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Soil moisture (SM) is an essential parameter for understanding the interactions and feedbacks between the atmosphere and the Earth's surface through energy and water cycles. Knowledge of the spatiotemporal distribution of land surface SM has long been a challenge in the remote sensing community. Over the past 50 years, electromagnetic spectra, from the optical/thermal to the microwave regions, have been intensively investigated for SM retrieval, providing a number of algorithms, models and products that are available for actual applications nowadays. However, certain issues with respect to retrieval accuracy, spatiotemporal resolution, and data consistency exist and remain unsolved between the state-of-the-art of SM retrieval and readily-used SM datasets for various domains at field, regional/watershed or global scales. In particular, several new theories and algorithms for SM retrieval proposed in recent years have not been well documented in previous articles. Therefore, a critical review of the established and emerging SM retrieval methods with respect to their advantages and disadvantages is necessary. In present study, future directions for each method are highlighted to address the scientific challenges of SM retrieval in the new era of rapid data expansion. [ABSTRACT FROM AUTHOR]