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Yunwei Li; Kegen Yu; Taoyong Jin; Xin Chang; Qi Wang; Jiancheng Li. Correction to: Development of a GNSS‑IR instrument based on low‑cost positioning chips and its performance evaluation for estimating the reflector height. GPS Solutions 2021, 25, 1 -1.
AMA StyleYunwei Li, Kegen Yu, Taoyong Jin, Xin Chang, Qi Wang, Jiancheng Li. Correction to: Development of a GNSS‑IR instrument based on low‑cost positioning chips and its performance evaluation for estimating the reflector height. GPS Solutions. 2021; 25 (4):1-1.
Chicago/Turabian StyleYunwei Li; Kegen Yu; Taoyong Jin; Xin Chang; Qi Wang; Jiancheng Li. 2021. "Correction to: Development of a GNSS‑IR instrument based on low‑cost positioning chips and its performance evaluation for estimating the reflector height." GPS Solutions 25, no. 4: 1-1.
Global Navigation Satellite System interferometric reflectometry (GNSS-IR) can be used to monitor a series of geophysical parameters in a cost-effective manner with high temporal resolution. The technique makes use of the simultaneous reception of direct and reflected GNSS signals with a single antenna. Based on the low-cost u-blox M8N chips, a GNSS-IR instrument is developed, which could be used to collect and process GNSS signals automatically and save and transmit generated GNSS data. Details about the instrument are described here for the first time. Then, the recorded SNR observation characteristics are analyzed by comparing three in-situ SNR sequences, which are simultaneously collected by the instrument with a low-cost patch antenna and a geodetic antenna and by a geodetic GNSS receiver with a geodetic antenna. Based on the developed function relating the peak power spectral density to peak frequency estimation error of the low-cost instrument, a weighting method is proposed to fuse multiple estimations of the reflector height to improve the estimation accuracy of the GNSS-IR-based reflector height. The performances of the developed low-cost instrument and the proposed reflector height estimation method are evaluated using a data set collected in Xinxiang City, Henan, China, over 6 days. The results show that there exists good agreement between the instrument-based reflector height estimates and the ground-truth estimates, with root-mean-square errors of 1.1 cm and 0.4 cm for the normal average and the proposed weighted average results, respectively, when the antenna height is in the range of 0.65 m to 2.15 m and the reflecting surface is flat, silty loam soil ground.
Yunwei Li; Kegen Yu; Taoyong Jin; Xin Chang; Qi Wang; Jiancheng Li. Development of a GNSS-IR instrument based on low-cost positioning chips and its performance evaluation for estimating the reflector height. GPS Solutions 2021, 25, 1 -12.
AMA StyleYunwei Li, Kegen Yu, Taoyong Jin, Xin Chang, Qi Wang, Jiancheng Li. Development of a GNSS-IR instrument based on low-cost positioning chips and its performance evaluation for estimating the reflector height. GPS Solutions. 2021; 25 (4):1-12.
Chicago/Turabian StyleYunwei Li; Kegen Yu; Taoyong Jin; Xin Chang; Qi Wang; Jiancheng Li. 2021. "Development of a GNSS-IR instrument based on low-cost positioning chips and its performance evaluation for estimating the reflector height." GPS Solutions 25, no. 4: 1-12.
Adaptive and accurate trend estimation of the sea level record is critically important for characterizing its nonlinear variations and its study as a consequence of anthropogenic climate change. Sea level change is a nonstationary or nonlinear process. The present modeling methods, such as least‐squares fitting, are unable to accommodate nonlinear changes, including the choice of a priori information to help constrain the modeling. All these problems affect the accuracy and adaptability of nonlinear trend estimation. Here, we propose a method called EMD‐SSA, that effectively combines adaptive empirical mode decomposition (EMD) and singular spectrum analysis (SSA). First, the sea level change time series is decomposed by EMD to estimate the intrinsic mode functions. Second, the periodic or quasi‐periodic signals in the intrinsic mode functions can be determined using Lomb‐Scargle spectral analysis. Third, the numbers of the identified periodicities/quasi‐periodicities are used as embedding dimensions of SSA to identify possible nonlinear trends. Then, the optimal nonlinear trend with the largest absolute Mann‐Kendall rank is selected as the final trend for the sea level change. Based on a comprehensive experiment using simulated sea level change time series, we concluded that the EMD‐SSA method can adaptively provide better estimate of the nonlinear trend in a realistic sea level change time series with consistency or high accuracy. We suggest that EMD‐SSA can be used not only to robustly extract nonlinear trends in sea level data, but also for trends in other geodetic or climatic records, including gravity, GNSS observed displacements, and altimetry observations. This article is protected by copyright. All rights reserved.
Taoyong Jin; Mingyu Xiao; Weiping Jiang; C. K. Shum; Hao Ding; Chung‐Yen Kuo; Junkun Wan. An Adaptive Method for Nonlinear Sea Level Trend Estimation by Combining EMD and SSA. Earth and Space Science 2021, 8, 1 .
AMA StyleTaoyong Jin, Mingyu Xiao, Weiping Jiang, C. K. Shum, Hao Ding, Chung‐Yen Kuo, Junkun Wan. An Adaptive Method for Nonlinear Sea Level Trend Estimation by Combining EMD and SSA. Earth and Space Science. 2021; 8 (3):1.
Chicago/Turabian StyleTaoyong Jin; Mingyu Xiao; Weiping Jiang; C. K. Shum; Hao Ding; Chung‐Yen Kuo; Junkun Wan. 2021. "An Adaptive Method for Nonlinear Sea Level Trend Estimation by Combining EMD and SSA." Earth and Space Science 8, no. 3: 1.
Satellite altimetry and tide gauges are the two main techniques used to measure sea level. Due to the limitations of satellite altimetry, a high-quality unified sea level model from coast to open ocean has traditionally been difficult to achieve. This study proposes a fusion approach of altimetry and tide gauge data based on a deep belief network (DBN) method. Taking the Mediterranean Sea as the case study area, a progressive three-step experiment was designed to compare the fused sea level anomalies from the DBN method with those from the inverse distance weighted (IDW) method, the kriging (KRG) method and the curvature continuous splines in tension (CCS) method for different cases. The results show that the fusion precision varies with the methods and the input measurements. The precision of the DBN method is better than that of the other three methods in most schemes and is reduced by approximately 20% when the limited altimetry along-track data and in-situ tide gauge data are used. In addition, the distribution of satellite altimetry data and tide gauge data has a large effect on the other three methods but less impact on the DBN model. Furthermore, the sea level anomalies in the Mediterranean Sea with a spatial resolution of 0.25° × 0.25° generated by the DBN model contain more spatial distribution information than others, which means the DBN can be applied as a more feasible and robust way to fuse these two kinds of sea levels.
Lianjun Yang; Taoyong Jin; Xianwen Gao; Hanjiang Wen; Tilo Schöne; Mingyu Xiao; Hailan Huang. Sea Level Fusion of Satellite Altimetry and Tide Gauge Data by Deep Learning in the Mediterranean Sea. Remote Sensing 2021, 13, 908 .
AMA StyleLianjun Yang, Taoyong Jin, Xianwen Gao, Hanjiang Wen, Tilo Schöne, Mingyu Xiao, Hailan Huang. Sea Level Fusion of Satellite Altimetry and Tide Gauge Data by Deep Learning in the Mediterranean Sea. Remote Sensing. 2021; 13 (5):908.
Chicago/Turabian StyleLianjun Yang; Taoyong Jin; Xianwen Gao; Hanjiang Wen; Tilo Schöne; Mingyu Xiao; Hailan Huang. 2021. "Sea Level Fusion of Satellite Altimetry and Tide Gauge Data by Deep Learning in the Mediterranean Sea." Remote Sensing 13, no. 5: 908.
Snow depth and snow water equivalent (SWE) are two parameters for measuring snowfall. By exploiting the Global Navigation Satellite System reflectometry (GNSS-R) technique and thousands of existing GNSS Continuous Operating Reference Stations (CORS) deployed in the cryosphere, it is possible to improve the temporal and spatial resolutions of the SWE measurement. In this paper, a fusion model for combining multi-satellite SNR (Signal to Noise Ratio) snow depth estimations is proposed, which uses peak spectral powers associated with each of the snow depth estimations. To simplify the estimation of SWE, the complete snowfall period over a winter season is split into snow accumulation, transition, and melting period in accordance with the variation characteristics of snow depth and SWE. By extensively using in situ snow depth and SWE observations recorded by snow telemetry network (SNOTEL) and regression analysis, three empirical models are developed to describe the relationship between snow depth and SWE for the three periods, respectively. Based on the snow depth fusion model and the SWE empirical models, an SWE estimation algorithm is proposed. Three data sets recorded in different environments are used to test the proposed method. The results demonstrate that there exists good agreement between the in situ SWE measurements and the SWE estimates produced by the proposed method; the root-mean-square error of SWE estimations is smaller than 6 cm when the SWE is up to 80 cm.
Kegen Yu; Yunwei Li; Taoyong Jin; Xin Chang; Qi Wang; Jiancheng Li. GNSS-R-Based Snow Water Equivalent Estimation with Empirical Modeling and Enhanced SNR-Based Snow Depth Estimation. Remote Sensing 2020, 12, 3905 .
AMA StyleKegen Yu, Yunwei Li, Taoyong Jin, Xin Chang, Qi Wang, Jiancheng Li. GNSS-R-Based Snow Water Equivalent Estimation with Empirical Modeling and Enhanced SNR-Based Snow Depth Estimation. Remote Sensing. 2020; 12 (23):3905.
Chicago/Turabian StyleKegen Yu; Yunwei Li; Taoyong Jin; Xin Chang; Qi Wang; Jiancheng Li. 2020. "GNSS-R-Based Snow Water Equivalent Estimation with Empirical Modeling and Enhanced SNR-Based Snow Depth Estimation." Remote Sensing 12, no. 23: 3905.
Terrestrial water storage (TWS) is a key variable in global and regional hydrological cycles. In this study, the TWS changes in the Yangtze River Basin (YRB) were derived using the Lagrange multiplier method (LMM) from Gravity Recovery and Climate Experiment (GRACE) data. To assess TWS changes from LMM, different GRACE solutions, different hydrological models, and in situ data were used for validation. Results show that TWS changes from LMM in YRB has the best performance with the correlation coefficients of 0.80 and root mean square error of 1.48 cm in comparison with in situ data. The trend of TWS changes over the YRB increased by 10.39 ± 1.27 Gt yr−1 during the 2003–2015 period. Moreover, TWS change is disintegrated into the individual contributions of hydrological components (i.e., glaciers, surface water, soil moisture, and groundwater) from satellite data, hydrologic models, and in situ data. The estimated changes in individual TWS components in the YRB show that (1) the contribution of glaciers, surface water, soil moisture, and groundwater to total TWS changes is 15%, 12%, 25% and 48%, respectively; (2) Geladandong glacier melt from CryoSat-2/ICESat data has a critical effect on TWS changes with a correlation coefficients of −0.51; (3) the Three Gorges Reservoir Impoundment has a minimal effect on surface water changes (mainly lake water storage), but it has a substantial effect on groundwater storage (GWS), (4) the Poyang and Doting Lake water storage changes are mainly caused by climate change, (5) soil moisture storage change is mainly influenced by surface water, (6) human-induced GWS changes accounted for approximately half of the total GWS. The results of this study can provide valuable information for decision-making in water resources management.
Nengfang Chao; Taoyong Jin; Zuansi Cai; Gang Chen; Xianglin Liu; Zhengtao Wang; Pat J.‐F. Yeh. Estimation of component contributions to total terrestrial water storage change in the Yangtze river basin. Journal of Hydrology 2020, 595, 125661 .
AMA StyleNengfang Chao, Taoyong Jin, Zuansi Cai, Gang Chen, Xianglin Liu, Zhengtao Wang, Pat J.‐F. Yeh. Estimation of component contributions to total terrestrial water storage change in the Yangtze river basin. Journal of Hydrology. 2020; 595 ():125661.
Chicago/Turabian StyleNengfang Chao; Taoyong Jin; Zuansi Cai; Gang Chen; Xianglin Liu; Zhengtao Wang; Pat J.‐F. Yeh. 2020. "Estimation of component contributions to total terrestrial water storage change in the Yangtze river basin." Journal of Hydrology 595, no. : 125661.
Soil moisture is an important variable in ecological, hydrological, and meteorological studies. An effective method for improving the accuracy of soil moisture retrieval is the mutual supplementation of multi-source data. The sensor configuration and band settings of different optical sensors lead to differences in band reflectivity in the inter-data, further resulting in the differences between vegetation indices. The combination of synthetic aperture radar (SAR) data with multi-source optical data has been widely used for soil moisture retrieval. However, the influence of vegetation indices derived from different sources of optical data on retrieval accuracy has not been comparatively analyzed thus far. Therefore, the suitability of vegetation parameters derived from different sources of optical data for accurate soil moisture retrieval requires further investigation. In this study, vegetation indices derived from GF-1, Landsat-8, and Sentinel-2 were compared. Based on Sentinel-1 SAR and three optical data, combined with the water cloud model (WCM) and the advanced integral equation model (AIEM), the accuracy of soil moisture retrieval was investigated. The results indicate that, Sentinel-2 data were more sensitive to vegetation characteristics and had a stronger capability for vegetation signal detection. The ranking of normalized difference vegetation index (NDVI) values from the three sensors was as follows: the largest was in Sentinel-2, followed by Landsat-8, and the value of GF-1 was the smallest. The normalized difference water index (NDWI) value of Landsat-8 was larger than that of Sentinel-2. With reference to the relative components in the WCM model, the contribution of vegetation scattering exceeded that of soil scattering within a vegetation index range of approximately 0.55–0.6 in NDVI-based models and all ranges in NDWI1-based models. The threshold value of NDWI2 for calculating vegetation water content (VWC) was approximately an NDVI value of 0.4–0.55. In the soil moisture retrieval, Sentinel-2 data achieved higher accuracy than data from the other sources and thus was more suitable for the study for combination with SAR in soil moisture retrieval. Furthermore, compared with NDVI, higher accuracy of soil moisture could be retrieved by using NDWI1 (R2 = 0.623, RMSE = 4.73%). This study provides a reference for the selection of optical data for combination with SAR in soil moisture retrieval.
Qi Wang; Jiancheng Li; Taoyong Jin; Xin Chang; Yongchao Zhu; Yunwei Li; Jiaojiao Sun; Dawei Li. Comparative Analysis of Landsat-8, Sentinel-2, and GF-1 Data for Retrieving Soil Moisture over Wheat Farmlands. Remote Sensing 2020, 12, 2708 .
AMA StyleQi Wang, Jiancheng Li, Taoyong Jin, Xin Chang, Yongchao Zhu, Yunwei Li, Jiaojiao Sun, Dawei Li. Comparative Analysis of Landsat-8, Sentinel-2, and GF-1 Data for Retrieving Soil Moisture over Wheat Farmlands. Remote Sensing. 2020; 12 (17):2708.
Chicago/Turabian StyleQi Wang; Jiancheng Li; Taoyong Jin; Xin Chang; Yongchao Zhu; Yunwei Li; Jiaojiao Sun; Dawei Li. 2020. "Comparative Analysis of Landsat-8, Sentinel-2, and GF-1 Data for Retrieving Soil Moisture over Wheat Farmlands." Remote Sensing 12, no. 17: 2708.
Taoyong Jin; Xiaolong Li; C. K. Shum; Hao Ding; Xinyu Xu. The Balance and Abnormal Increase of Global Ocean Mass Change From Land Using GRACE. Earth and Space Science 2020, 7, 1 .
AMA StyleTaoyong Jin, Xiaolong Li, C. K. Shum, Hao Ding, Xinyu Xu. The Balance and Abnormal Increase of Global Ocean Mass Change From Land Using GRACE. Earth and Space Science. 2020; 7 (5):1.
Chicago/Turabian StyleTaoyong Jin; Xiaolong Li; C. K. Shum; Hao Ding; Xinyu Xu. 2020. "The Balance and Abnormal Increase of Global Ocean Mass Change From Land Using GRACE." Earth and Space Science 7, no. 5: 1.
The GaoFen-7 (GF-7) satellite, which was launched on November 3, 2019, is China's first civilian submeter stereo mapping satellite. The satellite is equipped with the first laser altimeter officially in China for earth observation. Except for the laser altimeter, the GF-7 spaceborne laser altimeter system also includes two laser footprint cameras and a laser optical axis surveillance camera. The laser altimeter system is designed and used to assist improving the elevation accuracy without Ground Control Points (GCPs) of the two line-array stereo mapping cameras. This paper details the design of the GF-7 spaceborne laser altimeter system, its ranging performance in the laboratory and its data processing method. The type of data products is also released. These data will play a vital role in the application of geography, glaciology, forestry and other industries.
Junfeng Xie; Genghua Huang; Ren Liu; Chenguang Zhao; Jun Dai; Taoyong Jin; Fan Mo; Ying Zhen; Shaoli Xi; Hongzhao Tang; Xianhui Dou; Chenchen Yang. Design and Data Processing of China's First Spaceborne Laser Altimeter System for Earth Observation: GaoFen-7. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2020, 13, 1034 -1044.
AMA StyleJunfeng Xie, Genghua Huang, Ren Liu, Chenguang Zhao, Jun Dai, Taoyong Jin, Fan Mo, Ying Zhen, Shaoli Xi, Hongzhao Tang, Xianhui Dou, Chenchen Yang. Design and Data Processing of China's First Spaceborne Laser Altimeter System for Earth Observation: GaoFen-7. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2020; 13 (99):1034-1044.
Chicago/Turabian StyleJunfeng Xie; Genghua Huang; Ren Liu; Chenguang Zhao; Jun Dai; Taoyong Jin; Fan Mo; Ying Zhen; Shaoli Xi; Hongzhao Tang; Xianhui Dou; Chenchen Yang. 2020. "Design and Data Processing of China's First Spaceborne Laser Altimeter System for Earth Observation: GaoFen-7." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 13, no. 99: 1034-1044.
Global navigation satellite system (GNSS) multipath signals received by a geodetic-quality GNSS receiver can be used to estimate the water content of soil around the antenna. The direct signals from satellite to GNSS antenna are the most valuable signals in geodetic measurement, such as positioning, navigation, GNSS control network, deformation monitoring, and so on. However, the GNSS antenna also captures the reflected signals from the ground, which contain information of surrounding environment, so that useful information about the reflection surface can be inferred by analyzing the reflected signal. This technique is termed as GNSS-interferometric reflectometry. The signal-to-noise ratio (SNR) data recorded by a receiver contains SNR component of reflected signals, which is related to the soil moisture of the ground. The changes of soil moisture content will cause the change of soil permittivity and reflectivity which are the key factors that make further change of the SNR of reflected signals. We used the measured data to evaluate the correlation between amplitude of multipath induced SNR time series and real soil moisture. An improved soil moisture estimation algorithm based on multipath induced SNR amplitude data is proposed in this paper. The performance of the proposed soil moisture estimation method is evaluated using the 15-month data recorded by PBO H2O GNSS station and a 14-day experiment in Wuhan, China. The experimental results show that the estimated soil moisture has a strong correlation with the real soil moisture and the estimation accuracy in terms of root-mean-square error (RMSE) is 0.0345 cm3cm−3 and 0.0339 cm3cm−3, respectively. Meanwhile, the application scope of the method is given.
Xin Chang; Taoyong Jin; Kegen Yu; Yunwei Li; Jiancheng Li; Qiang Zhang. Soil Moisture Estimation by GNSS Multipath Signal. Remote Sensing 2019, 11, 2559 .
AMA StyleXin Chang, Taoyong Jin, Kegen Yu, Yunwei Li, Jiancheng Li, Qiang Zhang. Soil Moisture Estimation by GNSS Multipath Signal. Remote Sensing. 2019; 11 (21):2559.
Chicago/Turabian StyleXin Chang; Taoyong Jin; Kegen Yu; Yunwei Li; Jiancheng Li; Qiang Zhang. 2019. "Soil Moisture Estimation by GNSS Multipath Signal." Remote Sensing 11, no. 21: 2559.
The accuracy and resolution of the marine gravity field derived from multisatellite altimeter data sets mainly depend on the corresponding range precision and spatial distribution. Here, we preliminarily investigate the performance of HY-2A altimeter data by analyzing cross-mission sea surface height discrepancies with SARAL/AltiKa and calculating correlation coefficients with respect to tide gauge measurements. We also explore the improved range precision that can be achieved using a two-pass weighted least squares retracker which was proposed for the purpose of optimal gravity field recovery. Firstly, both the exact repetitive mission and the geodetic mission for HY-2A provide new track orientations and different data coverage for recovering the marine gravity field, and these dense geographical distributions are more greatly attributed to the geodetic mission in recent years. Secondly, HY-2A provides reliable sea surface height measurements based on exterior verifications by SARAL/AltiKa geophysical data records and tide gauge measurements, although the accuracy level is slightly lower than SARAL/AltiKa. Another more exciting finding is that the statistics of along-track sea surface heights in one-second intervals show that the two-pass retracking does further improve the range precision by a factor of 1.6 with respect to 20 Hz retracked results in sensor data records. In conclusion, the HY-2A mission can substantially improve the global accuracy and resolution of the marine gravity field and will reveal new tectonic features such as microplates, abyssal hill fabric, and new uncharted seamounts on the ocean floor.
Shengjun Zhang; Jiancheng Li; Taoyong Jin; Defu Che. HY-2A Altimeter Data Initial Assessment and Corresponding Two-Pass Waveform Retracker. Remote Sensing 2018, 10, 507 .
AMA StyleShengjun Zhang, Jiancheng Li, Taoyong Jin, Defu Che. HY-2A Altimeter Data Initial Assessment and Corresponding Two-Pass Waveform Retracker. Remote Sensing. 2018; 10 (4):507.
Chicago/Turabian StyleShengjun Zhang; Jiancheng Li; Taoyong Jin; Defu Che. 2018. "HY-2A Altimeter Data Initial Assessment and Corresponding Two-Pass Waveform Retracker." Remote Sensing 10, no. 4: 507.
Shengjun Zhang; David T. Sandwell; Taoyong Jin; Dawei Li. Inversion of marine gravity anomalies over southeastern China seas from multi-satellite altimeter vertical deflections. Journal of Applied Geophysics 2017, 137, 128 -137.
AMA StyleShengjun Zhang, David T. Sandwell, Taoyong Jin, Dawei Li. Inversion of marine gravity anomalies over southeastern China seas from multi-satellite altimeter vertical deflections. Journal of Applied Geophysics. 2017; 137 ():128-137.
Chicago/Turabian StyleShengjun Zhang; David T. Sandwell; Taoyong Jin; Dawei Li. 2017. "Inversion of marine gravity anomalies over southeastern China seas from multi-satellite altimeter vertical deflections." Journal of Applied Geophysics 137, no. : 128-137.
Several studies have indicated that glaciers in the Qinghai-Tibet plateau are thinning, resulting in reduced water supplies to major rivers such as the Yangtze, Yellow, Lancang, Indus, Ganges, Brahmaputra in China, and south Asia. Three rivers in the upstream of Yangtze River originate from glaciers around the Geladandong snow mountain group in central Tibet. Here we used elevation observations from Ice, Cloud, and land Elevation Satellite (ICESat) and reference elevations from a 3-arc-second digital elevation model (DEM) of Shuttle Radar Terrestrial Mission (SRTM), assisted with Landsat-7 images, to detect glacier elevation changes in the western (A), central (B), and eastern (C) regions of Geladandong. Robust fitting was used to determine rates of glacier elevation changes in regions with dense ICESat data, whereas a new method called rate averaging was employed to find rates in regions of low data density. The rate of elevation change was −0.158 ± 0.066 m·a−1 over 2003–2009 in the entire Geladandong and it was −0.176 ± 0.102 m·a−1 over 2003–2008 in Region C (by robust fitting). The rates in Regions A, B, and C were −0.418 ± 0.322 m·a−1 (2000–2009), −0.432 ± 0.020 m·a−1 (2000–2003), and −0.321 ± 0.139 m·a−1 (2000–2008) (by rate averaging). We used in situ hydroclimatic dataset to assess these negative rates: the glacier thinning was caused by temperature rises around Geladandong, based on the temperature records over 1979–2009, 1957–2013, and 1966–2013 at stations Tuotuohe, Wudaoliang, and Anduo. The thinning Geladandong glaciers led to increased discharges recorded at the river gauge stations Tuotuohe and Chumda over 1956–2012. An unabated Geladandong glacier melting will reduce its long-term water supply to the Yangtze River Basin, causing irreversible socioeconomic consequences and seriously degrading the ecological system of the Yangtze River Basin.
Nengfang Chao; Zhengtao Wang; Cheinway Hwang; Taoyong Jin; Yung-Sheng Cheng. Decline of Geladandong Glacier Elevation in Yangtze River’s Source Region: Detection by ICESat and Assessment by Hydroclimatic Data. Remote Sensing 2017, 9, 75 .
AMA StyleNengfang Chao, Zhengtao Wang, Cheinway Hwang, Taoyong Jin, Yung-Sheng Cheng. Decline of Geladandong Glacier Elevation in Yangtze River’s Source Region: Detection by ICESat and Assessment by Hydroclimatic Data. Remote Sensing. 2017; 9 (1):75.
Chicago/Turabian StyleNengfang Chao; Zhengtao Wang; Cheinway Hwang; Taoyong Jin; Yung-Sheng Cheng. 2017. "Decline of Geladandong Glacier Elevation in Yangtze River’s Source Region: Detection by ICESat and Assessment by Hydroclimatic Data." Remote Sensing 9, no. 1: 75.