Search results for "LOGIC"
showing 10 items of 33629 documents
Environmental and biological factors are joint drivers of mercury biomagnification in subarctic lake food webs along a climate and productivity gradi…
2021
Subarctic lakes are getting warmer and more productive due to the joint effects of climate change and intensive land-use practices (e.g. forest clear-cutting and peatland ditching), processes that potentially increase leaching of peat- and soil-stored mercury into lake ecosystems. We sampled biotic communities from primary producers (algae) to top consumers (piscivorous fish), in 19 subarctic lakes situated on a latitudinal (69.0-66.5 degrees N), climatic (+3.2 degrees C temperature and +30% precipitation from north to south) and catchment land-use (pristine to intensive forestry areas) gradient. We first tested how the joint effects of climate and productivity influence mercury biomagnific…
Smap-based retrieval of vegetation opacity and albedo
2020
Over land the vegetation canopy affects the microwave brightness temperature by emission, scattering and attenuation of surface soil emission. The questions addressed in this study are: 1) what is the transparency of the vegetation canopy for different biomes around the Globe at the low-frequency L-band?, 2) what is the seasonal amplitude of vegetation microwave optical depth for different biomes?, 3) what is the effective scattering at this frequency for different vegetation types?, 4) what is the impact of imprecise characterization of vegetation microwave properties on retrieval of soil surface conditions? These questions are addressed based on the recently completed one full annual cycl…
Evaluating roughness effects on C-band AMSR-E observations
2014
International audience; The usefulness of microwave remote sensing to retrieve near-surface soil moisture has already been demonstrated in many studies. However, obtaining high quality estimates of soil moisture is influenced by many effects from soil, vegetation and atmosphere; one of the key parameters is surface roughness. This research focusses on a semi-empirical method to evaluate the roughness effects from space borne observations. Global maps of roughness effects are evaluated at C-band from AMSR-E measurements.
LAI, FAPAR and FCOVER ground-truth map creation from FASat-C satellite imagery and in-situ measurements in Chimbarongo, Chile, for satellite products…
2016
[EN] In remote sensing, validation exercises are essential to ensure the quality of the products originated from satellite Earth observations. To assess the measurement uncertainty derived from satellite products, several ground field data from different ecosystems must be available for use. In the same order of importance, it is necessary to define data sampling and up-scaling methodologies to allow a suitable comparison between the ground data and the pixel size of the product. This paper shows the applied methodology used in the FP7 ImagineS project (Implementing Multi-scale Agricultural Indicators Exploiting Sentinels) to validate 10-days global LAI, FAPAR and vegetation cover products …
Spatio-temporal patterns of thermal anomalies and drought over tropical forests driven by recent extreme climatic anomalies
2018
The recent 2015–2016 El Niño (EN) event was considered as strong as the EN in 1997–1998. Given such magnitude, it was expected to result in extreme warming and moisture anomalies in tropical areas. Here we characterize the spatial patterns of temperature anomalies and drought over tropical forests, including tropical South America (Amazonia), Africa and Asia/Indonesia during the 2015–2016 EN event. These spatial patterns of warming and drought are compared with those observed in previous strong EN events (1982–1983 and 1997–1998) and other moderate to strong EN events (e.g. 2004–2005 and 2009–2010). The link between the spatial patterns of drought and sea surface temperature anomalies in th…
Vegetation vulnerability to drought in Spain
2014
[EN] Frequency of climatic extremes like long duration droughts has increased in Spain over the last century.The use of remote sensing observations for monitoring and detecting drought is justified on the basis that vegetation vigor is closely related to moisture condition. We derive satellite estimates of bio-physical variables such as fractional vegetation cover (FVC) from MODIS/EOS and SEVIRI/MSG time series. The study evaluates the strength of temporal relationships between precipitation and vegetation condition at time-lag and cumulative rainfall intervals. From this analysis, it was observed that the climatic disturbances affected both the growing season and the total amount of vegeta…
A review of environmental impacts of winter road maintenance
2019
Abstract The need for winter road maintenance (WRM) is changing in cold regions due to climate change. How the different modes of WRM will contribute to future overall emissions from infrastructure is therefore of great interest to road owners with a view to a more sustainable, low-carbon future. In the quest for near-zero-emissions transport, all aspects of the transport sector need to be accounted for in the search for possible mitigation of emissions. This study used 35 peer-reviewed articles published between 2000 and 2018 to map available information on the environmental impacts and effect of WRM and reveal any research gaps. The articles were categorized according to their research th…
Joint Gaussian processes for inverse modeling
2017
Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…
Recent Advances in Techniques for Hyperspectral Image Processing
2009
International audience; Imaging spectroscopy, also known as hyperspectral imaging, has been transformed in less than thirty years from being a sparse research tool into a commodity product available to a broad user community. Currently, there is a need for standardized data processing techniques able to take into account the special properties of hyperspec- tral data. In this paper, we provide a seminal view on recent advances in techniques for hyperspectral image processing. Our main focus is on the design of techniques able to deal with the high-dimensional nature of the data, and to integrate the spa- tial and spectral information. Performance of the discussed techniques is evaluated in …
Statistical retrieval of atmospheric profiles with deep convolutional neural networks
2019
Abstract Infrared atmospheric sounders, such as IASI, provide an unprecedented source of information for atmosphere monitoring and weather forecasting. Sensors provide rich spectral information that allows retrieval of temperature and moisture profiles. From a statistical point of view, the challenge is immense: on the one hand, “underdetermination” is common place as regression needs to work on high dimensional input and output spaces; on the other hand, redundancy is present in all dimensions (spatial, spectral and temporal). On top of this, several noise sources are encountered in the data. In this paper, we present for the first time the use of convolutional neural networks for the retr…