scholarly journals Analysis of Distributions of Macrobenthic in the Intertidal Zone of Suncheon Bay by using Satellite Image and In-situ Data

2016 ◽  
Vol 11 (3) ◽  
pp. 339-344
Author(s):  
Heung-Min Kim ◽  
Jae-Moon Park ◽  
Hong-Joo Yoon
Keyword(s):  
Intertidal Zone ◽  
Satellite Image ◽  
In Situ Data

scholarly journals Harmonized in situ JECAM datasets for agricultural land use mapping and monitoring in tropical countries

2021 ◽  
Author(s):  
Audrey Jolivot ◽  
Valentine Lebourgeois ◽  
Mael Ameline ◽  
Valérie Andriamanga ◽  
Beatriz Bellón ◽  
...  
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Satellite Image ◽  
Farming Systems ◽  
Agricultural Land Use ◽  
In Situ Data ◽  
Agricultural Census ◽  
Crop Types ◽  
The Tropics

Abstract. The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural census are often poorly georeferenced, and crop types are difficult to photo-interpret directly from satellite imagery. In this paper, we present nine datasets collected in a standardized manner between 2013 and 2020 in seven tropical and subtropical countries within the framework of the international JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative. These quality-controlled datasets are distinguished by in situ data collected at field scale by local experts, with precise geographic coordinates, and following a common protocol. Altogether, the datasets completed 27 074 polygons (20 257 crop and 6 817 non-crop) documented by detailed keywords. These datasets can be used to produce and validate agricultural land use maps in the tropics, but also, to assess the performances and the robustness of classification methods of cropland and crop types/practices in a large range of tropical farming systems. The dataset is available at https://doi.org/10.18167/DVN1/P7OLAP.

scholarly journals From zero to infinity: minimum to maximum diversity of the planet by spatio-parametric Rao’s quadratic entropy

2021 ◽  
Author(s):  
Duccio Rocchini ◽  
Matteo Marcantonio ◽  
Daniele Da Re ◽  
Giovanni Bacaro ◽  
Enrico Feoli ◽  
...  
Keyword(s):  
Satellite Image ◽  
Diversity Indices ◽  
Spatial Uncertainty ◽  
Species Determination ◽  
Quadratic Entropy ◽  
In Situ Data ◽  
Rao’S Quadratic Entropy ◽  
Work Done ◽  
First Time

AbstractAimThe majority of work done to gather information on Earth diversity has been carried out by in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannon’s Information Theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Rao’s quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, namely they can account only for a part of the whole diversity continuum. The aim of this paper is thus to generalize the Rao’s quadratic entropy by proposing its parameterization for the first time.InnovationThe parametric Rao’s quadratic entropy, coded in R, i) allows to represent the whole continuum of potential diversity indices in one formula, and ii) starting from the Rao’s quadratic entropy, allows to explicitly make use of distances among pixel reflectance values, together with relative abundances.Main conclusionsThe proposed unifying measure is an integration between abundance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale.

scholarly journals Harmonized in situ datasets for agricultural land use mapping and monitoring in tropical countries

2021 ◽  
Vol 13 (12) ◽  
pp. 5951-5967
Author(s):  
Audrey Jolivot ◽  
Valentine Lebourgeois ◽  
Louise Leroux ◽  
Mael Ameline ◽  
Valérie Andriamanga ◽  
...  
Keyword(s):  
Land Use ◽  
Agricultural Land ◽  
Satellite Image ◽  
Farming Systems ◽  
Agricultural Land Use ◽  
In Situ Data ◽  
Assessment And Monitoring ◽  
Crop Types ◽  
The Tropics

Abstract. The availability of crop type reference datasets for satellite image classification is very limited for complex agricultural systems as observed in developing and emerging countries. Indeed, agricultural land use is very dynamic, agricultural censuses are often poorly georeferenced and crop types are difficult to interpret directly from satellite imagery. In this paper, we present a database made of 24 datasets collected in a standardized manner over nine sites within the framework of the international JECAM (Joint Experiment for Crop Assessment and Monitoring) initiative; the sites were spread over seven countries of the tropical belt, and the number of data collection years depended on the site (from 1 to 7 years between 2013 and 2020). These quality-controlled datasets are distinguished by in situ data collected at the field scale by local experts, with precise geographic coordinates, and following a common protocol. Altogether, the datasets completed 27 074 polygons (20 257 crops and 6817 noncrops, ranging from 748 plots in 2013 (one site visited) to 5515 in 2015 (six sites visited)) documented by detailed keywords. These datasets can be used to produce and validate agricultural land use maps in the tropics. They can also be used to assess the performances and robustness of classification methods of cropland and crop types/practices in a large range of tropical farming systems. The dataset is available at https://doi.org/10.18167/DVN1/P7OLAP (Jolivot et al., 2021).

scholarly journals Validation of a method for determining the depth of glacial melt ponds using satellite imagery

2011 ◽  
Vol 52 (59) ◽  
pp. 15-22 ◽  
Author(s):  
William A. Sneed ◽  
Gordon S. Hamilton
Keyword(s):  
Satellite Imagery ◽  
Satellite Image ◽  
Minor Effect ◽  
Melt Pond ◽  
In Situ Data ◽  
Melt Ponds ◽  
Simplifying Assumptions ◽  
A Minor ◽  
Water Depths

AbstractIn situ measurements of water depth and optical properties of a melt pond in East Greenland were collected to verify a previously developed algorithm for determining supraglacial water depths using satellite imagery. That algorithm made five simplifying assumptions which we have tested using the in situ data and laboratory analysis of water samples. We conclude that three assumptions were justified, one was not and the remaining one (substrate homogeneity) requires further study, but probably has a minor effect on the retrieved water depths and volumes. Measured water depths of 0.2–3.0m agree well with those derived from a satellite image using the algorithm. Numerically modeled depths also agree well with those from the satellite image. This new analysis demonstrates the validity of our algorithm as a means for determining meltwater volumes in supraglacial ponds and lakes.

STORM ICE OIL WIND WAVE WATCH SYSTEM (SIOWS): WEB GIS APPLICATION FOR MONITORING THE ARCTIC

2017 ◽  
Author(s):  
Alexander Myasoedov ◽  
Alexander Myasoedov ◽  
Sergey Azarov ◽  
Sergey Azarov ◽  
Ekaterina Balashova ◽  
...  
Keyword(s):  
Satellite Data ◽  
Wind Wave ◽  
Arctic Region ◽  
Web Gis ◽  
The Arctic ◽  
Flexible Tool ◽  
In Situ Data ◽  
Current State ◽  
Watch System

Working with satellite data, has long been an issue for users which has often prevented from a wider use of these data because of Volume, Access, Format and Data Combination. The purpose of the Storm Ice Oil Wind Wave Watch System (SIOWS) developed at Satellite Oceanography Laboratory (SOLab) is to solve the main issues encountered with satellite data and to provide users with a fast and flexible tool to select and extract data within massive archives that match exactly its needs or interest improving the efficiency of the monitoring system of geophysical conditions in the Arctic. SIOWS - is a Web GIS, designed to display various satellite, model and in situ data, it uses developed at SOLab storing, processing and visualization technologies for operational and archived data. It allows synergistic analysis of both historical data and monitoring of the current state and dynamics of the "ocean-atmosphere-cryosphere" system in the Arctic region, as well as Arctic system forecasting based on thermodynamic models with satellite data assimilation.

scholarly journals Critical Dynamics of Defects and Mechanisms of Damage-Failure Transitions in Fatigue

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2554
Author(s):  
Oleg Naimark ◽  
Vladimir Oborin ◽  
Mikhail Bannikov ◽  
Dmitry Ledon
Keyword(s):  
Fatigue Damage ◽  
Kinetic Equations ◽  
Experimental Methodology ◽  
Preliminary Deformation ◽  
Scaling Properties ◽  
In Situ Data ◽  
Number Of Cycles ◽  
Fish Eye ◽  
Very High

An experimental methodology was developed for estimating a very high cycle fatigue (VHCF) life of the aluminum alloy AMG-6 subjected to preliminary deformation. The analysis of fatigue damage staging is based on the measurement of elastic modulus decrement according to “in situ” data of nonlinear dynamics of free-end specimen vibrations at the VHCF test. The correlation of fatigue damage staging and fracture surface morphology was studied to establish the scaling properties and kinetic equations for damage localization, “fish-eye” nucleation, and transition to the Paris crack kinetics. These equations, based on empirical parameters related to the structure of the material, allows us to estimate the number of cycles for the nucleation and advance of fatigue crack.

scholarly journals Measuring and inferring the ice thickness distribution of four glaciers in the Tien Shan, Kyrgyzstan

2020 ◽  
pp. 1-18
Author(s):  
Lander Van Tricht ◽  
Philippe Huybrechts ◽  
Jonas Van Breedam ◽  
Johannes J. Fürst ◽  
Oleg Rybak ◽  
...  
Keyword(s):  
Cross Validation ◽  
Thickness Distribution ◽  
Tien Shan ◽  
Ice Thickness ◽  
Ice Volume ◽  
In Situ Data ◽  
Radio Echo Sounding ◽  
Thickness Measurements ◽  
Tien Shan Mountains

Abstract Glaciers in the Tien Shan mountains contribute considerably to the fresh water used for irrigation, households and energy supply in the dry lowland areas of Kyrgyzstan and its neighbouring countries. To date, reconstructions of the current ice volume and ice thickness distribution remain scarce, and accurate data are largely lacking at the local scale. Here, we present a detailed ice thickness distribution of Ashu-Tor, Bordu, Golubin and Kara-Batkak glaciers derived from radio-echo sounding measurements and modelling. All the ice thickness measurements are used to calibrate three individual models to estimate the ice thickness in inaccessible areas. A cross-validation between modelled and measured ice thickness for a subset of the data is performed to attribute a weight to every model and to assemble a final composite ice thickness distribution for every glacier. Results reveal the thickest ice on Ashu-Tor glacier with values up to 201 ± 12 m. The ice thickness measurements and distributions are also compared with estimates composed without the use of in situ data. These estimates approach the total ice volume well, but local ice thicknesses vary substantially.

scholarly journals Evaluating model parameterizations of submicron aerosol scattering and absorption with in situ data from ARCTAS 2008

2016 ◽  
Vol 16 (14) ◽  
pp. 9435-9455 ◽  
Author(s):  
Matthew J. Alvarado ◽  
Chantelle R. Lonsdale ◽  
Helen L. Macintyre ◽  
Huisheng Bian ◽  
Mian Chin ◽  
...  
Keyword(s):  
Optical Properties ◽  
Size Distribution ◽  
Aerosol Size Distribution ◽  
Visible Radiation ◽  
Submicron Aerosol ◽  
In Situ Data ◽  
Aerosol Absorption ◽  
Aerosol Scattering ◽  
The Impact

Abstract. Accurate modeling of the scattering and absorption of ultraviolet and visible radiation by aerosols is essential for accurate simulations of atmospheric chemistry and climate. Closure studies using in situ measurements of aerosol scattering and absorption can be used to evaluate and improve models of aerosol optical properties without interference from model errors in aerosol emissions, transport, chemistry, or deposition rates. Here we evaluate the ability of four externally mixed, fixed size distribution parameterizations used in global models to simulate submicron aerosol scattering and absorption at three wavelengths using in situ data gathered during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) campaign. The four models are the NASA Global Modeling Initiative (GMI) Combo model, GEOS-Chem v9-02, the baseline configuration of a version of GEOS-Chem with online radiative transfer calculations (called GC-RT), and the Optical Properties of Aerosol and Clouds (OPAC v3.1) package. We also use the ARCTAS data to perform the first evaluation of the ability of the Aerosol Simulation Program (ASP v2.1) to simulate submicron aerosol scattering and absorption when in situ data on the aerosol size distribution are used, and examine the impact of different mixing rules for black carbon (BC) on the results. We find that the GMI model tends to overestimate submicron scattering and absorption at shorter wavelengths by 10–23 %, and that GMI has smaller absolute mean biases for submicron absorption than OPAC v3.1, GEOS-Chem v9-02, or GC-RT. However, the changes to the density and refractive index of BC in GC-RT improve the simulation of submicron aerosol absorption at all wavelengths relative to GEOS-Chem v9-02. Adding a variable size distribution, as in ASP v2.1, improves model performance for scattering but not for absorption, likely due to the assumption in ASP v2.1 that BC is present at a constant mass fraction throughout the aerosol size distribution. Using a core-shell mixing rule in ASP overestimates aerosol absorption, especially for the fresh biomass burning aerosol measured in ARCTAS-B, suggesting the need for modeling the time-varying mixing states of aerosols in future versions of ASP.

scholarly journals Flux rope axis geometry of magnetic clouds deduced from in situ data

2013 ◽  
Vol 8 (S300) ◽  
pp. 265-268
Author(s):  
Miho Janvier ◽  
Pascal Démoulin ◽  
Sergio Dasso
Keyword(s):  
Interplanetary Medium ◽  
Magnetic Cloud ◽  
Flux Rope ◽  
Magnetic Clouds ◽  
Direct Integration ◽  
Axis Orientation ◽  
In Situ Data ◽  
Geometrical Features ◽  
Wide Range

AbstractMagnetic clouds (MCs) consist of flux ropes that are ejected from the low solar corona during eruptive flares. Following their ejection, they propagate in the interplanetary medium where they can be detected by in situ instruments and heliospheric imagers onboard spacecraft. Although in situ measurements give a wide range of data, these only depict the nature of the MC along the unidirectional trajectory crossing of a spacecraft. As such, direct 3D measurements of MC characteristics are impossible. From a statistical analysis of a wide range of MCs detected at 1 AU by the Wind spacecraft, we propose different methods to deduce the most probable magnetic cloud axis shape. These methods include the comparison of synthetic distributions with observed distributions of the axis orientation, as well as the direct integration of observed probability distribution to deduce the global MC axis shape. The overall shape given by those two methods is then compared with 2D heliospheric images of a propagating MC and we find similar geometrical features.

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