# Advances in Quantitative Earth Remote Sensing: Past, Present and Future
## 2 Contributions  
We have accepted and published five innovative papers after peer review in this special issue of _Sensors_. The first paper by [PERSON] et al. [1] describes how Earth Polychromatic Imaging Camera (EPIC) observations can be used for studying large lakes and oceans based on their exchange of solar radiation with atmosphere. EPIC contains ten spectral channels in the 317-780 nm solar spectral range: EPIC data are used in a variety of scientific investigations, including the study of the global ozone levels, atmosphere aerosol index and aerosol optical depth, UV reflectivity of clouds over land and ocean, cloud height over land and ocean, and vegetation indices. In this paper, EPIC observations from narrow channels centered near 443, 551, and 680 nm were used to measure ocean color, an indicator of biological and biogeochemical processes that control the web of life in oceans, for different geographical regions, globally. To remove the effects of intervening atmosphere between the sensor and Earth surface, the authors used a modified version of a multichannel atmospheric correction algorithm for NASA Moderate Resolution Imaging SpectroRadiometer (MODIS) onboard the Terra and Aqua satellites that are also used for monitoring of ocean color. The authors report three case studies on water leaving reflectance retrievals using EPIC observation for a large turbid river, inland lakes, and oceans. They conclude that a future ocean color instrument onboard a satellite at the L1 point, which provides continuous view of the full sunlit disk of the Earth, will complement and extend ocean color observations from the polar orbiting and geostationary Earth-observing satellite, by enhancing current measurements from these sensors/satellites in both spatial and temporal domains. The second paper, by [PERSON] et al. [2], presents an improved bathymetric mapping of coasts and lakes using multidecadal Landsat and newly established European Sentinel satellite observations. Data from both satellites are available freely through a variety of portals on the world wide web and the Google Earth Engine, which also offers processing of large datasets, such as the entire Landsat records. The bathymetry of nearshore areas and lakes are affected by the change in sediment transport and dispersal pathways. There is a need for accurate bathymetric models for use in scientific research and management of these areas. Recent advances in space-based observations has revolutionized the availability of bathymetric data, offering new means for mapping of the coasts and lakes, and even remote islands with limited access. This paper is focused on assessing the suitability of Sentinel-2 and Landsat-8 measurements for the bathymetric mapping of coastal and lake areas. The authors used an empirical bathymetric model based on a random forest (RF) model, and the available high-resolution LiDAR bathymetric data for Mobile Bay, Tampa Bay, and Lake Huron for this study. They obtained all reference datasets from the National Oceanic and Atmospheric Administration (NOAA) National Geophysical Data Center (NGDC). Their results illustrate that the satellite-based bathymetry is suitable for obtaining depths of up to 10 m for coastal regions and up to 30 m for the lakes they studied. The root-mean-square error (RMSE) for derived data varied between 1.99 m and 4.74 m for the three cases studied. When they used the RF model, the RMSE for the bathymmetric model improved to 1.13 m and 1.95 m. Their comparative analysis suggests that Sentinel-2 has a slight edge over Landsat-8 observations when they used the empirical approach. However, they obtained a better bathymetric model when they used the RF model and Landsat-8 observations as compared with Sentinel-2. This study demonstrates that freely available Landsat 8 and Sentinel-2 observations are suitable for obtaining accurate and up-to-date bathymetric information for relatively large areas in a short period of time. The third paper, by [PERSON] et al.