Human societies have transformed terrestrial landscapes well before and throughout the Holocene through fire, cultivation, deforestation, and, more recently, large-scale industrial land-use, intensive agriculture, and forestry. Datasets that capture this trajectory of land use change represent essential boundary conditions for global climate and carbon cycle models. However, such datasets are difficult to create at high enough spatial and temporal scales, especially as we go further back in time. These legacy impacts of land use transitions is the reason why land use emissions continue to have the highest uncertainty in the global carbon budget at approximately 60%.
Over the recent decades, historical land use change datasets have evolved from coarse representation of a limited number of land use classes to complex frameworks that capture multiple land use transitions and land management practices. The integration of recent high-resolution earth observation data, LiDAR, historical archives with archeological and paleo-ecological evidence, historical maps, and dynamic vegetation modeling into long-term reconstruction workflows are enabling researchers to constrain historical LULCC at higher accuracies.
This session invites researchers working across the interface of paleo-environmental science, remote sensing, and Earth system modeling to showcase recent advances in historical and contemporary land-use reconstructions. The themes include, but are not limited to 1) long-term historical LULCC reconstructions using historical, archeological or paleo-environmental data, 2) earth observation driven approaches to quantify post-industrial LULCC, 3) harmonizing high resolution observations with millennial scale global land use forcing datasets.
We encourage interdisciplinary submissions from remote sensing scientists, ecological modelers, historical geographers, and paleoecologists to have discussions on building the next generation of LULCC datasets.