Forecast of manifestations of dangerous geological processes in Dnipropetrovsk with the use of methods of aerospace remote sensing of the Earth

2004 ◽  
Vol 10 (5-6) ◽  
pp. 194-196
Author(s):  
V.I. Voloshin ◽  
◽  
A.S. Levenko ◽  
N.N. Peremetchik ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Geological Processes ◽  
The Earth

System of Ukrainian wind power stations ecological monitoring with the use of remote sensing of the Earth

2004 ◽  
Vol 10 (5-6) ◽  
pp. 171-174
Author(s):  
V.I. Voloshin ◽  
◽  
A.S. Levenko ◽  
Keyword(s):  
Remote Sensing ◽  
Wind Power ◽  
Ecological Monitoring ◽  
Power Stations ◽  
The Earth

Ukrainian field sites system for remote sensing of the Earth as an element of the GEOSS/GMES global system

2008 ◽  
Vol 14 (2) ◽  
pp. 3-12
Author(s):  
V.I. Lyalko ◽  
◽  
M.O. Popov ◽  
Keyword(s):  
Remote Sensing ◽  
Global System ◽  
The Earth

Algorithm for planning of realization of thematic programs of the Earth remote sensing

2007 ◽  
Vol 13 (2) ◽  
pp. 39-42
Author(s):  
A.I. Kirillov ◽  
◽  
Ye.I. Kapustin ◽  
N.A. Kirillova ◽  
E.I. Makhonin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Earth Remote Sensing ◽  
The Earth

Basis for the technique of the external control of the optical equipment for the remote sensing of the Earth surface

1997 ◽  
Vol 3 (3-4) ◽  
pp. 50-53
Author(s):  
O.D. Fedorovskyi ◽  
◽  
V.I. Kononov ◽  
K.Yu. Sukhanov ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
External Control ◽  
Earth Surface ◽  
The Earth

System Information Model of Obtaining and Using Data of Remote Sensing the Earth

2008 ◽  
Vol 40 (11) ◽  
pp. 46-56
Author(s):  
Ludmila I. Samoilenko ◽  
Sergey A. Baulin ◽  
Tatyana V. Ilyenko ◽  
Margarita A. Kirnosova ◽  
Ludmila N. Kolos ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information Model ◽  
The Earth ◽  
System Information ◽  
Using Data

Development of the Earth Remote Sensing Methods at IRE NAS of Ukraine

2009 ◽  
Vol 68 (16) ◽  
pp. 1439-1459
Author(s):  
S. Ye. Yatsevich ◽  
V. K. Ivanov
Keyword(s):  
Remote Sensing ◽  
Earth Remote Sensing ◽  
The Earth ◽  
Remote Sensing Methods

The analysis is geometrically stable orbits of spacecraft remote sensing of the Еarth

2018 ◽  
Vol 15 (1) ◽  
pp. 12-22
Author(s):  
V. M. Artyushenko ◽  
D. Y. Vinogradov
Keyword(s):  
Remote Sensing ◽  
Gravitational Field ◽  
State Vector ◽  
Semimajor Axis ◽  
The State ◽  
Zonal Harmonics ◽  
The Earth ◽  
Conditions Of Stability

The article reviewed and analyzed the class of geometrically stable orbits (GUO). The conditions of stability in the model of the geopotential, taking into account the zonal harmonics. The sequence of calculation of the state vector of GUO in the osculating value of the argument of the latitude with the famous Ascoli-royski longitude of the ascending node, inclination and semimajor axis. The simulation is obtained the altitude profiles of SEE regarding the all-earth ellipsoid model of the gravitational field of the Earth given 7 and 32 zonal harmonics.

Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review

2020 ◽  
Vol 3 (2) ◽  
pp. 58-73
Author(s):  
Vijay Bhagat ◽  
Ajaykumar Kada ◽  
Suresh Kumar
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Satellite Remote Sensing ◽  
Vegetation Indices ◽  
Unmanned Aerial System ◽  
Sustainable Land Management ◽  
Efficient Tool ◽  
Site Specific ◽  
The Earth ◽  
Interesting Area

Unmanned Aerial System (UAS) is an efficient tool to bridge the gap between high expensive satellite remote sensing, manned aerial surveys, and labors time consuming conventional fieldwork techniques of data collection. UAS can provide spatial data at very fine (up to a few mm) and desirable temporal resolution. Several studies have used vegetation indices (VIs) calculated from UAS based on optical- and MSS-datasets to model the parameters of biophysical units of the Earth surface. They have used different techniques of estimations, predictions and classifications. However, these results vary according to used datasets and techniques and appear very site-specific. These existing approaches aren’t optimal and applicable for all cases and need to be tested according to sensor category and different geophysical environmental conditions for global applications. UAS remote sensing is a challenging and interesting area of research for sustainable land management.

scholarly journals Editorial for the Special Issue “Advanced Artificial Intelligence and Deep Learning for Remote Sensing”

2021 ◽  
Vol 13 (15) ◽  
pp. 2883
Author(s):  
Gwanggil Jeon
Keyword(s):  
Artificial Intelligence ◽  
Remote Sensing ◽  
Deep Learning ◽  
Special Issue ◽  
The Earth

Remote sensing is a fundamental tool for comprehending the earth and supporting human–earth communications [...]

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