Over the last two decades, urban growth has become a major issue in Lahore, accelerating land surface temperature (LST) rise. The present study focused on estimating the current situation and simulating the future LST patterns in Lahore using remote sensing data and machine learning
models. The semi-automated classification model was applied for the estimation of LST from 2000 to 2020. Then, the cellular automata-artificial neural networks (CA-ANN) module was implemented to predict future LST patterns for 2030 and 2040, respectively. Our research findings revealed that
an average of 2.8 °C of land surface temperature has increased, with a mean LST value from 37.25 °C to 40.10 °C in Lahore during the last two decades from 2000 to 2020. Moreover, keeping CA-ANN simulations for land surface temperature, an increase of 2.2 °C is projected through
2040, and mean LST values will be increased from 40.1 °C to 42.31 °C by 2040. The CA-ANN model was validated for future LST simulation with an overall Kappa value of 0.82 and 86.2% of correctness for the years 2030 and 2040 using modules for land-use change evaluation. The study also
indicates that land surface temperature is an important factor in environmental changes. Therefore, it is suggested that future urban planning should focus on urban rooftop plantations and vegetation conservation to minimize land surface temperature increases in Lahore.
Abstract. 3D Real Scene is an important part of new infrastructure construction, which provides a unified spatial base for economic and social development and informatization of various departments. According to the demand of real 3D Real Scene digital construction, this paper aims to study the method of indoor and outdoor structured monomer reconstruction of city 3D Real Scene, develop digital twin platform, and strive to lead the development of 3D Real Scene. The main research contents of this paper are as follows: 1) Spatio-temporal-spectral-angular remote sensing observation system and data fusion model; 2) Rapid construction method of vector monomer 3D model of indoor and outdoor entity object; 3) 3D structural reconstruction technology of urban component level based on vector images; 4) A universal digital twins platform, LuojiaDT. The technologies we have developed have been widely used in the national 3D Real Scene construction of China, including smart city, smart transportation, cultural heritage protection, public security and police, urban underground pipe network, indoor and outdoor location service. This research will promote the continuous development of digital twins technology.
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