Combined extraction of high spatial resolution wind speed and wind direction from SAR images: A new approach using wavelet transform

2002 ◽  
Vol 28 (3) ◽  
pp. 510-516 ◽  
Author(s):  
Nicolas Fichaux ◽  
Thierry Ranchin
Keyword(s):  
Wavelet Transform ◽  
Wind Speed ◽  
Spatial Resolution ◽  
Wind Direction ◽  
High Spatial Resolution ◽  
Sar Images ◽  
New Approach

scholarly journals Precipitation Atlas for Germany (GePrA)

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 737
Author(s):  
Christopher Jung ◽  
Dirk Schindler
Keyword(s):  
Spatial Resolution ◽  
Large Scale ◽  
High Spatial Resolution ◽  
Spline Interpolation ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Small Scale ◽  
Monthly Precipitation ◽  
New Approach ◽  
Very High Spatial Resolution

A new approach for modeling daily precipitation (RR) at very high spatial resolution (25 m × 25 m) was introduced. It was used to develop the Precipitation Atlas for Germany (GePrA). GePrA is based on 2357 RR time series measured in the period 1981–2018. It provides monthly percentiles (p) of the large-scale RR patterns which were mapped by a thin plate spline interpolation (TPS). A least-squares boosting (LSBoost) approach and orographic predictor variables (PV) were applied to integrate the small-scale precipitation variability in GePrA. Then, a Weibull distribution (Wei) was fitted to RRp. It was found that the mean monthly sum of RR ( R R ¯ s u m ) is highest in July (84 mm) and lowest in April (49 mm). A great dependency of RR on the elevation (ε) was found and quantified. Model validation at 425 stations showed a mean coefficient of determination (R2) of 0.80 and a mean absolute error (MAE) of less than 10 mm in all months. The high spatial resolution, including the effects of the local orography, make GePrA a valuable tool for various applications. Since GePrA does not only describe R R ¯ s u m , but also the entire monthly precipitation distributions, the results of this study enable the seasonal differentiation between dry and wet period at small scales.

scholarly journals NanoSIMS imaging: an approach for visualizing and quantifying lipids in cells and tissues

2016 ◽  
Vol 65 (3) ◽  
pp. 669-672 ◽  
Author(s):  
Cuiwen He ◽  
Loren G Fong ◽  
Stephen G Young ◽  
Haibo Jiang
Keyword(s):  
Mass Spectrometry ◽  
Spatial Resolution ◽  
Mass Spectrometry Imaging ◽  
Secondary Ion Mass Spectrometry ◽  
High Spatial Resolution ◽  
High Sensitivity ◽  
New Approach ◽  
The Past ◽  
Secondary Ion ◽  
In Cells

Over the past few decades, several approaches have been used to image lipids in cells and tissues, but most have limited spatial resolution and sensitivity. Here, we discuss a relatively new approach, nanoscale secondary ion mass spectrometry imaging, that makes it possible to visualize lipids in cells and tissues in a quantitative fashion and with high spatial resolution and high sensitivity.

scholarly journals A new approach to accurate validation of remote sensing retrieval of evapotranspiration based on data fusion

2010 ◽  
Vol 7 (2) ◽  
pp. 1745-1784 ◽  
Author(s):  
C. Sun ◽  
D. Jiang ◽  
J. Wang ◽  
Y. Zhu
Keyword(s):  
Remote Sensing ◽  
Data Fusion ◽  
Spatial Resolution ◽  
Hydrological Model ◽  
Assessment Tool ◽  
High Spatial Resolution ◽  
Meteorological Data ◽  
New Method ◽  
Distributed Hydrological Model ◽  
New Approach

Abstract. The study presented a new method of validating the remote-sensing (RS) retrieval of evapotranspiration (ET) under the support of a distributed hydrological model: Soil and Water Assessment Tool (SWAT). In this method, the output runoff data based on a fusion of ET data, meteorological data and rainfall data, etc. were compared with the observed runoff data, so as to carry out validation analysis. A new pattern of validating the ET data obtained from RS retrieval, which was more appropriate than the conventional means of observing the ET at several limited stations based on eddy covariance, was proposed. It has integrated the advantage of high requirement of ET with high spatial resolution in the distributed hydrological model and that of the capacity of providing ET with high spatial resolution in RS methods. First, the ET data in five years (2000–2004) were retrieved with RS according to the principle of energy balance. The temporal/spatial ditribution of monthly ET data and related causes were analyzed in the year of 2000, and the monthly ET in the five years was calculated according to the PM model. Subsequently, the results of the RS retrieval of ET and the PM-based ET calculation were compared and validated. Finnaly, the ET data obtained from RS retrieval was evaluated with the new method, under the support of SWAT, meteorologic data, Digital Elevation Model (DEM), landuse data and soil data, etc. as the input, being compared with the PM-based ET. According to the ET data analysis, it can be inferred that the ET obtained from RS retrieval was more continuous and stable with less saltation, while the PM-based ET presented saltation, especially in the year of 2000 and 2001. The correlation coefficient between the monthly ET in two methods reaches 0.8914, which could be explained by the influence from clouds and the inadequate representativeness of the meteorologic stations. Moreover, the PM-based ET was smaller than the ET obtained from RS retrieval, which was in accordance with previous studies (Jamieson, 1982; Dugas and Ainsworth, 1985; Benson et al., 1992; Pereira and Nova, 1992). After the data fusion, the correlation (R2=0.8516) between the monthly runoff obtained from the simulation based on ET retrieval and the observed data was higher than that (R2=0.8411) between the data obtained from the PM-based ET simulation and the observed data. As for the RMSE, the result (RMSE=26.0860) between the simulated runoff based on ET retrieval and the observed data was also superior to the result (RMSE=35.71904) between the simulated runoff obtained with PM-based ET and the observed data. As for the MBE parameter, the result (MBE=−8.6578) for the RS retrieval method was obviously better than that (MBE=−22.7313) for the PM-based method. The comparison of them showed that the RS retrieval had better adaptivity and higher accuracy than the PM-based method, and the new approach based on data fusion and the distributed hydrological model was feasible, reliable and worth being studied further.

scholarly journals Estimation of the high-spatial-resolution variability in extreme wind speeds for forestry applications

2017 ◽  
Vol 8 (3) ◽  
pp. 529-545 ◽  
Author(s):  
Ari Venäläinen ◽  
Mikko Laapas ◽  
Pentti Pirinen ◽  
Matti Horttanainen ◽  
Reijo Hyvönen ◽  
...  
Keyword(s):  
Wind Speed ◽  
Spatial Variation ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Maximum Wind Speed ◽  
Wind Damage ◽  
Return Level ◽  
Mapping Technique ◽  
Maximum Wind ◽  
Wind Speeds

Abstract. The bioeconomy has an increasing role to play in climate change mitigation and the sustainable development of national economies. In Finland, a forested country, over 50 % of the current bioeconomy relies on the sustainable management and utilization of forest resources. Wind storms are a major risk that forests are exposed to and high-spatial-resolution analysis of the most vulnerable locations can produce risk assessment of forest management planning. In this paper, we examine the feasibility of the wind multiplier approach for downscaling of maximum wind speed, using 20 m spatial resolution CORINE land-use dataset and high-resolution digital elevation data. A coarse spatial resolution estimate of the 10-year return level of maximum wind speed was obtained from the ERA-Interim reanalyzed data. Using a geospatial re-mapping technique the data were downscaled to 26 meteorological station locations to represent very diverse environments. Applying a comparison, we find that the downscaled 10-year return levels represent 66 % of the observed variation among the stations examined. In addition, the spatial variation in wind-multiplier-downscaled 10-year return level wind was compared with the WAsP model-simulated wind. The heterogeneous test area was situated in northern Finland, and it was found that the major features of the spatial variation were similar, but in some locations, there were relatively large differences. The results indicate that the wind multiplier method offers a pragmatic and computationally feasible tool for identifying at a high spatial resolution those locations with the highest forest wind damage risks. It can also be used to provide the necessary wind climate information for wind damage risk model calculations, thus making it possible to estimate the probability of predicted threshold wind speeds for wind damage and consequently the probability (and amount) of wind damage for certain forest stand configurations.

scholarly journals Distributed sensing of wind direction using fiber-optic cables

2021 ◽  
Author(s):  
Anita Freundorfer ◽  
Karl Lapo ◽  
Johann Schneider ◽  
Christoph K. Thomas
Keyword(s):  
Wind Speed ◽  
Spatial Resolution ◽  
Wind Direction ◽  
Fiber Optic ◽  
Sonic Anemometer ◽  
Distributed Sensing ◽  
Spatial And Temporal Scales ◽  
Spatially Distributed ◽  
Temporal Structures ◽  
Direction Information

AbstractIn the atmospheric boundary layer, phenomena exist with challenging properties such as spatial heterogeneity, particularly during stable weak wind situations. Studying spatially heterogeneous features requires spatially distributed measurements on fine spatial and temporal scales. Fiber-Optic Distributed Sensing (FODS) can provide spatially distributed measurements, simultaneously offering a spatial resolution on the order of decimeters and a temporal resolution on the order of seconds. While FODS has already been deployed to study various variables, FODS wind direction sensing has only been demonstrated in idealized wind tunnel experiments. We present the first distributed observations of FODS wind directions from field data. The wind direction sensing is accomplished by using pairs of actively heated fiber optic cables with cone-shaped microstructures attached to them. Here we present three different methods of calculating wind directions from the FODS measurements, two based on using combined wind speed and direction information and one deriving wind direction independently from FODS wind speed. For each approach, the effective temporal and spatial resolution is quantified using spectral coherence. With each method of calculating wind directions, temporal resolutions on the order of tens of seconds can be achieved. The accuracy of FODS wind directions was evaluated against a sonic anemometer, showing deviations of less than 15° most of the time. The applicability of FODS for wind direction measurements in different environmental conditions is tested by analysing the dependence of FODS wind direction accuracy and observable scales on environmental factors. Finally, we demonstrate the potential of this technique by presenting a period that displays spatial and temporal structures in the wind direction.

Use of Sentinel-1 C-Band SAR Images for Convective System Surface Wind Pattern Detection

2020 ◽  
Vol 59 (8) ◽  
pp. 1321-1332
Author(s):  
Tran Vu La ◽  
Christophe Messager ◽  
Marc Honnorat ◽  
Rémi Sahl ◽  
Ali Khenchaf ◽  
...  
Keyword(s):  
Wind Speed ◽  
Brightness Temperature ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Surface Wind ◽  
Sea Surface ◽  
Speed Estimation ◽  
Convective Clouds ◽  
Wind Intensity ◽  
Wind Patterns

AbstractConvective systems (CS) through their downdrafts hitting the sea surface may produce wind patterns (or cold pools) with wind intensity exceeding 10–25 m s−1. The latter for a long time have been significant for weather forecast and meteorological studies, especially in the tropical regions like the Gulf of Guinea since it is hard to detect the CS-associated wind patterns. Based on Sentinel-1 images [C-band Synthetic Aperture Radar (SAR)] with high spatial resolution and large swath, the current study proposed the detection of surface wind patterns through wind speed estimation by C-band model 5.N (CMOD5.N; for vertically polarized images) and two models proposed by Sapp and Komarov (for horizontally polarized images). Relative to the X-band SAR, the effects of precipitation on C-band radar backscattering are negligible, and thereby it has little impact on wind speed estimation from Sentinel-1 images. The detected surface wind patterns include a squall line and a bow echo at the mesoscale (>100 km) and many submesoscale (<100 km) convection cells. They are accompanied by various degrees of precipitation (from light to heavy rain). This study also used Meteosat infrared images for monitoring and detection of deep convective clouds (with low brightness temperature) corresponding to surface wind patterns. The agreement in location and sometimes in shape between them strengthened the assumption that the CS downdrafts may induce the sea surface patterns with high wind intensity (10–25 m s−1). In particular, because of the Sentinel-1 high spatial resolution, the pattern spots with high winds (20–25 m s−1) are detected on the illustrated images, which was not reported in the literature. They are located close to the coldest convective clouds (about 200-K brightness temperature).

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