Search results for "Lidar"
showing 10 items of 475 documents
Comment on “Thresholded Quantum LIDAR: Exploiting Photon-Number-Resolving Detection”
2020
International audience; The ratio of the SNR with thresholding and with proportional detection for one photon of mean background noise, for a threshold value N from 1 to 4.
New advances in dial-lidar-based remote sensing of the volcanic CO2 flux
2017
We report here on the results of a proof-of-concept study aimed at remotely sensing the volcanic CO2 flux using a Differential Adsorption lidar (DIAL-lidar). The observations we report on were conducted on June 2014 on Stromboli volcano, where our lidar (LIght Detection And Ranging) was used to scan the volcanic plume from ~ 3 km distance from the summit vents. The obtained results prove that a remotely operating lidar can resolve a volcanic CO2 signal of a few tens of ppm (in excess to background air) over km-long optical paths. We combine these results with independent estimates of plume transport speed (from processing of UV Camera images) to derive volcanic CO2 flux time-series of ≈16-3…
Lidar sounding of volcanic plumes
2013
ABSTRACT Accurate knowledge of gas composition in volcanic plumes has high scientific and societal value. On the one hand, it gives information on the geophysical processes taking place inside volcanos; on the other hand, it provides alert on possible eruptions. For this reasons, it has been suggested to monitor volcanic plumes by lidar. In particular, one of the aims of the FP7 ERC project BRIDGE is the measurement of CO 2 concentration in volcanic gases by differential absorption lidar. This is a very challenging task due to the harsh environment, the narrowness and weakness of the CO 2 absorption lines and the difficulty to procure a suitable laser source. This paper, after a review on r…
Tree Species Classification of Drone Hyperspectral and RGB Imagery with Deep Learning Convolutional Neural Networks
2020
Interest in drone solutions in forestry applications is growing. Using drones, datasets can be captured flexibly and at high spatial and temporal resolutions when needed. In forestry applications, fundamental tasks include the detection of individual trees, tree species classification, biomass estimation, etc. Deep neural networks (DNN) have shown superior results when comparing with conventional machine learning methods such as multi-layer perceptron (MLP) in cases of huge input data. The objective of this research is to investigate 3D convolutional neural networks (3D-CNN) to classify three major tree species in a boreal forest: pine, spruce, and birch. The proposed 3D-CNN models were emp…
A Cloud masking algorithm for the XBAER aerosol retrieval using MERIS data
2017
Abstract To determine aerosol optical thickness, AOT, and other geophysical parameters describing conditions in the atmosphere and at the earth's surface by inversion of remote sensing measurements from space based instrumentation, it is necessary to separate ground scenes into cloud free and cloudy or cloud contaminated. Identifying the presence of cloud in a ground scene and establishing an accurate and adequate cloud mask is a challenging task. In this study, measurements by the European Space Agency (ESA) MEdium Resolution Imaging Spectrometer (MERIS) have been used to develop a cloud identification and cloud mask algorithm for preprocessing prior to application of the new algorithm cal…
PHYSICS-based retrieval of scattering albedo and vegetation optical depth using multi-sensor data integration
2017
Vegetation optical depth and scattering albedo are crucial parameters within the widely used τ-ω model for passive microwave remote sensing of vegetation and soil. A multi-sensor data integration approach using ICESat lidar vegetation heights and SMAP radar as well as radiometer data enables a direct retrieval of the two parameters on a physics-derived basis. The crucial step within the retrieval methodology is the calculus of the vegetation scattering coefficient KS, where one exact and three approximated solutions are provided. It is shown that, when using the assumption of a randomly oriented volume, the backscatter measurements of the radar provide a sufficient first order estimate and …
Predicting year of plantation with hyperspectral and lidar data
2017
This paper introduces a methodology for predicting the year of plantation (YOP) from remote sensing data. The application has important implications in forestry management and inventorying. We exploit hyperspectral and LiDAR data in combination with state-of-the-art machine learning classifiers. In particular, we present a complete processing chain to extract spectral, textural and morphological features from both sensory data. Features are then combined and fed a Gaussian Process Classifier (GPC) trained to predict YOP in a forest area in North Carolina (US). The GPC algorithm provides accurate YOP estimates, reports spatially explicit maps and associated confidence maps, and provides sens…
Estimating Gravimetric Moisture of Vegetation Using an Attenuation-Based Multi-Sensor Approach
2018
Estimating parameters for global climate models via combined active and passive microwave remote sensing data has been a subject of intensive research in recent years. A variety of retrieval algorithms has been proposed for the estimation of soil moisture, vegetation optical depth and other parameters. A novel attenuation-based retrieval approach is proposed here to globally estimate the gravimetric moisture of vegetation (m g ) and retrieve information about the amount of water [kg] per amount of wet vegetation [kg]. The parameter m g is particularly interesting for agro-ecosystems, to assess the status of growing vegetation. The key feature of the proposed approach is that it relies on mu…
Embracing diverse worldviews to share planet Earth
2019
Leading societies toward a more sustainable, equitably shared, and environmentally just future requires elevating and strengthening conversations on the nonmaterial and perhaps unquantifiable values of nonhuman nature to humanity. Debates among conservationists relating to the appropriateness of valuing ecosystems in terms of their human utility have eclipsed the more important and impactful task of expressing conservation concerns in terms that are meaningful to diverse stakeholders. We considered the wide global diversity of perspectives on the biosocial complex-the relationships and interactions between all living species on Earth-and argue that humanity's best chance for effective conse…
La inclusión laboral de las personas con discapacidad desde la administración pública responsable en la Comunidad Valenciana
2020
En la presente coyuntura socioeconómica, la posibilidad de inclusión a través del empleo de las personas con discapacidad es importante no solo por las posibilidades de autonomía económica, sino también por las oportunidades de socialización. Sobre esta base, y considerando que las empresas socialmente responsables asumen la inclusión de estas personas en sus plantillas como una posibilidad de crecimiento y de diferenciación, en el texto se analiza, de manera descriptiva, el papel que las administraciones públicas (AA. PP.) autonómicas, con competencias en la materia, pueden, deben y están haciendo para fomentar la responsabilidad social corporativa (RSC) y la gestión de la inclusión labora…