Analysis of Urban Floodplain Encroachment: Strategic Approach to Flood and Floodplain Management in Kaduna Metropolis, Nigeria
Bibliographic record
Abstract
This study was aimed at monitoring, mapping and characterisation of floodplain encroachment patterns on the River Kaduna floodplain in Kaduna metropolis, Nigeria,as part of the approach to flood hazard evaluation, flood risk assessment and effective flood and floodplain management. A Topomap of 1967 was used to extract the base built-up layer, while Landsat.TM, 1987, Spot.XS, 1995, Landsat.ETM, 2001 and Quickbird, 2006 were used to generate other built-up layers, which were extracted by digitization and converted to polygon shape files and later used for overlay analysis. A Digital Elevation Map (DEM) of the area was used for delineation of floodplain boundary. ArcGIS sorfware 9.0 operational tools was highly robust and flexible for mapping and analysis of urban growth patterns and characterisation of floodplain encroachment by communities. From the results, it was observed that the highest extents and rates of encroachment are recorded by communities in the proximity of the Central Business District (CBD) such as T/Wada, Ung. Rimi, Barnawa, Doka and the industrial layouts of Kakuri and Kudenda. These areas are the centers of highest socio-economic infrastructure which implies greater flood risk and damage potential in the event of flooding. Results also showed that about 52.83% of the urban segment of the River Kaduna total floodplain area of 48.55km2, has been encroached by built-up. As a result of this pattern of encroachment, strong institutional framework and investment towards effective floodplain management is recommended.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 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".