Print Email Facebook Twitter A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform Title A scalable software package for time series reconstruction of remote sensing datasets on the Google Earth Engine platform Author Zhou, J. (TU Delft Optical and Laser Remote Sensing; Central China Normal University) Menenti, M. (TU Delft Optical and Laser Remote Sensing; Chinese Academy of Sciences) Jia, Li (Chinese Academy of Sciences) Gao, Bo (Capital Normal University) Zhao, Feng (Central China Normal University) Cui, Yilin (Central China Normal University) Xiong, Xuqian (Central China Normal University) Liu, Xuan (Central China Normal University) Li, Dengchao (The First Geological brigade of Hubei Geological Bureau) Date 2023 Abstract Spatiotemporal residual noise in terrestrial earth observation products, often caused by unfavorable atmospheric conditions, impedes their broad applications. Most users prefer to use gap-filled remote sensing products with time series reconstruction (TSR) algorithms. Applying currently available implementations of TSR to large-volume datasets is time-consuming and challenging for non-professional users with limited computation or storage resources. This study introduces a new open-source software package entitled ‘HANTS-GEE’ that implements a well-known and robust TSR algorithm, i.e. Harmonic ANalysis of Time Series (HANTS), on the Google Earth Engine (GEE) platform for scalable reconstruction of terrestrial earth observation data. Reconstruction tasks can be conducted on user-defined spatiotemporal extents when raw datasets are available on GEE. According to site-based and regional-based case evaluation, the new tool can effectively eliminate cloud contamination in the time series of earth observation data. Compared with traditional PC-based HANTS implementation, the HANTS-GEE provides quite consistent reconstruction results for most terrestrial vegetated sites. The HANTS-GEE can provide scalable reconstruction services with accelerated processing speed and reduced internet data transmission volume, promoting algorithm usage by much broader user communities. To our knowledge, the software package is the first tool to support full-stack TSR processing for popular open-access satellite sensors on cloud platforms. Subject gap-fillingGoogle Earth EngineHANTSremote sensingTime series reconstruction To reference this document use: http://resolver.tudelft.nl/uuid:43bc5020-1406-432c-bd2e-32c99d156c53 DOI https://doi.org/10.1080/17538947.2023.2192004 ISSN 1753-8947 Source International Journal of Digital Earth: a new journal for a new vision, 16 (1), 988-1007 Part of collection Institutional Repository Document type journal article Rights © 2023 J. Zhou, M. Menenti, Li Jia, Bo Gao, Feng Zhao, Yilin Cui, Xuqian Xiong, Xuan Liu, Dengchao Li Files PDF A_scalable_software_packa ... atform.pdf 3.39 MB Close viewer /islandora/object/uuid:43bc5020-1406-432c-bd2e-32c99d156c53/datastream/OBJ/view