Global Vegetation Cover Estimated from Remote Sensing

Dear Colleagues,

Over the past few decades, global vegetation cover has undergone significant changes influenced by both climate change and human activities. Significant greening has been observed worldwide, particularly in the northern mid-to-high latitudes, where increased vegetation coverage is responsible for such greening. Comparatively, vegetation cover in tropical and subtropical regions has not experienced significant changes, indicating relatively stable coverage over the past few decades. Such vegetation coverage changes would have large potential for climate mitigation, as well as local ecological conservation and restoration. Thus, conducting thorough studies is a high priority for estimating global vegetation cover in recent decades.

Remote sensing technologies have been developed for decades and are widely used to estimate and monitor global vegetation coverage changes, taking advantage of its relatively long-term nature and fine-scale observations. Therefore, remote sensing could serve as an important tool for estimating global vegetation cover, utilizing observations from various sensors and instruments. Machine learning has also been a popular approach for estimating global vegetation cover in recent years to specify the driving mechanisms and shape the distributions of global vegetation. This Special Issue will incorporate different useful methods and multi-sourced data to accurately estimate global vegetation cover at fine spatiotemporal scales.

Dr. Mingzhu He
Dr. Markus Hollaus
Guest Editors

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