Remote sensing data have already proven useful for environmental monitoring. Satellite remote sensors are major sources of consistent, continuous data for land, ocean, and atmospheric studies at a variety of spatial and temporal scales. As climate change and population growth place increasing pressures in many parts of the world, improved methods for monitoring urban growth across a range of spatial and temporal scales will be vital for understanding and addressing the impacts of urbanization on our natural resources. The meaningful interpretation of remote sensing data and in situ observations require implementation and analysis using advanced mathematics and statistical techniques.

The objective of this special issue is to provide a snapshot of status, potentials, challenges, and achievements of mathematical application in using remote sensing data to address environmental issues.

Potential topics include but are not limited to the following:

• Remote sensing image analysis and interpretation
• Remote sensing data fusion into numerical modelling
• Remote sensing heat, water, and carbon states and fluxes
• Remote sensing environmental hazards and quality