RT Journal Article
T1 URSUS_LST: URban SUStainability intelligent system for predicting the impact of urban green infrastructure on land surface temperatures
A1 Rodríguez-Gómez, Francisco
A1 Del-Campo-Ávila, José
A1 Pérez-Urrestarazu, Luis
A1 López-Rodríguez, Domingo
K1 Soporte lógico libre
K1 Urbanismo sostenible
AB Mitigating Urban Heat Island (UHI) effects has become a challenge to improve urban sustainability. The simulation tool URSUS_LST has been developed to allow urban planners to estimate how the addition of different green infrastructure elements would affect temperature. To achieve this, a new methodology was defined based on data mining, geospatial image processing and the knowledge of experts in the domain that predicts the Land Surface Temperature (LST) of any location within a city. It consists of a first data mining phase in which the real LST and the different urban elements of the nearby environment are considered: buildings, vegetation and water bodies. In a second phase, different regression models are induced to predict LST. Additionally, considering the most accurate models, the relevant attributes and their relationships are identified. A real application of the tool in the city of Malaga (Spain) has been used as an example of its usefulness.
PB Elsevier
SN 1364-8152
YR 2025
FD 2025
LK https://hdl.handle.net/10630/38471
UL https://hdl.handle.net/10630/38471
LA spa
NO Rodríguez-Gómez, F., del Campo-Ávila, J., Pérez-Urrestarazu, L., & López-Rodríguez, D. (2025). URSUS_LST: URban SUStainability intelligent system for predicting the impact of urban green infrastructure on land surface temperatures. Environmental Modelling & Software, 186, 106364.
NO Funding for open access charge: Universidad de Málaga / CBUA
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 19 ene 2026