Conference Agenda

This report will present the recent developments and accuracy validation of our project's snow remote sensing data products. In terms of snow cover area, we focused on analyzing the consistency between two snow products, VIRSS and MODIS. We found that although the NDSI obtained by the two sensors were very consistent, there were significant differences between the final snow cover area products due to differences in cloud identification algorithms. This study suggests that we should develop a cloud identification algorithm that can be applied to both VIRSS and MODIS to ensure the consistency of snow cover area data products and provide reliable data for further research on snow changes and related studies. In terms of snow depth remote sensing, we developed a machine learning-based fusion method for snow depth in the northern hemisphere. This method combined six existing snow depth remote sensing and reanalysis data, and through learning observations from nearly 20,000 stations in the northern hemisphere, obtained the fused snow depth data, which is much more accurate than existing data.

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The 2030 SDGs identify water (SDG 6), as well as vegetation/land use (SDG15) as keys parameters for providing the economic, social, and environmental well-being of the present and future generations. Remote sensing can be a powerful tool to reach these objectives and support SDG indicator analysis at different scales.

At regional and local scale, the consortium has is exploring tools to identify changes in sensitive ecosystems of the Yangtze River basin and surrounding regions. These include new approaches to study Poyang and Dongting lakes, as well as the Anhui’s small lakes. These have taken advantage of ICEYE and Radarsat data in synergy with Sentinel2 to ensure the monitoring of water extent, while IceSat and Sentinel3, Sentinel6 altimetric data have been exploited to monitor water bodies’ altitude. This acquired knowledge is crucial for the exploitation of SWOT products which first delivery will occur in summer 2023. Over Poyang, an increase in earlier draw off of the water since 2000 has an important effect on the mudflat evolution. Based on MR EO imagery, the mudflat has been increasing and the main distribution area is shifted from North to South. In the Northern area affected by sand mining, the water surface rate of the inlet channel has increased, and the overall outer edge of the mudflat is more fragmented than before. In the South side of the Ganjiang River, the delta area on the is affected by the water and sand entering the lake and is growing steadily, with the front edge of the delta extending outward for about 1.84 km.

Water quality assessment, a pilar for SDG6, requests to develop and validate processing protocols for multiple sensor systems. New advances have been done for the cCO2 estimation based on model using Sentinel-3-derived lake environmental variables and field data. Works done over sixteen lakes on the middle and lower reaches of the Yangtze basins shown that CO2 concentrations were low in the summer and autumn but high in the winter and spring with dramatic variations. The annual mean CO2 concentrations of lakes revealed that about 28% of the lakes acted as weak atmospheric CO2 sinks while the rest were sources. CO2 concentrations decreased with increasing eutrophication and decreasing lake size. With this problem of eutrophication, lacustrine ecosystem can undergo complex changes, often resulting in a shift from a clear macrophyte-dominated state to a turbid phytoplankton-dominated state. However, it’s not clear how lake transitions occur at regional and global scales. To answer this point, a long-term monitoring of 22 lakes of the Yangtze watershed have been carried out, exploiting a novel innovative and efficient three steps algorithm that can distinguish, aquatic vegetation, floating/emergent aquatic vegetation (FEAV), submerged aquatic vegetation (SAV) and algal bloom (AB). The AV showed a significant decrease over the past 37 years, mainly due to the decrease of SAV; while AB occurred with higher frequency and in more lakes. The transition from a macrophyte-dominated state to a phytoplankton-dominated aquatic systems is still ongoing in the middle Yangtze watershed. In addition, over large lakes (>500 km2), including the Taihu and Chaohu, daily MR satellite observations by developing a universal, practical, and robust algorithm to identify the spatiotemporal distribution of algal bloom dynamics. Chaohu and Taihu lakes are presenting perennial blooms with an increasing trend. Climate factors were found to be linked to changes in annual initial bloom time; while an increase in human activities was associated to bloom duration, area and frequency.

At a larger scale, an important work has been done on the distribution and dynamics of vegetation related to vegetation growth and carbon cycling, with an analysis of the impact of global climate change, changes in temperature and precipitation. Based on meteorological and remote sensing data; critical soil moisture (CSM) was used as a proxy of the land-atmosphere coupling to study the interaction process between land and atmosphere and its impact on land vegetation. Then, single models of CMIP6 were optimized through machine learning methods to develop future climate and Gross Primary Production (GPP) datasets and analyze the temporal and spatial changes of climate and GPP.

The vegetation in China has significantly increase over the last four decades, 1982-2020, with 72.34% of the regional greening. At regional scale, precipitation is appearing as a key factor affecting vegetation growth in arid and semi-arid areas such as the Mongolian Plateau, the Qinghai-Tibet Plateau, and the Loess Plateau. Precipitation resources are abundant in southeast China, and temperature is the dominant factor of regional vegetation growth. In another hand, it must be noticed that drought stress is also an important factor affecting vegetation growth. Short-term cumulative drought promotes regional vegetation greening (1-4 months), while medium-term and long-term cumulative drought inhibits vegetation greening (5-12 months). The carbon sequestration function of vegetation in southwestern and southeastern China will be affected under continuous drought conditions.

Drought conditions were analyzed through an innovative approach based on the differential correlation measure (∆Corr) that characterizes the strength of water or energy limitations. The ∆Corr detecting the response of surface water and energy to short-term surface processes. Based on climate and vegetation characteristics, sufficient variation was found in both global and grid unit CSM content. CSM content is wetter in areas with less annual rainfall, shorter root systems, and lower vegetation coverage. It was found that under three SPP scenarios in the future (2021-2100), the high-latitude regions of the Northern Hemisphere will warm significantly, while the spatiotemporal distribution pattern of precipitation shows no significant difference. Under different scenario models, GPP changes show obvious spatiotemporal heterogeneity.

Obtained results shown how EO data exploitation can provide important insight into the knowledge and understanding of keys parameters such as water resources and quality, eutrophication purposes and this from local to global scale.