Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies

TL;DR: A two-phase classification method is proposed to fuse the airborne LiDAR data and aerial photography imagery to obtain detailed urban vegetation classification map and yielded the result with the highest accuracy for vegetation classification.

Abstract: In such a framework the field of urban meteorology may be judged to be at an early stage and to be evolving in a rather unbalanced fashion. The literature of the past 150 years is replete with studies of ’urban effects’ carried out at levels 1 and 2. Usually they are concerned with simple description or statistical analysis based upon empirical evidence from a single city. With the exception of a very few notable studies, attention to the processes (i.e. the causes underlying the observed effects) and to physico-mathematical modelling has been restricted to the past decade. Of course it is not expected, nor indeed may it be desirable, that research in a field should progress in a simple manner through the sequence 1-4, but two important points should be evident. First. as time progresses the bulk of research in a field should move to higher levels of enquiry. Second, the predictive power of processresponse models is limited by the extent to which the processes are understood. Some special difficulties have contributed to this unsatisfactory state of the field including : (1) the inherent complexity of the city-atmosphere system. The atmospheric state is a response to exchanges of energy, mass and momentum covering a wide range of space and time scales; in urban areas the sources and sinks for these exchanges are located in an extremely heterogeneous fashion and involve significant anthropogenic as well as natural factors; (2) the lack of clear conceptual/theoretical frameworks for enquiry especially in the light of the complications placed upon conventional theory by (1) ; (3) the expense and difficulty of observation in cities. Commonly one must deal with conditions within a relatively large volume of air (typically lo2 to lo3 km3) containing significant spatial and temporal variability thereby creating sampling problems. Moreover there are restrictions on the use of observation systems (towers, aircraft, balloons, acoustic radar) not normally encountered in uninhabited terrain. Here we will use the example of the urban ‘heat island’ effect to illustrate the state of urban meteorological research. This will include a condensed review of our understanding