scholarly journals The Use of SAR Satellite Imagery to Measure Active Layer Moisture Contents in Arctic Alaska

1996 ◽  
Vol 27 (1-2) ◽  
pp. 25-38 ◽  
Author(s):  
D. L. Kane ◽  
L. D. Hinzman ◽  
Haofang Yu ◽  
D. J. Goering

Synthetic aperture radar (SAR) has the potential for measuring near surface soil moisture contents for very large areas. The polar orbiting European Remote Sensing satellite (ERS-1) of the European Space Agency (ESA) has onboard an active C-band SAR sensor. We have analyzed SAR imagery over a small research watershed, Imnavait Creek, located in the northern foothills of the Brooks Range in Alaska, U.S.A. This watershed is treeless and completely underlain with permafrost. After geometrically and radiometrically correcting each pixel (25 m by 25 m) in the image, corrected pixel values were correlated with corresponding field moisture contents measured along transects in the watershed for two passes of the satellite. Coefficients of determination, r2, between the corrected pixel value and measured moisture content were 0.49 on June 12, 1993 and 0.53 on August 2, 1993; with the data sets combined the value was 0.50.

2009 ◽  
Vol 2 (1) ◽  
pp. 87-98 ◽  
Author(s):  
C. Lerot ◽  
M. Van Roozendael ◽  
J. van Geffen ◽  
J. van Gent ◽  
C. Fayt ◽  
...  

Abstract. Total O3 columns have been retrieved from six years of SCIAMACHY nadir UV radiance measurements using SDOAS, an adaptation of the GDOAS algorithm previously developed at BIRA-IASB for the GOME instrument. GDOAS and SDOAS have been implemented by the German Aerospace Center (DLR) in the version 4 of the GOME Data Processor (GDP) and in version 3 of the SCIAMACHY Ground Processor (SGP), respectively. The processors are being run at the DLR processing centre on behalf of the European Space Agency (ESA). We first focus on the description of the SDOAS algorithm with particular attention to the impact of uncertainties on the reference O3 absorption cross-sections. Second, the resulting SCIAMACHY total ozone data set is globally evaluated through large-scale comparisons with results from GOME and OMI as well as with ground-based correlative measurements. The various total ozone data sets are found to agree within 2% on average. However, a negative trend of 0.2–0.4%/year has been identified in the SCIAMACHY O3 columns; this probably originates from instrumental degradation effects that have not yet been fully characterized.


2021 ◽  
Author(s):  
Chih-Chun Chou ◽  
Paul J. Kushner ◽  
Stéphane Laroche ◽  
Zen Mariani ◽  
Peter Rodriguez ◽  
...  

Abstract. In August 2018, the European Space Agency launched the Aeolus satellite, whose Atmospheric LAser Doppler INstrument (ALADIN) is the first spaceborne Doppler wind lidar to regularly measure vertical profiles of horizontal line-of-sight (HLOS) winds with global sampling. This mission is intended to assess improvement to numerical weather prediction provided by wind observations in regions poorly constrained by atmospheric mass, such as the tropics, but also, potentially, in polar regions such as the Arctic where direct wind observations are especially sparse. There remain gaps in the evaluation of the Aeolus products over the Arctic region, which is the focus of this contribution. Here, an assessment of the Aeolus Level-2B wind product is carried out from measurement stations in Canada’s north, to the pan-Arctic, with Aeolus data being compared to Ka-band radar measurements at Iqaluit, Nunavut; to radiosonde measurements over Northern Canada; to Environment and Climate Change Canada (ECCC)’s short-range forecast; and to the reanalysis product, ERA5, from the European Centre for Medium-Range Weather Forecasts (ECMWF). Periods covered include the early phase during the first laser nominal flight model (FM-A; 2018-09 to 2018-10), the early phase during the second flight laser (FM-B; 2019-08 to 2019-09), and the mid-FM-B periods (2019-12 to 2020-01). The adjusted r-square between Aeolus and other local datasets are around 0.9, except for somewhat lower values in comparison with the ground-based radar, presumably due to limited sampling. This consistency degraded by about 10 % for the Rayleigh winds in the summer, presumably due to scattering from the solar background. Over the pan-Arctic, consistency, with correlation greater than 0.8, is found in the Mie channel from the planetary boundary layer to the lower stratosphere (near surface to 16 km a.g.l.) and in the Rayleigh channel from the troposphere to the stratosphere (2 km to 25 km a.g.l.). Zonal and meridional projections of the HLOS winds are separated to account for the systematic changes in HLOS winds arising from sampling wind components from different viewing orientations in the ascending and descending phases. In all cases, Aeolus standard deviations are found to be 20 % greater than those from ECCC-B and ERA5. We found that L2B estimated error product for Aeolus is coherent with the differences between Aeolus and the other datasets, and can be used as a guide for expected consistency. Thus, our work confirms the quality of the Aeolus dataset over the Arctic and shows that the new Aeolus L2B wind product provides a valuable addition to current wind products in regions such as the Arctic Ocean region where few direct wind observations have been available to date.


2021 ◽  
Author(s):  
Wouter Dorigo ◽  
Irene Himmelbauer ◽  
Daniel Aberer ◽  
Lukas Schremmer ◽  
Ivana Petrakovic ◽  
...  

Abstract. In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort, funded by the European Space Agency, to serve as a centralised data hosting facility for globally available in situ soil moisture measurements (Dorigo et al., 2011a, b). The ISMN brings together in situ soil moisture measurements collected and freely shared by a multitude of organisations, harmonizes them in terms of units and sampling rates, applies advanced quality control, and stores them in a database. Users can freely retrieve the data from this database through an online web portal (https://ismn.earth). Meanwhile, the ISMN has evolved into the primary in situ soil moisture reference database worldwide, as evidenced by more than 3000 active users and over 1000 scientific publications referencing the data sets provided by the network. As of December 2020, the ISMN now contains data of 65 networks and 2678 stations located all over the globe, with a time period spanning from 1952 to present.The number of networks and stations covered by the ISMN is still growing and many of the data sets contained in the database continue to be updated. The main scope of this paper is to inform readers about the evolution of the ISMN over the past decade,including a description of network and data set updates and quality control procedures. A comprehensive review of existing literature making use of ISMN data is also provided in order to identify current limitations in functionality and data usage, and to shape priorities for the next decade of operations of this unique community-based data repository.


2020 ◽  
Vol 12 (22) ◽  
pp. 3737
Author(s):  
Nicola Paciolla ◽  
Chiara Corbari ◽  
Ahmad Al Bitar ◽  
Yann Kerr ◽  
Marco Mancini

Numerous Surface Soil Moisture (SSM) products are available from remote sensing, encompassing different spatial, temporal, and radiometric resolutions and retrieval techniques. Notwithstanding this variety, all products should be coherent with water inputs. In this work, we have cross-compared precipitation and irrigation with different SSM products: Soil Moisture Ocean Salinity (SMOS), Soil Moisture Active Passive (SMAP), European Space Agency (ESA) Climate Change Initiative (ESA-CCI) products, Copernicus SSM1km, and Advanced Microwave Scanning Radiometer 2 (AMSR2). The products have been analyzed over two agricultural sites in Italy (Chiese and Capitanata Irrigation Consortia). A Hydrological Consistency Index (HCI) is proposed as a means to measure the coherency between SSM and precipitation/irrigation. Any time SSM is available, a positive or negative consistency is recorded, according to the rainfall registered since the previous measurement and the increase/decrease of SSM. During the irrigation season, some agreements are labeled as “irrigation-driven”. No SSM dataset stands out for a systematic hydrological coherence with the rainfall. Negative consistencies cluster just below 50% in the non-irrigation period and lose 20–30% in the irrigation period. Hybrid datasets perform better (+15–20%) than single-technology measurements, among which active data provide slightly better results (+5–10%) than passive data.


2013 ◽  
Vol 6 (4) ◽  
pp. 7811-7865 ◽  
Author(s):  
F. Ebojie ◽  
C. von Savigny ◽  
A. Ladstätter-Weißenmayer ◽  
A. Rozanov ◽  
M. Weber ◽  
...  

Abstract. Tropospheric ozone, O3, has two sources: transport from the stratosphere and photochemical production in the troposphere. It plays important roles in atmospheric chemistry and climate change. In this manuscript we describe the retrieval of tropospheric O3 columns from limb-nadir matching (LNM) observations of the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument, which flies as part of the payload onboard the European Space Agency (ESA) satellite Envisat. This retrieval technique is a residual approach that utilizes the subtraction of the stratospheric O3 columns, derived from the limb observations, from the total O3 columns, derived from the nadir observations. The technique requires accurate knowledge of the stratospheric O3 columns, the total O3 columns, tropopause height, and their associated errors. The stratospheric O3 columns were determined from the stratospheric O3 profile retrieved in the Hartley and Chappius bands, based on SCIAMACHY limb scattering measurements. The total O3 columns were also derived from SCIAMACHY measurements, in the nadir viewing mode using the Weighting Function Differential Optical Absorption Spectroscopy (WFDOAS) technique in the Huggins band. Comparisons of the tropospheric O3 columns from SCIAMACHY and collocated measurements from ozonesondes, in both hemispheres between January 2003 and December 2011 show agreement to within 2–5 DU (1 DU = 2.69 × 1016 molecules cm−2). Comparison of tropospheric O3 from SCIAMACHY with the results from ozonesondes, the Tropospheric Emission Spectrometer (TES), and the LNM method combining Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) data (hereinafter referred to as OMI/MLS), have been investigated. We find that all four retrieved data sets show agreement within the error bars and exhibit strong seasonal variation, which differs in amplitude. The spatial distribution of tropospheric ozone observed shows pollution plumes related to the release of precursors at the different seasons in both hemispheres.


2021 ◽  
Author(s):  
Marloes Penning de Vries ◽  
Suhyb Salama ◽  
Chris Mannaerts ◽  
Daphne van der Wal

<p>As a consequence of the ever-increasing global temperature, not only the air, and surface, but also lakes are warming up. This is expressed by steadily increasing base temperatures, but also in increases in the frequency and intensity of lake heatwaves. Land-based organisms may adapt to a changing climate by migrating to more suitable habitats, but this is usually not an option for lake-dwellers. Because many livelihoods depend on the ecosystem services of lakes, understanding the effects of heatwaves on lake composition form  an important input for the assessment of climate change impacts and design of adaptation strategies.</p><p>Using satellite data of lake temperature and water quality observations, we here investigate the effects of heatwaves on lake composition by studying the relationship between heatwaves and water quality variables of temperature, chlorophyll-a , colored dissolved organic matter, and suspended particulate matter . The latter can be used to infer effects of heat stress on health and populations of phyto- and zooplankton communities and higher aquatic organisms. Satellite-based data sets provided by the Climate Change Initiative of the European Space Agency,  CCI-Lakes (https://climate.esa.int/en/projects/lakes/) are  used in conjunction with the 2SeaColor model to determine depth-dependent attenuation coefficients and water quality variables.These data are complemented with and compared to data from Copernicus Global Land Services (https://land.copernicus.eu/global/products/). </p><p>The co-occurrence of heatwaves and changes in lake composition is investigated using statistical tools, and the causality is examined by comparison with biophysical models. The results from this study are discussed in light of previously published projected changes in heatwave frequency and intensity.</p>


Author(s):  
M. E. Molinari ◽  
A. Monti-Guarnieri ◽  
M. Manzoni

Abstract. Detecting temporal changes is one of the most important applications of satellite sensors. In recent years, the increasing availability of regular time-series of SAR imagery, provided by the Sentinel-1 mission of the European Space Agency (ESA), has drawn increasing attention to these techniques, especially in earth environment monitoring and risk management. Within this paper, a coherent change detection analysis for evaluating the risk due to movements of dunes and sand sheets in desertic areas is proposed. To this purpose, we introduce a novel, coherence-based index, named Temporal Stability Index (TSI), that is suited for characterizing the percentage of stability of a target with time. TSI maps can be generated over areas as wide as hundreds of kilometers, in a short time, and mostly by exploiting available software tools (plus some simple coding). The information provided is complementary to the average of the short-term coherence, here shown. Results of analysis performed on two desertic regions (the United Arab Emirates and Egypt) document the usefulness of TSI for the identification of dune movements and areas subject to sand accumulation, supporting risk mitigation measures.


2010 ◽  
Vol 5 ◽  
pp. 37-48
Author(s):  
Markéta Potůčková ◽  
Eva Štefanová

European Space Agency (ESA) provides several open source toolboxes for visualization, processing and analyzing satellite images acquired both in optical and microwave domains. Basic ERS & Envisat (A)ATSR and MERIS Toolbox (BEAM) was originally developed for easier handling ENVISAT optical data. Today this toolbox supports several raster data formats and datasets collected with other EO instruments such as MODIS, AVHRR, CHRIS/Proba. The NEXT ESA SAR Toolbox (NEST) has been created for processing radar data acquired from different satellites such as ERS 1&2, ENVISAT, RADARSAT or TerraSAR X. Both toolboxes are suitable for the education of the basic principles of data processing (geometric and radiometric corrections, classification, filtering of radar data) but also for research. Possibilities for utilization of these toolboxes in remote sensing courses based on two examples of practical exercises are described. Use of the NEST toolbox is demonstrated on a research project dealing with snow cover detection from SAR imagery.


2020 ◽  
Author(s):  
Benjamin Witschas ◽  
Christian Lemmerz ◽  
Alexander Geiß ◽  
Oliver Lux ◽  
Uwe Marksteiner ◽  
...  

Abstract. Soon after the launch of Aeolus on 22 August 2018, the first ever wind lidar in space developed by the European Space Agency (ESA) has been providing profiles of the component of the wind vector along the instrument's line-of-sight (LOS) on a global scale. In order to validate the quality of Aeolus wind observations, the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt e.V., DLR) recently performed two airborne campaigns over Central Europe deploying two different Doppler wind lidars (DWL) on-board the DLR Falcon aircraft. The first campaign – WindVal III – was conducted from 5 November 2018 until 5 December 2018 and thus, still within the commissioning phase of the Aeolus mission. The second campaign – AVATARE (Aeolus Validation Through Airborne Lidars in Europe) – was performed from 6 May 2019 until 6 June 2019. Both campaigns were flown out of the DLR site in Oberpfaffenhofen, Germany. All together, 10 satellite underflights with 19 flight legs covering more than 7500 km of Aeolus swaths were performed and used to validate the early stage wind data product of Aeolus by means of collocated airborne wind lidar observations for the first time. For both campaign data sets, the statistical comparison of Aeolus data and the data of the reference lidar (2-µm DWL) on-board the Falcon aircraft shows enhanced systematic and random errors compared with the bias and precision requirements defined for Aeolus. In particular, the systematic errors are determined to be 2.1 m/s (Rayleigh) and 2.3 m/s (Mie) for WindVal III and −4.6 m/s (Rayleigh) and −0.2 m/s (Mie) for AVATARE. The corresponding random errors are determined to be 4.0 m/s (Rayleigh) and 2.2 m/s (Mie) for WindVal III, and 4.4 m/s (Rayleigh) and 2.2 m/s (Mie) for AVATARE. Potential reasons for those errors are analyzed and discussed.


2008 ◽  
Vol 1 (1) ◽  
pp. 249-279
Author(s):  
C. Lerot ◽  
M. Van Roozendael ◽  
J. van Geffen ◽  
J. van Gent ◽  
C. Fayt ◽  
...  

Abstract. Total O3 columns have been retrieved from six years of SCIAMACHY nadir UV radiance measurements using SDOAS, an adaptation of the GDOAS algorithm previously developed at BIRA-IASB for the GOME instrument. GDOAS and SDOAS have been implemented by the German Aerospace Center (DLR) in the version 4 of the GOME Data Processor (GDP) and in version 3 of the SCIAMACHY Ground Processor (SGP), respectively. The processors are being run at the DLR processing centre on behalf of the European Space Agency (ESA). We first focus on the description of the SDOAS algorithm with particular attention to the impact of uncertainties on the reference O3 absorption cross-sections. Second, the resulting SCIAMACHY total ozone data set is globally evaluated through large-scale comparisons with results from GOME and OMI as well as with ground-based correlative measurements. The various total ozone data sets are found to agree within 2% on average. However, a negative trend of 0.2–0.4%/year has been identified in the SCIAMACHY O3 columns; this probably originates from instrumental degradation effects that have not yet been fully characterized.


Sign in / Sign up

Export Citation Format

Share Document