The traditional field-based measurements of carbon dioxide (pCO(2)) for inland waters are a snapshot of the conditions on a particular site, which might not adequately represent the pCO(2) variation of the entire lake. However, these field measurements can be used in the pCO(2) remote sensing modeling and verification. By focusing on inland waters (including lakes, reservoirs, rivers, and streams), this paper reviews the temporal and spatial variability of pCO(2) based on published data. The results indicate the significant daily and seasonal variations in pCO(2) in lakes. Rivers and streams contain higher pCO(2) than lakes and reservoirs in the same climatic zone, and tropical waters typically exhibit higher pCO(2) than temperate, boreal, and arctic waters. Due to the temporal and spatial variations of pCO(2), it can differ in different inland water types in the same space-time. The estimation of CO2 fluxes in global inland waters showed large uncertainties with a range of 1.40-3.28 Pg C y(-1). This paper also reviews existing remote sensing models/algorithms used for estimating pCO(2) in sea and coastal waters and presents some perspectives and challenges of pCO(2) estimation in inland waters using remote sensing for future studies. To overcome the uncertainties of pCO(2) and CO2 emissions from inland waters at the global scale, more reliable and universal pCO(2) remote sensing models/algorithms will be needed for mapping the long-term and large-scale pCO(2) variations for inland waters. The development of inverse models based on dissolved biogeochemical processes and the machine learning algorithm based on measurement data might be more applicable over longer periods and across larger spatial scales. In addition, it should be noted that the remote sensing-retrieved pCO(2)/the CO2 concentration values are the instantaneous values at the satellite transit time. A major technical challenge is in the methodology to transform the retrieved pCO(2) values on time scales from instant to days/months, which will need further investigations. Understanding the interrelated control and influence processes closely related to pCO(2) in the inland waters (including the biological activities, physical mixing, a thermodynamic process, and the air-water gas exchange) is the key to achieving remote sensing models/algorithms of pCO(2) in inland waters. This review should be useful for a general understanding of the role of inland waters in the global carbon cycle.