22 research outputs found

    Temporal Characteristics of Boreal Forest Radar Measurements

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    Radar observations of forests are sensitive to seasonal changes, meteorological variables and variations in soil and tree water content. These phenomena cause temporal variations in radar measurements, limiting the accuracy of tree height and biomass estimates using radar data. The temporal characteristics of radar measurements of forests, especially boreal forests, are not well understood. To fill this knowledge gap, a tower-based radar experiment was established for studying temporal variations in radar measurements of a boreal forest site in southern Sweden. The work in this thesis involves the design and implementation of the experiment and the analysis of data acquired. The instrument allowed radar signatures from the forest to be monitored over timescales ranging from less than a second to years. A purpose-built, 50 m high tower was equipped with 30 antennas for tomographic imaging at microwave frequencies of P-band (420-450 MHz), L-band (1240-1375 MHz) and C-band (5250-5570 MHz) for multiple polarisation combinations. Parallel measurements using a 20-port vector network analyser resulted in significantly shorter measurement times and better tomographic image quality than previous tower-based radars. A new method was developed for suppressing mutual antenna coupling without affecting the range resolution. Algorithms were developed for compensating for phase errors using an array radar and for correcting for pixel-variant impulse responses in tomographic images. Time series results showed large freeze/thaw backscatter variations due to freezing moisture in trees. P-band canopy backscatter variations of up to 10 dB occurred near instantaneously as the air temperature crossed 0⁰C, with ground backscatter responding over longer timescales. During nonfrozen conditions, the canopy backscatter was very stable with time. Evidence of backscatter variations due to tree water content were observed during hot summer periods only. A high vapour pressure deficit and strong winds increased the rate of transpiration fast enough to reduce the tree water content, which was visible as 0.5-2 dB backscatter drops during the day. Ground backscatter for cross-polarised observations increased during strong winds due to bending tree stems. Significant temporal decorrelation was only seen at P-band during freezing, thawing and strong winds. Suitable conditions for repeat-pass L-band interferometry were only seen during the summer. C-band temporal coherence was high over timescales of seconds and occasionally for several hours for night-time observations during the summer. Decorrelation coinciding with high transpiration rates was observed at L- and C-band, suggesting sensitivity to tree water dynamics.The observations from this experiment are important for understanding, modelling and mitigating temporal variations in radar observables in forest parameter estimation algorithms. The results also are also useful in the design of spaceborne synthetic aperture radar missions with interferometric and tomographic capabilities. The results motivate the implementation of single-pass interferometric synthetic aperture radars for forest applications at P-, L- and C-band

    Radar Remote Sensing of Agricultural Canopies: A Review

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    Development and Evaluation of a Multi-Year Fractional Surface Water Data Set Derived from Active/Passive Microwave Remote Sensing Data

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    abstract: The sensitivity of Earth’s wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land cover-supported, atmospherically-corrected dynamic mixture model applied to 20+ years (1992–2013) of combined, daily, passive/active microwave remote sensing data. The resulting product, known as Surface WAter Microwave Product Series (SWAMPS), shows strong microwave sensitivity to sub-grid scale open water and inundated wetlands comprising open plant canopies. SWAMPS’ FW compares favorably (R[superscript 2] = 91%–94%) with higher-resolution, global-scale maps of open water from MODIS and SRTM-MOD44W. Correspondence of SWAMPS with open water and wetland products from satellite SAR in Alaska and the Amazon deteriorates when exposed wetlands or inundated forests captured by the SAR products were added to the open water fraction reflecting SWAMPS’ inability to detect water underneath the soil surface or beneath closed forest canopies. Except for a brief period of drying during the first 4 years of observation, the inundation extent for the global domain excluding the coast was largely stable. Regionally, inundation in North America is advancing while inundation is on the retreat in Tropical Africa and North Eurasia. SWAMPS provides a consistent and long-term global record of daily FW dynamics, with documented accuracies suitable for hydrologic assessment and global change-related investigations.The final version of this article, as published in Remote Sensing, can be viewed online at: http://www.mdpi.com/2072-4292/7/12/1584

    Development and Evaluation of a Multi-Year Fractional Surface Water Data Set Derived from Active/Passive Microwave Remote Sensing Data

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    The sensitivity of Earth’s wetlands to observed shifts in global precipitation and temperature patterns and their ability to produce large quantities of methane gas are key global change questions. We present a microwave satellite-based approach for mapping fractional surface water (FW) globally at 25-km resolution. The approach employs a land cover-supported, atmospherically-corrected dynamic mixture model applied to 20+ years (1992–2013) of combined, daily, passive/active microwave remote sensing data. The resulting product, known as Surface WAter Microwave Product Series (SWAMPS), shows strong microwave sensitivity to sub-grid scale open water and inundated wetlands comprising open plant canopies. SWAMPS’ FW compares favorably (R2 = 91%–94%) with higher-resolution, global-scale maps of open water from MODIS and SRTM-MOD44W. Correspondence of SWAMPS with open water and wetland products from satellite SAR in Alaska and the Amazon deteriorates when exposed wetlands or inundated forests captured by the SAR products were added to the open water fraction reflecting SWAMPS’ inability to detect water underneath the soil surface or beneath closed forest canopies. Except for a brief period of drying during the first 4 years of observation, the inundation extent for the global domain excluding the coast was largely stable. Regionally, inundation in North America is advancing while inundation is on the retreat in Tropical Africa and North Eurasia. SWAMPS provides a consistent and long-term global record of daily FW dynamics, with documented accuracies suitable for hydrologic assessment and global change-related investigations

    Assimilation de données satellitaires pour le suivi des ressources en eau dans la zone Euro-Méditerranée

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    Une estimation plus prĂ©cise de l'Ă©tat des variables des surfaces terrestres est requise afin d'amĂ©liorer notre capacitĂ© Ă  comprendre, suivre et prĂ©voir le cycle hydrologique terrestre dans diverses rĂ©gions du monde. En particulier, les zones mĂ©diterranĂ©ennes sont souvent caractĂ©risĂ©es par un dĂ©ficit en eau du sol affectant la croissance de la vĂ©gĂ©tation. Les derniĂšres simulations du GIEC (Groupe d'Experts Intergouvernemental sur l'Evolution du Climat) indiquent qu'une augmentation de la frĂ©quence des sĂ©cheresses et des vagues de chaleur dans la rĂ©gion Euro-MĂ©diterranĂ©e est probable. Il est donc crucial d'amĂ©liorer les outils et l'utilisation des observations permettant de caractĂ©riser la dynamique des processus des surfaces terrestres de cette rĂ©gion. Les modĂšles des surfaces terrestres ou LSMs (Land Surface Models) ont Ă©tĂ© dĂ©veloppĂ©s dans le but de reprĂ©senter ces processus Ă  diverses Ă©chelles spatiales. Ils sont habituellement forçés par des donnĂ©es horaires de variables atmosphĂ©riques en point de grille, telles que la tempĂ©rature et l'humiditĂ© de l'air, le rayonnement solaire et les prĂ©cipitations. Alors que les LSMs sont des outils efficaces pour suivre de façon continue les conditions de surface, ils prĂ©sentent encore des dĂ©fauts provoquĂ©s par les erreurs dans les donnĂ©es de forçages, dans les valeurs des paramĂštres du modĂšle, par l'absence de reprĂ©sentation de certains processus, et par la mauvaise reprĂ©sentation des processus dans certaines rĂ©gions et certaines saisons. Il est aussi possible de suivre les conditions de surface depuis l'espace et la modĂ©lisation des variables des surfaces terrestres peut ĂȘtre amĂ©liorĂ©e grĂące Ă  l'intĂ©gration dynamique de ces observations dans les LSMs. La tĂ©lĂ©dĂ©tection spatiale micro-ondes Ă  basse frĂ©quence est particuliĂšrement utile dans le contexte du suivi de ces variables Ă  l'Ă©chelle globale ou continentale. Elle a l'avantage de pouvoir fournir des observations par tout-temps, de jour comme de nuit. Plusieurs produits utiles pour le suivi de la vĂ©gĂ©tation et du cycle hydrologique sont dĂ©jĂ  disponibles. Ils sont issus de radars en bande C tels que ASCAT (Advanced Scatterometer) ou Sentinel-1. L'assimilation de ces donnĂ©es dans un LSM permet leur intĂ©gration de façon cohĂ©rente avec la reprĂ©sentation des processus. Les rĂ©sultats obtenus Ă  partir de l'intĂ©gration de donnĂ©es satellitaires fournissent une estimation de l'Ă©tat des variables des surfaces terrestres qui sont gĂ©nĂ©ralement de meilleure qualitĂ© que les simulations sans assimilation de donnĂ©es et que les donnĂ©es satellitaires elles-mĂȘmes. L'objectif principal de ce travail de thĂšse a Ă©tĂ© d'amĂ©liorer la reprĂ©sentation des variables des surfaces terrestres reliĂ©es aux cycles de l'eau et du carbone dans le modĂšle ISBA grĂące Ă  l'assimilation d'observations de rĂ©trodiffusion radar (sigma°) provenant de l'instrument ASCAT. Un opĂ©rateur d'observation capable de reprĂ©senter les sigma° ASCAT Ă  partir de variables simulĂ©es par le modĂšle ISBA a Ă©tĂ© dĂ©veloppĂ©. Une version du WCM (water cloud model) a Ă©tĂ© mise en Ɠuvre avec succĂšs sur la zone Euro-MĂ©diterranĂ©e. Les valeurs simulĂ©es ont Ă©tĂ© comparĂ©es avec les observations satellitaires. Une quantification plus dĂ©taillĂ©e de l'impact de divers facteurs sur le signal a Ă©tĂ© faite sur le sud-ouest de la France. L'Ă©tude de l'impact de la tempĂȘte Klaus sur la forĂȘt des Landes a montrĂ© que le WCM est capable de reprĂ©senter un changement brutal de biomasse de la vĂ©gĂ©tation. Le WCM est peu efficace sur les zones karstiques et sur les surfaces agricoles produisant du blĂ©. Dans ce dernier cas, le problĂšme semble provenir d'un dĂ©calage temporel entre l'Ă©paisseur optique micro-ondes de la vĂ©gĂ©tation et l'indice de surface foliaire de la vĂ©gĂ©tation. Enfin, l'assimilation directe des sigma° ASCAT a Ă©tĂ© Ă©valuĂ©e sur le sud-ouest de la France.More accurate estimates of land surface conditions are important for enhancing our ability to understand, monitor, and predict key variables of the terrestrial water cycle in various parts of the globe. In particular, the Mediterranean area is frequently characterized by a marked impact of the soil water deficit on vegetation growth. The latest IPCC (Intergovernmental Panel on Climate Change) simulations indicate that occurrence of droughts and warm spells in the Euro-Mediterranean region are likely to increase. It is therefore crucial to improve the ways of understanding, observing and simulating the dynamics of the land surface processes in the Euro-Mediterranean region. Land surface models (LSMs) have been developed for the purpose of representing the land surface processes at various spatial scales. They are usually forced by hourly gridded atmospheric variables such as air temperature, air humidity, solar radiation, precipitation, and are used to simulate land surface states and fluxes. While LSMs can provide a continuous monitoring of land surface conditions, they still show discrepancies due to forcing and parameter errors, missing processes and inadequate model physics for particular areas or seasons. It is also possible to observe the land surface conditions from space. The modelling of land surface variables can be improved through the dynamical integration of these observations into LSMs. Remote sensing observations are particularly useful in this context because they are able to address global and continental scales. Low frequency microwave remote sensing has advantages because it can provide regular observations in all-weather conditions and at either daytime or night-time. A number of satellite-derived products relevant to the hydrological and vegetation cycles are already available from C-band radars such as the Advanced Scatterometer (ASCAT) or Sentinel-1. Assimilating these data into LSMs permits their integration in the process representation in a consistent way. The results obtained from assimilating satellites products provide land surface variables estimates that are generally superior to the model estimates or satellite observations alone. The main objective of this thesis was to improve the representation of land surface variables linked to the terrestrial water and carbon cycles in the ISBA LSM through the assimilation of ASCAT backscatter (sigma°) observations. An observation operator capable of representing the ASCAT sigma° from the ISBA simulated variables was developed. A version of the water cloud model (WCM) was successfully implemented over the Euro-Mediterranean area. The simulated values were compared with those observed from space. A more detailed quantification of the influence of various factors on the signal was made over southwestern France. Focusing on the Klaus storm event in the Landes forest, it was shown that the WCM was able to represent abrupt changes in vegetation biomass. It was also found that the WCM had shortcomings over karstic areas and over wheat croplands. It was shown that the latter was related to a discrepancy between the seasonal cycle of microwave vegetation optical depth (VOD) and leaf area index (LAI). Finally, the direct assimilation of ASCAT sigma° observations was assessed over southwestern France

    Comparison of sea-ice freeboard distributions from aircraft data and cryosat-2

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    The only remote sensing technique capable of obtain- ing sea-ice thickness on basin-scale are satellite altime- ter missions, such as the 2010 launched CryoSat-2. It is equipped with a Ku-Band radar altimeter, which mea- sures the height of the ice surface above the sea level. This method requires highly accurate range measure- ments. During the CryoSat Validation Experiment (Cry- oVEx) 2011 in the Lincoln Sea, Cryosat-2 underpasses were accomplished with two aircraft, which carried an airborne laser-scanner, a radar altimeter and an electro- magnetic induction device for direct sea-ice thickness re- trieval. Both aircraft flew in close formation at the same time of a CryoSat-2 overpass. This is a study about the comparison of the sea-ice freeboard and thickness dis- tribution of airborne validation and CryoSat-2 measure- ments within the multi-year sea-ice region of the Lincoln Sea in spring, with respect to the penetration of the Ku- Band signal into the snow

    Microwave Indices from Active and Passive Sensors for Remote Sensing Applications

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    Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices
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