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We report on the mineralogical and chemical properties of materials investigated by the lunar rover Yutu-2, which landed on the Von Kármán crater in the pre-Nectarian South Pole–Aitken (SPA) basin. Yutu-2 carried several scientific payloads, including the Visible and Near-infrared Imaging Spectrometer (VNIS), which is used for mineral identification, offering insights into lunar evolution. We used 86 valid VNIS data for 21 lunar days, with mineral abundance obtained using the Hapke radiative transfer model and sparse unmixing algorithm and chemical compositions empirically estimated. The mineralogical properties of the materials at the Chang’E-4 (CE-4) site referred to as norite/gabbro, based on findings of mineral abundance, indicate that they may be SPA impact melt components excavated by a surrounding impact crater. We find that CE-4 materials are dominated by plagioclase and pyroxene and feature little olivine, with 50 of 86 observations showing higher LCP than HCP in pyroxene. In view of the effects of space weathering, olivine content may be underestimated, with FeO and TiO2 content estimated using the maturity-corrected method. Estimates of chemical content are 7.42–18.82 wt% FeO and 1.48–2.1 wt% TiO2, with a low-medium Mg number (Mg # ~ 55). Olivine-rich materials are not present at the CE-4 landing site, based on the low-medium Mg #. Multi-origin materials at the CE-4 landing site were analyzed with regard to concentrations of FeO and TiO2 content, supporting our conclusion that the materials at CE-4 do not have a single source but rather are likely a mixture of SPA impact melt components excavated by surrounding impact crater and volcanic product ejecta.
Qinghong Zeng; Shengbo Chen; Yuanzhi Zhang; Yongling Mu; Rui Dai; Congyu Yang; Anzhen Li; Peng Lu. Mineralogical and chemical properties inversed from 21-lunar-day VNIS observations taken during the Chang’E-4 mission. Scientific Reports 2021, 11, 1 -10.
AMA StyleQinghong Zeng, Shengbo Chen, Yuanzhi Zhang, Yongling Mu, Rui Dai, Congyu Yang, Anzhen Li, Peng Lu. Mineralogical and chemical properties inversed from 21-lunar-day VNIS observations taken during the Chang’E-4 mission. Scientific Reports. 2021; 11 (1):1-10.
Chicago/Turabian StyleQinghong Zeng; Shengbo Chen; Yuanzhi Zhang; Yongling Mu; Rui Dai; Congyu Yang; Anzhen Li; Peng Lu. 2021. "Mineralogical and chemical properties inversed from 21-lunar-day VNIS observations taken during the Chang’E-4 mission." Scientific Reports 11, no. 1: 1-10.
With the development of industrialization and urbanization, heavy metal contamination in agricultural soils tends to accumulate rapidly and harm human health. Visible and near-infrared (Vis-NIR) spectroscopy provides the feasibility of fast monitoring of the variation of heavy metals. This study explored the potential of fractional-order derivative (FOD), the optimal band combination algorithm and different mathematical models in estimating soil heavy metals with Vis-NIR spectroscopy. A total of 80 soil samples were collected from an agriculture area in Suzi river basin, Liaoning Province, China. The spectra for mercury (Hg), chromium (Cr), and copper (Cu) of the samples were obtained in the laboratory. For spectral preprocessing, FODs were allowed to vary from 0 to 2 with an increment of 0.2 at each step, and the optimal band combination algorithm was applied to the spectra after FOD. Then, four mathematical models, namely, partial least squares regression (PLSR), adaptive neural fuzzy inference system (ANFIS), random forest (RF) and generalized regression neural network (GRNN), were used to estimate the concentration of Hg, Cr and Cu. Results showed that high-order FOD had an excellent effect in highlighting hidden information and separating minor absorbing peaks, and the optimal band combination algorithm could remove the influence of spectral noise caused by high-order FOD. The incorporation of the optimal band combination algorithm and FOD is able to further mine spectral information. Furthermore, GRNN made an obvious improvement to the estimation accuracy of all studied heavy metals compared to ANFIS, PLSR, and RF. In summary, our results provided more feasibility for the rapid estimation of Hg, Cr, Cu and other heavy metal pollution areas in agricultural soils.
Xitong Xu; Shengbo Chen; Liguo Ren; Cheng Han; Donglin Lv; Yufeng Zhang; Fukai Ai. Estimation of Heavy Metals in Agricultural Soils Using Vis-NIR Spectroscopy with Fractional-Order Derivative and Generalized Regression Neural Network. Remote Sensing 2021, 13, 2718 .
AMA StyleXitong Xu, Shengbo Chen, Liguo Ren, Cheng Han, Donglin Lv, Yufeng Zhang, Fukai Ai. Estimation of Heavy Metals in Agricultural Soils Using Vis-NIR Spectroscopy with Fractional-Order Derivative and Generalized Regression Neural Network. Remote Sensing. 2021; 13 (14):2718.
Chicago/Turabian StyleXitong Xu; Shengbo Chen; Liguo Ren; Cheng Han; Donglin Lv; Yufeng Zhang; Fukai Ai. 2021. "Estimation of Heavy Metals in Agricultural Soils Using Vis-NIR Spectroscopy with Fractional-Order Derivative and Generalized Regression Neural Network." Remote Sensing 13, no. 14: 2718.
China’s first Mars exploration mission (Tianwen-1) landed on the southern part of Mars’ Utopia Planitia on 15 May 2021. The Zhurong rover will focus on high-resolution and in situ observations of key areas on the surface of Mars. Dust devils (DDs) are heat-driven vortices that lift material from the surface and inject it into the atmosphere. The dark or bright surface lineaments left by DDs are called dust devil tracks (DDTs). Dust devils can clear dust from solar panels deposited by gusts and dust storms. Therefore, it is of importance to study the encounter rates of dust devils at the Tianwen-1 landing site for achieving the rover’s long-term scientific goals. Based on High Resolution Imaging Science Experiment (HiRISE) and Context Camera (CTX) images, 248 newly formed DDTs in 12 image pairs were firstly identified, and their lengths, widths, and direction in the study area were measured. The distribution of their width frequency follows a −2 differential power law. Secondly, DDT formation rates were computed and analyzed with the range of 0.00006 to 0.1275 ddt km−2 sol−1, mainly affected by factors such as seasons and dust storm occurrence. Thirdly, the solar panel clearing recurrence interval derived from the orbital data in our study area was calculated from ~980 to 166,700 sols. The dust storm occurrence probability at the Tianwen-1 landing area is less than 3%, and there is a special anti-dust coating on board the Zhurong rover. Thus, the Zhurong rover can be considered competent for scientific exploration.
Yi Wang; Bo Li; Jiang Zhang; ZongCheng Ling; Le Qiao; Shengbo Chen; Shaojie Qu. The Preliminary Study of Dust Devil Tracks in Southern Utopia Planitia, Landing Area of Tianwen-1 Mission. Remote Sensing 2021, 13, 2601 .
AMA StyleYi Wang, Bo Li, Jiang Zhang, ZongCheng Ling, Le Qiao, Shengbo Chen, Shaojie Qu. The Preliminary Study of Dust Devil Tracks in Southern Utopia Planitia, Landing Area of Tianwen-1 Mission. Remote Sensing. 2021; 13 (13):2601.
Chicago/Turabian StyleYi Wang; Bo Li; Jiang Zhang; ZongCheng Ling; Le Qiao; Shengbo Chen; Shaojie Qu. 2021. "The Preliminary Study of Dust Devil Tracks in Southern Utopia Planitia, Landing Area of Tianwen-1 Mission." Remote Sensing 13, no. 13: 2601.
The suitability evaluation of agricultural land at the regional scale is of great significance for protecting land and water resources and building sustainable agricultural systems. Based on climate, soil, topographical, and surface water resources, land suitability index (LSI) data for maize, rice, and soybeans are established using an analytical hierarchy process and matter element analysis (AHP–MEA) model in Jilin Province, China. The results show that there is a significant positive linear correlation between the LSI and the measured yield, which indicates that the model has an ideal effect and certain reference and extension significance. The main limiting factors for maize and soybean planting are pH, total nitrogen (TN), available phosphorus (AP), and soil texture, while water shortage limits rice planting. Different spatial structure optimization schemes for planting are established using the LSI and measured yield, along with economic indices. This study shows that the scheme that integrates policy and cost can make full use of land and water resources and promote the economic growth of agriculture. After optimization, the planting areas of maize, rice, and soybeans were 7.22, 2.44, and 0.71 million ha, respectively, representing an increase of 15.71 billion yuan over the agricultural GDP for the existing planting structure. It is expected that this study will provide a basis for follow-up studies on crop cultivation suitability.
Cheng Han; Shengbo Chen; Yan Yu; Zhengyuan Xu; Bingxue Zhu; Xitong Xu; Zibo Wang. Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China. Agriculture 2021, 11, 370 .
AMA StyleCheng Han, Shengbo Chen, Yan Yu, Zhengyuan Xu, Bingxue Zhu, Xitong Xu, Zibo Wang. Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China. Agriculture. 2021; 11 (4):370.
Chicago/Turabian StyleCheng Han; Shengbo Chen; Yan Yu; Zhengyuan Xu; Bingxue Zhu; Xitong Xu; Zibo Wang. 2021. "Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China." Agriculture 11, no. 4: 370.
Image encryption is a confidential strategy to keep the information in digital images from being leaked. Due to excellent chaotic dynamic behavior, self-feedbacked Hopfield networks have been used to design image ciphers. However, Self-feedbacked Hopfield networks have complex structures, large computational amount and fixed parameters; these properties limit the application of them. In this paper, a single neuronal dynamical system in self-feedbacked Hopfield network is unveiled. The discrete form of single neuronal dynamical system is derived from a self-feedbacked Hopfield network. Chaotic performance evaluation indicates that the system has good complexity, high sensitivity, and a large chaotic parameter range. The system is also incorporated into a framework to improve its chaotic performance. The result shows the system is well adapted to this type of framework, which means that there is a lot of room for improvement in the system. To investigate its applications in image encryption, an image encryption scheme is then designed. Simulation results and security analysis indicate that the proposed scheme is highly resistant to various attacks and competitive with some exiting schemes.
Xitong Xu; Shengbo Chen. Single Neuronal Dynamical System in Self-Feedbacked Hopfield Networks and Its Application in Image Encryption. Entropy 2021, 23, 456 .
AMA StyleXitong Xu, Shengbo Chen. Single Neuronal Dynamical System in Self-Feedbacked Hopfield Networks and Its Application in Image Encryption. Entropy. 2021; 23 (4):456.
Chicago/Turabian StyleXitong Xu; Shengbo Chen. 2021. "Single Neuronal Dynamical System in Self-Feedbacked Hopfield Networks and Its Application in Image Encryption." Entropy 23, no. 4: 456.
Saturation effects limit the application of vegetation indices (VIs) in dense vegetation areas. The possibility to mitigate them by adopting a negative soil adjustment factor X is addressed. Two leaf area index (LAI) data sets are analyzed using the Google Earth Engine (GEE) for validation. The first one is derived from observations of MODerate resolution Imaging Spectroradiometer (MODIS) from 16 April 2013, to 21 October 2020, in the Apiacás area. Its corresponding VIs are calculated from a combination of Sentinel-2 and Landsat-8 surface reflectance products. The second one is a global LAI dataset with VIs calculated from Landsat-5 surface reflectance products. A linear regression model is applied to both datasets to evaluate four VIs that are commonly used to estimate LAI: normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), transformed SAVI (TSAVI), and enhanced vegetation index (EVI). The optimal soil adjustment factor of SAVI for LAI estimation is determined using an exhaustive search. The Dickey-Fuller test indicates that the time series of LAI data are stable with a confidence level of 99%. The linear regression results stress significant saturation effects in all VIs. Finally, the exhaustive searching results show that a negative soil adjustment factor of SAVI can mitigate the SAVIs’ saturation in the Apiacás area (i.e., X = −0.148 for mean LAI = 5.35), and more generally in areas with large LAI values (e.g., X = −0.183 for mean LAI = 6.72). Our study further confirms that the lower boundary of the soil adjustment factor can be negative and that using a negative soil adjustment factor improves the computation of time series of LAI.
Zhijun Zhen; Shengbo Chen; Tiangang Yin; Eric Chavanon; Nicolas Lauret; Jordan Guilleux; Michael Henke; Wenhan Qin; Lisai Cao; Jian Li; Peng Lu; Jean-Philippe Gastellu-Etchegorry. Using the Negative Soil Adjustment Factor of Soil Adjusted Vegetation Index (SAVI) to Resist Saturation Effects and Estimate Leaf Area Index (LAI) in Dense Vegetation Areas. Sensors 2021, 21, 2115 .
AMA StyleZhijun Zhen, Shengbo Chen, Tiangang Yin, Eric Chavanon, Nicolas Lauret, Jordan Guilleux, Michael Henke, Wenhan Qin, Lisai Cao, Jian Li, Peng Lu, Jean-Philippe Gastellu-Etchegorry. Using the Negative Soil Adjustment Factor of Soil Adjusted Vegetation Index (SAVI) to Resist Saturation Effects and Estimate Leaf Area Index (LAI) in Dense Vegetation Areas. Sensors. 2021; 21 (6):2115.
Chicago/Turabian StyleZhijun Zhen; Shengbo Chen; Tiangang Yin; Eric Chavanon; Nicolas Lauret; Jordan Guilleux; Michael Henke; Wenhan Qin; Lisai Cao; Jian Li; Peng Lu; Jean-Philippe Gastellu-Etchegorry. 2021. "Using the Negative Soil Adjustment Factor of Soil Adjusted Vegetation Index (SAVI) to Resist Saturation Effects and Estimate Leaf Area Index (LAI) in Dense Vegetation Areas." Sensors 21, no. 6: 2115.
The use of satellite remote sensing could effectively predict maize yield. However, many statistical prediction models using remote sensing data cannot extend to the regional scale without considering the regional climate. This paper first introduced the hierarchical linear modeling (HLM) method to solve maize-yield prediction problems over years and regions. The normalized difference vegetation index (NDVI), calculated by the spectrum of the Landsat 8 operational land imager (OLI), and meteorological data were introduced as input parameters in the maize-yield prediction model proposed in this paper. We built models using 100 samples from 10 areas, and used 101 other samples from 34 areas to evaluate the model’s performance in Jilin province. HLM provided higher accuracy with an adjusted determination coefficient equal to 0.75, root mean square error (RMSEV) equal to 0.94 t/ha, and normalized RMSEV equal to 9.79%. Results showed that the HLM approach outperformed linear regression (LR) and multiple LR (MLR) methods. The HLM method based on the Landsat 8 OLI NDVI and meteorological data could flexibly adjust in different regional climatic conditions. They had higher spatiotemporal expansibility than that of widely used yield estimation models (e.g., LR and MLR). This is helpful for the accurate management of maize fields.
Bingxue Zhu; Shengbo Chen; Yijing Cao; Zhengyuan Xu; Yan Yu; Cheng Han. A Regional Maize Yield Hierarchical Linear Model Combining Landsat 8 Vegetative Indices and Meteorological Data: Case Study in Jilin Province. Remote Sensing 2021, 13, 356 .
AMA StyleBingxue Zhu, Shengbo Chen, Yijing Cao, Zhengyuan Xu, Yan Yu, Cheng Han. A Regional Maize Yield Hierarchical Linear Model Combining Landsat 8 Vegetative Indices and Meteorological Data: Case Study in Jilin Province. Remote Sensing. 2021; 13 (3):356.
Chicago/Turabian StyleBingxue Zhu; Shengbo Chen; Yijing Cao; Zhengyuan Xu; Yan Yu; Cheng Han. 2021. "A Regional Maize Yield Hierarchical Linear Model Combining Landsat 8 Vegetative Indices and Meteorological Data: Case Study in Jilin Province." Remote Sensing 13, no. 3: 356.
Single-frequency precise point positioning (PPP) is widely used with the advantage of cost-efficient, while its further development and application are limited by the difficulty of ionospheric delay correction and the long-time convergence, especially for real-time positioning. And the development of high-accuracy ionospheric models plays an important role for the correction of ionospheric delay in single-frequency PPP. In this paper, the final and rapid global ionospheric map (GIM) products released by Chinese Academy of Science (CAS), Center for Orbit Determination in Europe (CODE), European Space Agency (ESA), Jet Propulsion Laboratory (JPL), Universitat Politècnica de Catalunya (UPC), Wuhan University (WHU) and International GNSS Service (IGS) were used as external constraints in static, simulation kinematic and kinematic single-frequency PPP respectively. The performance and practicality of each product were analyzed by using IGS station observation data (September 2017 and January 2018, with different ionospheric activity levels) and a kinematic experiment. The results indicate that GIM products may improve convergence time in most areas of middle and high latitudes of the globe. However, the improvement of convergence time of some regions in low latitudes or near the equator with dense and uniform distributed IGS stations show even better performance than the regions in middle and high latitudes. Comparing with standard PPP (S-PPP), the convergence time of static PPP is reduced about 14–42% and 13–29% with GIM final and rapid products respectively. In simulation kinematic PPP, the convergence time improves 10–43% and 12–25% for final and rapid products respectively. In the kinematic positioning, the addition of external ionospheric constraints may speed up the convergence in the early stage of positioning and improve the accuracy to a certain extent. Among all GIM products, the final products show better performance than that of the rapid products obviously. The GIM products from CAS and CODE and UQRG from UPC express the best performance are recommended to process ionospheric delay in the high-accuracy positioning.
Qiong Wu; Peng Zhang; Mengfei Sun; Shi Liu; He Wang; Shengbo Chen. Performance evaluation of GIMs released by different IGS ionosphere associate analysis centers in ionospheric constrained single-frequency precise point positioning. Advances in Space Research 2020, 1 .
AMA StyleQiong Wu, Peng Zhang, Mengfei Sun, Shi Liu, He Wang, Shengbo Chen. Performance evaluation of GIMs released by different IGS ionosphere associate analysis centers in ionospheric constrained single-frequency precise point positioning. Advances in Space Research. 2020; ():1.
Chicago/Turabian StyleQiong Wu; Peng Zhang; Mengfei Sun; Shi Liu; He Wang; Shengbo Chen. 2020. "Performance evaluation of GIMs released by different IGS ionosphere associate analysis centers in ionospheric constrained single-frequency precise point positioning." Advances in Space Research , no. : 1.
Black soil in northeast China is gradually degraded and soil organic matter (SOM) content decreases at a rate of 0.5% per year because of the long-term cultivation. SOM content can be obtained rapidly by visible and near-infrared (Vis–NIR) spectroscopy. It is critical to select appropriate preprocessing techniques for SOM content estimation through Vis–NIR spectroscopy. This study explored three categories of preprocessing techniques to improve the accuracy of SOM content estimation in black soil area, and a total of 496 ground samples were collected from the typical black soil area at 0–15 cm in Hai Lun City, Heilongjiang Province, northeast of China. Three categories of preprocessing include denoising, data transformation and dimensionality reduction. For denoising, Svitzky-Golay filter (SGF), wavelet packet transform (WPT), multiplicative scatter correction (MSC), and none (N) were applied to spectrum of ground samples. For data transformation, fractional derivatives were allowed to vary from 0 to 2 with an increment of 0.2 at each step. For dimensionality reduction, multidimensional scaling (MDS) and locally linear embedding (LLE) were introduced and compared with principal component analysis (PCA), which was commonly used for dimensionality reduction of soil spectrum. After spectral pretreatments, a total of 132 partial least squares regression (PLSR) models were constructed for SOM content estimation. Results showed that SGF performed better than the other three denoising methods. Low-order derivatives can accentuate spectral features of soil for SOM content estimation; as the order increases from 0.8, the spectrum were more susceptible to spectral noise interferences. In most cases, 0.2–0.8 order derivatives exhibited the best estimation performance. Furthermore, PCA yielded the optimal predictability, the mean residual predictive deviation (RPD) and maximum RPD of the models using PCA were 1.79 and 2.60, respectively. The application of appropriate preprocessing techniques could improve the efficiency and accuracy of SOM content estimation, which is important for the protection of ecological and agricultural environment in black soil area.
Xitong Xu; Shengbo Chen; Zhengyuan Xu; Yan Yu; Sen Zhang; Rui Dai. Exploring Appropriate Preprocessing Techniques for Hyperspectral Soil Organic Matter Content Estimation in Black Soil Area. Remote Sensing 2020, 12, 3765 .
AMA StyleXitong Xu, Shengbo Chen, Zhengyuan Xu, Yan Yu, Sen Zhang, Rui Dai. Exploring Appropriate Preprocessing Techniques for Hyperspectral Soil Organic Matter Content Estimation in Black Soil Area. Remote Sensing. 2020; 12 (22):3765.
Chicago/Turabian StyleXitong Xu; Shengbo Chen; Zhengyuan Xu; Yan Yu; Sen Zhang; Rui Dai. 2020. "Exploring Appropriate Preprocessing Techniques for Hyperspectral Soil Organic Matter Content Estimation in Black Soil Area." Remote Sensing 12, no. 22: 3765.
Radar imagery have few polarization bands which can limit the ability to do traditional digital classification. Harmonization of Sentinel-1 and Landsat 8 data despite having complementary texture information can be a challenge. The objectives of this paper are to explore texture features derived from Landsat 8 OLI and dual-polarized Sentinel-1 SAR speckle filtered and unfiltered backscatter, to aggregate classification results using Decision-Level Fusion (DLF), and to evaluate the performance of decision-level fused maps. Gray Level Co-occurrence Matrix (GLCM) is employed to derive sets of seven texture features for Landsat 8 bands and VV + VH backscatter using 5 × 5, 7 × 7, 9 × 9, and 11 × 11 window sizes. Each texture feature is stacked with a respective source image and classified using Support Vector Machine (SVM). Classified maps from the best three performers from both speckle filtered and unfiltered are aggregated with classified maps from Landsat 8 using plurality voting algorithm and compared using Z-test. Results indicate an overall classification accuracy of 96.02% from DLF images of Landsat and non-speckle filtered maps, whereas Landsat and speckle filtered achieved 94.69%. The best texture information are derived from the blue band followed by the red band, whereas speckle unfiltered textures performed better than speckle filtered textures. We conclude that integration of Landsat 8 and Sentinel-1, either speckle filtered or unfiltered, improves crop classification and speckles do not have statistically significant effects (p = 0.1208).
Shengbo Chen; Juliana Useya; Hillary Mugiyo. Decision-level fusion of Sentinel-1 SAR and Landsat 8 OLI texture features for crop discrimination and classification: case of Masvingo, Zimbabwe. Heliyon 2020, 6, 1 .
AMA StyleShengbo Chen, Juliana Useya, Hillary Mugiyo. Decision-level fusion of Sentinel-1 SAR and Landsat 8 OLI texture features for crop discrimination and classification: case of Masvingo, Zimbabwe. Heliyon. 2020; 6 (11):1.
Chicago/Turabian StyleShengbo Chen; Juliana Useya; Hillary Mugiyo. 2020. "Decision-level fusion of Sentinel-1 SAR and Landsat 8 OLI texture features for crop discrimination and classification: case of Masvingo, Zimbabwe." Heliyon 6, no. 11: 1.
Ecological water replenishment (EWR) has been increasingly applied to the restoration and maintenance of wetland hydrological conditions across China since the beginning of the 21st century. However, little is known about whether EWR projects help protect and/or restore wetland ecohydrology. As one of the earliest and longest-running EWR projects in China, water has been released from the Nenjiang River into the Zhalong wetland since 2001. It is important to examine the ecohydrological effects of this EWR project. In this study, long time series remote sensing data were used to extract the water area, inundation frequency, and normalized difference vegetation index (NDVI) to explore how eco-hydrological conditions changed during the pre- (1984–2000) and post-EWR (2001–2018) periods in the Zhalong wetland. Results show that the inundation area decreased due to the reduced surface water inflow during the pre-EWR period. Similarly, monthly vegetation NDVI in the growing season generally exhibited a decreasing and an increasing trend during the pre- and post-EWR periods, respectively. In the post-EWR period, NDVI increased by 19%, 73%, 45%, 28%, 13% for the months of May through September, respectively. Due to EWR, vegetation growth in areas with low inundation frequency was better than in areas with high inundation frequency. We found that the EWR project, runoff, and precipitation contributed 25%, 11%, and 64% to changes in the NDVI, respectively, and 46%, 37%, and 17% to changes in inundation area, respectively. These results indicate that the EWR project has improved hydrological conditions in the Zhalong wetland. For further maximum benefits of EWR in the Zhalong wetlands, we suggest that implementing similar eco-hydrological projects in the future should focus on flood pulse management to increase the inundation area, improve hydrological connectivity, and create new habitats.
Liwen Chen; Sixin Liu; Yanfeng Wu; Y. Xu; Shengbo Chen; Shiliang Pang; Zongting Gao; Guangxin Zhang. Does Ecological Water Replenishment Help Prevent a Large Wetland from Further Deterioration? Results from the Zhalong Nature Reserve, China. Remote Sensing 2020, 12, 3449 .
AMA StyleLiwen Chen, Sixin Liu, Yanfeng Wu, Y. Xu, Shengbo Chen, Shiliang Pang, Zongting Gao, Guangxin Zhang. Does Ecological Water Replenishment Help Prevent a Large Wetland from Further Deterioration? Results from the Zhalong Nature Reserve, China. Remote Sensing. 2020; 12 (20):3449.
Chicago/Turabian StyleLiwen Chen; Sixin Liu; Yanfeng Wu; Y. Xu; Shengbo Chen; Shiliang Pang; Zongting Gao; Guangxin Zhang. 2020. "Does Ecological Water Replenishment Help Prevent a Large Wetland from Further Deterioration? Results from the Zhalong Nature Reserve, China." Remote Sensing 12, no. 20: 3449.
The Rümker region is located in the northern Oceanus Procellarum, which has been selected as the landing and sampling region for China’s Chang’e-5 (CE-5) mission. The thermophysical features of the mare units are studied in detail using the brightness temperature (TB) maps (TB, normalized TB, TB difference) derived from the CE-2 microwave radiometer data. The previously interpreted geological boundaries of the Rümker region are revisited in this study according to their TB behaviors: IR1, IR2, and IR3 Rümker plateau units are combined into one single unit (IR); and a hidden unit is found on the Mons Rümker; Mare basaltic units Im1 and Em1 are combined into Em1; and Em2 is more likely the extending of Im2. Each of the previous proposed landing sites and their scientific value are summarized and reevaluated. Based on this, four landing sites are recommended in order to maximize the scientific outcome of the CE-5 mission. We suggest that the Eratosthenian-aged Em4 and Em1 units as the top priority landing site for the CE-5 mission; the age-dating results will provide important clues concerning the thermal evolution of the Moon.
Zhiguo Meng; Jietao Lei; Yuqi Qian; Long Xiao; James Head; Shengbo Chen; Weiming Cheng; Jiancheng Shi; Jinsong Ping; Zhizhong Kang. Thermophysical Features of the Rümker Region in Northern Oceanus Procellarum: Insights from CE-2 CELMS Data. Remote Sensing 2020, 12, 3272 .
AMA StyleZhiguo Meng, Jietao Lei, Yuqi Qian, Long Xiao, James Head, Shengbo Chen, Weiming Cheng, Jiancheng Shi, Jinsong Ping, Zhizhong Kang. Thermophysical Features of the Rümker Region in Northern Oceanus Procellarum: Insights from CE-2 CELMS Data. Remote Sensing. 2020; 12 (19):3272.
Chicago/Turabian StyleZhiguo Meng; Jietao Lei; Yuqi Qian; Long Xiao; James Head; Shengbo Chen; Weiming Cheng; Jiancheng Shi; Jinsong Ping; Zhizhong Kang. 2020. "Thermophysical Features of the Rümker Region in Northern Oceanus Procellarum: Insights from CE-2 CELMS Data." Remote Sensing 12, no. 19: 3272.
Chlorophyll-a (Chl-a) concentration retrieval is essential for water quality monitoring, aquaculture, and guiding coastline infrastructure construction. Compared with common ocean color satellites, land observation satellites have the advantage of a higher resolution and more data sources for retrieving the concentration of Chl-a from optically shallow waters. However, the sun glint (Rsg), bottom reflectance (Rb), and non-algal particle (NAP) derived from terrigenous matter affect the accuracy of Chl-a concentration retrieval using land observation satellite image data. In this paper, we propose a semi-empirical algorithm based on the remote sensing reflectance (Rrs) of SPOT6 to retrieve the Chl-a concentration in Sanya Bay (SYB), considering the effect of Rsg, Rb, and NAP. In this semi-empirical algorithm, the Cox–Munk anisotropic model and radiative transfer model (RTM) were used to reduce the effects of Rsg and Rb on Rrs, and the Chl-a concentration was retrieved by the Chl-a absorption coefficient at 490 nm (aphy(490)) to remove the effect of NAP. The semi-empirical algorithm was in the form of Chl-a = 43.3[aphy(490)]1.454, where aphy (490) was calculated by the total absorption coefficient and the absorption coefficients of each component by empirical algorithms. The results of the Chl-a concentration retrieval show the following: (1) SPOT6 data are available for Chl-a retrieval using this semi-empirical algorithm in oligotrophic or mesotrophic coastal waters, and the accuracy of the algorithm can be improved by removing the effects of Rsg, Rb, and NAP (R2 from 0.71 to 0.93 and root mean square error (RMSE) from 0.23 to 0.11 ug/L); (2) empirical algorithms based on the blue-green band are suitable for oligotrophic or mesotrophic coastal waters, and the algorithm based on the blue-green band difference Chl-a index (DCI) has stronger anti-interference in terms of the effects of sun glint and bottom reflectance than the algorithm based on the blue-green ratio (BGr); (3) in the case of ignoring Rsg unrelated to inherent optical properties (IOPs), NAP is the biggest interference factor when >9.5 mg/L and the effect of bottom reflectance should be considered when the water depth (H) <5 m in SYB; and (4) the inherent optical properties of the waters in SYB are dominated by NAP (Chl-a = 0.2−2.6 ug/L and NAP = 2.2−30.1 mg/L), and the nutrients are concentrated by enclosed terrain and southeast current. This semi-empirical algorithm for Chl-a concentration retrieval has the potential to monitor Chl-a in oligotrophic and mesotrophic coastal waters using other land observation satellites (e.g., Landsat8 OLI, ASTER, and GaoFen2).
Yan Yu; Shengbo Chen; Wenhan Qin; Tianqi Lu; Jian Li; Yijing Cao. A Semi-Empirical Chlorophyll-a Retrieval Algorithm Considering the Effects of Sun Glint, Bottom Reflectance, and Non-Algal Particles in the Optically Shallow Water Zones of Sanya Bay Using SPOT6 Data. Remote Sensing 2020, 12, 2765 .
AMA StyleYan Yu, Shengbo Chen, Wenhan Qin, Tianqi Lu, Jian Li, Yijing Cao. A Semi-Empirical Chlorophyll-a Retrieval Algorithm Considering the Effects of Sun Glint, Bottom Reflectance, and Non-Algal Particles in the Optically Shallow Water Zones of Sanya Bay Using SPOT6 Data. Remote Sensing. 2020; 12 (17):2765.
Chicago/Turabian StyleYan Yu; Shengbo Chen; Wenhan Qin; Tianqi Lu; Jian Li; Yijing Cao. 2020. "A Semi-Empirical Chlorophyll-a Retrieval Algorithm Considering the Effects of Sun Glint, Bottom Reflectance, and Non-Algal Particles in the Optically Shallow Water Zones of Sanya Bay Using SPOT6 Data." Remote Sensing 12, no. 17: 2765.
Mons Rümker is a preferred candidate landing region for China's Chang'e-5 (CE-5) mission, from where it is of great significance to select safe landing areas. Lunar terrain factors from Digital Elevation Model (DEM) data, limited by their low resolutions (~10 m/pixel), are inapplicable to evaluating the lunar landing area safety, in spite of the fact that lunar remote sensing imagery has higher resolution (~50 cm/pixel). In this paper, we extracted terrain factors in divided square girds by the aid of the high-resolution Lunar Reconnaissance Orbiter (LRO) Narrow-angle Camera (NAC) images, namely, flat area percentage (Fap), distribution pattern of uneven objects (NNI) based on the double-threshold Otsu method, and roughness based on gray level histogram analysis. Mons Rümker can be divided into four geological units, named as LD, B1, B2, and B3, respectively. Unit B1 has a higher roughness and a lower Fap. Unit B2 and B3 are characterized with the highest Fap and the lowest roughness. NNIs of Unit B1, B2, and B3 are >1 while LD's is <1. Thus, the distribution patterns of uneven objects in Unit LD are clustered but dispersed in all Unit B1, B2, and B3. This paper tends to take Fap and roughness as the main terrain factors to evaluate the safety for CE-5 landing in Mons Rümker with NNI being a supplement to Fap. According to Standard 1–3 mentioned in this paper, we would classify the divided square grids of the Mons Rümker region as the safe or unsafe areas, and then discriminate five potential landing areas for CE-5 probe safe landing.
Bo Li; Jiang Zhang; Zongyu Yue; Peiwen Yao; Chenfan Li; Shengbo Chen; Le Qiao; Xiaohui Fu; ZongCheng Ling; Jian Chen; Shouxin Liu. Deriving terrain factors from high-resolution lunar images: A case study of the Mons Rümker Region. Geomorphology 2020, 358, 107114 .
AMA StyleBo Li, Jiang Zhang, Zongyu Yue, Peiwen Yao, Chenfan Li, Shengbo Chen, Le Qiao, Xiaohui Fu, ZongCheng Ling, Jian Chen, Shouxin Liu. Deriving terrain factors from high-resolution lunar images: A case study of the Mons Rümker Region. Geomorphology. 2020; 358 ():107114.
Chicago/Turabian StyleBo Li; Jiang Zhang; Zongyu Yue; Peiwen Yao; Chenfan Li; Shengbo Chen; Le Qiao; Xiaohui Fu; ZongCheng Ling; Jian Chen; Shouxin Liu. 2020. "Deriving terrain factors from high-resolution lunar images: A case study of the Mons Rümker Region." Geomorphology 358, no. : 107114.
Mare Moscoviense (148°E, 27°N) is one of the few large maria on the lunar farside, with the thinnest crust and a positive gravity anomaly. In this paper, the Chang’E-2 Microwave Sounder (CELMS) data was employed to study the microwave thermal emission features of mare basalts in Moscoviense Basin. The time angle and linear interpolation method are used to generate the brightness temperature (TB) maps at noon and night, as well as the TB difference (dTB) map. The obtained important results are as follows. (1) A new geologic map is generated with the TB and dTB maps using the maximum likelihood method, which gives a new expression about the basaltic units in Mare Moscoviense compared to the optical results; (2) the substrate temperature of Moscoviense Basin is likely warmer than what we know; (3) unit Ihtm (a Late (?) Imbrian, mid- to high-Ti, high-Fe basalt) is re-understood as two independent volcanic features with their own fissures; (4) the dTB maps firstly indicate that the depth lunar regolith is homogeneous in the highlands surrounding Mare Moscoviense, at least in the microwave domain, and secondly that there exists a special material bringing about the low dTB anomaly in the shallow layer of the east highlands. The results will be of great significance to better understand the basaltic volcanism of the Moon.
Zhiguo Meng; Shengbo Chen; Yongzhi Wang; Tianxing Wang; ZhanChuan Cai; Yuanzhi Zhang; Yongchun Zheng; Shuo Hu. Reevaluating Mare Moscoviense And Its Vicinity Using Chang’e-2 Microwave Sounder Data. Remote Sensing 2020, 12, 535 .
AMA StyleZhiguo Meng, Shengbo Chen, Yongzhi Wang, Tianxing Wang, ZhanChuan Cai, Yuanzhi Zhang, Yongchun Zheng, Shuo Hu. Reevaluating Mare Moscoviense And Its Vicinity Using Chang’e-2 Microwave Sounder Data. Remote Sensing. 2020; 12 (3):535.
Chicago/Turabian StyleZhiguo Meng; Shengbo Chen; Yongzhi Wang; Tianxing Wang; ZhanChuan Cai; Yuanzhi Zhang; Yongchun Zheng; Shuo Hu. 2020. "Reevaluating Mare Moscoviense And Its Vicinity Using Chang’e-2 Microwave Sounder Data." Remote Sensing 12, no. 3: 535.
Spatiotemporal changes in the surface area of inland water bodies have important implications in regional water resources, flood control, and drought hazard prediction. Although inland water bodies have been investigated intensively, few studies have looked at the effect of human activities and climate variability on surface area of inland waters at a larger scale over time and space. In this study, we used MODIS (MOD13Q1) images to determine water surface area extent at 250 m spatial resolution. We then applied this algorithm with MOD13Q1 images taken at 16-day intervals from 2000 to 2018 to a large river basin in China’s northeast high latitude region with dense stream network and abundant wetlands to investigate spatiotemporal distribution and dynamics of inland water bodies. The study identified 209 ponds, lakes, and reservoirs with an average total surface area of 2080 km2 in the past 19 years. The total water surface area fluctuated largely from 942 km2 to 5169 km2, corresponding to rainfall intensity and flood. We found that the total water surface area in this high latitude river basin showed an increasing trend during the study period, while the annual precipitation amount in the river basin also had an increasing trend concurrently. Precipitation and irrigation significantly contributed to the monthly change of water surface area, which reached the highest during June and August. The increase of water surface area was significant in the lower basin floodplain region, where agricultural irrigation using groundwater for rice production has progressed. Four nationally important wetland preserves (Zhalong, Xianghai, Momoge, and Chagan Lake) in the river basin made up nearly 50% of the basin’s total water surface area, of which Zhalong, Xianghai, and Momoge are designated by The Ramsar Convention as wetland sites of international importance. Seasonally, these water bodies reached their maximal surface area in August, when both the monsoon weather and agricultural discharge prevailed. This study demonstrates that water surface area in a high latitude river basin is affected by both human activities and climate variation, implying that high latitude regions will likely experience more changes in surface water distribution as global climate change continues and agriculture becomes intensified.
Liwen Chen; Guangxin Zhang; Y. Jun Xu; Shengbo Chen; Yanfeng Wu; Zongting Gao; Haiyang Yu; Chen. Human Activities and Climate Variability Affecting Inland Water Surface Area in a High Latitude River Basin. Water 2020, 12, 382 .
AMA StyleLiwen Chen, Guangxin Zhang, Y. Jun Xu, Shengbo Chen, Yanfeng Wu, Zongting Gao, Haiyang Yu, Chen. Human Activities and Climate Variability Affecting Inland Water Surface Area in a High Latitude River Basin. Water. 2020; 12 (2):382.
Chicago/Turabian StyleLiwen Chen; Guangxin Zhang; Y. Jun Xu; Shengbo Chen; Yanfeng Wu; Zongting Gao; Haiyang Yu; Chen. 2020. "Human Activities and Climate Variability Affecting Inland Water Surface Area in a High Latitude River Basin." Water 12, no. 2: 382.
The selection of an appropriate global gravity field model and refinement method can effectively improve the accuracy of the refined regional geoid model in a certain research area. We analyzed the accuracy of Experimental Geopotential Model (XGM2016) based on the GPS-leveling data and the modification parameters of the global mean square errors in the KTH geoid refinement in Jilin Province, China. The regional geoid was refined based on Earth Gravitational Model (EGM2008) and XGM2016 using both the Helmert condensation method with an RCR procedure and the KTH method. A comparison of the original two gravity field models to the GPS-leveling benchmarks showed that the accuracies of XGM2016 and EGM2008 in the plain area of Jilin Province are similar with a standard deviation (STD) of 5.8 cm, whereas the accuracy of EGM2008 in the high mountainous area is 1.4 cm better than that of XGM2016, which may be attributed to its low resolution. The modification parameters between the two gravity field models showed that the coefficient error of XGM2016 model was lower than that of EGM2008 for the same degree of expansion. The different modification limits and integral radii may produce a centimeter level difference in global mean square error, while the influence of the truncation error caused by the integral was at the millimeter level. The terrestrial gravity data error accounted for the majority of the global mean square error. The optimal least squares modification obtained the minimum global mean square error, and the global mean square error calculated based on XGM2016 model was reduced by about 1~3 cm compared with EGM2008. The refined geoid based on the two gravity field models indicated that both KTH and RCR method can effectively improve the STD of the geoid model from about six to three centimeters. The refined accuracy of EGM2008 model using RCR and KTH methods is slightly better than that of XGM2016 model in the plain and high mountain areas after seven-parameter fitting. EGM2008 based on the KTH method was the most precise at ± 2.0 cm in the plain area and ± 2.4 cm in the mountainous area. Generally, for the refined geoid based on the two Earth gravity models, KTH produced results similar to RCR in the plain area, and had relatively better performance for the mountainous area where terrestrial gravity data is sparse and unevenly distributed.
Qiong Wu; Hongyao Wang; Bin Wang; Shengbo Chen; Hongqing Li. Performance Comparison of Geoid Refinement between XGM2016 and EGM2008 Based on the KTH and RCR Methods: Jilin Province, China. Remote Sensing 2020, 12, 324 .
AMA StyleQiong Wu, Hongyao Wang, Bin Wang, Shengbo Chen, Hongqing Li. Performance Comparison of Geoid Refinement between XGM2016 and EGM2008 Based on the KTH and RCR Methods: Jilin Province, China. Remote Sensing. 2020; 12 (2):324.
Chicago/Turabian StyleQiong Wu; Hongyao Wang; Bin Wang; Shengbo Chen; Hongqing Li. 2020. "Performance Comparison of Geoid Refinement between XGM2016 and EGM2008 Based on the KTH and RCR Methods: Jilin Province, China." Remote Sensing 12, no. 2: 324.
The relationship between urban landscape pattern and land surface temperature (LST) is one of the core issues in urban thermal environment research. Although previous studies have shown a significant correlation between LST and landscape pattern, most were conducted at a single scale and rarely involve multi-scale effects of the landscape pattern. Wavelet coherence can relate the correlation between LST and landscape pattern to spatial scale and location, which is an effective multi-scale correlation method. In this paper, we applied wavelet coherence and Pearson correlation coefficient to analyze the multi-scale correlations between landscape pattern and LST, and analyzed the spatial pattern of the urban thermal environment during the urbanization of Beijing from 2004 to 2017 by distribution index of high-temperature center (HTC). The results indicated that the HTC of Beijing gradually expands from the main urban zone and urban function extended zone to the new urban development zone and far suburb zone, and develops from monocentric to polycentric spatial pattern. Land cover types, such as impervious surfaces and bare land, have a positive contribution to LST, while water and vegetation play a role in mitigating LST. The wavelet coherence and Pearson correlation coefficients showed that landscape composition and spatial configuration have significant effects on LST, but landscape composition has a greater effect on LST in Beijing metropolitan area. Landscape composition indexes (NDBI and NDVI) showed significant multi-scale characteristics with LST, especially at larger scales, which has a strong correlation on the whole transect. There was no significant correlation between the spatial configuration indexes (CONTAG, DIVISION, and LSI) and LST at smaller scales, only at larger scales near the urban area has a significant correlation. With the increase of the scale, Pearson correlation coefficient calculated by spatial rectangle sampling and wavelet coherence coefficient have the same trend, although it had some fluctuations in several locations. However, the wavelet coherence coefficient diagram was smoother and less affected by position and rectangle size, which more conducive to describe the correlation between landscape pattern index and LST at different scales and locations. In general, wavelet coherence provides a multi-scale method to analyze the relationship between landscape pattern and LST, helping to understand urban planning and land management to mitigate the factors affecting urban thermal environment.
Qiong Wu; Jinxiang Tan; Fengxiang Guo; Hongqing Li; Shengbo Chen. Multi-Scale Relationship between Land Surface Temperature and Landscape Pattern Based on Wavelet Coherence: The Case of Metropolitan Beijing, China. Remote Sensing 2019, 11, 3021 .
AMA StyleQiong Wu, Jinxiang Tan, Fengxiang Guo, Hongqing Li, Shengbo Chen. Multi-Scale Relationship between Land Surface Temperature and Landscape Pattern Based on Wavelet Coherence: The Case of Metropolitan Beijing, China. Remote Sensing. 2019; 11 (24):3021.
Chicago/Turabian StyleQiong Wu; Jinxiang Tan; Fengxiang Guo; Hongqing Li; Shengbo Chen. 2019. "Multi-Scale Relationship between Land Surface Temperature and Landscape Pattern Based on Wavelet Coherence: The Case of Metropolitan Beijing, China." Remote Sensing 11, no. 24: 3021.
The lunar permanently shaded areas are located on the Moon’s poles and are usually deep in craters where sunlight can’t reach. Moon is centered on the very cold regions near both lunar poles that...
Liang Zhao; Shengbo Chen. Lunar Permanently Shaded Areas. Encyclopedia of Lunar Science 2019, 1 -4.
AMA StyleLiang Zhao, Shengbo Chen. Lunar Permanently Shaded Areas. Encyclopedia of Lunar Science. 2019; ():1-4.
Chicago/Turabian StyleLiang Zhao; Shengbo Chen. 2019. "Lunar Permanently Shaded Areas." Encyclopedia of Lunar Science , no. : 1-4.
Yan’an new district (YND) is one of the largest civil engineering projects for land creation in Loess Plateau, of which the amount of earthwork exceeds 600 million m3, to create 78.5 km2 of flat land. Such mega-scale engineering activities and complex geological characteristics have induced wide land deformation in the region. Small baseline subset synthetic aperture radar interferometry (SBAS-InSAR) method and 55 Sentinel-1A (S-1A) images were utilized in the present work to investigate the urban surface deformation in the Yan’an urban area and Yan’an new airport (YNA) from 2015 to 2019. The results were validated by the ground leveling measurements in the YNA. It is found that significant uneven surface deformation existed in both YND and YNA areas with maximum accumulative subsidence of 300 and 217 mm, respectively. Moreover, the average subsidence rate of the YND and YNA areas ranged from −70 to 30 mm/year and −50 to 25 mm/year, respectively. The present work shows that the land deformation suffered two periods (from 2015 to 2017 and from 2017 to 2019) and expanded from urban center to surrounding resettlement area, which are highly relevant with urban earthwork process. It is found that more than 60% of land subsidence occurs at filled areas, while more than 65% of surface uplifting occurs at excavation areas. The present work shows that the subsidence originates from the earth filling and the load of urban buildings, while the release of stress is the major factor for the land uplift. Moreover, it is found that the collapsibility of loess and concentrated precipitation deteriorates the degree of local land subsidence. The deformation discovered by this paper shows that the city may suffer a long period of subsidence, and huge challenges may exist in the period of urban maintaining buildings and infrastructure facilities.
Qiong Wu; Chunting Jia; Shengbo Chen; Hongqing Li. SBAS-InSAR Based Deformation Detection of Urban Land, Created from Mega-Scale Mountain Excavating and Valley Filling in the Loess Plateau: The Case Study of Yan’an City. Remote Sensing 2019, 11, 1673 .
AMA StyleQiong Wu, Chunting Jia, Shengbo Chen, Hongqing Li. SBAS-InSAR Based Deformation Detection of Urban Land, Created from Mega-Scale Mountain Excavating and Valley Filling in the Loess Plateau: The Case Study of Yan’an City. Remote Sensing. 2019; 11 (14):1673.
Chicago/Turabian StyleQiong Wu; Chunting Jia; Shengbo Chen; Hongqing Li. 2019. "SBAS-InSAR Based Deformation Detection of Urban Land, Created from Mega-Scale Mountain Excavating and Valley Filling in the Loess Plateau: The Case Study of Yan’an City." Remote Sensing 11, no. 14: 1673.