Map is one of the communication means created by human being. Cartographers have been making efforts on the comparison of maps to natural languages so as to establish a “cartographic language” or “map language”. One of such efforts is to adopt the Shannon’s Information Theory originated in digital communication into cartography so as to establish an entropy-based cartographic communication theory. However, success has been very limited although research work had started as early as the mid-1960s. It is then found that the bottleneck problem was the lack of appropriate measures for the spatial (configurational) information of (graphic and image) maps, as the classic Shannon entropy is only capable of characterizing statistical information but fails to capture the configurational information of (graphic and image) maps. Fortunately, after over 40-year development, some bottleneck problems have been solved. More precisely, generalized Shannon entropies for metric and thematic information of (graphic) maps have been developed and the first feasible solution for computing the Boltzmann entropy of image maps has been invented, which is capable of measuring the spatial information of not only numerical images but also categorical maps. With such progress, it is now feasible to build the “Information Theory of Cartography”. In this paper, a framework for such a theory is proposed and some key issues are identified. For these issues, some have already been tackled while others still need efforts. As a result, a research agenda is set for future action. After all these issues are tackled, the theory will become matured so as to become a theoretic basis of cartography. It is expected that the Information Theory of Cartography will play an increasingly important role in the discipline of cartography because more and more researchers have advocated that information is more fundamental than matter and energy.

In studies of upwelling, usually data from infrared and optical sensors is used which provides information on the sea surface temperature (SST) and the chlorophyll-a (Chl-a) concentration. In this paper, we show that also synthetic aperture radars (SAR) images can give valuable contribution to such studies. Upwelling regions become detectable by SAR because they are associated with a reduction of the radar backscatter due to ① the change of the stability of the air-sea interface or/and ② the presence of biogenic slicks. Furthermore, the boundary of upwelling regions consists of a line of increased radar backscatter due to the presence of convergent surface flow.

In this study, a large time series of TerraSAR-X Stripmap co-polarized (HH-VV) Synthetic Aperture Radar (SAR) imagery collected over the Taylor Energy oil platform site in the Gulf of Mexico is exploited to investigate this 13 year-long unconventional oil spill. The σ_CPD approach is used to estimate the polluted area along time. In addition, a sensitivity analysis is undertaken to point out the dependence of σ_CPD to imaging (noise floor, incidence angle) and environment (sea state) parameters. Experimental results demonstrate that σ_CPD can be effectively used to monitor the Taylor Energy oil spill, estimating the polluted area. For the TSX SAR data avail-ability most dense period (year 2013), a daily spill of about 2.2km² is observed in average, even though high variability (about 2.0km²) is experienced due to the un-conventional characteristics of the spill.

In this study, the azimuth cut-off method, typically used for SAR moderate wind speed estimation purposes, is analyzed under high wind regimes. Firstly, the importance of the pixel spacing, the size of the boxes selected for Synthetic Aperture Radar (SAR) image partitioning and the image texture in terms of homogeneities are discussed by considering their influence on the azimuth cut-off (λc) estimation. Secondly, a quality control analysis of the reliability of λc is carried out by evaluating the distance between the autocorrelation functions (ACF) and their correspondent fittings. This analysis points out the importance of filtering out the unreliable and unfeasible λc values in order to improve the wind speed estimation. The quality control procedure is based on a x² test, applied on a large Sentinel-1A dataset. The soundness of the test is verified by an increment in terms of correlation between λc estimations and wind speed values. This approach is, then, applied under high wind regimes, i.e., tropical cyclones.

In this paper, studies on offshore wind farm wakes observed by spaceborne synthetic aperture radar (SAR) are reviewed mainly based on our previous research. Particularly, we focus on investigating wind wakes and tidal current wakes observed by spaceborne SAR of TerraSAR-X, Gaofen-3 and Radarsat-2 in high spatial resolution, in two offshores wind farms, i.e., the Alpha Ventus in the North Sea and the one near Donghai bridge in the East China Sea. Representing examples of wind wakes and tidal current wakes observed by SAR in the two farms are presented and compared. A preliminary statistical analysis on morphology of wind feature downstream Alpha Ventus is presented as well. Besides these studies on wind wakes generated by a single offshore wind farm, we show an example of wakes downstream multiple wind farms in the North Sea to demonstrate “cluster” effect of multiple offshore wind farms on sea wind.

The Circum-Bohai-Sea Region is an important economic zone of China. The sea ice, which occurs at each winter, is the major marine hazard of the Bohai Sea. As a result, it is very important to evaluate the damage effects quantitatively in this region, which is seldom studied and analyzed systematically using long-time-series data. In this paper, the sea-ice disaster in the Bohai Sea is evaluated quantitatively based on the Sentinel-1 and GOCI. For different hazard-bearing bodies of the marine transportation and the offshore constructions, different sea-ice-hazard indexes are defined, which can be applied to analyze the sea-ice disaster quantitatively in the Bohai Sea, including the annual and inter-annual variations in the period from 2011 to 2017. The analysis results can provide the reference of the sea-ice monitoring in the Bohai Sea.

In this study, the north-western Pacific Ocean of Kuroshio region is selected as the experimental area to analyze the mesoscale eddies observation abilities of Sentinel-3A SRAL, including the independent detection abilities of Sentinel-3A SRAL and the improvement of mesoscale eddies detection abilities by data fusion with other satellite altimetry data. The Sentinel-3A SRAL data are mapped by the spatial-temporal objective analysis method to the sea level anomaly grid data. The mapping errors are analyzed by the comparisons between the grid data of different combinations and along the ground track of Jason-2/3. The independent detection abilities of Sentinel-3A SRAL are analyzed by the comparison between the grid data and the AVISO MSLA data. On the other hand, through the multi-satellite data fusion of different combinations of Sentinel-3A altimeter and other satellite altimeters such as Jason-2/3, the mesoscale eddies detection was performed based on the merged sea level anomaly data and the addition of Sentinel-3A SRAL data for the improvements of mesoscale eddies detection abilities by multi-satellite altimeters are concluded. It is concluded that Sentinel-3A SRAL has good abilities of mesoscale eddies detection as the combination of Jason-2 and Jason-3, and it is better than that of single altimeter of Jason-2 or Jason-3.

In this study, we provide a summary of research advances in the field of maritime target detection using DP (dual-polarimetric) SAR (Synthetic Aperture Radar) imagery, accomplished during the European and China collaboration in the framework of the Dragon-4 program ID 32235. The main innovative contribution is twofold: ①We addressed ship detection proposing an improved GP-PNF (Geometrical Perturbation-Polarimetric Notch Filter), termed as IGP-PNF, that is characterized by a new feature vector that includes three new scattering features; ②We addressed oil platform detection by contrasting single-polarization SAR methods with polarimetric ones in order to quantify the extra- benefit carried on polarimetric information. The proposed theoretical framework is tested against actual multi-polarization SAR data. In particular, ship detection methods are verified against a Sentinel-1 SAR scene where a large number of ships is present; while, oil platform detection is discussed using TerraSAR-X SAR data. Experimental analysis shows that: ①The IGP-PNF method performs best in terms of clutter-to-target ratio; ②Coherent polarimetric information significantly outperforms single-polarization SAR measurements in highlighting targets in challenging cases.

In 2017, China’s central government approved the national strategy to build Xiong’an New Area (XNA, 100km southwest to Beijing), which was announced as a “millennium strategy” and a “demo area” for a sustainable, modern, and innovative urban model. Xiong’an will draw in as much as $380 billion investment and is expected to help accelerate the development of the wider Beijing-Tianjin-Hebei (Jingjinji) Area. In this paper, present subsidence in the XNA area is investigated using InSAR observations for the first time. The 24 SAR images acquired by European Space Agency’s Sentinel-1 satellites during the period from June 2017 to July 2018 suggest that in the north of Xiong County, the subsidence rate reaches up to 90mm/y, which is highly correlated with the exploitation of geothermal drilling. As the construction in the XNA area will significantly accelerate and its high-quality development, the InSAR findings could provide valuable information for future sustainable urban planning and underground infrastructure construction.

China has been affected by some of the world’s most serious geological disasters and experiences high economic damage every year. Geohazards occur not only in remote areas but also in highly populated cities. In the framework of the Dragon-4 32365 Project, this paper presents the main results and the major conclusions derived from an extensive exploitation of Sentinel-1, ALOS-2 (Advanced Land Observing Satellite 2), GF-3 (GaoFen Satellite 3), and latest launched SAR (Synthetic Aperture Radar), together with methods that allow the evaluation of their importance for various geohazards. Therefore, in the scope of this project, the great benefits of recent remote sensing data (wide spatial and temporal coverage) that allow a detailed reconstruction of past displacement events and to monitor currently occurring phenomena are exploited to study different areas and geohazards problems, including: surface deformation of mountain slopes; identification and monitoring of ground movements and subsidence; landslides; ground fissure; and building inclination studies. Suspicious movements detected in the different study areas were cross validated with different SAR sensors and truth data.

This paper is intended to report on the progresses made during the Dragon-4 project Three and Four-Dimensional Topographic Measurement and Validation (ID: 32278), sub-project Multi-baseline SAR Processing for 3D/4D Reconstruction (ID: 32278_2). The work here reported focuses on two important aspects of SAR remote sensing of tropical forests, namely the retrieval of forest biomass and the assessment of effects due to changing weather conditions. Recent studies have shown that by using SAR tomography the backscattered power at 30m layer above the ground is linearly correlated to the forest Above Ground Biomass (AGB). However, the two parameters that determine this linear relationship might vary for different tropical forest sites. For purpose of solving this problem, we investigate the possibility of using LiDAR derived AGB to help training the two parameters. Experimental results obtained by processing data from the TropiSAR campaign support the feasibility of the proposed concept. This analysis is complemented by an assessment of the impact of changing weather conditions on tomographic imaging, for which we simulate BIOMASS repeat pass tomography using ground-based TropiSCAT data with a revisit time of 3 days and rainy days included. The resulting backscattered power variation at 30m is within 1.5dB. For this forest site, this error is translated into an AGB error of about 50~80t/hm ², which is 20% or less of forest AGB.

The Swarm satellite mission was launched on 22 November 2013, it is the first European Space Agency’s constellation of three satellites, dedicated to monitoring geomagnetic field changes. The measurements delivered by the three satellites are very valuable for a range of applications, including the earthquake prediction study. However, for more than 5 years, relatively little advancement has been achieved in establishing a systematic approach for detecting anomalies from the satellite measurements for predicting earthquakes. This paper presents the challenges of developing a pragmatic framework for automatic anomaly detection and highlights innovative features of functional components developed. Through a case study we demonstrate a functionality pipeline of the system in detecting anomalies, and present our solutions to coping with data sparsity and parameter tuning as well as insights into the differences between discovering seismic anomalies from periodic and non-periodic data observed by the Swarm satellites.

The tremendous development of Synthetic Aperture Radar (SAR) missions in recent years facilitates the study of smaller amplitude ground deformation over greater spatial scales using longer time series. However, this poses greater challenges for correcting atmospheric effects due to the wider coverage of SAR imagery than ever. Previous attempts have used observations from Global Positioning System (GPS) and Numerical Weather Models (NWMs) to separate atmospheric delays, but they are limited by ①The availability (and distribution) of GPS stations; ②The low spatial resolution of NWM; And ③The difficulties in quantifying their performance. To overcome these limitations, we have developed the Generic Atmospheric Correction Online Service for InSAR (GACOS) which utilizes the high-resolution European Centre for Medium-Range Weather Forecasts (ECMWF) products using an Iterative Tropospheric Decomposition (ITD) model. This enables the reduction of the coupling effects of the troposphere turbulence and stratification and hence achieves equivalent performances over flat and mountainous terrains. GACOS comprises a range of notable features: ①Global coverage; ②All-weather, all-time usability; ③Available with a maximum of two-day latency; And ④Indicators available to assess the model’s performance and feasibility. In this paper, we demonstrate some successful applications of the GACOS online service to a variety of geophysical studies.

It is a debated topic if there are any observable precursor anomalies prior to the earthquake (EQ hereafter) and if the stronger EQ can be successfully predicted. During last few decades quite a lot of observable electromagnetic (EM) precursors were published by using techniques equipped in either satellites or on ground-based stations. But there are only a few cases that the short-term precursor anomalies of EM field before earthquakes were observed by using alternate EM fields on ground. This paper will present a new EM observation network built in recent years and show a new finding of EM field with the variation of a one-year cycle observed using the network. As an example, the short-term precursor anomalies of apparent resistivity before the Yangbi EQ (Ms 5.1) occurred on March 27, 2017 in Yunnan Province will be studied. The observed anomalous phenomena indicate that the anomaly before the EQ can be captured only if reasonable effective methods including sophisticated analytical techniques are used, and it is believed that continuously observed data on the fixed observation network for a long time is an effective means for studying anomalies that appeared before earthquakes. This network can also play an important role in studying the EM environment from space.

Coastal regions are becoming increasingly vulnerable to flooding because of accelerating sea-level-rise (SLR), local ground subsidence, and the changes in topography and morphology. Moreover, coastal areas are usually highly urbanized and increased human activities have an effect on the stability and preservation of the environment. For instance, the growing demand for new lands to accommodate the population and the industrial facilities in China has required the design and the deployment of land-reclamation projects from the ocean, with a marked impact on fragile coastal eco-systems. Specifically, the Yangtze River and Pearl River Estuary, two major estuaries of the world, have long been subject to intensive human activities over the past decades. Long-term ground subsidence evolution, topographic changes, and morphological variation of the coastal regions have drawn great attention. This paper provides an overview of well-established Earth Observation (EO) remote sensing (RS) technologies that are employed to continuously monitor the changes of urbanized regions. The combined use of EO-based DInSAR analyses along with the knowledge of the geomorphology of the coastal regions allows a more precise picture of the SLR risk in the investigated coastal regions. In this paper, we will concentrate on remote sensing technologies that allow the gathering of heterogeneous information, such as those based on the use of synthetic aperture radar (SAR), satellite altimeters and tide gauge data. We will underline how human activities trigger changes in the living environment of coastal zones and the associated risks for the population. Observed coastline changes, coastal regions terrain subsidence, and offshore bathymetry have a pronounced effect on the increasing risk of flooding. Accordingly, we also present insights into some inundation model projections employed for evaluating the potential flooding risk in coastal regions.

Surface energy budget components (such as net radiation flux, sensible heat flux, latent heat flux and soil heat flux) at multiple temporal scales have significant meaning for understanding the energy and water cycle over the Tibetan Plateau (TP). In the framework of ESA-MOST Dragon Programme 4, the surface energy balance system (SEBS) was tested and used to derive surface heat fluxes at different temporal scales over the TP by a combination use of geostationary satellite (FY-2C) data, polar orbiting satellite (SPOT/VGT, Terra/MODIS) data and ITPCAS forcing data. The validation results show there is a good agreement between derived heat fluxes and in situ measurements from Third Pole Environment Observation and Research Platform (TPEORP), which means the feasibility to derive surface heat fluxes over heterogeneous landscapes by a combination use of geostationary and polar orbiting satellite data in SEBS. The diurnal, seasonal and inter-annual variation characteristics were also clearly identified through analyses of derived turbulent fluxes.