The Spatial and Temporal Availability Differences of Cloud-Free Landsat Images Over Three Gorges Reservoir Area

Abstract

Abstract. Availability analysis of cloud-free optical remote sensing data is a prerequisite for remote sensing applications. In this study, spatio-temporal availability differences of cloud-free Landsat TM, ETM+, and OLI sensors images over Three Gorges Reservoir Area (TGRA) were analyzed from 1986 to 2019 based on the Google Earth Engine (GEE). The results show that: 1) in Summer, especially in August, the probabilities of obtaining Landsat images with no more than 30% cloud cover (CC) is higher. 2) the northeast of TGRA has higher probability of acquiring cloudless images than the southwest. 3) In TGRA, annual monitoring which require at least one cloud-free observation in a year largely unaffected by CC, but when considering seasonal monitoring, cloud contaminate will become a limitation, and monthly monitoring in this area is basically not feasible even if the three sensors data are combined. The results of this paper will provide important references for the research of using optical data in this area, and although the research area is relatively small, the analysis method and the program developed in this paper have no restrictions on the area.

Analysis and Quantification of the Distribution of Marabou (Dichrostachys cinerea (L.) Wight & Arn.) in Valle de los Ingenios, Cuba: A Remote Sensing Approach

“…Our results first highlight the importance of using cost-effective and user-friendly tools such as Google Earth Engine to assess marabou infestation in developing countries. GEE's ability to accurately locate and monitor marabou infestations over time, as well as its ability to detect the impact of human activities on the environment, make it a valuable tool for environmental management and decision making [40,41]. Furthermore, our results are consistent with previous findings that emphasize the importance of time series analysis, particularly the NDVI, for understanding the successional trajectories of both tropical forests and coastal areas [39,42].…”