GeoCrossBench is a newly proposed benchmark aimed at improving the generalization capabilities of Earth observation models amid the increasing number and diversity of remote sensing satellites. As the remote sensing field expands, models face challenges in effectively training on data from various satellite sources. GeoCrossBench addresses this issue by providing a standardized framework to evaluate and enhance cross-band generalization, ensuring models can adapt to new satellite data more robustly. This development is particularly relevant given the growing complexity in satellite data acquisition and the need for scalable training approaches. The benchmark has been positively received for its potential to advance remote sensing applications by fostering more adaptable and resilient Earth observation models. GeoCrossBench thus represents a significant step toward overcoming the challenges posed by satellite heterogeneity in the remote sensing domain.