Seguridad de las aplicaciones web

Conferencia "Seguridad de las aplicaciones web" impartida en la Escuela Politécnica Nacional (Quito, Ecuador) el 22 de mayo de 2014

An evaluation of SMOS L-band vegetation optical depth (L-VOD) data sets:high sensitivity of L-VOD to above-ground biomass in Africa

The vegetation optical depth (VOD) measured at microwave frequencies is related to the vegetation water content and provides information complementary to visible/infrared vegetation indices. This study is devoted to the characterization of a new VOD data set obtained from SMOS (Soil Moisture and Ocean Salinity) satellite observations at L-band (1.4 GHz). Three different SMOS L-band VOD (LVOD) data sets (SMOS level 2, level 3 and SMOS-IC) were compared with data sets on tree height, visible/infrared indexes (NDVI, EVI), mean annual precipitation and above-ground biomass (AGB) for the African continent. For all relationships, SMOS-IC showed the lowest dispersion and highest correlation. Overall, we found a strong (R > 0.85) correlation with no clear sign of saturation between L-VOD and four AGB data sets. The relationships between L-VOD and the AGB data sets were linear per land cover class but with a changing slope depending on the class type, which makes it a global non-linear relationship. In contrast, the relationship linking L-VOD to tree height (R = 0.87) was close to linear. For vegetation classes other than evergreen broadleaf forest, the annual mean of L-VOD spans a range from 0 to 0.7 and it is linearly correlated with the average annual precipitation. SMOS L-VOD showed higher sensitivity to AGB compared to NDVI and K/X/C-VOD (VOD measured at 19, 10.7 and 6.9 GHz). The results showed that, although the spatial resolution of L-VOD is coarse (similar to 40 km), the high temporal frequency and sensitivity to AGB makes SMOS L-VOD a very promising indicator for large-scale monitoring of the vegetation status, in particular biomass

Inter-comparison of optical and SAR-based forest disturbance warning systems in the Amazon shows the potential of combined SAR-optical monitoring

More than half a decade after the launch of the Sentinel-1A C-band SAR satellite, several near real-time forest disturbances detection systems based on backscattering time series analysis have been developed and made operational. Every system has its own particular approach to change detection. Here, we have compared the performance of the main SAR-based near real-time operational forest disturbance detection systems produced by research agencies (INPE, in Brazil, CESBIO, in France, JAXA, in Japan, and Wageningen University, in the Netherlands), and compared them to the state-of-the-art optical algorithm, University of Maryland’s GLAD-S2. We implemented an innovative validation protocol, specially conceived to encompass all the analysed systems, which measured every system’s accuracy and detection speed in four different areas of the Amazon basin. The results indicated that, when parametrized equally, all the Sentinel-1 SAR methods outperformed the reference optical method in terms of sample-count F1-Score, having comparable results among them. The GLAD-S2 optical method showed superior results in terms of user’s accuracy (UA), issuing no false detections, but had a lower producer accuracy (PA, 84.88%) when compared to the Sentinel-1 SAR-based systems (PA∼90%). Wageningen University’s system, RADD, proved to be relatively faster, especially in heavily clouded regions, where RADD warnings were issued 41 days before optical ones, and the one that better performs on small disturbed patches

Remote sensing of β-diversity: Evidence from plant communities in a semi-natural system

Question: Do remote sensing signals represent β‐diversity? Does β‐diversity agree with community types? Location: UNESCO Man and the Biosphere Reserve, La Palma, Canary Islands. Methods: We recorded perennial, vascular plant species abundances in 69 plots (10 m × 10 m) in three pre‐defined community types along an elevational gradient of 2,400 m: succulent scrubland, Pinus canariensis forest and subalpine scrubland. The remote sensing data consists of structural variables from airborne Light Detection and Ranging (LiDAR) and multispectral variables from a time series of Sentinel‐2 (S2) images. Non‐metric Multidimensional Scaling was used to assess β‐diversity between plots. K‐means unsupervised clustering was applied to remote sensing variables to distinguish three community types. We subsequently quantified the explanatory power of S2 and LiDAR variables representing β‐diversity via the Mantel test, variation partitioning and multivariate analysis of variance. We also investigated the sensitivity of results to grain size of remote sensing data (20, 40, 60 m). Results: The β‐diversity between the succulent and pine community is high, whereas the β‐diversity between the pine and subalpine community is low. In the wet season, up to 85% of β‐diversity is reflected by remote sensing variables. The S2 variables account for more explanatory power than the LiDAR variables. The explanatory power of LiDAR variables increases with grain size, whereas the explanatory power of S2 variables decreases. Conclusion: At the lower ecotone, β‐diversity agrees with the pre‐defined community distinction, while at the upper ecotone the community types cannot be clearly separated by compositional dissimilarity alone. The high β‐diversity between the succulent scrub and pine forest results from positive feedback switches of P. canariensis, being a fire‐adapted, key tree species. In accordance with the spectral variation hypothesis, remote sensing signals can adequately represent β‐diversity for a large extent, in a short time and at low cost. However, in‐situ sampling is necessary to fully understand community composition. Nature conservation requires such interdisciplinary approaches

Sub 1 μm Pitch Achievement for Cu/SiO2 Hybrid Bonding

With hybrid bonding pitch reduction, many challenges are arising especially the ones related to Cu-Cu connections with submicron Cu pads. A methodology is presented here to achieve submicron hybrid bonding pitch starting from single Cu pad thermomechanical behavior study to quantifying Cu-Cu contact resistivity. Depending on the single crystal Cu orientation, several nanometers difference in total deformation is obtained. The Cu dishing limit should be restricted with respect to the lowest deformation. Contact resistivity studies allow to further refine the Cu dishing to get a contribution of contact resistivity below 10−11 Ω.cm2 . By respecting these criteria, a 100 % yield was achieved down to 0.81 µm Cu/SiO 2 hybrid bonding pitch. A successful method for the capacitance increase compensation with pitch reduction is also presented based on the adaptation of the geometric parameters of the hybrid bonding interconnects

Upscaling Forest Biomass from Field to Satellite Measurements: Sources of Errors and Ways to Reduce Them

International audienceForest biomass monitoring is at the core of the research agenda due to the critical importance of forest dynamics in the carbon cycle. However, forest biomass is never directly measured; thus, upscaling it from trees to stand or larger scales (e.g., countries, regions) relies on a series of statistical models that may propagate large errors. Here, we review the main steps usually adopted in forest aboveground biomass mapping, highlighting the major challenges and perspectives. We show that there is room for improvement along the scaling-up chain from field data collection to satellite-based large-scale mapping, which should lead to the adoption of effective practices to better control the propagation of errors. We specifically illustrate how the increasing use of emerging technologies to collect massive amounts of high-quality data may significantly improve the accuracy of forest carbon maps. Furthermore, we discuss how sources of spatially structured biases that directly propagate into remote sensing models need to be better identified and accounted for when extrapolating forest carbon estimates, e.g., through a stratification design. We finally discuss the increasing realism of 3D simulated stands, which, through radiative transfer modelling, may contribute to a better understanding of remote sensing signals and open avenues for the direct calibration of large-scale products, thereby circumventing several current difficulties

Synergetic use of Sentinel-1 and 2 to improve agro-hydrological modeling Preliminary results on Rice paddy detection in South-India

International audienc

Synergetic use of Sentinel-1 and 2 to improve agro-hydrological modeling Preliminary results on Rice paddy detection in South-India

International audienc