The local climate zone (LCZ) system provides a universal classification mechanism for
urban and natural landscapes and plays an increasingly important role in urban climate …

Various forms of machine learning (ML) methods have historically played a valuable role in
environmental remote sensing research. With an increasing amount of “big data” from earth …

The advancement in satellite remote sensing technology has revolutionised the approaches
to monitoring the Earth's surface. The development of the Copernicus Programme by the …

Since their introduction in 2012, Local Climate Zones (LCZs) emerged as a new standard for
characterizing urban landscapes, providing a holistic classification approach that takes into …

Urbanization is the second largest mega-trend right after climate change. Accurate
measurements of urban morphological and demographic figures are at the core of many …

Abstract The Local Climate Zone (LCZ) scheme is a classification system providing a
standardization framework to present the characteristics of urban forms and functions …

In order to achieve accurate hyperspectral image (HSI) classification, the convolutional
neural network (CNN) has been extensively utilized. However, most existing patch-based …

Land cover and its change are crucial for many environmental applications. This study
focuses on the land cover classification and change detection with multitemporal and …

Spatial multi-criteria decision analysis (MCDA) is increasingly being used to inform urban
green infrastructure planning. We explore the use of modern cloud computing technologies …

Remote sensing (RS) image scene classification has obtained increasing attention for its
broad application prospects. Conventional fully-supervised approaches usually require a …