Search results for "ASCAT"

Assessment and inter-comparison of recently developed/reprocessed microwave satellite soil moisture products using ISMN ground-based measurements

2019

Soil moisture (SM) is a key state variable in understanding the climate system through its control on the land surface energy, water budget partitioning, and the carbon cycle. Monitoring SM at regional scale has become possible thanks to microwave remote sensing. In the past two decades, several satellites were launched carrying on board either radiometer (passive) or radar (active) or both sensors in different frequency bands with various spatial and temporal resolutions. Soil moisture algorithms are in rapid development and their improvements/revisions are ongoing. The latest SM retrieval products and versions of products that have been recently released are not yet, to our knowledge, com…

First Retrievals of ASCAT-IB VOD (Vegetation Optical Depth) at Global Scale

2021

Global and long-term vegetation optical depth (VOD) dataset are very useful to monitor the dynamics of the vegetation features, climate and environmental changes. In this study, the radar-based global ASCAT (Advanced SCATterometer) IB (INRAE-BORDEAUX) VOD was retrieved using a model which was recently calibrated over Africa. In order to assess the performance of IB VOD, the Saatchi biomass and three other VOD datasets (ASCAT V16, AMSR2 LPRM V5 and VODCA LPRM V6) derived from C-band observations were used in the comparison. The preliminary results show that IB VOD has a promising ability to predict biomass $(\mathrm{R}=0.74,\ \text{RMSE} =44.82\ \text{Mg}\ \text{ha}^{-1})$ , which is better …

Analisi di cicli frigoriferi a cascata e confronto con cicli frigoriferi a doppio stadio

2008

Vēja plūsmas Baltijas jūras Kurzemes piekrastē

2018

Meteoroloģisko novērojumu staciju dati Kurzemes Baltijas jūras piekrastē rāda, ka gada siltajā periodā (marts – oktobris) diennakts siltajā laikā vēja ātruma sadalījumam ir maksimumi, kas atbilst krastam paralēliem vējiem gan no ziemeļu, gan dienvidu virziena. 2013. gada 3. un 6. maijs tika izvēlēti tālākai analīzei. Tika veikta matemātiskā modelēšana izmantojot WRF (Weather Research and Forecast) modeli, kā arī novērojumu analīze, iekļaujot ASCAT attālinātās izpētes vēja ātruma un virziena mērījumus no satelīta. Rezultāti rāda, ka ziemeļu virziena plūsmas var izskaidrot ar piekrastes zemo līmeņu plūsmu (coastal low-level jet), bet dienvidu virziena plūsmas var skaidrot ar krastam paralēlaj…

Integrating Domain Knowledge in Data-Driven Earth Observation With Process Convolutions

2022

The modelling of Earth observation data is a challenging problem, typically approached by either purely mechanistic or purely data-driven methods. Mechanistic models encode the domain knowledge and physical rules governing the system. Such models, however, need the correct specification of all interactions between variables in the problem and the appropriate parameterization is a challenge in itself. On the other hand, machine learning approaches are flexible data-driven tools, able to approximate arbitrarily complex functions, but lack interpretability and struggle when data is scarce or in extrapolation regimes. In this paper, we argue that hybrid learning schemes that combine both approa…

Multi-technical approach for the characterization of polychrome decorative surfaces at Spanish Mission Churches in Nueva Vizcaya (Chihuahua, Mexico)

2020

An interdisciplinary and multi-institutional group of science and art conservation specialists has provided new insight into the painting materials used in the polychrome walls and wooden ceilings in four seventeenth century Spanish colonial churches of Nueva Vizcaya (Chihuahua, Mexico). A multi-analytical study of the decorative surfaces was performed in situ using spectroscopic approaches (XRF, FORS), False Colour Infrared Reflectography – IRFC, as well as micro sampling for ATR-FTIR, LM and GC/MS laboratory analyses. A survey of natural resources were also studied by ATR-FTIR and LM to elucidate the natural occurrence of a select number of materials found in the surrounding areas of the …

Autocorrelation Metrics to Estimate Soil Moisture Persistence From Satellite Time Series: Application to Semiarid Regions

2021

Satellite-derived soil moisture (SM) products have become an important information source for the study of land surface processes in hydrology and land monitoring. Characterizing and estimating soil memory and persistence from satellite observations is of paramount relevance, and has deep implications in ecology, water management, and climate modeling. In this work, we address the problem of SM persistence estimation from microwave sensors using several autocorrelation metrics that, unlike traditional approaches, build on accurate estimates of the autocorrelation function from nonuniformly sampled time series. We show how the choice of the autocorrelation estimator can have a dramatic impac…