AI4GEO: An automatic 3D geospatial information capability

2020 ◽  
Author(s):  
Simon Baillarin ◽  
Pierre-Marie Brunet ◽  
Pierre Lassalle ◽  
Gwenael Souille ◽  
Laurent Gabet ◽  
...  
Keyword(s):  
Big Data ◽  
Value Chain ◽  
Large Scale ◽  
Value Added ◽  
Current Status ◽  
Geospatial Information ◽  
Automatic Production ◽  
In Situ Data ◽  
Big Data Technologies

<p>The availability of <strong>3D Geospatial information</strong> is a key stake for many expanding sectors such as autonomous vehicles, business intelligence and urban planning.</p><p>The availability of huge volumes of satellite, airborne and in-situ data now makes this production feasible on a large scale. It needs nonetheless a certain level of skilled manual intervention to secure a certain level of quality, which prevents mass production.</p><p>New artificial intelligence and big data technologies <strong>are key in lifting these obstacles. </strong></p><p>The AI4GEO project aims at developing an automatic solution for producing 3D geospatial information and offer new value-added services leveraging innovative methods adapted to 3D imagery.</p><p>The AI4GEO consortium consists of <strong>institutional partners </strong>(CNES, IGN, ONERA)<strong> and industrial groups</strong> (CS-SI, AIRBUS, CLS, GEOSAT, QWANT, QUANTCUBE) covering the whole value chain of Geospatial Information.</p><p>With a 4 years’ timeline, the project is structured around 2 R&D axes which will progress simultaneously and feed each other.</p><p>The first axis consists in <strong>developing a set of technological bricks allowing the automatic production of qualified 3D maps composed of 3D objects and associated semantics</strong>. This <strong>collaborative work</strong> benefits from the latest research from all partners in the field of AI and Big Data technologies as well as from an <strong>unprecedented database</strong> (satellite and airborne data (optics, radars, lidars) combined with cartographic and in-situ data).</p><p>The second axis consists in deriving from these technological bricks <strong>a variety of services for different fields</strong>: 3D semantic mapping of cities, macroeconomic indicators, decision support for water management, autonomous transport, consumer search engine.</p><p>Started in 2019, the first axis of the project has already produced very promising results. A first version of the platform and technological bricks are now available.</p><p>This paper will first introduce AI4GEO initiative: context and overall objectives.</p><p>It will then present the current status of the project and in particular it will focus on the innovative approach to handle big 3D datasets for analytics needs and it will present the first results of 3D semantic segmentations on various test sites and associated perspectives.</p>

scholarly journals Regional CO<sub>2</sub> inversions with LUMIA, the Lund University Modular Inversion Algorithm, v1.0

2019 ◽  
Author(s):  
Guillaume Monteil ◽  
Marko Scholze
Keyword(s):  
Large Scale ◽  
Transport Model ◽  
Inverse Modelling ◽  
Current Status ◽  
Model Errors ◽  
Inversion Algorithm ◽  
New Developments ◽  
In Situ Data ◽  
Modular Inversion

Abstract. Atmospheric inversions are commonly used for estimating large-scale (continental to regional) net sources and sinks of CO2 and other stable atmospheric tracers from their observed concentrations. Recently, there has been an increasing demand from stakeholders for robust estimates of greenhouse gases at country-scale (or higher) resolution, in particular in the framework of the Paris agreement. This increase in resolution is in theory enabled by the growing availability of observations from surface in-situ networks (such as ICOS in Europe) and from remote sensing products (OCO-2, GOSAT-2). The increase in the resolution of inversions is also a necessary step to provide efficient feedback to the process-based (bottom-up) modelling community (vegetation models, fossil fuel emission inventories). This, however, calls for new developments in the inverse modelling systems, mainly in terms of diversification of the inversion approaches, shift from global to regional inversions, and improvement in the computational efficiency, We have developed the Lund University Modular Inversion Algorithm (LUMIA) as a tool to address some of these new developments. LUMIA is meant to be a platform for inverse modelling developments at Lund University. It aims at being a flexible, yet simple and easy to maintain set of tools that modellers can combine to build inverse modelling experiments. It is in particular designed to be transport model agnostic, which should facilitate isolating the transport model errors from those introduced by the inversion setup itself. Here, we briefly describe the motivations for developing LUMIA as well as the underlying development principles, current status and future prospects. We present a first LUMIA inversion setup for a regional CO2 inversions over Europe, based on a new coupling between the Lagrangian FLEXPART (high resolution foreground transport) and the global coarse resolution TM5 transport models, using in-situ data from surface and tall tower observation sites.

scholarly journals Basic Mechanical Parameter Relations of Soft Clay in Pearl River Delta

2014 ◽  
Vol 8 (1) ◽  
pp. 320-325 ◽  
Author(s):  
Zhangming Li ◽  
Na Qi ◽  
Zhibin Masumi ◽  
Weidi Lin
Keyword(s):  
Shear Strength ◽  
Pearl River Delta ◽  
Large Scale ◽  
Soft Clay ◽  
River Delta ◽  
Pearl River ◽  
Cylindrical Cavity Expansion ◽  
In Situ Data ◽  
The Pearl River

Basic parameters relations among CPT parameters, un-drained strength and other mechanical parameters of soft clay are presented based on an elastic-plastic solution for cylindrical cavity expansion for soil investigation in energy engineering. The relation between CPT parameters and shear strength from vane test is also presented based on the result. Thus, the CPT parameters can be determined directly by elastic parameters and shear strength or vane shear parameters and vice versa. That makes it possible to save the high test costs and provide theoretical formulas to avoid some tests which are limited due to the site and/or other condition. Results are compared between the relations and in situ data at a large-scale project in the Pearl River Delta. The results showed consistency between the relation and in situ data.

scholarly journals Freeboard, snow depth and sea-ice roughness in East Antarctica from in situ and multiple satellite data

2011 ◽  
Vol 52 (57) ◽  
pp. 242-248 ◽  
Author(s):  
Thorsten Markus ◽  
Robert Massom ◽  
Anthony Worby ◽  
Victoria Lytle ◽  
Nathan Kurtz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Correlation Coefficient ◽  
Satellite Data ◽  
Snow Depth ◽  
Large Scale ◽  
Mean Difference ◽  
Laser Altimeter ◽  
In Situ Data ◽  
Ice Roughness

AbstractIn October 2003 a campaign on board the Australian icebreaker Aurora Australis had the objective to validate standard Aqua Advanced Microwave Scanning Radiometer (AMSR-E) sea-ice products. Additionally, the satellite laser altimeter on the Ice, Cloud and land Elevation Satellite (ICESat) was in operation. To capture the large-scale information on the sea-ice conditions necessary for satellite validation, the measurement strategy was to obtain large-scale sea-ice statistics using extensive sea-ice measurements in a Lagrangian approach. A drifting buoy array, spanning initially 50 km × 100 km, was surveyed during the campaign. In situ measurements consisted of 12 transects, 50–500 m, with detailed snow and ice measurements as well as random snow depth sampling of floes within the buoy array using helicopters. In order to increase the amount of coincident in situ and satellite data an approach has been developed to extrapolate measurements in time and in space. Assuming no change in snow depth and freeboard occurred during the period of the campaign on the floes surveyed, we use buoy ice-drift information as well as daily estimates of thin-ice fraction and rough-ice vs smooth-ice fractions from AMSR-E and QuikSCAT, respectively, to estimate kilometer-scale snow depth and freeboard for other days. the results show that ICESat freeboard estimates have a mean difference of 1.8 cm when compared with the in situ data and a correlation coefficient of 0.6. Furthermore, incorporating ICESat roughness information into the AMSR-E snow depth algorithm significantly improves snow depth retrievals. Snow depth retrievals using a combination of AMSR-E and ICESat data agree with in situ data with a mean difference of 2.3 cm and a correlation coefficient of 0.84 with a negligible bias.

scholarly journals status of agricultural financing by commercial banks in Zimbabwe

2021 ◽  
Vol 14 (1-2) ◽  
Author(s):  
Blessing Ropafadzo Chigunhah ◽  
Ezekia Svotwa ◽  
Tendai J. Mabvure ◽  
Gerald Munyoro ◽  
Lovemore Chikazhe
Keyword(s):  
Land Tenure ◽  
Value Chain ◽  
Commercial Banks ◽  
Large Scale ◽  
Agricultural Sector ◽  
Capital Expenditure ◽  
Physical Capital ◽  
Current Status ◽  
Small Scale ◽  
Productive Capacity

Agricultural finance is indispensable for enhancing productive capacity in both small-scale and commercial farming. This study sought to establish the current status of agricultural financing by 12 registered and operational commercial banks in Zimbabwe in the year 2019. Questionnaires and interview guides were used to collect data. SPSS and NVivo were used for data analysis. All the commercial banks participated in agricultural financing with an average agricultural loan portfolio of 30%. However, their participation in agricultural lending is yet to reach the pre-land reform maximum of 91.3% attained in 1999. Land tenure and weather risks, as well as lack of collateral among farmers reduced the banks’ appetite for lending to the agricultural sector. The majority of the commercial banks offered value chain finance, invoice finance, overdraft facilities, and term loans to agricultural sector clients that mainly included; suppliers, medium-scale, and large-scale commercial farmers. The study established a mismatch in the demand and supply of loans in the medium to long term tenure range of 1 to more than 3 years. There was low demand for 1-3-year tenure loans according to the commercial banks, and a corresponding deficit in the supply of highly demanded longer-term loans of more than 3 years for capital expenditure (CAPEX). Therefore, government should aim to; stabilize currency; arrest hyperinflation; restore economic stability; address land tenure to ensure the bankability of the 99-year Lease; and create an environment that is conducive for investment in climate and weather resilience infrastructure. Local farmers should also invest in human and physical capital to improve their access to bank credit. JEL Code: Q14

scholarly journals Use of absorption optical indices to assess seasonal variability of dissolved organic matter in amazon floodplain lakes

2019 ◽  
Author(s):  
Maria Paula da Silva ◽  
Lino A. Sander de Carvalho ◽  
Evlyn Novo ◽  
Daniel S. F. Jorge ◽  
Claudio C. F. Barbosa
Keyword(s):  
Remote Sensing ◽  
Organic Matter ◽  
Dissolved Organic Matter ◽  
Seasonal Variability ◽  
Large Scale ◽  
River Bank ◽  
In Situ Data ◽  
Amazon Floodplain ◽  
Significant Difference

Abstract. Given the importance of DOM in the carbon cycling of aquatic ecosystems, information on its seasonal variability is crucial. This study assesses the use of available absorption optical indices based on in situ data to both characterize the seasonal variability of the DOM dynamics in a highly complex environment and their viability of being used for satellite remote sensing on large scale studies. The study area comprises four lakes located at the Mamirauá Sustainable Development Reserve (MSDR). Samples for the determination of coloured dissolved organic matter (CDOM) and remote sensing reflectance (Rrs) were acquired in situ. The Rrs was applied to simulate MSI visible bands and used in the proposed models. Differences between lakes were tested regarding CDOM indices. Significant difference in the average of aCDOM (440), aCDOM spectra and S275–295 were found between lakes located inside the flood forest and those near the river bank. The proposed model showed that aCDOM can be used as proxy of S275–295 during rising water with good validation results, demonstrating the potential of Sentinel/MSI imagery data in large scale studies on the dynamics of DOM.

The MLT distribution and detailed structure of ring current:  MMS observations

2021 ◽  
Author(s):  
Xin Tan ◽  
Malcolm Dunlop ◽  
Xiangcheng Dong ◽  
Yanyan Yang ◽  
Christopher Russell
Keyword(s):  
Current Density ◽  
Large Scale ◽  
Ring Current ◽  
Current System ◽  
Radial Profile ◽  
Three Dimensional ◽  
Current Density Distribution ◽  
Magnetic Storms ◽  
In Situ Data

&lt;p&gt;The ring current is an important part of the large-scale magnetosphere-ionosphere current system; mainly concentrated in the equatorial plane, between 2-7 R&lt;sub&gt;E&lt;/sub&gt;, and strongly ordered between &amp;#177; 30 &amp;#176; latitude. The morphology of ring current directly affects the geomagnetic field at low to middle latitudes. Rapid changes in ring current densities can occur during magnetic storms/sub-storms. Traditionally, the Dst index is used to characterize the intensity of magnetic storms and to reflect the variation of ring current intensity, but this index does not reflect the MLT distribution of ring current. In fact, the ring current has significant variations with MLT, depending on geomagnetic activity, due to the influence of multiple factors; such as, the partial ring current, region 1/region 2 field-aligned currents, the magnetopause current and sub-storm cycle (magnetotail current). The form of the ring current has been inferred from the three-dimensional distribution of ion differential fluxes from neutral atom imaging; however, this technique can not directly obtain the current density distribution (as can be obtained using multi-spacecraft in situ data). Previous in situ estimates of current density have used: Cluster, THEMIS and other spacecraft groups to study the distribution of the ring current for limited ranges of either radial profile, or MLT and MLAT variations. Here, we report on an extension to these studies using FGM data from MMS obtained during the period September 1, 2015 to December 31, 2016, when the MMS orbit and configuration provided good coverage. We employ the curlometer method to calculate the current density, statistically, to analysis the MLT distribution according to different geomagnetic conditions. Our results show the clear asymmetry of the ring current and its different characteristics under different geomagnetic conditions.&lt;/p&gt;

scholarly journals Satellite Remote Sensing Signatures of the Major Baltic Inflows

2019 ◽  
Vol 11 (8) ◽  
pp. 954
Author(s):  
Malgorzata Stramska ◽  
Paulina Aniskiewicz
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Large Scale ◽  
Spatial Information ◽  
The Baltic Sea ◽  
Salty Water ◽  
In Situ Data ◽  
The North ◽  
The Baltic

Variability of sea level in the North and Baltic Seas, enforced by weather patterns, affects the intensity of water exchange between these seas. Transfer of salty water from the North Sea is very important for the hydrography of the Baltic Sea. The volume of inflowing salty water can occasionally increase remarkably. Such incidents, called the Major Baltic Inflows (MBIs), are unpredictable, of relatively short duration, and difficult to observe using in situ data. We have shown that remote sensing altimetry can be used as a complementary source of information about the MBI events. The advantage of using such data is that large-scale spatial information about SLA is available with daily resolution. We have described changes in SLA during several MBI events observed in 1993–2017. The net volume of water transported into the Baltic Sea varied between the events due to differences in atmospheric forcing. Based on SLA data, the largest inflow of water happened during the 2014 MBI. This is in agreement with previously published results, based on in situ data.

scholarly journals Biological control of aflatoxins in Africa: current status and potential challenges in the face of climate change

2016 ◽  
Vol 9 (5) ◽  
pp. 771-789 ◽  
Author(s):  
R. Bandyopadhyay ◽  
A. Ortega-Beltran ◽  
A. Akande ◽  
C. Mutegi ◽  
J. Atehnkeng ◽  
...  
Keyword(s):  
Climate Change ◽  
Biological Control ◽  
Value Chain ◽  
Large Scale ◽  
Aflatoxin Contamination ◽  
Sub Saharan Africa ◽  
Current Status ◽  
Health Food ◽  
Carrier Distribution ◽  
Sub Saharan

Aflatoxin contamination of crops is frequent in warm regions across the globe, including large areas in sub-Saharan Africa. Crop contamination with these dangerous toxins transcends health, food security, and trade sectors. It cuts across the value chain, affecting farmers, traders, markets, and finally consumers. Diverse fungi within Aspergillus section Flavi contaminate crops with aflatoxins. Within these Aspergillus communities, several genotypes are not capable of producing aflatoxins (atoxigenic). Carefully selected atoxigenic genotypes in biological control (biocontrol) formulations efficiently reduce aflatoxin contamination of crops when applied prior to flowering in the field. This safe and environmentally friendly, effective technology was pioneered in the US, where well over a million acres of susceptible crops are treated annually. The technology has been improved for use in sub-Saharan Africa, where efforts are under way to develop biocontrol products, under the trade name Aflasafe, for 11 African nations. The number of participating nations is expected to increase. In parallel, state of the art technology has been developed for large-scale inexpensive manufacture of Aflasafe products under the conditions present in many African nations. Results to date indicate that all Aflasafe products, registered and under experimental use, reduce aflatoxin concentrations in treated crops by >80% in comparison to untreated crops in both field and storage conditions. Benefits of aflatoxin biocontrol technologies are discussed along with potential challenges, including climate change, likely to be faced during the scaling-up of Aflasafe products. Lastly, we respond to several apprehensions expressed in the literature about the use of atoxigenic genotypes in biocontrol formulations. These responses relate to the following apprehensions: sorghum as carrier, distribution costs, aflatoxin-conscious markets, efficacy during drought, post-harvest benefits, risk of allergies and/or aspergillosis, influence of Aflasafe on other mycotoxins and on soil microenvironment, dynamics of Aspergillus genotypes, and recombination between atoxigenic and toxigenic genotypes in natural conditions.

scholarly journals Sherlock: an open-source data platform to store, analyze and integrate Big Data for biology

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 409
Author(s):  
Balázs Bohár ◽  
David Fazekas ◽  
Matthew Madgwick ◽  
Luca Csabai ◽  
Marton Olbei ◽  
...  
Keyword(s):  
Big Data ◽  
Data Management ◽  
Open Source ◽  
Large Scale ◽  
Genomic Sequence ◽  
Large Data ◽  
Structured Data ◽  
Biological Research ◽  
Data Platform ◽  
Big Data Technologies

In the era of Big Data, data collection underpins biological research more so than ever before. In many cases this can be as time-consuming as the analysis itself, requiring downloading multiple different public databases, with different data structures, and in general, spending days before answering any biological questions. To solve this problem, we introduce an open-source, cloud-based big data platform, called Sherlock (https://earlham-sherlock.github.io/). Sherlock provides a gap-filling way for biologists to store, convert, query, share and generate biology data, while ultimately streamlining bioinformatics data management. The Sherlock platform provides a simple interface to leverage big data technologies, such as Docker and PrestoDB. Sherlock is designed to analyse, process, query and extract the information from extremely complex and large data sets. Furthermore, Sherlock is capable of handling different structured data (interaction, localization, or genomic sequence) from several sources and converting them to a common optimized storage format, for example to the Optimized Row Columnar (ORC). This format facilitates Sherlock’s ability to quickly and easily execute distributed analytical queries on extremely large data files as well as share datasets between teams. The Sherlock platform is freely available on Github, and contains specific loader scripts for structured data sources of genomics, interaction and expression databases. With these loader scripts, users are able to easily and quickly create and work with the specific file formats, such as JavaScript Object Notation (JSON) or ORC. For computational biology and large-scale bioinformatics projects, Sherlock provides an open-source platform empowering data management, data analytics, data integration and collaboration through modern big data technologies.

scholarly journals Incidence of rough and irregular atmospheric ice particles from Small Ice Detector 3 measurements

2013 ◽  
Vol 13 (9) ◽  
pp. 24975-25012 ◽  
Author(s):  
Z. Ulanowski ◽  
P. H. Kaye ◽  
E. Hirst ◽  
R. S. Greenaway ◽  
R. J. Cotton ◽  
...  
Keyword(s):  
Light Scattering ◽  
Large Scale ◽  
Extreme Values ◽  
Mixed Phase ◽  
Radiative Properties ◽  
Small Scale ◽  
In Situ Data ◽  
Ice Particles ◽  
Test Particles

Abstract. The knowledge of properties of ice crystals such as size, shape, concavity and roughness is critical in the context of radiative properties of ice and mixed phase clouds. Limitations of current cloud probes to measure these properties can be circumvented by acquiring two-dimensional light scattering patterns instead of particle images. Such patterns were obtained in situ for the first time using the Small Ice Detector 3 (SID-3) probe during several flights in a variety of mid-latitude mixed phase and cirrus clouds. The patterns are analyzed using several measures of pattern texture, selected to reveal the magnitude of particle roughness or complexity. The retrieved roughness is compared to values obtained from a range of well-characterized test particles in the laboratory. It is found that typical in situ roughness corresponds to that found in the rougher subset of the test particles, and sometimes even extends beyond the most extreme values found in the laboratory. In this study we do not differentiate between small-scale, fine surface roughness and large-scale crystal complexity. Instead, we argue that both can have similar manifestations in terms of light scattering properties and also similar causes. Overall, the in situ data is consistent with ice particles with highly irregular or rough surfaces being dominant. Similar magnitudes of roughness were found in growth and sublimation zones of cirrus. The roughness was found to be negatively correlated with the halo ratio, but not with other thermodynamic or microphysical properties found in situ. Slightly higher roughness was observed in cirrus forming in clean oceanic airmasses than in a continental, polluted one. Overall, the roughness and complexity is expected to lead to increased shortwave cloud reflectivity, in comparison with cirrus composed of more regular, smooth ice crystal shapes. These findings put into question suggestions that climate could be modified through aerosol seeding to reduce cirrus cover and optical depth, as the seeding may result in decreased shortwave reflectivity.

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