BUILDING EARTH OBSERVATION DATA CUBES ON AWS Ferreira, K. R.; Queiroz, G. R.; Marujo, R. F. B. ...
International archives of the photogrammetry, remote sensing and spatial information sciences.,
05/2022, Letnik:
XLIII-B3-2022
Journal Article, Conference Proceeding
Recenzirano
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Image time series analysis and machine learning methods have been widely used in recent years to extract information from big data of remote sensing images. To support image time series analysis, ...remote sensing images have been modeled as Earth observation (EO) data cubes. EO data cubes can be defined as a set of time series associated to spatially aligned pixels ready for analysis. This paper describes an application for building EO data cubes on the Amazon Web Service (AWS) cloud computing environment. The Data Cube Builder on AWS application is based on a serverless approach to produce EO data cubes from remote sensing images stored in AWS buckets. In this work, we present the architecture of this application and its use to produce EO data cubes for Brazil from big data of remote sensing images.
A new concept for the direct measurement of muons in air showers is presented. The concept is based on resistive plate chambers (RPCs), which can directly measure muons with very good space and time ...resolution. The muon detector is shielded by placing it under another detector able to absorb and measure the electromagnetic component of the showers such as a water-Cherenkov detector, commonly used in air shower arrays. The combination of the two detectors in a single, compact detector unit provides a unique measurement that opens rich possibilities in the study of air showers.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Monitoring changes on Earth’s surface is a difficult task commonly performed using multi-spectral remote sensing images. The absence of surface information in optical images due to the presence of ...cloud, low temporal resolution and sensors defects interfere in analyses. In this context, we present an approach for filling gaps in imagery mainly caused by small clouds and sensor defects. Our method consists of an adaptation from an existing method that uses spatial context of close-in-time images through the use of the most frequent value obtained using multiscale segmentation. Our method uses the pixel proportion contained in each segment to fill missing values. We applied the gap-filling methodology on three dates containing simulated images from Landsat7 using Landsat8 images. We validated the method by introducing and filling artificial gaps, and comparing the original data with model predictions. The developed approach surpassed Maxwell et al. (2007) gap-filling method for all bands, presenting a minimal R2 of 0.78. Our method proved to enhance the Maxwell et al. (2007) gap-filling method, while also asymptotically maintaining the algorithm cost. It also allowed image texture to be conserved on reconstructed images. This characteristic enables narrow features, e.g., as roads, riparian areas, and small streams capable of being detected on the filled images. Based on that, further object-based approaches can be used on images filled using this methodology, demonstrating its capacity to estimate Earth’s surface data.
Accurate and consistent Surface Reflectance estimation from optical remote sensor observations is directly dependant on the used atmospheric correction processor and the differences caused by it may ...have implications on further processes, e.g. classification. Brazil is a continental scale country with different biomes. Recently, new initiatives, as the Brazil Data Cube Project, are emerging and using free and open data policy data, more specifically medium spatial resolution sensor images, to create image data cubes and classify the Brazilian territory crops. For this reason, the purpose of this study is to verify, on Landsat-8 and Sentinel-2 images for the Brazilian territory, the suitability of the atmospheric correction processors maintained by their image providers, LaSRC from USGS and Sen2cor from ESA, respectively. To achieve this, we tested the surface reflectance products from Landsat-8 processed through LaSRC and Sentinel-2 processed through LaSRC and Sen2cor comparing to a reference dataset computed by ARCSI and AERONET. The obtained results point that Landsat-8/OLI images atmospherically corrected using the LaSRC corrector are consistent to the surface reflectance reference and other atmospheric correction processors studies, while for Sentinel-2/MSI images, Sen2cor performed best. Although corrections over Sentinel-2/MSI data weren’t as consistent as in Landsat-8/OLI corrections, in comparison to the surface reflectance references, most of the spectral bands achieved acceptable APU results.
The Brazilian National Institute for Space Research (INPE) produces official information about deforestation as well as land use and cover in the country, based on remote sensing images. The current ...open data policy adopted by many space agencies and governments worldwide provided access to petabytes of remote sensing images. To properly deal with this vast amount of images, novel technologies have been proposed and developed based on cloud computing and big data systems. This paper describes the INPE’s initiatives in using remote sensing images and cloud services of the Amazon Web Services (AWS) infrastructure to improve land use and cover monitoring.
Recently, remote sensing image time series analysis has being widely used to investigate the dynamics of environments over time. Many studies have combined image time series analysis with machine ...learning methods to improve land use and cover change mapping. In order to support image time series analysis, analysis-ready data (ARD) image collections have been modeled and organized as multidimensional data cubes. Data cubes can be defined as sets of time series associated with spatially aligned pixels. Based on lessons learned in the research project e-Sensing, related to national demands for land use and cover monitoring and related to state-of-the-art studies on relevant topics, we define the requirements to build Earth observation data cubes for Brazil. This paper presents the methodology to generate ARD and multidimensional data cubes from remote sensing images for Brazil. We describe the computational infrastructure that we are developing in the Brazil Data Cube project, composed of software applications and Web services to create, integrate, discover, access, and process the data sets. We also present how we are producing land use and cover maps from data cubes using image time series analysis and machine learning techniques.
In their comments about our paper, the authors remark on two issues regarding our results relating to the MACCS-ATCOR Joint Algorithm (MAJA). The first relates to the sub-optimal performance of this ...algorithm under the conditions of our tests, while the second corresponds to an error in our interpretation of MAJA’s bit mask. To answer the first issue, we acknowledge MAJA’s capacity to improve its performance as the number of images increases with time. However, in our paper, we used the images we had available at the time we wrote our paper. Regarding the second issue, we misread the MAJA’s bit mask and mistakenly labelled shadows as clouds. We regret our error and here we present the updated tables and images. We corrected our estimation and, consequently, there is an increment in MAJA’s accuracy in the detection of clouds and cloud shadows. However, these increments are not enough to change the conclusion of our original paper.
The LHCb Detector at the LHC Drancourt, C; Rambure, T; Bohner, G ...
Journal of instrumentation,
2008, Letnik:
3, Številka:
8
Journal Article
Recenzirano
Odprti dostop
The LHCb experiment is dedicated to precision measurements of CP violation and rare decays of B hadrons at the Large Hadron Collider (LHC) at CERN (Geneva). The initial configuration and expected ...performance of the detector and associated systems, as established by test beam measurements and simulation studies, is described.
CMS iRPC FEB development and validation Gouzevitch, M.; El Sawy, M.; Alves, G.A. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
07/2024, Letnik:
1064
Journal Article
Recenzirano
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In view of the High Luminosity upgrade of the CERN LHC, the forward CMS Muon spectrometer will be extended with two new stations of improved Resistive Plate Chambers (iRPC) covering the ...pseudorapidity range from 1.8 to 2.4. Compared to the present RPC system, the gap thickness is reduced to lower the avalanche charge, and an innovative 2D strip readout geometry is proposed. These improvements will allow iRPC detector to cope with higher background rates. A new Front-End-Board (FEB) is designed to readout iRPC signals with a threshold as low as 30fC and an integrated Time Digital Converter with a resolution of 30ps. In addition, the communication bandwidth is significantly increased by using optical fibers. The history, final design, certification, and calibration of this FEB are presented.
Improved resistive plate chambers for HL-LHC upgrade of CMS Samalan, A.; Thiel, M.; Asilar, E. ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
03/2024, Letnik:
1060, Številka:
C
Journal Article
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