scholarly journals Analyzing Water Dynamics Based on Sentinel-1 Time Series—a Study for Dongting Lake Wetlands in China

2020 ◽  
Vol 12 (11) ◽  
pp. 1761 ◽  
Author(s):  
Juliane Huth ◽  
Ursula Gessner ◽  
Igor Klein ◽  
Hervé Yesou ◽  
Xijun Lai ◽  
...  
Keyword(s):  
Time Series ◽  
Wetland Management ◽  
Dongting Lake ◽  
Water Dynamics ◽  
Minimum Size ◽  
Optical Data ◽  
Small Scale ◽  
Lake Area ◽  
Ramsar Site ◽  
Extreme Flood

In China, freshwater is an increasingly scarce resource and wetlands are under great pressure. This study focuses on China’s second largest freshwater lake in the middle reaches of the Yangtze River—the Dongting Lake—and its surrounding wetlands, which are declared a protected Ramsar site. The Dongting Lake area is also a research region of focus within the Sino-European Dragon Programme, aiming for the international collaboration of Earth Observation researchers. ESA’s Copernicus Programme enables comprehensive monitoring with area-wide coverage, which is especially advantageous for large wetlands that are difficult to access during floods. The first year completely covered by Sentinel-1 SAR satellite data was 2016, which is used here to focus on Dongting Lake’s wetland dynamics. The well-established, threshold-based approach and the high spatio-temporal resolution of Sentinel-1 imagery enabled the generation of monthly surface water maps and the analysis of the inundation frequency at a 10 m resolution. The maximum extent of the Dongting Lake derived from Sentinel-1 occurred in July 2016, at 2465 km2, indicating an extreme flood year. The minimum size of the lake was detected in October, at 1331 km2. Time series analysis reveals detailed inundation patterns and small-scale structures within the lake that were not known from previous studies. Sentinel-1 also proves to be capable of mapping the wetland management practices for Dongting Lake polders and dykes. For validation, the lake extent and inundation duration derived from the Sentinel-1 data were compared with excerpts from the Global WaterPack (frequently derived by the German Aerospace Center, DLR), high-resolution optical data, and in situ water level data, which showed very good agreement for the period studied. The mean monthly extent of the lake in 2016 from Sentinel-1 was 1798 km2, which is consistent with the Global WaterPack, deviating by only 4%. In summary, the presented analysis of the complete annual time series of the Sentinel-1 data provides information on the monthly behavior of water expansion, which is of interest and relevance to local authorities involved in water resource management tasks in the region, as well as to wetland conservationists concerned with the Ramsar site wetlands of Dongting Lake and to local researchers.

scholarly journals Surface Deformation Retrieving Over Soft Clay Based on an Improved Time Series InSAR Model: A Case Study of Dongting Lake Area, China

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 195703-195720
Author(s):  
Yikai Zhu ◽  
Xuemin Xing ◽  
Zhihui Yuan ◽  
Liang Bao ◽  
Lingjie Zhu ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Deformation ◽  
Soft Clay ◽  
Dongting Lake ◽  
Lake Area ◽  
Dongting Lake Area

scholarly journals MAPPING WETLANDS OF DONGTING LAKE IN CHINA USING LANDSAT AND SENTINEL-1 TIME SERIES AT 30M

2018 ◽  
Vol XLII-3 ◽  
pp. 1971-1976 ◽  
Author(s):  
L. Xing ◽  
X. Tang ◽  
H. Wang ◽  
W. Fan ◽  
X. Gao
Keyword(s):  
Time Series ◽  
Land Cover ◽  
Water Body ◽  
Land Surface ◽  
Dongting Lake ◽  
Sensor Data ◽  
Optical Data ◽  
Svm Classifier ◽  
Threshold Method ◽  
Land Cover Types

Mapping and monitoring wetlands of Dongting lake using optical sensor data has been limited by cloud cover, and open access Sentinal-1 C-band data could provide cloud-free SAR images with both have high spatial and temporal resolution, which offer new opportunities for monitoring wetlands. In this study, we combined optical data and SAR data to map wetland of Dongting Lake reserves in 2016. Firstly, we generated two monthly composited Landsat land surface reflectance, NDVI, NDWI, TC-Wetness time series and Sentinel-1 (backscattering coefficient for VH and VV) time series. Secondly, we derived surface water body with two monthly frequencies based on the threshold method using the Sentinel-1 time series. Then the permanent water and seasonal water were separated by the submergence ratio. Other land cover types were identified based on SVM classifier using Landsat time series. Results showed that (1) the overall accuracies and kappa coefficients were above 86.6 % and 0.8. (3) Natural wetlands including permanent water body (14.8 %), seasonal water body (34.6 %), and permanent marshes (10.9 %) were the main land cover types, accounting for 60.3 % of the three wetland reserves. Human-made wetlands, such as rice fields, accounted 34.3 % of the total area. Generally, this study proposed a new flowchart for wetlands mapping in Dongting lake by combining multi-source remote sensing data, and the use of the two-monthly composited optical time series effectively made up the missing data due to the clouds and increased the possibility of precise wetlands classification.

scholarly journals Time Series Deformation Monitoring over Large Infrastructures around Dongting Lake Using X-Band PSI with a Combined Thermal Expansion and Seasonal Model

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Liang Bao ◽  
Xuemin Xing ◽  
Lifu Chen ◽  
Zhihui Yuan ◽  
Bin Liu ◽  
...  
Keyword(s):  
Time Series ◽  
Thermal Expansion ◽  
Dongting Lake ◽  
Deformation Monitoring ◽  
Deformation Model ◽  
Lake Area ◽  
External Temperature ◽  
X Band ◽  
Thermal Dilation

The long-term spatial-temporal deformation monitoring of densely distributed infrastructures near the lake area is of great significance to understand the urban health status and prevent the potential traffic safety problems. In this paper, the permanent scatterer interferometry (PSI) technology with TerraSAR-X imagery over the area around Dongting Lake was utilized to generate the long-term spatial-temporal deformation. Since the X-band SAR interferometric phases are highly influenced by the thermal dilation of the observed objects, and the deformation of large infrastructures are highly related to external temperature, a combined deformation model considering the thermal expansion and the seasonal environmental factors was proposed to model the temporal variations of the deformation. The time series deformation and the thermal dilation parameter over the area were obtained, and a comparative study with the traditional linear model was conducted. The Dongting Lake Bridge and the typical feature points distributed around the lake were analyzed in details. In order to compensate for the unavailability of external in situ measurements over the area, phase residuals and the subsidence generated through Differential Interferometric Synthetic Aperture Radar (D-InSAR) were utilized to verify the accuracy of the obtained deformation time series. Experiment results suggested that the proposed model is suitable and suggested for the selected study site. The root mean square error (RMSE) of the residual phase was estimated as 0.32 rad, and the RMSE compared with D-InSAR derived deformation was ±1.1 mm.

scholarly journals Fully Automated Detection of Supraglacial Lake Area for Northeast Greenland Using Sentinel-2 Time-Series

2021 ◽  
Vol 13 (2) ◽  
pp. 205
Author(s):  
Philipp Hochreuther ◽  
Niklas Neckel ◽  
Nathalie Reimann ◽  
Angelika Humbert ◽  
Matthias Braun
Keyword(s):  
Time Series ◽  
Observation Interval ◽  
Lake Area ◽  
Climate Data ◽  
Melt Pond ◽  
Automated Processing ◽  
Average Observation ◽  
Average Size ◽  
Lake Size ◽  
Sentinel 2

The usability of multispectral satellite data for detecting and monitoring supraglacial meltwater ponds has been demonstrated for western Greenland. For a multitemporal analysis of large regions or entire Greenland, largely automated processing routines are required. Here, we present a sequence of algorithms that allow for an automated Sentinel-2 data search, download, processing, and generation of a consistent and dense melt pond area time-series based on open-source software. We test our approach for a ~82,000 km2 area at the 79°N Glacier (Nioghalvfjerdsbrae) in northeast Greenland, covering the years 2016, 2017, 2018 and 2019. Our lake detection is based on the ratio of the blue and red visible bands using a minimum threshold. To remove false classification caused by the similar spectra of shadow and water on ice, we implement a shadow model to mask out topographically induced artifacts. We identified 880 individual lakes, traceable over 479 time-steps throughout 2016–2019, with an average size of 64,212 m2. Of the four years, 2019 had the most extensive lake area coverage with a maximum of 333 km2 and a maximum individual lake size of 30 km2. With 1.5 days average observation interval, our time-series allows for a comparison with climate data of daily resolution, enabling a better understanding of short-term climate-glacier feedbacks.

scholarly journals Evidence of Preferential Flow Activation in the Vadose Zone via Geophysical Monitoring

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1358
Author(s):  
Lorenzo De Carlo ◽  
Kimberlie Perkins ◽  
Maria Clementina Caputo
Keyword(s):  
Preferential Flow ◽  
Water Movement ◽  
Test Site ◽  
Water Dynamics ◽  
Small Scale ◽  
Strong Impact ◽  
Aquifer Recharge ◽  
Spatial Moments ◽  
Artificial Rainfall ◽  
Preferential Pathways

Preferential pathways allow rapid and non-uniform water movement in the subsurface due to strong heterogeneity of texture, composition, and hydraulic properties. Understanding the importance of preferential pathways is crucial, because they have strong impact on flow and transport hydrodynamics in the unsaturated zone. Particularly, improving knowledge of the water dynamics is essential for estimating travel time through soil to quantify hazards for groundwater, assess aquifer recharge rates, improve agricultural water management, and prevent surface stormflow and flooding hazards. Small scale field heterogeneities cannot be always captured by the limited number of point scale measurements collected. In order to overcome these limitations, noninvasive geophysical techniques have been widely used in the last decade to predict hydrodynamic processes, due to their capability to spatialize hydrogeophysical properties with high resolution. In the test site located in Bari, Southern Italy, the geophysical approach, based on electrical resistivity tomography (ERT) monitoring, has been implemented to detect preferential pathways triggered by an artificial rainfall event. ERT-derived soil moisture estimations were obtained in order to quantitatively predict the water storage (m3m−3), water velocity (ms−1), and spread (m2) through preferential pathways by using spatial moments analysis.

Study of Thermal Activity in The Mixing Layer During First Generated Single Cloud by Using Combined Observation From Boundary Layer Radar, Doppler Lidar and Time Lapse Camera 

2021 ◽  
Author(s):  
Ginaldi Ari Nugroho ◽  
Kosei Yamaguchi ◽  
Eiichi Nakakita ◽  
Masayuki K. Yamamoto ◽  
Seiji Kawamura ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Time Series ◽  
Atmospheric Boundary Layer ◽  
Vertical Velocity ◽  
Time Lapse ◽  
Small Scale ◽  
Thermal Activity ◽  
Doppler Lidar ◽  
Cumulus Cloud ◽  
Scale Perturbation

<p>Detailed observation of small scale perturbation in the atmospheric boundary layer during the first generated cumulus cloud are conducted. Our target is to study this small scale perturbation, especially related to the thermal activity at the first generated cumulus cloud. The observation is performed during the daytime on August 17, 2018, and September 03, 2018. Location is focused in the urban area of Kobe, Japan. High-resolution instruments such as Boundary Layer Radar, Doppler Lidar, and Time Lapse camera are used in this observation. Boundary Layer Radar, and Doppler Lidar are used for clear air observation. Meanwhile Time Lapse Camera are used for cloud existence observation. The atmospheric boundary layer structure is analyzed based on vertical velocity profile, variance, skewness, and estimated atmospheric boundary layer height. Wavelet are used to observe more of the period of the thermal activity. Furthermore, time correlation between vertical velocity time series from height 0.3 to 2 km and image pixel of generated cloud time series are also discussed in this study.</p>

Application of close range photogrammetry in structural health monitoring by processing generated point cloud datasets

2021 ◽  
Author(s):  
Ali Mirzazade ◽  
Cosmin Popescu ◽  
Thomas Blanksvärd ◽  
Björn Täljsten
Keyword(s):  
Health Monitoring ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Optical Data ◽  
Small Scale ◽  
Relevant Parameter ◽  
Bridge Inspection ◽  
Close Range Photogrammetry ◽  
Close Range

<p>In bridge inspection, vertical displacement is a relevant parameter for both short and long-term health monitoring. Assessing change in deflections could also simplify the assessment work for inspectors. Recent developments in digital camera technology and photogrammetry software enables point cloud with colour information (RGB values) to be generated. Thus, close range photogrammetry offers the potential of monitoring big and small-scale damages by point clouds. The current paper aims to monitor geometrical deviations in Pahtajokk Bridge, Northern Sweden, using an optical data acquisition technique. The bridge in this study is scanned two times by almost one year a part. After point cloud generation the datasets were compared to detect geometrical deviations. First scanning was carried out by both close range photogrammetry (CRP) and terrestrial laser scanning (TLS), while second scanning was performed by CRP only. Analyzing the results has shown the potential of CRP in bridge inspection.</p>

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