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An 8-week feeding experiment aimed to investigate the effects of fermented soybean residue in diets on the growth performance, serum antioxidant parameters, intestinal digestive capacity, and microbial composition of the hindgut of Furong crucian carp. The feeds were formulated to contain 0%, 6%, 12%, 18%, and 24% fermented soybean residue (CON, FSR6, FSR12, FSR18, and FSR24, respectively), respectively, to form five diets (crude protein: 33%; crude lipid: 5%). The results showed that incorporating 6% fermented soybean residue into the diet significantly increased the weight gain rate (WGR) and specific growth rate (SGR) and decreased the feed coefficient rate (p < 0.05). Through regression analysis of WGR and SGR, the optimal levels of the dietary fermented soybean residue of Furong crucian carp were determined to be 6.78% and 7.06%. Incorporating fermented soybean residue into the diet decreased the lipid content of the whole body and the levels of glucose, total cholesterol, and triglyceride in the serum of Furong crucian carp. The inclusion of 6% and 12% fermented soybean residue in the diet markedly increased the antioxidant capacity, intestinal amylase activity, and intestinal villous height of Furong crucian carp (p < 0.05). At the 6% level, fermented soybean residue significantly increased the abundance of Romboutsia and Clostridium_sensu_stricto_1 while significantly decreasing the abundance of Vibrio (p < 0.05), indicating that a 6% level of fermented soybean residue was beneficial for intestinal health. In conclusion, incorporating 6–7% fermented soybean residue into the diet of Furong crucian carp was recommended. [ABSTRACT FROM AUTHOR]

Accurate estimation and regular monitoring of soil moisture is very important for many agricultural, hydrological, or climatological applications. Our objective was to evaluate potential contributions of polarimetry to soil moisture estimation during crop growing cycles using RADARSAT-2 C-band images. The research focused on wheat field data collected during Soil Moisture Active Passive Validation Experiment (SMAPVEX12) conducted in 2012 in Manitoba (Canada). A sensitivity analysis was performed to select the most relevant non-polarimetric and polarimetric variables extracted from RADARSAT-2, and statistical models were developed to estimate soil moisture. In fine, three models were developed and validated: a non-polarimetric model based on cross-polarized backscattering coefficient σ H V 0 ; a polarimetric mixed model using six polarimetric and non-polarimetric retained variables after the sensitivity analysis; and a simplified polarimetric mixed model considering only the phase difference ( ϕ H H − V V ) and the co-polarized backscattering coefficient σ H H 0 . The validation reveals significant positive contributions of polarimetry. It shows that the non-polarimetric model has a much larger error (RMSE = 0.098 m3/m3) and explains only 19% of observed soil moisture variation compared to the polarimetric mixed model, which has an error of 0.087 m3/m3, with an explained variance of 44%. The simplified model has the lowest error (0.074 m3/m3) and explains 53.5% of soil moisture variation. [ABSTRACT FROM AUTHOR]

With the continuous advancement of image-editing technologies, it is particularly important to develop image forensics methods for digital information security. In this study, a deep neural network called multi-path inpainting forensics network (MPIF-Net) was developed to locate the inpainted regions in an image. The interaction of shallow and deep features between different paths was established, which not only preserved detailed information but also allowed for the further mining of deep features. Meanwhile, an improved residual dense block was employed as the deep feature extraction module of each path, which can enhance the feature extraction ability of the model by introducing a frequency domain attention mechanism. In addition, a boundary guidance module was constructed to alleviate the prediction distortion in the boundaries of the inpainted region. Finally, extensive experimental results regarding various deep inpainting datasets demonstrated that the proposed network can accurately locate inpainted regions, exhibit excellent generalization and robustness, and verify the effectiveness of the designed module. [ABSTRACT FROM AUTHOR]

The rapid development of digital image inpainting technology is causing serious hidden danger to the security of multimedia information. In this paper, a deep network called frequency attention-based dual-stream network (FADS-Net) is proposed for locating the inpainting region. FADS-Net is established by a dual-stream encoder and an attention-based blue-associative decoder. The dual-stream encoder includes two feature extraction streams, the raw input stream (RIS) and the frequency recalibration stream (FRS). RIS directly captures feature maps from the raw input, while FRS performs feature extraction after recalibrating the input via learning in the frequency domain. In addition, a module based on dense connection is designed to ensure efficient extraction and full fusion of dual-stream features. The attention-based associative decoder consists of a main decoder and two branch decoders. The main decoder performs up-sampling and fine-tuning of fused features by using attention mechanisms and skip connections, and ultimately generates the predicted mask for the inpainted image. Then, two branch decoders are utilized to further supervise the training of two feature streams, ensuring that they both work effectively. A joint loss function is designed to supervise the training of the entire network and two feature extraction streams for ensuring optimal forensic performance. Extensive experimental results demonstrate that the proposed FADS-Net achieves superior localization accuracy and robustness on multiple datasets compared to the state-of-the-art inpainting forensics methods. [ABSTRACT FROM AUTHOR]

High-spatiotemporal resolution soil moisture (SM) plays an essential role in optimized irrigation, agricultural droughts, and hydrometeorological model simulations. However, producing high-spatiotemporal seamless soil moisture products is challenging due to the inability of optical bands to penetrate clouds and the coarse spatiotemporal resolution of microwave and reanalysis products. To address these issues, this study proposed a framework for multi-source data merging based on the triple collocation (TC) method with an explicit physical mechanism, which was dedicated to generating seamless 1 km daily soil moisture products. Current merging techniques based on the TC method often lack seamless daily optical data input. To remedy this deficiency, our study performed a spatiotemporal reconstruction on MODIS LST and NDVI, and retrieved seamless daily optical soil moisture products. Then, the optical-derived sm1, microwave-retrieved sm2 (ESA CCI combined), and reanalysis sm3 (CLDAS) were matched by the cumulative distribution function (CDF) method to eliminate bias, and their weights were determined by the TC method. Finally, the least squares algorithm and the significance judgment were adopted to complete the merging. Although the CLDAS soil moisture presented anomalies over several stations, our proposed method can detect and reduce this impact by minimizing its weight, which shows the robustness of the method. This framework was implemented in the Naqu region, and the results showed that the merged products captured the temporal variability of the SM and depicted spatial information in detail; the validation with the in situ measurement obtained an average ubRMSE of 0.046 m³/m³. Additionally, this framework is transferrable to any area with measured sites for better agricultural and hydrological applications. [ABSTRACT FROM AUTHOR]

This study investigates the potential of L- and C- bands Polarimetric Synthetic Aperture Radar (PolSAR) data to monitor soil moisture over the forested sites of SMAP Validation Experiment 2012 (SMAPVEX12). The optimal backscattering coefficients and polarimetric parameters to characterize the soil moisture were determined based on L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), C-band RADARSAT-2, and ground measurements composed of soil and vegetation parameters collected during SMAPVEX12. Linear and circular backscattering coefficients (σ0) and polarimetric parameters such as correlation coefficients (ρHHVV) and phase difference (φHHVV) between HH and VV, pedestal height (PH), entropy (H), anisotropy (A), α angle, surface (Ps), and double bounce (Pd) powers were used to develop the relationships with soil moisture. The analysis of these relationships shows that over the forested sites of SMAPVEX12: (a) at L-band several optimal backscattering coefficients and polarimetric parameters allow the monitoring of soil moisture, particularly the linear and circular σ0 (r = 0.60–0.96), Ps (r = 0.59–0.84), Pd (r = 0.60–0.82), ρHHHV_30°, ρVVHV_30°, φHHHV_30° and φHHVV_30° (r = 0.56–0.81). However, compared to the results obtained with σ0, there is no added value of the polarimetric parameters for soil moisture retrievals. (b) at C-band, only a few polarimetric parameters φHHHV, φVVHV, and φHHVV are correlated with soil moisture (r = ~0.90). They can contribute to soil moisture retrievals over forested sites when L-band data are not available. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a crucial driving variable for the global land surface-atmosphere water and energy cycle. There are now many satellite-based SM products available internationally and it is necessary to consider all available SM products under the same context for comprehensive assessment and inter-comparisons at the global scale. Moreover, product performances varying with dynamic environmental factors, especially those closely related to retrieval algorithms, were less investigated. Therefore, this study evaluated and identified the relative strengths of nine mainstream satellite-based SM products derived from the Advanced Microwave Scanning Radiometer 2 (AMSR2), Chinese Fengyun-3B (FY3B), the Soil Moisture Active Passive (SMAP), the Soil Moisture and Ocean Salinity (SMOS), and the European Space Agency (ESA) Climate Change Initiative (CCI) by using the Pearson correlation coefficient (R), R of SM seasonal anomalies (Ranom), unbiased Root Mean Square Error (ubRMSE), and bias metrics against ground observations from the International Soil Moisture Network (ISMN), as well as the Global Land Data Assimilation System (GLDAS) Noah model simulations, overall and under three dynamic (Land Surface Temperature (LST), SM, and Vegetation Optical Depth (VOD)) conditions. Results showed that the SMOS-INRA-CESBIO (IC) product outperformed the SMOSL3 product in most cases, especially in Australia, but it exhibited greater variability and higher random errors in Asia. ESA CCI products outperformed other products in capturing the spatial dynamics of SM seasonal anomalies and produced significantly high accuracy in croplands. Although the Chinese FY3B presented poor skills in most cases, it had a good ability to capture the temporal dynamics of the original SM and SM seasonal anomalies in most regions of central Africa. Under various land cover types, with the changes in LST, SM, and VOD, different products exhibited distinctly dynamic error characteristics. Generally, all products tended to overestimate the low in-situ SM content but underestimate the high in-situ SM content. It is expected that these findings can provide guidance and references for product improvement and application promotions in water exchange and land surface energy cycle. [ABSTRACT FROM AUTHOR]

Interaction between the chemokine receptor XCR1 and its ligand is closely related to the immune function in animals; however, there are only a few reports on role of XCR1 in the immune system of fish. We aimed to analyze the expression of XCR1 in various organs or tissues of grass carp before and after Grass Carp Reovirus (GCRV) infection to better understand the function of XCR1 in resistance to GCRV infection. We cloned and sequenced the cDNA of grass carp XCR1 and analyzed the molecular structure of XCR1 based its amino acid sequence. Further, we analyzed the relative expression levels of XCR1 in different organs or tissues of male parent grass carp with GCRV resistance (P1) and their first-generation offspring (F1) before and after GCRV infection. Our results show that the total length of cDNA of the grass carp XCR1 gene is 1659 bp and encodes 365 amino acids. XCR1 contains seven conserved transmembrane helical domains. The homologous tertiary structure of XCR1 is similar to its homologs in other species. After artificial GCRV infection, there were significant differences in the expression of the grass carp XCR1 gene in different tissues, at different time points, and between P1 and F1 fish. These results will contribute to our understanding of the role of XCR1 in fish immune responses and contribute to the development of GCRV-resistant grass carp. [ABSTRACT FROM AUTHOR]

Fermented soybean meal (FSM) is an important feed material that can replace fish meal to solve the shortage of animal protein. To improve the utilization of FSM, we optimized the co-fermentation conditions of soybean meal using Bacillus subtilis and Enterococcus faecium and studied the effects of replacing fish meal with different proportions of FSM on serum antioxidant indices and gut microbiota (GM) composition of crucian carp (Carassius auratus). Our results showed that the co-fermentation of soybean meal was the most effective when the ratio of B. subtilis X-2 and E. faecium X-4 was 2:3, glucose addition was 4.5%, KH2PO4 addition was 0.15%, MgSO4·7H2O addition was 0.1%, anhydrous sodium acetate addition was 0.4%, fermentation time was 120 h, and the solid–water ratio was 1:1. Replacing 40% fish meal with FSM in the feed significantly improved the serum T-AOC, POD, and IgM levels in C. auratus. Although there were significant differences in the midgut and hindgut microbiota structures of C. auratus, the addition of FSM to the feed did not cause significant differences in the GM structure, whether in the midgut or hindgut. Therefore, 40% FSM is the most suitable substitute for fish meal in the feed of C. auratus. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Effects of Replacing Dietary Fish Meal by Soybean Meal Co-Fermented Using Bacillus subtilis and Enterococcus faecium on Serum Antioxidant Indices and Gut Microbiota of Crucian Carp Carassius auratus." The correction states that there was an error in Figure 1 of the original publication, where Figure 1F was mistakenly duplicated as Figure 1G. The corrected figure has been provided, and the authors assure that this correction does not affect the scientific conclusions of the study. The original publication has been updated accordingly. [Extracted from the article]

COVID-19 has spread around the world and caused serious public health and social problems. Although several vaccines have been authorized for emergency use, new effective antiviral drugs are still needed. Some repurposed drugs including Chloroquine, Hydroxychloroquine and Remdesivir were immediately used to treat COVID-19 after the pandemic. However, the therapeutic effects of these drugs have not been fully demonstrated in clinical studies. In this paper, we found an antimalarial drug, Naphthoquine, showed good broad-spectrum anti-coronavirus activity. Naphthoquineinhibited HCoV-229E, HCoV-OC43 and SARS-CoV-2 replication in vitro, with IC50 = 2.05 ± 1.44 μM, 5.83 ± 0.74 μM, and 2.01 ± 0.38 µM, respectively. Time-of-addition assay was also performed to explore at which stage Naphthoquine functions during SARS-CoV-2 replication. The results suggested that Naphthoquine may influence virus entry and post-entry replication. Considering the safety of Naphthoquine was even better than that of Chloroquine, we think Naphthoquine has the potential to be used as a broad-spectrum drug for coronavirus infection. [ABSTRACT FROM AUTHOR]

Complement factor D (Df) is a serine protease well known for activating the alternative pathway (AP) in mammals by promoting the cleavage of complement component 3 (C3), thus becoming involved in innate defense. In teleost fish, however, the functional mechanisms of Df in the AP and against pathogen infection are far from clear. In the present study, we cloned and characterized the Df gene, CiDf, from grass carp (Ctenopharyngodon idella) and analyzed its function in promoting C3 cleavage and expression changes after grass carp reovirus (GCRV) infection. The open reading frame of CiDf was found to be 753 bp, encoding 250 amino acids with a molecular mass of 27.06 kDa. CiDf harbors a conserved Tryp_SPc domain, with three conserved residues representing the catalytic triad and three conserved binding sites in the substrate specificity pocket. Pairwise alignment showed that CiDf shares the highest identity (96%) and similarity (98%) with Df from Anabarilius grahami. Phylogenetic analysis indicated that CiDf and other fish Dfs formed a distinct evolutionary branch. Similar to most Dfs from other vertebrates, the CiDf gene structure is characterized by four introns and five exons. The incubation of recombinant CiDf protein with grass carp serum significantly increased the C3b content, demonstrating the conserved function of CiDf in the AP in promoting C3 cleavage, similar to Dfs in mammals. CiDf mRNA expression was widely detected in various tissues and levels were relatively higher in the liver, spleen, and intestine of grass carp. During GCRV infection over a 168-hour period, a high level of CiDf mRNA expression in the liver, spleen, and intestine was maintained at 144 and 168 h, suggesting AP activity at the late stage of GCRV infection. Collectively, the above results reveal the conserved structure and function of CiDf and its distinct expression patterns after GCRV infection, which provide a key basis for studying the roles of Df and AP during GCRV infection in the grass carp C. idella. [ABSTRACT FROM AUTHOR]

This paper presents an approach for retrieval of soil moisture in Nagqu region of Tibetan Plateau using VV-polarized Sentinel-1 SAR and MODIS optical data, by coupling the semi-empirical Oh-2004 model and the Water Cloud Model (WCM). The Oh model is first used to estimate the surface roughness parameter based on the hypothesis that the roughness is invariant among SAR acquisitions. Afterward, the vegetation water content (VWC) in the WCM is calculated from the daily MODIS NDVI data obtained by temporal interpolation. To improve the performance of the model, the parameters A, B, and α of the WCM are analyzed and optimized using randomly selected half of the sampled dataset. Then, the soil moisture is retrieved by minimizing a cost function between the simulated and measured backscattering coefficients. The comparison of the retrieved soil moisture with the ground measurements shows the determination coefficient R2 and the Root Mean Square Error (RMSE) are 0.46 and 0.08 m3/m3, respectively. These results demonstrate the capability and reliability of Sentinel-1 SAR data for estimating the soil moisture over the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

Although high dynamic range (HDR) is now a common format of digital images, limited work has been done for HDR source forensics. This paper presents a method based on a convolutional neural network (CNN) to detect the source of HDR images, which is built in the discrete cosine transform (DCT) domain. Specifically, the input spatial image is converted into DCT domain with discrete cosine transform. Then, an adaptive multi-scale convolutional (AMSC) layer extracts features related to HDR source forensics from different scales. The features extracted by AMSC are further processed by two convolutional layers with pooling and batch normalization operations. Finally, classification is conducted by a fully connected layer with Softmax function. Experimental results indicate that the proposed DCT-CNN outperforms the state-of-the-art schemes, especially in accuracy, robustness, and adaptability. [ABSTRACT FROM AUTHOR]

The existing face image completion approaches cannot be utilized to rationally complete damaged face images where their identity information is completely lost due to being obscured by center masks. Hence, in this paper, a reference-guided double-pipeline face image completion network (RG-DP-FICN) is designed within the framework of the generative adversarial network (GAN) completing the identity information of damaged images utilizing reference images with the same identity as damaged images. To reasonably integrate the identity information of reference images into completed images, the reference image is decoupled into identity features (e.g., the contour of eyes, eyebrows, nose) and pose features (e.g., the orientation of face and the positions of the facial features), and then the resulting identity features are fused with posture features of damaged images. Specifically, a lightweight identity predictor is used to extract the pose features; an identity extraction module is designed to compress and globally extract the identity features of the reference images, and an identity transfer module is proposed to effectively fuse identity and pose features by performing identity rendering on different receptive fields. Furthermore, quantitative and qualitative evaluations are conducted on a public dataset CelebA-HQ. Compared to the state-of-the-art methods, the evaluation metrics peak signal-to-noise ratio (PSNR), structure similarity index (SSIM) and L1 loss are improved by 2.22 dB, 0.033 and 0.79%, respectively. The results indicate that RG-DP-FICN can generate completed images with reasonable identity, with superior completion effect compared to existing completion approaches. [ABSTRACT FROM AUTHOR]

This paper aims to retrieve the temporal dynamics of soil moisture from 2015 to 2019 over an agricultural site in Southeast Australia using the Soil Moisture Active Passive (SMAP) brightness temperature. To meet this objective, two machine learning approaches, Random Forest (RF), Support Vector Machine (SVM), as well as a statistical Ordinary Least Squares (OLS) model were established, with the auxiliary data including the 16-day composite MODIS NDVI (MOD13Q1) and Surface Temperature (ST). The entire data were divided into two parts corresponding to ascending (6:00 p.m. local time) and descending (6:00 a.m. local time) orbits of SMAP overpasses. Thus, the three models were trained using the descending data acquired during the five years (2015 to 2019), and validated using the ascending product of the same period. Consequently, three different temporal variations of the soil moisture were obtained based on the three models. To evaluate their accuracies, the retrieved soil moisture was compared against the SMAP level-2 soil moisture product, as well as to in-situ ground station data. The comparative results show that the soil moisture obtained using the OLS, RF and SVM algorithms are highly correlated to the SMAP level-2 product, with high coefficients of determination (R2OLS = 0.981, R2SVM = 0.943, R2RF = 0.983) and low RMSE (RMSEOLS = 0.016 cm3/cm3, RMSESVM = 0.047 cm3/cm3, RMSERF = 0.016 cm3/cm3). Meanwhile, the estimated soil moistures agree with in-situ station data across different years (R2OLS = 0.376~0.85, R2SVM = 0.376~0.814, R2RF = 0.39~0.854; RMSEOLS = 0.049~0.105 cm3/cm3, RMSESVM = 0.073~0.1 cm3/cm3, RMSERF = 0.047~0.102 cm3/cm3), but an overestimation issue is observed for high vegetation conditions. The RF algorithm outperformed the SVM and OLS, in terms of the agreement with the ground measurements. This study suggests an alternative soil moisture retrieval scheme, in complementary to the SMAP baseline algorithm, for a fast soil moisture retrieval. [ABSTRACT FROM AUTHOR]

The reserve of rare-earth element-bearing phosphorite ores in Guizhou province in western China is huge. Increased demand for the different products manufactured from rare-earth elements has resulted in an extreme need for reasonable and comprehensive extraction of rare-earth elements. An improved understanding of rare-earth element occurrence states in single minerals of ores is important for their further processing. In this paper, rare-earth element contents were analyzed by inductively coupled plasma (ICP), and the occurrence states in single minerals were further investigated through SEM-EDS and focused ion beam-scanning electron microscope (FIB-SEM) methods. The results indicate that rare-earth element contents of apatite are far more than that of dolomite. No independent mineral of rare-earth elements exists for the studied sample. Rare-earth elements are present in the form of ions in the lattices of apatite. Based on the analysis of occurrence states and properties in single minerals, the distribution of rare-earth elements in the flotation process was investigated by reverse flotation technology. It shows that rare-earth elements are mainly concentrated in apatite concentrate. Under the optimized conditions, the P2O5 grade increases from 11.36% in the raw ore to 26.04% in the concentrate, and the recovery is 81.92%, while the total rare-earth oxide grade increases from 0.09% to 0.21% with the recovery of 80.01%, which is similar to P2O5 recovery. This study presents the feasibility of extracting rare-earth elements from rare-earth element-bearing phosphorite ores through the flotation of apatite. [ABSTRACT FROM AUTHOR]

Geopolymer-TiO2 nanocomposites were prepared by two different techniques, namely the two-step acidification calcination treatment and one-step adding method. The potential photocatalytic activities of geopolymer-TiO2 nanocomposites prepared by the two different methods were tested and compared. Nanocomposites prepared via the one-step process showed better photocatalytic activity. The amount of TiO2 particles loaded on the surface of the foaming materials was investigated by XRD and SEM-Mapping. By comparing with the sample obtained from two-step treatment, the TiO2 particles were distributed uniformly on the surface of the foaming materials for the sample obtained from the one-step method in this study. Results showed that the specific surface area of the geopolymer-TiO2 prepared by the one-step treatment process (28.67 m2/g) was significantly lower than the two-step acidification calcination process (215.04 m2/g), while the photocatalytic efficiency with methylene blue trihydrate (MB) was better. This is due to the more stable structure of geopolymer-TiO2 nanocomposites, the better dispersion and more loading of TiO2 particles on the foaming materials surfaces, leading to the enhanced photocatalytic activity. [ABSTRACT FROM AUTHOR]

Ecosystem water use efficiency (WUE describes carbon-water flux coupling in terrestrial ecosystems. Understanding response and resilience of WUE to drought are essential for sustainable water resource and ecosystem management under increasing drought risks over China due to climate warming. Here we analyzed the response of ecosystem WUE to drought (spatiotemporal variability and resilience) over China during 1982–2015 based on an evapotranspiration (ET) dataset based on the model tree ensemble (MTE) algorithm using flux-tower ET measurements and satellite-retrieved GPP data. The results showed that the multiyear average WUE was 1.55 g C kg−1 H2O over China. WUE increased in 77.1% of Chinese territory during the past 34 years. During drought periods, the ecosystem WUE increased mainly in the northeast of Inner Mongolia, Northeast China and some regions in southern China with abundant forests but decreased in northwestern and central China. An apparent lagging effect of drought on ecosystem WUE was observed in the east of Inner Mongolia and Northeast China, the west and east regions of North China and the central part of Tibetan Plateau. Some ecosystems (e.g., deciduous needle-leaf forests, deciduous broadleaf forests, evergreen broadleaf forests and evergreen needle-leaf forests) in Central China, Northeast and Southwest China exhibited relatively greater resilience to drought than others by improving their WUE. Our findings would provide useful information for Chinese government to adopt a reasonable approach for maintaining the structure and functions of ecosystems under drought disturbance in future. [ABSTRACT FROM AUTHOR]

The European Space Agency (ESA) Climate Change Initiative (CCI) project combines multi-sensors at different microwave frequencies to derive three harmonized soil moisture products using active, passive and combined approaches. These long-term soil moisture products assist in understanding the global water and carbon cycles. However, extensive validations are a prerequisite before applying the retrieved soil moisture into climatic or hydrological models. To fulfill this objective, we assess the performances of three CCI soil moisture products (active, passive and combined) with respect to in-situ soil moisture networks located in China, Spain and Canada. In order to compensate the scale differences between ground stations and the CCI product's coarse resolution, we adopted two upscaling approaches of Inverse Distance Weighting (IDW) interpolation and simple Arithmetic Mean (AM). The temporal agreements between the satellite retrieved and ground-measured soil moisture were quantified using the unbiased root mean square error (ubRMSE), RMSE, correlation coefficients (R) and bias. Furthermore, the temporal variability of the CCI soil moisture is interpreted and verified with respect to the Tropical Rainfall Measuring Mission (TRMM) precipitation observations. The results show that the temporal variations of CCI soil moisture agreed with the in-situ ground measurements and the precipitation observations over the China and Spain test sites. In contrast, a significant overestimation was observed over the Canada test sites, which may be due to the strong heterogeneity in soil and vegetation characteristics in accordance with the reported poor performance of soil moisture retrieval there. However, despite a retrieval bias, the relatively temporal variation of the CCI soil moisture also followed the ground measurements. For all the three test sites, the soil moisture retrieved from the combined approach outperformed the active-only and passive-only methods, with ubRMSE of 0.034, 0.050, and 0.050–0.054 m3/m3 over the test sites in China, Spain and Canada, respectively. Thus, the CCI combined soil moisture product is suggested to drive the climatic and hydrological studies. [ABSTRACT FROM AUTHOR]

Monitoring urban expansion and greenspace change is an urgent need for planning and decision-making. This paper presents a methodology integrating Principal Component Analysis (PCA) and hybrid classifier to undertake this kind of work using a sequence of multi-sensor SPOT images (SPOT-2,3,5) and Sentinel-2A data from 1996 to 2016 in Hangzhou City, which is the central metropolis of the Yangtze River Delta in China. In this study, orthorectification was first applied on the SPOT and Sentinel-2A images to guarantee precise geometric correction which outperformed the conventional polynomial transformation method. After pre-processing, PCA and hybrid classifier were used together to enhance and extract change information. Accuracy assessment combining stratified random and user-defined plots sampling strategies was performed with 930 reference points. The results indicate reasonable high accuracies for four periods. It was further revealed that the proposed method yielded higher accuracy than that of the traditional post-classification comparison approach. On the whole, the developed methodology provides the effectiveness of monitoring urban expansion and green space change in this study, despite the existence of obvious confusions that resulted from compound factors. [ABSTRACT FROM AUTHOR]