No abstract

Satellite remote sensing data that lacks spatial resolution and timeliness is of limited ability to access urban thermal environment on a micro scale. This paper presents an unmanned airship low-altitude thermal infrared remote sensing system (UALTIRSS), which is composed of an unmanned airship, an onboard control and navigation subsystem, a task subsystem, a communication subsystem, and a ground-base station. Furthermore, an experimental method and an airborne-field experiment for collecting land surface temperature (LST) were designed and conducted. The LST pattern within 0.8-m spatial resolution and with root mean square error (RMSE) value of 2.63 °C was achieved and analyzed in the study region. Finally, the effects of surface types on the surrounding thermal environment were analyzed by LST profiles. Results show that the high thermal resolution imagery obtained from UALTIRSS can provide more detailed thermal information, which are conducive to classify fine urban material and assess surface urban heat island (SUHI). There is a significant positive correlation between the average LST of profiles and the percent impervious surface area (ISA%) with R 2 around 0.917. Overall, OPEN ACCESSRemote Sens. 2015, 7 14260UALTIRSS and the retrieval method were proved to be low-cost and feasible for studying micro urban thermal environments.

Based on the investigation to 59 residential buildings in China, this study establishes the prediction model of annual energy consumption of residential buidlings using four diff erent modeling methods such as support vector machine (SVM), traditional back propagation neural network (BPNN), radial basis function neural network (RBFNN) and general regression neural network (GRNN). The simulation results show that SVM and GRNN methods achieve better accuracy and generalization than BPNN and RBFNN methods, and are effective for prediction of annual building energy consumption.

Moisture diffusivity is an important material property for performing the hygrothermal analysis of buildings and the built environment. Its experimental determination is still a challenge, albeit various destructive and non-destructive experimental methods are available. This paper compares the X-ray method, the ruler method, the multi-step method and the Kießl-Künzel method to non-destructively determine the moisture diffusivity of calcium silicate, ceramic brick and lime mortar. Results show that the ruler method can provide the closest results to the well-known X-ray attenuation method with a more straightforward process, but it's mainly suitable for materials with a sharp and visible water front. The multi-step method is easy to operate in experiments and suits most porous building materials, but it takes a long time to condition samples and needs complicated data processing, which seems too complex to get the moisture diffusivity as a step function. The Kießl-Künzel method is the simplest but not always accurate.