Satellite-Based Assessment of Land Use and Land Cover (LULC) Changes around Lake Fitri, Republic of Chad
Bibliographic record
Abstract
Lake Fitri, located northeast of the Republic of Chad’s Capital, N’Djamena, and southeast of Lake Chad, is especially important because it serves as an alternative source to Lake Chad in supporting the livelihood of pastoralists and subsidence farmers displaced from the Lake Chad region. It therefore serves to relieve population pressures on Lake Chad, which has undergone drastic reduction in total water volume in the last few decades. The area has also been the epicenter of recent violent campaigns and devastating insurgency mounted by the so-called Boko Haram. This study investigated the land use land cover around Lake Fitri from 1986 to 2003, and from 2003 to 2013 using Landsat 5 (TM), Landsat 7 (ETM+), and Landsat 8 (OLI_TIRS). The satellite imageries were retrieved from the Global Visualization (GloVis) web-based platform and analyzed using ERDAS Imagine 2014. Supervised classification of areas around the lake was performed into five land use land cover classes. The results revealed significant changes in three land use types, namely Farmland and Grassland combined, Forest, Savanna, and Steppe combined, and Wetland. Farmland and Grassland combined increased from a mere 0.38% of the total study area in 1986 to 41.05% in 2013. At the same time, Forest, Savanna, and Steppe combined decreased from about 23% in 1986 to about 7.40% in 2013. This increase in farmlands and grasslands coverage and the concomitant decrease in trees and shrubs can be explained by the persistent pressures on land from increasing population and livestock in the area. The findings also show a major decline in Wetland, which decreased from about 14% of the total study area to 3% in the same time period. This loss in wetland coverage is regrettable because of the important environmental and ecological functions of wetlands.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".