Modelling urban systems has interested planners and modellers for decades. Different
models have been achieved relying on mathematics, cellular automation, complexity, and …

Introduction In low-and middle-income countries (LMICs), household survey data are a main
source of information for planning, evaluation, and decision-making. Standard surveys are …

Accurate projections of seasonal agricultural output are essential for improving food security.
However, the collection of agricultural information through seasonal agricultural surveys is …

Data collected at large scale and low cost (eg satellite and street level imagery) have the
potential to substantially improve resolution, spatial coverage, and temporal frequency of …

Road intersection data have been used across a range of geospatial analyses. However,
many datasets dating from before the advent of GIS are only available as historical printed …

Aerial scene classification is an active and challenging problem in high-resolution remote
sensing imagery understanding. Deep learning models, especially convolutional neural …

Human health is known to be affected by the physical environment. Various environmental
influences have been identified to benefit or challenge people's physical condition. Their …

Artificial intelligence (AI) has demonstrated its ability to complete complex tasks in various
fields. In urban studies, AI technology has been utilized in some limited domains, such as …

Researchers and engineers have increasingly used Deep Learning (DL) for a variety of
Remote Sensing (RS) tasks. However, data from local observations or via ground truth is …

Recent advances in Earth Observation (EO) placed Citizen Science (CS) in the highest
position, declaring their essential provision of information in every discipline that serves the …