C Zhao, M Jia, Z Wang, D Mao, Y Wang - Remote Sensing of Environment, 2023 - Elsevier
Coastal salt marshes suffering from anthropogenic coastal development and sea level rise have attracted much attention because of their capacity for carbon sequestration and global …
CJ Crawford, DP Roy, S Arab, C Barnes… - Science of Remote …, 2023 - Elsevier
The Landsat global consolidated data archive now exceeds 50 years. In recognition of the need for consistently processed data across the Landsat satellite series, the US Geological …
Satellite remote sensing of chlorophyll-a concentration (chla) in oligotrophic and mesotrophic lakes faces uncertainties from sources such as atmospheric correction …
D Frantz, P Rufin, A Janz, S Ernst… - Remote Sensing of …, 2023 - Elsevier
The Landsat archive is one of the richest Earth observation datasets available and provides long-term data at fairly high temporal and spatial resolution globally. Temporal aggregation …
J Li, Z Wu, Q Sheng, B Wang, Z Hu, S Zheng… - Remote Sensing of …, 2022 - Elsevier
Cloud detection is a crucial step in the optical satellite image processing pipeline for Earth observation. Clouds in optical remote sensing images seriously affect the visibility of the …
Monitoring snow depth is important for applications such as hydrology, energy planning, ecology, and safety evaluation for outdoor winter activities. Most methods able to estimate …
C Zhao, M Jia, Z Wang, D Mao, Y Wang - ISPRS Journal of …, 2023 - Elsevier
Black-box algorithms are among the dominant mangrove mapping approaches with complex decision-making procedures. Model internals and tacit knowledge were neglected …
Clouds and haze often occlude optical satellite images, hindering continuous, dense monitoring of the Earth's surface. Although modern deep learning methods can implicitly …
Over large areas, land cover classification has conventionally been undertaken using satellite time series. Typically temporal metric percentiles derived from single pixel location …