  Earth observation satellites generate large amounts of real-time data for
monitoring and managing time-critical events such as disaster relief missions.
This presents a major challenge for satellite-to-ground communications
operating under limited bandwidth capacities. This paper explores semantic
communication (SC) as a potential alternative to traditional communication
methods. The rationality for adopting SC is its inherent ability to reduce
communication costs and make spectrum efficient for 6G non-terrestrial networks
(6G-NTNs). We focus on the critical satellite imagery downlink communications
latency optimization for Earth observation through SC techniques. We formulate
the latency minimization problem with SC quality-of-service (SC-QoS)
constraints and address this problem with a meta-heuristic discrete whale
optimization algorithm (DWOA) and a one-to-one matching game. The proposed
approach for captured image processing and transmission includes the
integration of joint semantic and channel encoding to ensure downlink sum-rate
optimization and latency minimization. Empirical results from experiments
demonstrate the efficiency of the proposed framework for latency optimization
while preserving high-quality data transmission when compared to baselines.
