scholarly journals Combining and Comparing an Unmanned Aerial Vehicle and Multiple Remote Sensing Satellites to Calculate Long-Term River Discharge in an Ungauged Water Source Region on the Tibetan Plateau

2020 ◽  
Vol 12 (13) ◽  
pp. 2155 ◽  
Author(s):  
Hezhen Lou ◽  
Pengfei Wang ◽  
Shengtian Yang ◽  
Fanghua Hao ◽  
Xiaoyu Ren ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Tibetan Plateau ◽  
Unmanned Aerial Vehicle ◽  
River Discharge ◽  
The Tibetan Plateau ◽  
Aerial Vehicle ◽  
Spot 5 ◽  
Sentinel 2

Research into global water resources is challenged by the lack of ground-based hydrometric stations and limited data sharing. It is difficult to collect good quality, long-term information about river discharges in ungauged regions. Herein, an approach was developed to determine the river discharges of 24 rivers in ungauged regions on the Tibetan Plateau on a long-term scale. This method involved coupling the Manning–Strickler formula, and data from an unmanned aerial vehicle (UAV) and the Gaofen-2, SPOT-5, and Sentinel-2 satellites. We also compared the discharges calculated by using the three satellites’ data. Fundamental information about the rivers was extracted from the UAV data. Comparison of the discharges calculated from the in-situ measurements and the UAV data gave an R2 value of 0.84, an average NSE of 0.79, and an RMSE of 0.11 m3/s. The river discharges calculated with the GF-2 remote sensing data and the in-situ experiments for the same months were compared and the R2, RMSE, and the NSE were 0.80, 1.8 m3/s, and 0.78, respectively. Comparing the discharges calculated over the long term from the measured in-situ data and the SPOT-5 and Sentinel-2 data gave R2 values of 0.93 and 0.92, and RMSE values of 2.56 m3/s and 3.16 m3/s, respectively. The results showed that the GF-2 and UAV were useful for calculating the discharges for low-flow rivers, while the SPOT-5 or the Sentinel-2 satellite gave good results for high-flow river discharges in the long-term. Our results demonstrate that the discharges in ungauged tributaries can be reliably estimated in the long-term with this method. This method extended the previous research, which described river discharge only in one period and provided more support to the monitoring and management of the tributaries in ungauged regions.

scholarly journals Measurement report: Changing characteristics of atmospheric CH<sub>4</sub> in the Tibetan Plateau: records from 1994 to 2019 at the Mount Waliguan station

2021 ◽  
Vol 21 (1) ◽  
pp. 393-413
Author(s):  
Shuo Liu ◽  
Shuangxi Fang ◽  
Peng Liu ◽  
Miao Liang ◽  
Minrui Guo ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
The Tibetan Plateau ◽  
Atmospheric Methane ◽  
Continuous Increase ◽  
Northern India ◽  
Source Regions ◽  
City Regions

Abstract. A 26-year, long-term record of atmospheric methane (CH4) measured in situ at the Mount Waliguan (WLG) station, the only World Meteorological Organization (WMO) and Global Atmosphere Watch (GAW) global station in inland Eurasia, is presented. Overall, a nearly continuous increase in atmospheric CH4 was observed at WLG, with a yearly growth rate of 5.1±0.1 parts per billion (ppb) per year during 1994–2019, except for some particular periods with near-zero or negative values, e.g., 1999–2000 and 2004–2006. The average CH4 mole fraction was only 1799.0±0.4 ppb in 1994 but increased to about 133 ppb and reached a historic level of 1932.0±0.1 ppb in 2019. The case study in the Tibetan Plateau showed that the atmospheric CH4 increased rapidly. During some special periods, it is even larger than that of city regions (e.g., 6.7±0.2 ppb yr−1 in 2003–2007). Generally, the characteristics of CH4 varied in different observing periods as follows: (i) the diurnal cycle has become apparent and the amplitudes of the diurnal or seasonal cycles increased over time; (ii) the wind sectors with elevated CH4 mole fractions switched from ENE-E-ESE-SE-SSE sectors (wind directions) in early periods to NNE-NE-ENE-E sectors in later years; (iii) the area of source regions increased as the years progressed, and strong sources shifted from northeast (city regions) to southwest (northern India); and (iv) the annual growth rates in recent years (e.g., 2008–2019) were significantly larger than those in the early periods (e.g., 1994–2007).

scholarly journals Quantifying Long-Term Land Surface and Root Zone Soil Moisture over Tibetan Plateau

2020 ◽  
Vol 12 (3) ◽  
pp. 509 ◽  
Author(s):  
Ruodan Zhuang ◽  
Yijian Zeng ◽  
Salvatore Manfreda ◽  
Zhongbo Su
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Land Surface ◽  
Root Zone ◽  
Cumulative Distribution ◽  
Analytical Relationship ◽  
The Tibetan Plateau ◽  
Climate Systems

It is crucial to monitor the dynamics of soil moisture over the Tibetan Plateau, while considering its important role in understanding the land-atmosphere interactions and their influences on climate systems (e.g., Eastern Asian Summer Monsoon). However, it is very challenging to have both the surface and root zone soil moisture (SSM and RZSM) over this area, especially the study of feedbacks between soil moisture and climate systems requires long-term (e.g., decadal) datasets. In this study, the SSM data from different sources (satellites, land data assimilation, and in-situ measurements) were blended while using triple collocation and least squares method with the constraint of in-situ data climatology. A depth scaling was performed based on the blended SSM product, using Cumulative Distribution Function (CDF) matching approach and simulation with Soil Moisture Analytical Relationship (SMAR) model, to estimate the RZSM. The final product is a set of long-term (~10 yr) consistent SSM and RZSM product. The inter-comparison with other existing SSM and RZSM products demonstrates the credibility of the data blending procedure used in this study and the reliability of the CDF matching method and SMAR model in deriving the RZSM.

The evaluation of land surface parameters for model to derive land surface fluxes in the Tibetan Plateau

2021 ◽  
Author(s):  
Weiqiang Ma ◽  
Yaoming Ma ◽  
Yizhe Han ◽  
Wei Hu ◽  
Lei Zhong ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Default Model ◽  
Model Configuration

&lt;p&gt;Firstly, based on the difference of model and in-situ observations, a serious of sensitive experiments were done by using WRF. In order to use remote sensing products, a land-atmosphere model was initialized by ingesting land surface parameters, such as AMSR-E RS products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations.&lt;/p&gt;&lt;p&gt;Secondly, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations. The differences between the AMSR-E initialized model runs with the default model configuration and in situ data showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model configuration. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data ingestion was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in-situ data and the results of the default model configuration. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model over the Tibetan Plateau.&lt;/p&gt;&lt;p&gt;All of the different methods will clarify the land surface heating field in complex plateau, it also can affect atmospheric cycle over the Tibetan Plateau even all of the global atmospheric cycle pattern.&lt;/p&gt;

A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards

2019 ◽  
pp. 271-294 ◽  
Author(s):  
Adam J. Mathews
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Spectral Information ◽  
Digital Cameras ◽  
Individual Bands ◽  
Aerial Vehicle ◽  
Best Fit

This paper explores the use of compact digital cameras to remotely estimate spectral reflectance based on unmanned aerial vehicle imagery. Two digital cameras, one unaltered and one altered, were used to collect four bands of spectral information (blue, green, red, and near-infrared [NIR]). The altered camera had its internal hot mirror removed to allow the sensor to be additionally sensitive to NIR. Through on-ground experimentation with spectral targets and a spectroradiometer, the sensitivity and abilities of the cameras were observed. This information along with on-site collected spectral data were used to aid in converting aerial imagery digital numbers to estimates of scaled surface reflectance using the empirical line method. The resulting images were used to create spectrally-consistent orthophotomosaics of a vineyard study site. Individual bands were subsequently validated with in situ spectroradiometer data. Results show that red and NIR bands exhibited the best fit (R2: 0.78 for red; 0.57 for NIR).

scholarly journals Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset

2020 ◽  
Author(s):  
Pei Zhang ◽  
Donghai Zheng ◽  
Rogier van der Velde ◽  
Jun Wen ◽  
Yijian Zeng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Current Model ◽  
Regional Scale ◽  
In Situ Measurements ◽  
The Tibetan Plateau ◽  
Model Based ◽  
Network Area

Abstract. The Tibetan Plateau observatory of plateau scale soil moisture and soil temperature (Tibet-Obs) was established ten years ago, which has been widely used to calibrate/validate satellite- and model-based soil moisture (SM) products for their applications to the Tibetan Plateau (TP). This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface SM dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs that consists of three regional-scale SM monitoring networks, i.e. the Maqu, Naqu, and Ngari (including Ali and Shiquanhe) networks. This surface SM dataset includes the original 15-min in situ measurements collected by multiple SM monitoring sites of the three networks, and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks. Comparisons between four spatial upscaling methods, i.e. arithmetic averaging, Voronoi diagram, time stability and apparent thermal inertia, show that the arithmetic average of the monitoring sites with long-term (i.e. ≥ six years) continuous measurements are found to be most suitable to produce the upscaled SM records. Trend analysis of the 10-year upscaled SM records using the Mann-Kendall method shows that the Maqu network area in the eastern part of the TP is drying while the Shiquanhe network area in the west is getting wet that generally follow the change of precipitation. To further demonstrate the uniqueness of the upscaled SM records in validating existing SM products for long term period (~ 10 years), comparisons are conducted to evaluate the reliability of three reanalysis datasets for the Maqu and Shiquanhe network areas. It is found that current model-based SM products still show deficiencies in representing the trend and variation of measured SM dynamics in the Tibetan grassland (i.e. Maqu) and desert ecosystems (i.e. Shiquanhe) that dominate the landscape of the TP. The dataset would be also valuable for calibrating/validating long-term satellite-based SM products, evaluation of SM upscaling methods, development of data fusion methods, and quantifying the coupling strength between precipitation and SM at 10-year scale. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/uuid:21220b23-ff36-4ca9-a08f-ccd53782e834 (Zhang et al., 2020).

scholarly journals Status of the Tibetan Plateau observatory (Tibet-Obs) and a 10-year (2009–2019) surface soil moisture dataset

2021 ◽  
Vol 13 (6) ◽  
pp. 3075-3102
Author(s):  
Pei Zhang ◽  
Donghai Zheng ◽  
Rogier van der Velde ◽  
Jun Wen ◽  
Yijian Zeng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Tibetan Plateau ◽  
Current Model ◽  
Regional Scale ◽  
In Situ Measurements ◽  
The Tibetan Plateau ◽  
Monitoring Networks ◽  
Model Based

Abstract. The Tibetan Plateau observatory (Tibet-Obs) of plateau scale soil moisture and soil temperature was established 10 years ago and has been widely used to calibrate/validate satellite- and model-based soil moisture (SM) products for their applications to the Tibetan Plateau (TP). This paper reports on the status of the Tibet-Obs and presents a 10-year (2009–2019) surface SM dataset produced based on in situ measurements taken at a depth of 5 cm collected from the Tibet-Obs that consists of three regional-scale SM monitoring networks, i.e. the Maqu, Naqu, and Ngari (including Ali and Shiquanhe) networks. This surface SM dataset includes the original 15 min in situ measurements collected by multiple SM monitoring sites of the three networks and the spatially upscaled SM records produced for the Maqu and Shiquanhe networks. Comparisons between four spatial upscaling methods – i.e. arithmetic averaging, Voronoi diagrams, time stability, and apparent thermal inertia – show that the arithmetic average of the monitoring sites with long-term (i.e. ≥ 6-year) continuous measurements is found to be most suitable to produce the upscaled SM records. Trend analysis of the 10-year upscaled SM records indicates that the Shiquanhe network in the western part of the TP is getting wet, while there is no significant trend found for the Maqu network in the east. To further demonstrate the uniqueness of the upscaled SM records in validating existing SM products for a long-term period (∼10 years), the reliability of three reanalysis datasets is evaluated for the Maqu and Shiquanhe networks. It is found that current model-based SM products still show deficiencies in representing the measured SM dynamics in the Tibetan grassland (i.e. Maqu) and desert ecosystems (i.e. Shiquanhe). The dataset would also be valuable for calibrating/validating long-term satellite-based SM products, evaluation of SM upscaling methods, development of data fusion methods, and quantifying the coupling of SM and precipitation at a 10-year scale. The dataset is available in the 4TU.ResearchData repository at https://doi.org/10.4121/12763700.v7 (Zhang et al., 2020).

Estimation of River Discharge using Multi-Mission Satellite Altimetry and Optical Remote Sensing Imagery

2020 ◽  
Author(s):  
Daniel Scherer ◽  
Christian Schwatke ◽  
Denise Dettmering
Keyword(s):  
Remote Sensing ◽  
Time Series ◽  
Water Level ◽  
River Discharge ◽  
Water Surface ◽  
Satellite Altimetry ◽  
Remote Sensing Data ◽  
Sensing Data

&lt;p&gt;Despite increasing interest in monitoring the global water cycle, the availability of in-situ discharge time series is decreasing. However, this lack of ground data can be compensated by using remote sensing techniques to observe river discharge.&lt;/p&gt;&lt;p&gt;In this contribution, a new approach for estimating the discharge of large rivers by combining various long-term remote sensing data with physical flow equations is presented. For this purpose, water levels derived from multi-mission satellite altimetry and water surface extents extracted from optical satellite images are used, both provided by DGFI-TUM&amp;#8217;s &amp;#8220;Database of Hydrological Time series of Inland Waters&amp;#8221; (DAHITI, https://dahiti.dgfi.tum.de). The datasets are combined by fitting a hypsometric curve in order to describe the stage-width relation, which is then used to derive the water level for each acquisition epoch of the long-term multi-spectral remote sensing missions. In this way, the chance of detecting water level extremes is increased and a bathymetry can be estimated from water surface extent observations. Below the minimum hypsometric water level, the river bed elevation is estimated using an empirical width-to-depth relationship in order to determine the final cross-sectional geometry. The required flow gradient is computed based on a linear adjustment of river surface slope using all altimetry-observed water level differences between synchronous measurements at various virtual stations along the river. The roughness coefficient is set based on geomorphological features quantified by adjustment factors. These are chosen using remote sensing data and a literature decision guide.&lt;/p&gt;&lt;p&gt;Within this study, all parameters are estimated purely based on remote sensing data, without using any ground data. In-situ data is only used for the validation of the method at the Lower Mississippi River. It shows that the presented approach yields best results for uniform and straight river sections. The resulting normalized root mean square error for those targets varies between 10% to 35% and is comparable with other studies.&lt;/p&gt;

scholarly journals In situ measurements of the ice flow motion at Eqip Sermia Glacier using a remotely controlled unmanned aerial vehicle (UAV)

2020 ◽  
Vol 9 (1) ◽  
pp. 1-10
Author(s):  
Guillaume Jouvet ◽  
Eef van Dongen ◽  
Martin P. Lüthi ◽  
Andreas Vieli
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
In Situ Measurements ◽  
In Situ Monitoring ◽  
High Temporal Resolution ◽  
Ice Flow ◽  
Flow Motion ◽  
Aerial Vehicle ◽  
Matching Techniques

Abstract. Measuring the ice flow motion accurately is essential to better understand the time evolution of glaciers and ice sheets and therefore to better anticipate the future consequence of climate change in terms of sea level rise. Although there are a variety of remote sensing methods to fill this task, in situ measurements are always needed for validation or to capture high-temporal-resolution movements. Yet glaciers are in general hostile environments where the installation of instruments might be tedious and risky when not impossible. Here we report the first-ever in situ measurements of ice flow motion using a remotely controlled unmanned aerial vehicle (UAV). We used a quadcopter UAV to land on a highly crevassed area of Eqip Sermia Glacier, West Greenland, to measure the displacement of the glacial surface with the aid of an onboard differential GNSS receiver. We measured approximately 70 cm of displacement over 4.36 h without setting foot onto the glacier – a result validated by applying UAV photogrammetry and template matching techniques. Our study demonstrates that UAVs are promising instruments for in situ monitoring and have great potential for capturing continuous ice flow variations in inaccessible glaciers – a task that remote sensing techniques can hardly achieve.

A Practical UAV Remote Sensing Methodology to Generate Multispectral Orthophotos for Vineyards

2019 ◽  
pp. 298-322
Author(s):  
Adam J. Mathews
Keyword(s):  
Remote Sensing ◽  
Unmanned Aerial Vehicle ◽  
Spectral Reflectance ◽  
Near Infrared ◽  
Spectral Information ◽  
Digital Cameras ◽  
Individual Bands ◽  
Aerial Vehicle ◽  
Best Fit

This paper explores the use of compact digital cameras to remotely estimate spectral reflectance based on unmanned aerial vehicle imagery. Two digital cameras, one unaltered and one altered, were used to collect four bands of spectral information (blue, green, red, and near-infrared [NIR]). The altered camera had its internal hot mirror removed to allow the sensor to be additionally sensitive to NIR. Through on-ground experimentation with spectral targets and a spectroradiometer, the sensitivity and abilities of the cameras were observed. This information along with on-site collected spectral data were used to aid in converting aerial imagery digital numbers to estimates of scaled surface reflectance using the empirical line method. The resulting images were used to create spectrally-consistent orthophotomosaics of a vineyard study site. Individual bands were subsequently validated with in situ spectroradiometer data. Results show that red and NIR bands exhibited the best fit (R2: 0.78 for red; 0.57 for NIR).

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