{"id":14528,"date":"2021-09-06T14:52:59","date_gmt":"2021-09-06T13:52:59","guid":{"rendered":"https:\/\/www.innovationnewsnetwork.com\/?p=14528"},"modified":"2024-01-18T15:13:53","modified_gmt":"2024-01-18T15:13:53","slug":"satellite-advancements-fine-scale-observation-earths-surface","status":"publish","type":"post","link":"https:\/\/www.innovationnewsnetwork.com\/satellite-advancements-fine-scale-observation-earths-surface\/14528\/","title":{"rendered":"Satellite advancements for the fine-scale observation of the Earth\u2019s surface"},"content":{"rendered":"
The Earth has suffered vast environmental changes which are closely connected to anthropogenic activities. Satellite remote sensing presents a quantitative method of observing these changes but is frequently restricted to coarse spatial or temporal resolutions. Now, the arrival of Planet\u2019s Dove satellites \u2013 a constellation of CubeSats comprised of over 190 satellite sensors to deliver daily and global coverage at a 3-metre resolution \u2013 present an unparalleled opportunity for fine-scale observation of the Earth\u2019s surface.<\/p>\n
There are, however, challenges with CubeSat observations that are currently inhibiting its wider application. These include: recurrent clouds and cloud shadows that can interfere with the satellite signal; CubeSat observations source from more than 190 satellite sensors with variable sun angles, resulting in data discrepancy issues across different sensors; and precise biophysical interpretation of satellite signal needs improvement.<\/p>\n
Dr Jin WU and Dr Jing WANG from Global Ecology and Remote Sensing (GEARS) Lab at the School of Biological Sciences, The University of Hong Kong (HKU), undertook research to investigate these shortcomings by developing innovative observational techniques that deliver a greater accuracy on observing Earth\u2019s fine-scale changes from space.<\/p>\n
The research group has now established an automatic cloud and cloud shadow screening technique for CubeSats. It leverages the spatial and temporal information of satellite reflectance bands and has been shown to allow cloud and shadow screening with the greatest precision and least sensitivity to land cover type. The study\u2019s findings, therefore, improve the observation of atmospheric cloud covers whilst enhancing the data quality measurements for land-surface monitoring and biophysical extraction.<\/p>\n