Flood detection from synthetic aperture radar (SAR) images should be performed with accurate, stable, automated and time-efficient algorithms; however, few methods meet all these requirements. ...Recently, Giustarini et al. proposed an automated promising methodology, capable of providing satisfactory results in flood detection. The algorithm is based on the assumption that a flood image contains a relatively high number of pixels with low backscatter values, exhibiting a bimodal histogram. For the case of a histogram that is not bimodal, the optimization of the theoretical curve describing the water pixels has to be manually constrained in a user-defined range. To overcome this shortcoming, this letter proposes an alternative procedure for core water body identification. First, by thresholding the difference image, derived by change detection between the flood and reference images, a mask of core water bodies is identified. Then, the mask is applied on the flood image, to extract the water pixels located in the core water bodies and straightforwardly derive the statistical curve describing water pixels. Successively, a sequence of thresholding, region growing and change detection is applied. The experimental results with two pairs of SAR images show that the proposed automated algorithm is stable and time-efficient, and provides accurate results.
Canopy and aerodynamic conductances (g.sub.C and g.sub.A) are some of the key land surface variables determining the land surface response of climate models. Their representation is crucial for ...predicting transpiration (λE.sub.T) and evaporation (λE.sub.E ), which has important implications for global climate change and water resource management. Here, we present a novel approach to directly quantify the controls of the canopy-scale conductances on λE.sub.T and λE.sub.E over multiple plant functions types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a physically-based modeling approach, we identified the canopy-scale feedback-response mechanism between g.sub.C, λE.sub.T, and atmospheric vapor pressure deficit (D.sub.A ), which was originally postulated to occur at the leaf-scale. We show minor biophysical control on λE.sub.T under wet conditions where net radiation (R.sub.N) determines 75 % to 80 % of the variances of λE.sub.T . However, biophysical control on λE.sub.T is amplified during the drought year (2005) and dry conditions, explaining 50 % to 65 % of the variances of λE.sub.T . Despite substantial differences in g.sub.A, nearly similar âcouplingâ was found in forests and pastures due to the increase of g.sub.C induced by soil moisture. This suggests that the relative response of g.sub.C to per unit change of wetness is significantly higher compared to g.sub.A . Our results reveal the occurrence of a larger magnitude of hysteresis between λE.sub.T and g.sub.C during the dry season for the pasture sites, which is attributed to relatively low soil water availability compared to the rainforest. Evaporation was significantly influenced by g.sub.A for all the PFTs and across all wetness conditions. Our analytical framework faithfully captures the responses of g.sub.C and g.sub.A to changing atmospheric radiation, D.sub.A, and surface skin temperature, and, thus appears to be promising for the improvement of existing land surface parameterisations at a range of spatial scales.
Drone Services for Plant Water-Status Mapping Bruscolini, Margherita; Suttor, Ben; Giustarini, Laura ...
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS,
2021-July-11
Conference Proceeding
Achieving an efficient management of agricultural fields is crucial for farmers, considering the challenges posed by water resources sustainability. Monitoring tools allow winemakers to keep their ...vineyards under control and improve the plants' health with targeted actions, such as irrigations scheduling or specific treatments. Knowing the actual number of plants may not be evident, particularly in old plantation, where vines might have been removed or added to the initial planting scheme, or even they have never been counted. However, the knowledge of the number and position of the plants is important to be able to adapt the irrigation network and properly adjust the irrigation schedule. The aim of this project is to build a drone service for precision monitoring of vineyards. Here, an algorithm to detect the position and number of plants in vineyards using drone RGB imagery is presented. First results show a plant detection accuracy of 87%.
With the ongoing proliferation of satellite data, in particular open-access satellite imagery, from both optical and synthetic aperture radar (SAR) sensors, the number of downstream applications is ...rapidly growing. Developers of Earth Observation (EO)-based products and services, as well as expert and non-expert users of such tools, thus need access to a cloud computing infrastructure offering interoperable analysis functionality. Here, we present the versatility of such a cloud-based infrastructure called WASDI. WASDI, a web-advanced space development interface, is an online EO analytics platform where EO experts can develop and deploy applications (apps) and users can use them to processes satellite images on demand to generate value-added content.
Observations of the temporal and spatial variations of water depth in rivers and floodplains are very important in operational hydrology. However, our capacity to monitor water depth at large scale ...is still very limited. As a result, the need to measure water storage changes in all wetlands, lakes, and reservoirs has motivated the radar interferometry-based Surface Water Ocean Topography Mission (SWOT) scheduled for launch in 2020.
A new method for flood hazard mapping that integrates global flood inundation modeling and microwave remote sensing is presented. It combines the time and space continuity of a global inundation ...model with the limited revisit time but high spatial resolution of satellite observations. The availability of model simulations over a long time period allows a robust estimate of non-exceedance probabilities that can be attributed to the corresponding satellite observations. The resulting flood hazard map will have a spatial resolution equal to that of the used satellite images, generally higher than that of the global inundation model. This can theoretically be done for any point in the world, allowing the estimation of flood hazard at a global scale, provided that a sufficient number of remote sensing images are available. The method is tested on the Severn River (UK), with a high number of flood events observed by ENVISAT ASAR. The global ECMWF flood inundation model is considered for this study.
Canopy and aerodynamic conductances (g(C) and g(A)) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their ...representation is crucial for predicting transpiration (lambda E-T) and evaporation (lambda E-E) flux components of the terrestrial latent heat flux (lambda E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (T-R) into an integrated framework of the Penman-Monteith and Shuttleworth-Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on lambda E-T and lambda E-E over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a T-R-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between g(C), lambda E-T, and atmospheric vapor pressure deficit (D-A), without using any leaf-scale empirical parameterizations for the modeling. The T-R-based model shows minor biophysical control on lambda E-T during the wet (rainy) seasons where lambda E-T becomes predominantly radiation driven and net radiation (RN) determines 75 to 80% of the variances of lambda E-T. However, biophysical control on lambda E-T is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65% of the variances of lambda E-T, and indicates lambda E-T to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in g(A) between forests and pastures, very similar canopy-atmosphere "coupling" was found in these two biomes due to soil moistureinduced decrease in g(C) in the pasture. This revealed the pragmatic aspect of the T-R-driven model behavior that exhibits a high sensitivity of g(C) to per unit change in wetness as opposed to g(A) that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between lambda E-T and g(C) during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by g(A) for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of g(C) and g(A) to changes in atmospheric radiation, D-A, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land-surface-atmosphere exchange parameterizations across a range of spatial scales.
Triple-negative breast cancer (TNBC) is a very aggressive and heterogeneous group of tumors. In order to develop effective therapeutic strategies, it is therefore essential to identify the ...subtype-specific molecular mechanisms underlying disease progression and resistance to chemotherapy. TNBC cells are highly dependent on exogenous cystine, provided by overexpression of the cystine/glutamate antiporter SLC7A11/xCT, to fuel glutathione synthesis and promote an oxidative stress response consistent with their high metabolic demands. Here we show that TNBC cells of the mesenchymal stem-like subtype (MSL) utilize forced cystine uptake to induce activation of the transcription factor NRF2 and promote a glutathione-independent mechanism to defend against oxidative stress. Mechanistically, we demonstrate that NRF2 activation is mediated by direct cysteinylation of the inhibitor KEAP1. Furthermore, we show that cystine-mediated NRF2 activation induces the expression of important genes involved in oxidative stress response, but also in epithelial-to-mesenchymal transition and stem-like phenotype. Remarkably, in survival analysis, four upregulated genes (OSGIN1, RGS17, SRXN1, AKR1B10) are negative prognostic markers for TNBC. Finally, expression of exogenous OSGIN1, similarly to expression of exogenous NRF2, can prevent cystine depletion-dependent death of MSL TNBC cells. The results suggest that the cystine/NRF2/OSGIN1 axis is a potential target for effective treatment of MSL TNBCs.
