scholarly journals New Methods for Linking Science Objectives to Remote Sensing Observations: A Concept Study Using Single‐ and Dual‐Pair Satellite Gravimetry Architectures

2020 ◽  
Vol 7 (3) ◽  
Author(s):  
M. Hauk ◽  
D. N. Wiese
Keyword(s):  
Remote Sensing ◽  
Dual Pair ◽  
Concept Study ◽  
Satellite Gravimetry ◽  
New Methods

SOURCES OF GLOBAL SCALE SOIL MOISTURE MONITORING DATA BY SATELLITE BASED REMOTE SENSING OF EARTH’S SURFACE

2021 ◽  
Vol 100 (1) ◽  
pp. 36-41
Author(s):  
A.A. Volchek ◽  
◽  
D.O. Petrov ◽  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Global Scale ◽  
Research Papers ◽  
Equivalent Thickness ◽  
Satellite Gravimetry ◽  
Volumetric Soil Moisture ◽  
Characteristic Features ◽  
Agricultural Regions ◽  
Land Water

A review of modern tools of global monitoring of soil moisture by means of remote sensing of the Earth’s surface is presented. The characteristic features of the use of orbital radiometers and radars of C, X and L microwave bands for estimating the volumetric soil moisture at a depth of 5 cm and the root layer of vegetation are considered. A review of the capabilities of satellite gravimetry to assess the land water equivalent thickness is made. A number of sources have been proposed for obtaining estimates of soil water content from satellite based radiometric devices and orbital gravimetric systems. Based on the analysis of scientific research papers, the complexity of monitoring the level of fire danger indices in forests is shown, and the prospects of assessing soil moisture in agricultural regions using microwave orbital instruments are demonstrated, and the adequacy of calculating the moisture content in soil at a depth of up to one meter using satellite gravimetry is described.

scholarly journals One View Per City for Buildings Segmentation in Remote-Sensing Images via Fully Convolutional Networks: A Proof-of-Concept Study

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 141
Author(s):  
Jianguang Li ◽  
Wen Li ◽  
Cong Jin ◽  
Lijuan Yang ◽  
Hui He
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
Environmental Benefits ◽  
Sustainable Urban Development ◽  
Aerial Image ◽  
Proof Of Concept ◽  
Data Set ◽  
Concept Study ◽  
Convolutional Networks ◽  
Fully Convolutional Networks

The segmentation of buildings in remote-sensing (RS) images plays an important role in monitoring landscape changes. Quantification of these changes can be used to balance economic and environmental benefits and most importantly, to support the sustainable urban development. Deep learning has been upgrading the techniques for RS image analysis. However, it requires a large-scale data set for hyper-parameter optimization. To address this issue, the concept of “one view per city” is proposed and it explores the use of one RS image for parameter settings with the purpose of handling the rest images of the same city by the trained model. The proposal of this concept comes from the observation that buildings of a same city in single-source RS images demonstrate similar intensity distributions. To verify the feasibility, a proof-of-concept study is conducted and five fully convolutional networks are evaluated on five cities in the Inria Aerial Image Labeling database. Experimental results suggest that the concept can be explored to decrease the number of images for model training and it enables us to achieve competitive performance in buildings segmentation with decreased time consumption. Based on model optimization and universal image representation, it is full of potential to improve the segmentation performance, to enhance the generalization capacity, and to extend the application of the concept in RS image analysis.

A Unique Airborne Multi-angular Dataset for Calibration and Validation of Earth Satellite Products

2020 ◽  
Author(s):  
Charles Gatebe ◽  
Rajesh Poudyal ◽  
Michael King
Keyword(s):  
Remote Sensing ◽  
Surface Albedo ◽  
Transfer Functions ◽  
Earth Satellite ◽  
Bidirectional Reflectance Distribution Function ◽  
Bidirectional Reflectance ◽  
New Methods ◽  
Field Campaigns ◽  
Bidirectional Reflectance Distribution ◽  
Unique Dataset

<p>The Cloud Absorption Radiometer (CAR) Science Team, and the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) recently released a unique dataset of bidirectional reflectance-distribution function (BRDF) of different surface types including clouds, snow/ice, vegetation, ocean, lakes, desert, city scape, smoke and other mixed surface types. The data were acquired during numerous field campaigns around the world, with measurements spanning 1991 to 2017. This presentation will address several uses of these data including developing new methods that define important surface and atmosphere radiative transfer functions, improve remote sensing retrievals of multiple geophysical parameters such as aerosols, clouds and surface albedo, and support satellite remote sensing activities.  CAR data are archived at GES DISC:  https://disc.gsfc.nasa.gov/datasets?keywords=car.</p>

scholarly journals SIRTA, a ground-based atmospheric observatory for cloud and aerosol research

2005 ◽  
Vol 23 (2) ◽  
pp. 253-275 ◽  
Author(s):  
M. Haeffelin ◽  
L. Barthès ◽  
O. Bock ◽  
C. Boitel ◽  
S. Bony ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Data Interpretation ◽  
Data Sets ◽  
Atmospheric Processes ◽  
Passive Remote Sensing ◽  
Atmospheric Column ◽  
New Methods ◽  
Complex Interactions ◽  
Research Activities ◽  
Routine Monitoring

Abstract. Ground-based remote sensing observatories have a crucial role to play in providing data to improve our understanding of atmospheric processes, to test the performance of atmospheric models, and to develop new methods for future space-borne observations. Institut Pierre Simon Laplace, a French research institute in environmental sciences, created the Site Instrumental de Recherche par Télédétection Atmosphérique (SIRTA), an atmospheric observatory with these goals in mind. Today SIRTA, located 20km south of Paris, operates a suite a state-of-the-art active and passive remote sensing instruments dedicated to routine monitoring of cloud and aerosol properties, and key atmospheric parameters. Detailed description of the state of the atmospheric column is progressively archived and made accessible to the scientific community. This paper describes the SIRTA infrastructure and database, and provides an overview of the scientific research associated with the observatory. Researchers using SIRTA data conduct research on atmospheric processes involving complex interactions between clouds, aerosols and radiative and dynamic processes in the atmospheric column. Atmospheric modellers working with SIRTA observations develop new methods to test their models and innovative analyses to improve parametric representations of sub-grid processes that must be accounted for in the model. SIRTA provides the means to develop data interpretation tools for future active remote sensing missions in space (e.g. CloudSat and CALIPSO). SIRTA observation and research activities take place in networks of atmospheric observatories that allow scientists to access consistent data sets from diverse regions on the globe.

scholarly journals X ANNIVERSARY CONFERENCE “CURRENT PROBLEMS IN OPTICS OF NATURAL WATERS” ONW’2019: THEORY, FIELD STUDIES, REMOTE SENSING, NEW METHODS AND EQUIPMENT

2019 ◽  
Vol 47 (4) ◽  
pp. 242-247
Author(s):  
O. V. Kopelevich ◽  
A. A. Rodionov
Keyword(s):  
Remote Sensing ◽  
Natural Waters ◽  
Radiation Transfer ◽  
Field Studies ◽  
Ocean Optics ◽  
New Methods ◽  
Color Sensors ◽  
International Participation ◽  
Satellite Ocean Color ◽  
Russian Conference

X Anniversary All-Russian Conference with international participation “Current Problems in Optics of Natural Waters” (ONW’2019) was held in St. Petersburg from October 9 to 11; 57 reports were presented on the main aspects of modern ocean optics, including fundamental problems of radiation transfer theory, field studies, remote sensing, especially satellite ocean color sensors, and lidars, new methods, and equipment.

Estimation of the Under-Surface Temperature Pattern by Dynamic Remote Sensing

1995 ◽  
Vol 7 (2) ◽  
pp. 135-140
Author(s):  
Minoru Inamura ◽  
◽  
Hiromichi Toyota ◽  
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Underground Water ◽  
Temperature Pattern ◽  
Electric Circuits ◽  
New Methods ◽  
Thermal Output ◽  
Non Destructive ◽  
Effective Reflectivity ◽  
Fundamental Experiment

The remote sensing (R/S) methods can be classified into three kinds: 1) the measurement of the reflection of sun beams (passive R/S); 2) the measurement using millimeter wave or laser radar (active R/S); and 3) the measurement of infrared radiation. By these methods, one can obtain information on a measured object concerning 1) its surface temperature, 2) its effective emissivity, and 3) its effective reflectivity. The surface temperature, in effect, contains the total information on the under-surface structure. The authors performed a fundamental experiment for extracting such under-surface information by R/S, which is known as ""dynamic remote sensing"". In the first place, we determined a special function for the medium (sand in our experiment), and then filtering the surface temperature pattern, and calculated the undersurface temperature pattern; from this data we estimated the form of the sample in the medium. In the second place, we analyzed the relation between the thermal input (the temperature in the bottom) and thermal output (the surface temperature) by analogy with electric circuits, calculated the heat capacity and ther thermal conductivity of the sample, and estimated its substance. As a result, the present study is expected to provide us with guidance to new methods for the exploration of underground water or minerals as well as non-destructive tests.

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