Conference Agenda

ReSCCoME addresses research and development activities that focus on the way, in which the rapidly increasing amount of high-resolution EO data can be used for the surveillance of marine coastal environments, and how EO sensors can detect and quantify processes and phenomena that are crucial for the local fauna and flora, for coastal residents and local authorities. During the first project phase, we focussed on the SAR monitoring of exposed intertidal flats, of nonlinear oceanic internal waves, and of offshore wind installations near the coast.

SAR data acquired from intertidal flats are being used to assess their economic use through intensive aquacultures and to identify areas of strong morphodynamics. Polarimetric decomposition of Gaofen-3 SAR data of various spots on the Chinese coast revealed that aquacultural rafts show different backscattering mechanisms than the surrounding mud flats. Moreover, Sentinel-1 SAR-C data are used to generate topographic maps of extended intertidal flats on the German North Sea coast. Those maps, derived for different time periods, will be used to assess morphodynamic changes.

Nonlinear internal waves (NLIW) around Hainan Island in the South China Sea play a critical role in local mixing, thermohaline circulation and nearshore ecosystem. However, the generation of NLIWs around Hainan Island are rarely studied. We have been investigating the source sites and generation mechanisms of NLIWs around Hainan Island based on the synergistic analysis of SAR observations, field measurements and numerical analyses. It is found that the NLIWs in different regions around Hainan Island have different generation regimes.

Offshore wind installations in the South China Sea near the coast, which trigger a new demand for studying the effects of horizontal wind speed gradients and the wind power variation within the coastal zone. We have retrieved wind maps at 10 m height from Sentinel-1 SAR-C and Envisat ASAR observations and found that generally, the speed of the prevailing south-easterly winds and wind power declined by about 8% and 22%, respectively.

Apart from the various ongoing research activities, efforts have been undertaken to stimulate the exchange of Young Scientists and to educate them through dedicated Summer Schools. The efforts, however, were strongly affected by the ongoing pandemic.

The project aims at exploiting microwave satellite measurements to generate innovative added-value products to observe coastal areas characterized by harsh environments, even under extreme weather conditions. The following added-values products are addressed: water pollution, coast classification and erosion monitoring, ship and metallic target observation, typhoon monitoring.

Up to the mid-term deadline the following activities have been addressed:

Water pollution: Theoretical scattering models (under monostatic and bistatic configurations) have been developed to predict sea surface scattering with or without surfactants. In the monostatic case, theoretical predictions have been contrasted with actual measurements collected by the Synthetic Aperture Radar.

Target detection: Multi-polarization backscattering from a known ship observed at different incidence angles. The analysis is carried on using metrics based on both power and phase information.

Extreme weather events: SAR and ancillary scatterometer and model-based information are used to estimate the wind vector from SAR scenes under moderate and extreme weather conditions.

All this matter will be detailed in the proposed piece of study.

The Earth's surface waters are a fundamental resource and encompass a broad range of ecosystems that are core to global biogeochemical cycling and food and energy production. The mounting and conflicting pressures from the number of users and uses, coupled with population growth, industrialisation, land use intensification and climate change bring into focus the urgent need for the sustainable management of our aquatic resources and space. The last decades are witnessing a revolution in Earth observation (EO) capabilities for characterising coastal and inland water dynamics through the Copernicus programme of satellite missions (Sentinel 1/2/3) and Chinese Earth observation missions (e.g. from HY-1). The increasing monitoring capabilities are now extending satellite applications to near-shore and transitional systems such as lagoons and estuaries.

Our project aims to develop and validate innovative products for transitional and coastal waters to support and improve the water ecosystem services, sustainable management and security. It is widely recognised that the successful uptake of new Earth observation (EO) products and services is predicated by reliable and robust calibration and validation activities. Inland, transitional and near-shore coastal waters are spatially and temporally heterogeneous regarding their optical properties. It is further widely recognised within the EO and user communities, that there exists a significant lack in high quality data for calibration, validation, and uncertainty assessment. As part of the H2020 CoastObs, CERTO, NSFC and CAS projects, dedicated effort was made to collect high quality in-situ data from coastal and transitional ecosystems, including ria de Vigo, lagoons in the Danube Delta, Taihu Lake, Yuqiao Reservoir, and Danjiangkou Reservoir. The collection of new in-situ data has been challenged by the Covid-19 related travel restrictions and cruise operation difficulties in the Black Sea, which is one of our case study areas. Nevertheless, during this reporting period in-situ data were collected in the Razelm-Sinoe lagoon system,rivers and transitional waters in Hainan Island and Yantai coastal region in Shandong Peninsula coast in 2021 and 2022. Typically, the in-situ data collected included above-water Remote Sensing reflectance (Rrs), Inherent optical properties (absorption, scattering, attenuation, backscatter), chloroplastic pigments, suspended sediments (inorganic, total), coloured dissolved organic material, suspended particles composition, primary production, and size fractionated pigments. Radiometric data collected here were used in the Atmospheric Correction Intercomparison Exercise (ACIX-Aqua), a joint NASA – ESA activity (Pahlevan et al. 2021). Detection algorithms and products for Harmful Algal Blooms (HABs) products were developed based on Sentinel-3 OLCI, HY-1C and ground-based multispectral remote sensing images respectively. HABs detected by Sentinel-3 OLCI included a regional neural network model for the retrieval of chlorophyll-a concentration and innovative species indicators based on machine learning methods (i.e. support vector machines) for Pseudo-nitzschia spp. and Alexandrium minutum. According to the validation results, Pseudo-nitzschia spp. products are quite robust and reliable, detecting over 90 % of the blooms with a false alarm rate around 10 %. A manuscript on the detection of Pseudo-nitzschia spp. has been submitted. HABs detected by HY-1C investigated the ultraviolet (UV) reflection spectra of floating cyanobacteria blooms and identified that the blooms have significant UV reflection features associated with the floating status. HABs detected by ground-based multispectral remote sensing represent a new technical method to dynamically monitoring cyanobacteria blooms which can operate under cloud cover and can provide accurate and continuous spatiotemporal patterns of the blooms. Two articles have been published in regards to the detection of HABs (Suo et al., 2021; Zhao et al., 2021). For the marine oil spills (MOS), a new lab-derived HSV colour model was proposed for the optical quantification of oil emulsions using multi-band coarse-resolution imagery and one article has been published (Jiao et al., 2021). Other relevant work during this reporting period included the development of a meta-classification framework (Werther et al. 2021) to assess the trophic status of nearshore and inland waters, and development of water clarity products for Taihu Lake (Yin et al., 2021), Yangtze River (Zhao et al., 2021) and lakes across Sri Lanka (Somasundaram et al., 2021). These will provide the basis the estimation of phytoplankton size classes and the primary production in transitional systems. We also worked on the development of new frameworks for optical conditions found in transitional systems. In-situ data of biogeochemical and inherent optical properties were used to characterise the relationships among optical clusters in inland, coastal, and transitional systems. We provide new information on the optics in these systems, which is important for optical models and remote sensing of coastal and transitional waters.

Coastal zones are essential for the socio-economic well-being of many nations [1] Coastal regions have multiple uses, needs and opportunities, and are particularly exposed to extreme events and climate change. Many key sectors are affected by long-term effects in these zones, such as the monitoring of public/private infrastructures, cultural/natural heritage preservation, risk management, and agriculture. The combined effects of sea level rise (SLR), tidal evolution, modulated ocean currents and extreme events can have numerous impacts on coastal, river delta, and inland water zones, including water management, which in turn lead to cascading and unpredictable impacts on other sectors. The ESA-DRAGON V GREENISH project [2] aims to provide extensive research and development analyses of areas in Europe and China subject to climate change induced (e.g., Sea Level Rise, flooding, and urban climate threats) and anthropogenic disasters (e.g., ground subsidence over reclaimed-land platforms), with the goal to improve the knowledge and develop new remote-sensing methods. Global sea-level is rising, and tides are also changing worldwide, and these risks are accompanied by increasing concerns about the growing urbanization of the world’s low-lying coastal regions and related coastal hazards (e.g., flooding). On the other hand, Inland water bodies such as lake and river system also experience substantial degradation with rapid economic development.

The main project goals are: i) To study the ground deformation in coastal/deltaic regions with conventional and novel interferometric SAR approaches; ii) To monitor changes in urbanized areas via coherent and incoherent change detection analyses; iii) To study interactions between ocean currents and coasts, such as coastal erosion, using high resolution optical and SAR satellite images; iv) To properly assess SLR, tidal evolution, and hydrogeological risks in urban coastal areas; v) To study the interactions between Poyang Lake and its connecting rivers. vi) To develop atmospheric phase screen correction methods in multi-temporal SAR images. vi) To develop interactive maps of coastal, urban, and inland zones susceptible to primary and secondary risks via GIS, and finally vii) To train Young Scientists.

A number of planned activities have already started and some results have already been achieved, which will be presented at the on-line event scheduled for October 2022. Specifically, we processed a sequence of SAR data related to the area of Venice Lagoon and the Po ‘river system to create a base for further analyses devoted to analyzing the effect of extreme weather conditions and sea level rise in the lagoon [3]. To this aim, we investigated the impact of a recent flood event that occurred in the area in 2019. In this context, we applied/tested methods of incoherent change detection [4]-[5]. Some experiments have also been carried out in the city of Shanghai to apply artificial intelligence methods with TerraSAR-X image time-series in urban context to reveal changes triggered by human activities. Assessment and analysis of capability of disaster reduction and crucial index at district Level in Shanghai have also been made. We also investigated the recent decade deformation time-series in Chongming Island of Shanghai by using four space-borne Synthetic Aperture Radar (SAR) satellite datasets.

The risk of flooding in the coastal area of the Shanghai megacity was further characterized. To this aim, two independent sets of synthetic aperture radar (SAR) data collected at the X- and C-band through the COSMO-SkyMed (CSK) and the European Copernicus Sentinel-1 (S-1) sensors have been exploited. By assuming that the still extreme seawater depth is chi-square distributed, the probability of waves overtopping the coast was estimated. We also evaluated the impact on the territory of potential extreme flood events by counting the number of very-coherent objects (at most anthropic, such as buildings and public infrastructures) that could be seriously affected by a flood. To forecast possible inundation patterns, we used the LISFLOOD-FP hydrodynamic model [6]. Experimental results, which are detailed in [7], showed that two coastline segments located in the southern districts of Shanghai, where the height of the seawall is lower, had the highest probability of wave overtopping and the most significant density of coherent objects potentially subjected to severe flood impacts. The slowly developing landslides in the districts of Istanbul have also been investigated using S-1 sensors [8].

Other planned activities are in course for: i) the analysis of the Istanbul/Marmara-Sea coastal environment, ii) the investigation of large-scale coverage of Bohai Rim Region ground subsidence caused by underground resources extraction such as underground water, oil, gas and brine over Bohai rim region, iii) the analysis of ocean currents and the SLR impact.

References

1. Sengupta, D.; Chen, R.; Meadows, M.E. Building beyond land: An overview of coastal land reclamation in 16 global megacities. Appl. Geogr. 2018, 90, 229-238.
2. https://dragon5.esa.int/projects/
3. Mastro P, Calò F., Giordan D., Notti D., Pepe A., “On Monitoring the Impact of Floods and Extreme Weather Events in Protected Cultural Heritage Areas: The Venice Lagoon Case Study”, proceedings of Living Planet Symposium, 23 – 27 May, 2022, Bonn, Germany.
4. Lu, D.; Mausel, P.; Brondizio, E.; Moran, E. Change Detection Techniques. Int. J. Remote Sens. 2004, 25, 2365–2407
5. Mastro, P.; Masiello, G.; Serio, C.; Pepe, A. Change Detection Techniques with Synthetic Aperture Radar Images: Experiments with Random Forests and Sentinel-1 Observations. Remote Sens. 2022, 14, 3323. https://doi.org/10.3390/rs1414332.
6. Bates, P.D.; De Roo, A.P.J. A simple raster-based model for flood inundation simulation. J. Hydrol. 2000, 236, 54–77
7. Tang, M.; Zhao, Q.; Pepe, A.; Devlin, A.T.; Falabella, F.; Yao, C.; Li, Z. Changes of Chinese Coastal Regions Induced by Land Reclamation as Revealed through TanDEM-X DEM and InSAR Analyses. Remote Sens. 2022, 14, 637. https://doi.org/10.3390/rs14030637.
8. Bayik, C.; Abdikan, S.; Ozdemir, A.; Arikan M.; Balik Sanli F.; Dogan U. Investigation of the landslides in Beylikdüzü-Esenyurt Districts of Istanbul from InSAR and GNSS observations. Nat Hazards 109, 1201–1220 (2021).

It is presented in this paper some recent progresses of ESA-MOST China Dragon Cooperation Program “Synergistic Monitoring of Ocean Dynamic Environment from Multi-Sensors (ID. 58009)” including: (1) Assessment of ocean swell height observations from Sentinel-1A/B Wave Mode against buoy in situ and modeling hindcasts; (2) Quantifying uncertainties in the partitioned swell heights observed from CFOSAT SWIM and Sentinel-1 SAR via triple collocation; (3) Up-to-Downwave asymmetry of the CFOSAT SWIM fluctuation spectrum for wave direction ambiguity removal; and (4) Validation of wave spectral partitions from SWIM instrument on-board CFOSAT against in situ data.

This is the first presentation of quasi-synchronous spaceborne synthetic aperture radar (SAR) high-resolution images acquired from C-band Radar Constellation Mission (RCM) and RADARSAT-2 consisting of quad-polarization (HH+HV+VH+VV) wide swath observations of Hurricane Epsilon. These measurements clearly show that the denoised HV- and VH-polarized normalized radar cross sections (NRCSs) have great consistency. NRCS values at HV- and VH-polarizations are more sensitive to wind speeds and less sensitive to incidence angles or wind directions than those at HH and VV for hurricane-force winds. For large incidence angles and high wind speeds, the sensitivity of HH-polarized NRCS to wind speed is higher than that of VV. HH- and VV-polarized NRCS gradually lose wind direction dependency at high winds. It is notable that the time interval between the two SAR acquisitions is only 3 minutes. This allows for a direct comparison of HV- and VH-polarized images to investigate the variations of high-resolution backscattering within the hurricane vortex, thereby revealing the most dynamical areas. An asymmetric dynamic is observed around the eye of Hurricane Epsilon, based on positive and negative differences (VH–HV) in the western and eastern parts of the eye. The impacts of rain on quad-polarized NRCS are also examined using collocated rain rates from the Global Precipitation Mission (GPM) and wind speeds from the Soil Moisture Active Passive (SMAP). Significant rain-induced NRCS attenuations are about 1.7 dB for HH and VV, and 2.2 dB for HV and VH, when the rain rate is 20 mm/hr. These attenuations are associated with rain-induced turbulence and atmospheric absorption. This work shows that the collocated RCM and RADARSAT-2 hurricane observations provide a unique analysis of synoptic and joint C-band measurements of the ocean surface in quad-polarization; this is noteworthy in view of preparations for the next generation of dual-polarization scatterometer (SCA) onboard MetOp-SG.

Ocean wave is one of the important objects of ocean observation by satellite microwave remote sensing. Since the successful launch of TOPEX/Poseidon in 1992, the satellite altimeters had provided the abundant global ocean wave height observations. But the altimeters can only observe the ocean wave height of the points under the satellite along track. Synthetic Aperture Radar (SAR) can obtain ocean wave spectrum data with a certain swath observation, but SAR ocean wave data have the issue of wave wavelength truncation. China-France Oceanography Satellite (CFOSAT) was launched on 20^th Oct. 2018, and the equipped SWIM on CFOSAT provided a new means for global ocean remote sensing observation. In this study, CFOSAT SWIM ocean wave observation data are evaluated by buoy and altimeter data firstly. The nadir and non-nadir ocean wave data of SWIM are compared to buoys and altimeter data. Then the study on ocean wave data fusion based on multi-source satellite remote sensing is carried out, and the global ocean wave remote sensing data from 2016 to 2020 are generated by using HY-2 series, sentinel-3 series, jason-3 altimeter, Sentinel-1 SAR and CFOSAT SWIM ocean wave data. In addition, the components of ocean waves are identified according to the wave age by combining the sea surface wind data, and the swell remote sensing fusion is carried out to generate global ocean swell products with the period more than one year. Finally, the preliminary analysis of ocean wave characteristics is carried out with the global ocean wave products produced in this study.

A SAR internal wave amplitude inversion algorithm based on Euler numerical simulation is proposed. The traditional satellite SAR internal wave amplitude inversion algorithm is based on the analytic relationship between the half width and the amplitude of the internal solitary wave revealed by the KdV equation or its variants. Those methods often underestimate the internal wave amplitude. There are at least two reasons for this problem: 1) KdV and its variants are insufficient to accurately describe the nonlinear behavior of large-amplitude internal waves; 2) The half-width of internal waves on the sea surface observed by SAR are different from that on the water layer where the maximum vertical displacement is located. The proposed new method iteratively conducts the numerical simulation of internal waves with different amplitudes. The best amplitude is obtained when the simulated half-width of the internal waves apprearing on the sea surface is most close to the half-width observed by SAR.

However, there are two possible amplitudes for one half-width. The inversion algorithm has to choose one of the two amplitudes. Such selection is done by comparing the simulated SAR NRCS modulation corresponding to the two amplitudes with the observed SAR NRCS modulation.

Case studies in multiple sea areas around the world show that the amplitude accuracy obtained by the new SAR internal wave amplitude inversion algorithm is significantly better than the KdV algorithm. In addition, in order to accelerate the convergence of the model at large amplitudes, the Miyata equation was used to calculate the initial flow field.

HY-1C and HY-1D are the two ocean color satellites in China which play the important role in routine work of global marine environment monitoring launched separately in 2018 and 2020. The overall objective of HY-1 serial satellite is to monitor global ocean color and SST (Sea Surface Temperature), as well as the coastal zones’ environment. The China France Oceanography Satellite (CFOSAT) and Haiyang-2B (HY-2B) satellites were successively launched in China in 2018. As missions for measuring the dynamic marine environment, both satellites can measure the nadir significant wave height (SWH). Sentinel-2A/B satellites were launched in 2015 and 2017 separately. In this project, all these satellites data have been used to monitor marine disaster and environmental changes. Based on the various methods and different data types, satellite remote sensing monitoring research have been conducted in several typical marine disasters and dynamic environment changes. The results show the advantages both in new algorithms and multiple satellite data applications. The main developments in the mid-term of the project are as follows:
1) Using HY-1C/D and Sentinel-2 satellite data, this project investigates the sea ice, oil spill and green tide disaster in Bohai Sea and the Yellow Sea, as well as the East China Sea. The results show that both HY-1
C/D and Sentinel satellite data have played an important role in ocean ecological disaster monitoring. It’s deserved to point out that the Coastal Zone Imager (CZI) on-board HY-1C/D displays much powerful performance in operational monitoring of marine spills, green-tides and sea-ice disasters because of the large width, rapid coverage and high signal-to noise ratio of data. According to the characteristics of different spatial resolution data, we develop a comprehensive method to classify the difference of monitoring results using various satellite data which could improve the accuracy of greed-tide detection and coherence the green-tide bio-mass evaluations resulted from different satellite data.
2) Based on the time series HY-1C/D satellite data in 2019-2021, the long-term oil spills detection has been conducted in China Seas and coherent areas. The results show that it’s possible to distinguish the various spill types, for example the emulsified and non-emulsified oils, using the CZI satellite data in the condition of different sun-glint reflections which also displays the outstanding advantages of HY-1C/D data applications. According to the 3 years data analysis, the spatial patterns of oil spill distributions have been conducted for the first time in the China Seas.
3）In this project, the HY-2B altimeter and CFOSAT nadir SWHs have been validated against the National Data Buoy Center (NDBC) buoys and the Jason-3 altimeter SWH data, respectively, which resulted in CFOSAT nadir SWH having the best accuracy and HY-2B having the best precision. The SWHs of the two missions are also calibrated by Jason-3 and NDBC buoys. Following calibration, the root mean square error (RMSE) of CFOSAT and HY-2B are 0.21 and 0.27 m, respectively, when compared to Jason-3, and 0.23 and 0.30 m, respectively, compared to the buoys. Our results show that the two missions can provide good-quality SWH and can be relied upon as a new data resource of global SWH.
4）Using simultaneous observations of wind and wave fields by the CFOSAT, this project reports preliminary investigation results of the typhoon waves during the passage of super typhoon Lingling (2019) over the China offshore waters. The results show that the significant wave heights (SWHs) are over 5 m on the right side of the typhoon track for wind speeds over 14 m s-1, agreeing with the theoretical estimates. The dominant waves have wavelengths of 150 – 180 m, and propagate eastward for northwestward blowing winds. The misalignments of the wind and wave directions increase with the distance from the typhoon center, agreeing with theoretical prediction. We also present the typhoon monitoring results with multiple satellites such as CFOSAT, HY-2B and ASCAT.

Better prediction of sea state integrated parameters has a key role in the estimate of momentum and heat fluxes exchanges between ocean and atmosphere. By using deep learning technique we are now able to retrieve Significant Wave Height on the wide swath of scatterometer, as proposed by Wang et al. (2021). The objective of this work is to assess the impact of assimilating wide swath SWH and directional wave spectra from CFOSAT and Seninel-1 on the wave forecasting. We also investigated the impact of improved wave forcing on the ocean mixed layer in a coupled experiment of wave model and ocean model.

During the DRAGON-5 project we have processed two years of wide swath SWH from HY-2B-2C and CFOSAT mission. Wave model runs have been performed with data assimilation and control run for this long period. The validation of the results have been implemented with independent wave data from altimeters and also from buoys networks.

The results show the capacity of using wide swath SWH and directional wave spectra to track and well capture the initial conditions of swell generated in severe storms. We also highlight the complementary of using SWIM and SAR wave spactra for different wavelength scales. This significantly improves the wind-wave growth in critical ocean regions such as the Southern ocean.

Furtehr comments and conclusions will be given during the oral presentation.

Sea ice is a highly sensitive indicator of past and present climate change. The demand for getting comprehensive, continuous, and reliable sea ice information from multi-source satellite data is growing as a result of climate change and its impact on environment, regional weather conditions, and on human activities such as operations in ice-covered ocean regions. This paper provides an overview of the Dragon 5 project dealing with synergistic monitoring of arctic sea ice by multi-source remote sensing data. For operational ice charting, new methods were developed to classify sea ice types from SAR imagery and CFOSAT SWIM data. Operationally used dual-polarization C-band wide-swath data were complemented by corresponding L-band images, and the benefit of an L- and C-band combination for ice type separation and ice feature detection for winter and summer conditions was assessed. The discrimination ability of sea ice types at small incidence angle provided by CFOSAT SWIM data was investigated and analyzed. The polarimetric backscatter behavior of sea ice in L-, S-, and C-band SAR images was compared to spatially and temporally coincident airborne SAR campaign data. A second topic included implementation and development of sea ice concentration (SIC) estimation and SIC noise reduction algorithms with the Chinese microwave radiometers such as e.g. the HY-2 Microwave Radiometer and the FY-3 Microwave Radiation Imager. We investigated the brightness temperature signatures of different surface types in various sea ice and weather conditions. The uncertainty and error statistics of the retrieved SIC are determined using validation data from in-situ measurements and high-resolution SAR satellite data. Thirdly, we proposed sea ice thickness retrieval algorithms from SAR and altimeter data (e.g. CryoSat-2, Sentinel-3 and HY-2). Especially, the consistency and intermission bias were compared and assessed by using different altimeters, upward looking sonar (ULS) instruments and Operation IceBridge (OIB) data. A method of merging multiple altimeter data to improve the temporal-resolution of the ice thickness product was proposed. Another effort was to develop robust and automated methods for iceberg detection in sea ice and on the open ocean. The study analyzed and evaluated the capability of the proposed methods using different radar frequencies, and in dependence of spatial resolution, incident angle, and the surface conditions around the icebergs.

High Mountain Asia (HMA), including the Tibetan Plateau and the adjacent mountains, is the region with the largest ice masses in the world. Known as the "Water Tower of Asia", meltwater from snow and glaciers feeds the major of Asia's rivers and is an important freshwater resource, affecting the regional water cycle and ecology. Here, we combine Earth System Observations (ESOs) and a novel eco-hydrological model to deliver a new understanding of the cryosphere and water cycle of key water towers of High Mountain Asia (HMA). We focus on blue (runoff) and green (evapotranspiration) water interactions in HMA, to integrate water supply changes due to a vanishing cryosphere with the effect of vegetation to dampen or amplify those changes, especially in periods of droughts. Our investigationstrategy has three steps, and we have progressed substantially on all three.

In the first step, we aimed to substantially advance our understanding of cryospheric, vegetation and land surface changes from remote sensing observations at benchmark sites. We have generated snow cover and glacier extent, glacier mass balance, glacier flow velocity, soil moisture, snow water equivalent, snow and glacier albedo, snow and glacier radiation balance. We studied snow cover variability and its impact on glaciers in the high mountain ranges of the Tarim Basin using multi-temporal remote sensing data. We carried out snow cover monitoring by using Landsat 8 / OLI clear sky condition data with a spatial resolution of 30m. Due to the complex terrain of the mountainous area, in view of the general overestimation problem of the normalized snow cover index method in the Himalayas, we used the support vector machine (SVM) classification method to select the snow cover training samples of different terrain, shadow and other conditions on a scene-by-scene basis to monitor snow accumulation from 2013 to 2020. Using Sentinel-2 as a reference, our retrievals gave a correlation coefficient above 0.95, and root mean square error about 0.1%. We produced a Global Daily-scale Soil Moisture Fusion Dataset (GDSMFD) for the period (2011-2018) at 25km spatial resolution by applying the Triple Collocation Analysis (TCA) and Linear Weight Fusion (LWF) methods. The data set was evaluated against in-situ measurements at 331 sites worldwide, including 57 sites in China, including all the permanent observatories on the Tibetan Plateau. We retrieved glacier albedo in the Western Nyainqentanglha Mountains (WNM) with MODIS data to characterize its spatiotemporal variability from 2001 to 2020. Glacier albedo experienced large inter-annual fluctuations, with an important decreasing trend of 0.043±2.2×10-4 per decade. A new parameterization of snow albedo was developed by combining WRF estimates of snow depth and age with MODIS retrievals of snow albedo, and led to significant relative reductions in RMSE and increases in correlation coefficients in WRF predictions of air temperature, albedo, sensible heat flux and snow depth.
Two advanced algorithms to retrieve land surface albedo and aerosol amount and properties were developed to improve: a) the characterization of the land surface background to separate the surface and atmospheric signals in aerosol retrievals and b) the separation of direct and diffuse irradiance in the retrieval of land surface albedo. The correlation of snow and ice albedo with aerosol loading was documented by comparing the evolution of Aerosol Optical Depth (AOD) at the ITP Nam Co observatory with glacier albedo in the Western Nyainqentanglha Mountains (WNM) during 2009 – 2018. We optimized the procedure to extract a Digital Elevation Model (DEM) from ZiYuan-3 (ZY-3) Three-Line-Array (TLA) stereo images and estimated the geodetic mass balance of glaciers in two areas of the Nyainqentanglha Mountains (NM) using ZY-3 DEMs and the C-band Shuttle Radar Topography Mission (SRTM) DEM in the periods 2000–2013, 2013–2017 and 2000–2017.
A time series of glacier surface velocity in the Parlung Zangbo Basin, southeast Tibetan Plateau, was generated applying the normalized image cross-correlation method to Sentinel 2 (S2) MSI and Landsat-8 (L8) OLI image data from 2013 to 2020.
Enhanced-resolution passive microwave satellite data (PMW) were used to investigate the Tibetan Plateau Lake Ice Phenology (PMW LIP). The Freeze Onset (FO), Complete Ice Cover (CIC), Melt Onset (MO), and Complete Ice Free (CIF) dates were derived for 109 lakes, including 22 lakes for the period 1978 to 2021 and 87 lakes for 2002 to 2021.

Our second step of investigation focuses on generating glacier-specific altitudinal surface mass balance profiles that provide patterns of changes in glacier mass balance at the project study sites. Our approach is based on high-quality digital elevation change and glacier surface velocity datasets along we estimated ice thickness by applying the continuity equation. We derived multidecadal altitudinal mass balance profiles and quantified the equilibrium line altitude and accumulation area ratio for over 5000 glaciers across High Mountain Asia. We applied high resolution Pleiades, Deimos, and UAV datasets to retrieve precise glacier thinning and velocity datasets for the project selected catchments. . These results provide a crucial dataset to validate the eco-hydrological land surface model including its glacier components.

In the third, integrative step, we produce simulations of the land-surface interactions across the cryosphere, hydrosphere and biosphere of the selected study catchments. We used the land-surface model Tethys-Chloris, which describes both vegetation biophysics and cryospheric processes such as snow and ice melt, snow gravitational redistribution and snowpack processes. We have setup the model for five of the study catchments to date, forced with downscaled ERA5 data . We carefully validated the model simulations with the multiple datasets obtained in step one and two. The latent heat flux by snow sublimation and evapotranspiration can account for water losses as high as ice melt.

Part 1, Glacier velocity estimation based on Sentinel-2 observations at the Karakoram.

Twin satellites of Sentinel-2A/B provide 5-day repeat observation to the Earth and are capable of deriving glacier velocity with high-temporal resolution. Here we take the Karakoram as a study site and proposed a data processing procedure of deriving quasi-monthly glacier flow velocity fields by performing offset-tracking technique to 4 years of Sentinel-2 observations. We performed offset-tracking of each acquisition to its next three almost cloud-free acquisitions to increase the number of redundant observations. Flow speed and direction referenced method is taken to remove the wrong value of offset-tracking. Then an iterative SVD method solves the glacier velocity and removes the observation with a large residual. From Oct 2017 to Sep 2021, our results capture plenty of surged glaciers starting and/or ending their surging phases. Several glaciers show speed up one year ago before their surging phase. Rimo south glacier experienced a full surging phase during our study period and last for about two years, the maximum speed exceeded 9m/day. The normal type of glaciers also presented annually speed up and slow down, with acceleration starting in late April or earth May, and ending before September. We estimated RMSE of estimated velocity is about 0.11-0.29 m/day.

Part 2, Sea ice motion detection using Sentinel-1 imagery feature tracking.

Applying feature tracking techniques to Sentinel-1 imagery generates high resolution sea ice motion fields. However, the bad matching vectors still exist after the NNDR (Nearest Neighbor Distance Ratio) test and contaminate the derived motion fields, which need to be identified and filtered out. We propose two algorithms to eliminate such wrong matching vectors. The first employs the matching results derived by the maximum cross-correlation (MCC) method as the reference motion fields to evaluate such wrong matches. The second method employs the local spatial consistency presumption of sea ice motion fields. A Voronoi diagram is applied to slice the overlapping area of two SAR images into many fractions, and each fraction extends its size 50% outward to calculate the regional mean sea ice flow vector and standard deviation. Any vector within the fraction that exceeds 3 times the regional standard deviation will be recognized as an outlier and filtered out. Two methods are tested to two cases with strong rotation or irregular sea ice motion fields derived from Sentinel-1 imagery. The overall accuracy of our two methods is 93.9% and 98.7%, and they sacrifice 6.12% /1.22% of the correct vectors to filter out 100.0% / 94.12% of the wrong vectors for the MCC referenced filter and Voronoi fragmented filter, respectively.

Part 3, Incidence angle normalization of Sentinel-1 backscatter imagery for Greenland ice sheet.

This study proposes an incidence angle normalization method for dual-polarized Sentinel-1 image for Greenland Ice Sheet. A multiple linear regression model is trained using the ratio between backscatter coefficient differences and incidence angle differences of quasi-simultaneously observed ascending and descending image pairs. Regression factors include geographical position and elevation. The precision evaluation of the ascending and descending images suggests better normalization results than the widely-used cosine-square correction method for HH images and little improvement for the HV images. Another dataset of GrIS Sentinel-1 mosaics in four 6-day repeating periods in 2020 is also employed to evaluate the proposed method and yield similar results. For HH images, the proposed method performs better than the cosine-square method, reducing 0.34 dB RMSE on average. The overall accuracy of our proposed method is 0.77 dB and 0.75 dB for HH and HV images, respectively. The proposed incidence angle normalization method can benefit in applying wide-swath and high temporal resolution Sentinel-1 images for producing backscatter mosaic images for GrIS.

Continued glacier mass loss in High Mountain Asia impacts freshwater supply in and beyond the mountains. Previous studies have shown large spatial variations in glacier mass balance in this region, but the reasons for this variability are not well understood. We developed a new index based on satellite-derived surface characteristics to discriminate winter- and summer-accumulation type glaciers across High Mountain Asia. Combined with the existing mass balance data, it is found that the accumulation type is closely related with accumulation type. Glacier regions that gain mass predominantly from summer snow have thinned on average nearly four times faster than those gaining most mass in winter (-0.43 ± 0.12 m water equivalent (w.e.) a^-1 vs -0.10 ± 0.06 m w.e. a^-1 from 2000 to 2018). The results highlight the importance of the seasonality of snowfall for the glacier mass budget emphasizing that accurate precipitation fields are paramount to quantify future glacier changes reliably in this region.

The monitoring and forecasting of global water cycle under climate changes indeed require enhancement of satellite remote sensing products in both of spatial resolution and accuracy. To strengthen the ability of microwave remote sensing in global water cycle studies and seek for new opportunities of satellite missions, we put forward research contents as follows in the second year of project implementation:

(1) Continuous L-Band Soil Moisture (SM) Datasets from SMOS and SMAP Observations

The Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) are two existing satellites capable of providing L-band observations at a global scale. Although both satellites have independently performed calibrations, there are some differences in brightness temperature (TB) between the two. Intercalibrations were conducted to develop a consistent SMOS-SMAP TB, then the multi-channel collaborative algorithm (MCCA), which utilizes information from collaborative channels expressed as an analytical form of brightness temperature at the core channel to rule out the parameters to be retrieved, is adopted to develop a consistent L-band soil moisture dataset. Inter-comparison with other SM products (MT-DCA version 5, and DCA, SCA-H, and SCA-V from SMAP Level-3 products version 7) shows an analogous spatial pattern. The MCCA derived SM had the lowest ubRMSD (about 0.058 m3/m3) followed by DCA (0.061 m3/m3), and an overall Pearson’s correlation coefficient of 0.702 (DCA performed best with R=0.746) when evaluated against in situ observations from 19 dense soil moisture networks. The MCCA generates vegetation optical depth (VOD) at both vertical and horizontal polarization, which were found to have a good linearity with the live biomass and canopy height, though partial saturation exists in the relationship with live biomass of tropical forests but not canopy height. The polarization difference of VOD mainly located at densely vegetated and arid areas. It is important to note that this continuous L-band SM and polarized VOD dataset is expected to improve our understanding of the water-transport process in the soil-vegetation continuum.

(Submitted to Remote Sensing of Environment)

(2) Continuous X-Band Soil Moisture (SM) Datasets from FY-3 Series Observations

Long term SM data with stable and consistent quality are critical for global environment and climate change monitoring. SM products from L-band observations have proven to be optimal global estimations. Although X-band has a lower sensitivity to soil moisture than that of L-band, Chinese FengYun-3 series satellites (FY-3A/B/C/D) have provided sustainable and daily multiple SM products from X-band since 2008. This research developed a new global SSM product (NNsm-FY) from FY-3B MWRI from 2010 to 2019, transferred high accuracy of SMAP L-band to FY-3B X-band. The NNsm-FY shows good agreement with in-situ observations and SMAP product and has a higher accuracy than that of official FY-3B product. At selected dense in-situ networks, it is found that NNsm-FY has a relatively good performance with median CC of 0.66 and median ubRMSE of 0.046 m3/m3, With this new dataset, Chinese FY-3 satellites may play a larger role and provide opportunities of sustainable and longer-term soil moisture data record for hydrological study.

(Submitted to Scientific Data)

The main objective of the project is to develop prototypes of real-time remote sensing (RS) land data assimilation systems (LDAS) for monitoring the water cycle in the silk road endorheic river basins and EUROCORDEX-domain. This will provide a synergic and innovative way to integrate RS data from NRSCC and ESA into terrestrial system models for better quantifying the water cycle at the watershed/regional scale. The objective will be achieved through the following sub-objectives: i) Retrieval of key water cycle variables from multi-source RS data (WP1); ii) Development of real time RS LDAS to integrate RS data into terrestrial system models (WP2); iii) Calibration/validation of terrestrial system models using RS retrievals of key water cycle variables (WP3); iv) Parameter estimations for terrestrial system models based on the LDAS (WP3); v) Closing and quantifying the water cycle at the watershed/regional scale based on the LDAS (WP4).

Two LDAS will be developed in the project, one for the silk road endorheic river basins (LDAS_Silk) and one for EUROCORDEX-domain (LDAS_EU). LDAS_Silk will be based on the recently developed watershed system model and a common software for nonlinear and non-Gaussian land data assimilation (ComDA). LDAS_EU will be based on the recently developed Terrestrial System Modeling Platform (TSMP) and Parallel Data Assimilation Framework (PDAF). Multi-source RS data, from visible to thermal infrared and microwave, will be used to retrieve key ecohydrological variables, such as evapotranspiration (ET), snow coverage area (SCA), snow water equivalent (SWE), snow depth (SD), soil moisture (SM), lake and glacier extents, irrigation, and vegetation density and structure. These data will be used as forcing data, calibration and validation data, and for assimilation into the two LDAS.

In this presentation, the mid-term progress on the project will be reported.

The objective of this project is to assess the feasibility of remotely sensed products of key cryospheric and hydrological elements (snow, evapotranspiration, soil moisture and precipitation) in representative regions across the Third Pole region and the Heihe River Basin of China and selected test sites in other regions, e.g. northern Finland. The in-situ measurements used to validate remotely sensed products have been collected from several ground-based observation networks including the Finnish Meteorological Institute (FMI), the TERrestrial ENvironmental Observatories (TERENO), the Agrosphere institute (IBG-3) and The Qilian Mountain Observatories (QMO). Essential remote sensing products e.g. the GlobSnow data sets covering northern hemisphere and the soil moisture data set from SMOS, were evaluated by referencing ground-based observations in representative regions. The upscaling methods were developed to improve the representativeness of ground-based observations to remote sensing pixels. The validated products were also inter-compared with other gridded products, and the spatiotemporal trends were diagnosed by statistical indexes, e.g., RMSE and correlation coefficient. The performance of each product will be further evaluated in different landscapes, topographic conditions in the representative regions selected in China and Europe. The research results have been submitted to or published in international journals such as IEEE TGARS, Remote Sensing, and the Cryosphere. In addition, young scientists on this project made considerable efforts to observe snow, evapotranspiration, soil moisture and precipitation. They also assist with the validation of remotely sensed products on preprocessing data, developing validation algorithms and writing validation reports.

Driven by climate change and large-scale forestry projects, the vegetation coverage has been significantly afforested in China. An increase in vegetation greenness improves ecosystem productivity and reduce the water supply, which leads to potential conflict of water demands between ecosystems and humans. This problem has been well-assessed in dry environments with significant evidence, but there are a few studies in humid areas. Therefore, this study will focus on the Poyang Lake Basin in the humid areas of southern China. This study analyzed the change in global vegetation greenness reflected by the satellite-derived growing season LAI (LAIgs). The causes of vegetation dynamic change are firstly analyzed in combination with climate and land use data. The impact of vegetation greenness change on watershed water yield is then investigated based on the modified Water Supply Stress Index (WaSSI) model.

Results show that the vegetation in Poyang Lake Basin grows well. During the study period, the NDVI of the basin increased significantly with a trend of 0.0031/a, in which 78% of the regional vegetation showed a greening trend, while 22% of the regional vegetation showed a browning trend. Temperature rise and afforestation promote regional vegetation greening, but urbanization is the main driving factor of vegetation browning. The partial correlation coefficient between temperature and NDVI was 0.959 (p<0.01), while the partial correlation coefficient between precipitation and NDVI was -0.647 (p<0.05). The correlation between climatic factors and NDVI showed obvious spatial heterogeneity, which indicated the vegetation in the central basin was more vulnerable to climate change than that in other regions. During the study period, frequent droughts occurred in the Poyang Lake basin. The increase of vegetation greenness by 20-80% under different drought intensities resulted in a decrease in water yield by 3-27%. At the scale of sub-basins, the increase of vegetation greenness had a negative effect on water yield. In addition, the decrease of water yield caused by increasing vegetation greenness under persistent high-intensity drought was 2-3 times that under short-term moderate drought. The effect of vegetation greenness increase on water yield under drought conditions is related to vegetation type, duration, and intensity of drought.

The rapid increase of forest greenness caused by massive afforestation may lead to new environmental problems under the condition of continuous high-intensity drought in humid areas such as the Poyang Lake basin. Therefore, given the increasing frequency of extreme climatic events, afforestation with a targeted approach should be implemented as it would provide the most benefits. In addition, selective harvesting in forested areas with high density could be an effective strategy to maintain water supply in humid regions.