Characterization and monitoring of forest productivity and structure are crucial for understanding current and future forest conditions and carbon stocks. Recent strides in the capabilities of remote sensing products and upgrades in computing power offer a new synergy with high resolution forest models. When used in conjunction with fine-scale remote sensing measurements of forest characteristics, forest models provide deeper understanding of the state of the forest through time. High resolution remote sensing can inform forest models to better simulate structural realism and expand the scale of application. We seek studies that integrate high-resolution forest models with remote sensing observations to improve estimates of current ecosystem dynamics and state, including studies that investigate techniques in filling data gaps using modeling or remote sensing, studies that include novel approaches to combining modeling with remote sensing, studies that broaden the spatial or temporal coverage and studies that predict forest response to environmental change.