Retrieval of At-Surface Upwelling Radiance and Albedo by Parameterizing Cloud Scattering and Transmittance over Rugged Terrain

Accurate and continuous estimation of surface albedo is vital for assessing and understanding land–surface–atmosphere interactions. We developed a method for estimating instantaneous all-sky at-surface shortwave upwelling radiance and albedo over the Tibetan Plateau. The method accounts for the complex interplay of topography and atmospheric interactions and aims to mitigate the occurrence of data gaps. Employing an RTLSR-kernel-driven model, we retrieved surface shortwave albedo with a 1 km resolution, incorporating direct, isotropic diffuse; circumsolar diffuse; and surrounding terrain irradiance into the all-sky solar surface irradiance. The at-surface upwelling radiance and surface shortwave albedo estimates were in satisfactory agreement with ground observations at four stations in the Tibetan Plateau, with RMSE values of 56.5 W/m2 and 0.0422, 67.6 W/m2 and 0.0545, 98.6 W/m2 and 0.0992, and 78.0 98.6 W/m2 and 0.639. This comparison indicated an improved accuracy of at-surface upwelling radiance and surface albedo and significantly reduced data gaps. Valid observations increased substantially in comparison to the MCD43A2 data product, with the new method achieving an increase ranging from 40% to 200% at the four stations. Our study demonstrates that by integrating terrain, cloud properties, and radiative transfer modeling, the accuracy and completeness of retrieved surface albedo and radiance in complex terrains can be effectively improved.Optical and Laser Remote Sensin

Improving the AMSR-E/NASA soil moisture data product using in-situ measurements from the Tibetan Plateau

The daily AMSR-E/NASA(the Advanced Microwave Scanning Radiometer-Earth Observing System/the National Aeronautics and Space Administration) and JAXA (the Japan Aerospace Exploration Agency) soil moisture (SM) products from 2002 to 2011 at 25 km resolution were developed and distributed by the NASA National Snow and Ice Data Center Distributed Active Archive Center (NSIDC DAAC) and JAXA archives, respectively. This study analyzed and evaluated the temporal changes and accuracy of the AMSR-E/NASA SM product and compared it with the AMSR-E/JAXA SM product. The accuracy of both AMSR-E/NASA and JAXA SM was low, with RMSE (root mean square error) > 0.1 cm3 cm-3 against the in-situ SM measurements, especially the AMSR-E/NASA SM. Compared with the AMSR-E/JAXA SM, the dynamic range of AMSR-E/NASA SM is very narrow in many regions and does not reflect the intra- and inter-annual variability of soil moisture. We evaluated both data products by building a linear relationship between the SM and the Microwave Polarization Difference Index (MPDI) to simplify the AMSR-E/NASA SM retrieval algorithm on the basis of the observed relationship between samples extracted from the MPDI and SM data. We obtained the coe°cients of this linear relationship (i.e., A0 and A1) using in-situ measurements of SM and brightness temperature (TB) data simulated with the same radiative transfer model applied to develop the AMSR-E/NASA SM algorithm. Finally, the linear relationships between the SM and MPDI were used to retrieve the SM monthly from AMSR-E TB data, and the estimated SM was validated using the in-situ SM measurements in the Naqu area on the Tibetan Plateau of China. We obtained a steeper slope, i.e., A1 = 8, with the in-situ SM measurements against A1 = 1, when using the NASA SM retrievals. The low A1 value is a measure of the low sensitivity of the NASA SM retrievals to MPDI and its narrow dynamic range. These results were confirmed by analyzing a data set collected in Poland. In the case of the Tibetan Plateau, the higher value A1 = 8 gave more accurate monthly AMSR-E SM retrievals with RMSE = 0.065 cm3 cm-3. The dynamic range of the improved retrievals was more consistent with the in-situ SM measurements than with both the AMSR-E/NASA and JAXA SM products in the Naqu area of the Tibetan Plateau in 2011.Optical and Laser Remote Sensin

Regional surface soil heat flux estimate from multiple remote sensing data in a temperate and semiarid basin

The regional surface soil heat flux (G0) estimation is very important for the large-scale land surface process modeling. However, most of the regional G0 estimation methods are based on the empirical relationship between G0 and the net radiation flux. A physical model based on harmonic analysis was improved (referred to as "HM model") and applied over the Heihe River Basin northwest China with multiple remote sensing data, e.g., FY-2C, AMSR-E, and MODIS, and soil map data. The sensitivity analysis of the model was studied as well. The results show that the improved model describes the variation of G0 well. Land surface temperature (LST) and thermal inertia (Γ) are the two key input variables to the HM model. Compared with in situ G0, there are some differences, mainly due to the differences between remote-sensed LST and the in situ LST. The sensitivity analysis shows that the errors from-7 to-0.5K in LST amplitude and from-300 to 300J m-2 K-1 s-0.5 in Γ will cause about 20% errors, which are acceptable for G0 estimation.Optical and Laser Remote Sensin

Surface Water Mapping and Flood Monitoring in the Mekong Delta Using Sentinel-1 SAR Time Series and Otsu Threshold

The annual flood and the alteration in hydrological regimes are the most vital concerns in the Vietnamese Mekong Delta (VMD). Although synthetic aperture radar (SAR) Sentinel-1 imagery is widely used for water management, only a few studies have used Sentinel-1 data for mapping surface water and monitoring flood events in the VMD. This study developed an algorithm to implement (i) automatic Otsu threshold on a series of Sentinel-1 images to extract surface water and (ii) time series analyses on the derived surface water maps to detect flood water extent in near-real-time (NRT). Specifically, only cross-polarized VH was selected after an assessment of different Sentinel-1 polarizations. The dynamic Otsu thresholding algorithm was applied to identify an optimal threshold for each pre-processed Sentinel-1 VH image to separate water from non-water pixels for producing a time series of surface water maps. The derived Sentinel-1 surface water maps were visually compared with the Sentinel-2 Full Resolution Browse (FRB) and statistically examined with the Sentinel-2 Multispectral Instrument (MSI) surface water maps, which were generated by applying the Otsu threshold on the normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) images. The visual comparison showed a strong correspondence between the Sentinel-1 surface water maps and Sentinel-2 FRB images in three periods, including rice’s sowing season, flood period, and rice’s maturation stage. A good statistical agreement suggested that the performance of the dynamic Otsu thresholding algorithm on Sentinel-1 image time series to map surface water is effective in river areas (R2 = 0.97 and RMSE = 1.18%), while it is somewhat lower in paddy field areas (R2 = 0.88 and RMSE = 3.88%). Afterward, a flood mapping algorithm in NRT was developed by applying the change-detection-based time series analyses on the derived Sentinel-1 surface water maps. Every single pixel at the time is respectively referred to its state in the water/non-water and flooded/non-flooded maps at the previous time to be classified into a flooded or non-flooded pixel. The flood mapping algorithm enables updates at each time step to generate temporal flood maps in NRT for monitoring flood water extent in large-scale areas. This study provides a tool to rapidly generate surface water and flood maps to support water management and risk reduction in the VMD. The future improvement of the current algorithm is discussed.Optical and Laser Remote Sensin

Understanding spatial patterns in the drivers of greenness trends in the Sahel-Sudano-Guinean region

The region-wide spatial pattern of the drivers of vegetation trends in the African Sahel-Sudano-Guinean region, one of the main drylands of the world, has not been fully investigated. Time-series satellite earth observation datasets were used to investigate spatiotemporal patterns of the vegetation greenness changes in the region and then a principal component regression method was applied to identify the region-wide spatial pattern of driving factors. Results find that vegetation greening is widespread in the region, while vegetation browning is more clustered in central West Africa. The dominant drivers of vegetation greenness have a distinct spatial pattern. Climatic factors are the primary drivers, but the impacts of precipitation decrease from north to south, while the impacts of temperature are contrariwise. Coupled with climatic drivers, land cover changes lead to greening trends in the arid zone, especially in the western Sahelian belt. However, the cluster of browning trends in central West Africa can primarily be attributed to the human-induced land cover changes, including an increasing fractional abundance of agriculture. The results highlight the spatial pattern of climatic and anthropic factors driving vegetation greenness changes, which helps natural resources sustainable use and mitigation of climate change and human activities in global dryland ecosystems.Optical and Laser Remote Sensin

Quantitative analyses of ageing status of dam concrete for a 25-year-old dam

In order to evaluate the aging status of the dam concrete for a 25-years-old concrete dam, the internal concrete and surface layer of the dam were tested by elastic wave computerized tomography (CT) and spectral analysis of surface wave (SASW). Also mechanical strength and elastic wave velocity were tested for the concrete cores from the dam. The CT results show that the elastic wave velocities of the three dam sections are basically around 4400~4500m/s and no obvious low-speed zone could be detected, indicating the quality of the internal concrete is good without aging signs. The SASW results show that the Rayleigh wave velocity of the surface layer (deeper than 25cm) is about 2500 m/s (the corresponding P wave velocity is 4500 m/s) which is basically consistent with the CT results. The average compressive strength of the concrete cores is over 40 MPa (higher than the design values) while the elastic wave velocities are between 3600 and 4400 m/s. Microstructural analysis results show that the a few microcracks could be observed in all the 16 cores from the upstream, the downstream, the gallery and the spillway. The overall results indicate that the dam concrete is of good quality and no obvious aging signs could be found

Glacier mass balance in the Nyainqentanglha mountains between 2000 and 2017 retrieved from ZiYuan-3 stereo images and the SRTM DEM

Mountain glaciers are excellent indicators of climate change and have an important role in the terrestrial water cycle and food security in many parts of the world. Glaciers are the major water source of rivers and lakes in the Nyainqentanglha Mountains (NM) region, where the glacier area has the second largest extent on the Tibetan Plateau. The potential of the high spatial resolution ZiYuan-3 (ZY-3) Three-Line-Array (TLA) stereo images to retrieve glacier mass balance has not been sufficiently explored. In this study, we optimized the procedure to extract a Digital Elevation Model (DEM) from ZY-3 TLA stereo images and estimated the geodetic mass balance of representative glaciers in the two typical areas of the NM using ZY-3 DEMs and the C-band Shuttle Radar Topography Mission (SRTM) DEM in three periods, i.e., 2000-2013, 2013-2017 and 2000-2017. The results provide detailed information towards better understanding of glacier change and specifically show that: (1) with our new stereo procedure, ZY-3 TLA data can significantly increase point cloud density and decrease invalid data on the glacier surface map to generate a high resolution (5 m) glacier mass balance map; (2) the glacier mass balance in both the Western Nyainqentanglha Mountains (WNM) and Eastern Nyainqentanglha Mountains (ENM) was negative in 2000-2017, and experienced faster mass loss in recent years (2013-2017) in the WNM. Overall, the glaciers in the western and eastern NM show different change patterns since they are influenced by different climate regimes; the glacier mass balances in WNM was-0.22 ± 0.23 m w.e. a-1 and-0.43 ± 0.06 m w.e. a-1 in 2000-2013 and 2013-2017, respectively, while in 2000-2017, it was-0.30 ± 0.19 m w.e. a-1 in the WNM and-0.56 ± 0.20 m w.e. a-1 in the ENM; (3) in the WNM, the glaciers experienced mass loss in 2000-2013 and 2013-2017 in the ablation zone, while in the accumulation zone mass increased in 2000-2013 and a large mass loss occurred in 2013-2017; as regards the ENM, the glacier mass balance was negative in 2000-2017 in both zones; (4) glacier mass balance can be affected by the fractional abundance of debris and glacier slope; (5) the glacier mass balances retrieved by ZY-3 and TanDEM-X data agreed well in the ablation zone, while a large difference occurred in the accumulation zone because of the snow/firn penetration of the X-band SAR signal.Optical and Laser Remote Sensin

Glacier facies mapping using a machine-learning algorithm: The Parlung Zangbo Basin case study

Glaciers in the Tibetan Plateau are an important indicator of climate change. Automatic glacier facies mapping utilizing remote sensing data is challenging due to the spectral similarity of supraglacial debris and the adjacent bedrock. Most of the available glacier datasets do not provide the boundary of clean ice and debris-covered glacier facies, while debris-covered glacier facies play a key role in mass balance research. The aim of this study was to develop an automatic algorithm to distinguish ice cover types based on multi-temporal satellite data, and the algorithm was implemented in a subregion of the Parlung Zangbo basin in the southeastern Tibetan Plateau. The classification method was built upon an automated machine learning approach: Random Forest in combination with the analysis of topographic and textural features based on Landsat-8 imagery and multiple digital elevation model (DEM) data. Very high spatial resolution Gao Fen-1 (GF-1) Panchromatic and Multi-Spectral (PMS) imagery was used to select training samples and validate the classification results. In this study, all of the land cover types were classified with overall good performance using the proposed method. The results indicated that fully debris-covered glaciers accounted for approximately 20.7% of the total glacier area in this region and were mainly distributed at elevations between 4600 m and 4800 m above sea level (a.s.l.). Additionally, an analysis of the results clearly revealed that the proportion of small size glaciers (< 1 km 2 ) were 88.3% distributed at lower elevations compared to larger size glaciers (≥1 km 2 ). In addition, the majority of glaciers (both in terms of glacier number and area) were characterized by a mean slope ranging between 20° and 30°, and 42.1% of glaciers had a northeast and north orientation in the Parlung Zangbo basin. In the Special Issue 'Remote Sensing of Glaciers at Global and Regional Scales'Optical and Laser Remote Sensin

Land-Atmosphere Interactions and Effects on the Climate of the Tibetan Plateau and Surrounding Regions: Remote Sensing

The global climate has undergone unequivocal warming [...]Optical and Laser Remote Sensin

Investigating the Response of Vegetation to Flash Droughts by Using Cross-Spectral Analysis and an Evapotranspiration-Based Drought Index

Flash droughts tend to cause severe damage to agriculture due to their characteristics of sudden onset and rapid intensification. Early detection of the response of vegetation to flash droughts is of utmost importance in mitigating the effects of flash droughts, as it can provide a scientific basis for establishing an early warning system. The commonly used method of determining the response time of vegetation to flash drought, based on the response time index or the correlation between the precipitation anomaly and vegetation growth anomaly, leads to the late detection of irreversible drought effects on vegetation, which may not be sufficient for use in analyzing the response of vegetation to flash drought for early earning. The evapotranspiration-based (ET-based) drought indices are an effective indicator for identifying and monitoring flash drought. This study proposes a novel approach that applies cross-spectral analysis to an ET-based drought index, i.e., Evaporative Stress Anomaly Index (ESAI), as the forcing and a vegetation-based drought index, i.e., Normalized Vegetation Anomaly Index (NVAI), as the response, both from medium-resolution remote sensing data, to estimate the time lag of the response of vegetation vitality status to flash drought. An experiment on the novel method was carried out in North China during March–September for the period of 2001–2020 using remote sensing products at 1 km spatial resolution. The results show that the average time lag of the response of vegetation to water availability during flash droughts estimated by the cross-spectral analysis over North China in 2001–2020 was 5.9 days, which is shorter than the results measured by the widely used response time index (26.5 days). The main difference between the phase lag from the cross-spectral analysis method and the response time from the response time index method lies in the fundamental processes behind the definitions of the vegetation response in the two methods, i.e., a subtle and dynamic fluctuation signature in the response signal (vegetation-based drought index) that correlates with the fluctuation in the forcing signal (ET-based drought index) versus an irreversible impact indicated by a negative NDVI anomaly. The time lag of the response of vegetation to flash droughts varied with vegetation types and irrigation conditions. The average time lag for rainfed cropland, irrigated cropland, grassland, and forest in North China was 5.4, 5.8, 6.1, and 6.9 days, respectively. Forests have a longer response time to flash droughts than grasses and crops due to their deeper root systems, and irrigation can mitigate the impacts of flash droughts. Our method, based on cross-spectral analysis and the ET-based drought index, is innovative and can provide an earlier warning of impending drought impacts, rather than waiting for the irreversible impacts to occur. The information detected at an earlier stage of flash droughts can help decision makers in developing more effective and timely strategies to mitigate the impact of flash droughts on ecosystems.Optical and Laser Remote Sensin