the Micro-Dam Anti-Salt in the Sub-Watershed of Agnack Lower Casamance (Senegal)
Bibliographic record
Abstract
Agriculture, mainly based on rain, is one the most important economic activities in Lower Casamance region. Its agricultural production is vulnerable to climatic variability. The water management has become an important issue for rural populations food security. This research aims at the characterization of environmental evolution and agricultural production, around the anti-salt micro-dams in Lower Casamance area, which has a high rainfall and a rich potential of water resources. This study examines the hydro-agricultural planning issues in Lower Casamance and aims at the analysis of the land use change and its evolution in the Agnack sub-basin around anti- salt micro-dam between 1984 and 2010. Based on the importance of rice production area around micro-dams, the analysis focus on eight sites. Using satellite imagery Landsat TM of 1984 and 1992 and ETM of 2000 and 2010 combined with ground, socio-economic survey and soil analysis data, this research investigates land use change through image classifications, change detection and landscape pattern analysis. We conducted a mapping of the rice paddies to determine the evolution of riceland during these dates. Through a pseudo-supervised classification coupled with field data, we characterized the different types of land use and cover. Results of land use/cover change analysis showed a decrease of riceland area; while there is a relative vegetation regeneration between 1984 and 2010. The soil analysis showed a deterioration in soil quality which is showed by a very high acidity in all sites and a soil salinity of riceland in the upstream developed valleys. Socio-economic surveys showed the importance of the micro-dams. In the term, the micro-dam did not achieve the expected results. It could not solve the problem of degraded soil desalination and intensification of rice growing.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".