Spatio-temporal analysis of surface urban heat island (SUHI) using MODIS land surface temperature (LST) for summer 2003–2012, A case study of the Netherlands
Bibliographic record
Abstract
Surface urban heat island phenomenon refers to the relative warmth of urban surfaces compared with surrounding rural areas. For the purpose of this study, Netherlands has been chosen as it has been suffering from extreme heat events and the formation of urban heat islands in 2003 with nearly 2200 deaths, and 1000 deaths in 2006. This study analyses the spatio-temporal pattern of surface urban heat islands using MODIS land surface temperature in relation to normalized difference vegetation index (NDVI). MODIS land surface temperature product (LST) and NDVI were used for the period of this research between summers 2003-2012. A strong negative relationship (R <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> = 0.834) was found between mean LST and positive NDVI values, suggesting that vegetation can effectively reduce the surface temperature. These findings are helpful for land use and urban planning purposes to mitigate the potential environmental and social impacts of extreme heat events.
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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 | 0.001 |
| 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) | 0.001 | 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".