Search results for "021101 geological & geomatics engineering"
showing 10 items of 476 documents
Prediction of surface treatment effects on the tribological performance of tool steels using artificial neural networks
2019
The present paper discussed the development of a reliable and robust artificial neural network (ANN) capable of predicting the tribological performance of three highly alloyed tool steel grades. Experimental results were obtained by performing plane-contact sliding tests under non-lubrication conditions on a pin-on-disk tribometer. The specimens were tested both in untreated state with different hardening levels, and after surface treatment of nitrocarburizing. We concluded that wear maps via ANN modeling were a user-friendly approach for the presentation of wear-related information, since they easily permitted the determination of areas under steady-state wear that were appropriate for use…
Discriminating irrigated and rainfed olive orchards with thermal ASTER imagery and DART 3D simulation
2009
Article in Press
Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two c…
2018
Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System – Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (…
Coastal zone water quality: Calibration of a water-turbidity equation for MODIS data
2013
AbstractA nephelometric turbidity algorithm has been specifically calibrated for coastal waters in Sicily. To this purpose, intensive field campaigns were performed in July, August and September 2008. Measurements were collected in situ in three different gulfs. Statistical analysis suggests that field data should be spatially grouped but temporally separated; hence, new calibration parameters have been proposed.Turbidity retrieved by applying the algorithm using literature coefficients and the ones calibrated in situ are shown and compared. The comparison demonstrated that a specific calibration was necessary for quantitatively monitoring turbidity in Sicilian gulfs.
Traitement de données RGB et Lidar à extrêmement haute résolution: retombées de la compétition de fusion de données 2015 de l'IEEE GRSS - Partie A / …
2016
International audience; In this paper, we discuss the scientific outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high-resolution RGB images and a three-dimensional (3-D) LiDAR point cloud. The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this paper, we discuss the sci…
Sentinel-3/FLEX Biophysical Product Confidence Using Sentinel-2 Land-Cover Spatial Distributions
2021
The estimation of biophysical variables from remote sensing data raises important challenges in terms of the acquisition technology and its limitations. In this way, some vegetation parameters, such as chlorophyll fluorescence, require sensors with a high spectral resolution that constrains the spatial resolution while significantly increasing the subpixel land-cover heterogeneity. Precisely, this spatial variability often makes that rather different canopy structures are aggregated together, which eventually generates important deviations in the corresponding parameter quantification. In the context of the Copernicus program (and other related Earth Explorer missions), this article propose…
Exploring the Validity of the Long-Term Data Record V4 Database for Land Surface Monitoring
2016
A new version of the long-term data record (LTDR)—Version 4—has been released recently by NASA. This database includes daily information for all advanced very high resolution radiometer channels, as well as ancillary data, from July 1981 up to present. This dataset is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the daily estimation of vegetation indices, as well as the estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring, especially as regards long-term trends and their validity. To that end, we estimated normalized difference vegetation index (NDVI), LST, as well …
Evaluation of Disaggregation Methods for Downscaling MODIS Land Surface Temperature to Landsat Spatial Resolution in Barrax Test Site
2016
Thermal infrared (TIR) data are usually acquired at a coarser spatial resolution (CR) than visible and near infrared (VNIR). Several disaggregation methods have been recently developed to enhance the TIR spatial resolution using VNIR data. These approaches are based on the retrieval of a relation between TIR and VNIR data at CR, or training of a neural network, to be applied at the fine resolution afterward. In this work, different disaggregation methods are applied to the combination of two different sensors in the experimental test site of Barrax, Spain. The main objective is to test the feasibility of these techniques when applied to satellites provided with no TIR bands. Landsat and mod…
Trends in phenological parameters and relationship between land surface phenology and climate data in the Hyrcanian forests of Iran
2017
Vegetation activity may be changed in response to climate variability by affecting seasonality and phenological events. Monitoring of land surface phenological changes play a key role in understanding feedback of ecosystem dynamics. This study focuses on the analysis of trends in land surface phenology derived parameters using normalized difference vegetation index time series based on Global Inventory Monitoring and Mapping Studies data in the Hyrcanian forests of Iran covering the period 1981–2012. First, we applied interpolation for data reconstruction in order to remove outliers and cloud contamination in time series. Phenological parameters were retrieved by using the midpoint approach…
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation
2017
Source at https://doi.org/10.1109/JSTARS.2016.2641583. Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one can derive mean and variance predictive estimates, i.e., point-wise predictions and associated confidence intervals. GPR typically uses translation invariant covariances that make the prediction function very flexible and nonlinear. This, however, makes the relative relevance of the input features hardly accessible, unlike in linear prediction models. In this paper, we introduce the sensitivity analysis of the GPR predictive mean and variance functions…