scholarly journals Management of ground and remote sensing data for remote monitoring of vineyards

2016 ◽  
Vol 13 (1) ◽  
pp. 79-92
Author(s):  
E.A. Rybalko ◽  
◽  
N.V. Baranova ◽  
E.A. Loupian ◽  
V.A. Tolpin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Monitoring ◽  
Remote Sensing Data ◽  
Sensing Data

scholarly journals Remote monitoring of the state of hydrocarbon pollution of the geological environment and assessment of the risks of dangerous situations in areas of long-term oil and gas production and compact living of the population

2020 ◽  
pp. 14-26
Author(s):  
Volodymyr Filipovych ◽  
Anton Mychak ◽  
Alexandr Kudryashov ◽  
Ruslan Shevchuk
Keyword(s):  
Remote Sensing ◽  
Remote Monitoring ◽  
Oil And Gas ◽  
Remote Sensing Data ◽  
Field Work ◽  
Gas Production ◽  
Hydrocarbon Production ◽  
Sensing Data ◽  
Space Data

The results of the analysis of geoecological problems of territories of long-term hydrocarbon production are presented. Based on the analysis of ground-based and remote studies, the possibilities of space data were determined during the eco-monitoring of hydrocarbon deposits. A methodological and technological scheme for assessing the risks of harming the environment is proposed. The list of tasks that can be solved using Earth remote sensing data:- control of environmental pollution by hydrocarbons (oil, gas) at different stages of the functioning of the oil and gas complex - from the search and exploitation of deposits, to the transportation, storage and processing of petroleum products;- flooding and flooding of territories of oil production by underground waters;- identification, mapping, field studies, discontinuous violations of various ranks, are ways of migration of oil and gas in the upper layers of the earth's crust;- identification and mapping of technogenic sources of gas contamination of the surface layer of the atmosphere, namely:- non-geometrical wells, oil and gas pipelines;- buried under modern sediments, pit-well houses, mines.Satellite monitoring consists of 4 stages. At the first, preliminary stage, objects of remote monitoring are determined, a base of satellite and thematic data is formed, the foundations of a future thematic GIS are laid. At the second stage, the actual detection (decryption) of objects and territories polluted with hydrocarbons is carried out. At the next, third stage, a set of field work is carried out in order to validate the research methodology and verify the data obtained using ground-based measurements.At the fourth, final stage, based on an analysis of all the information received, an assessment of the risks of dangerous situations is carried out and their possible consequences are predicted.The possibilities of assessing the risks of dangerous situations in areas of long-term hydrocarbon production according to remote sensing data are considered. A review of hazardous situations resulting from hydrocarbon production in the city of Borislav is given .; recommendations are proposed to reduce the risk of their occurrence.

Assessment of the national market demand for high-resolution remote sensing data

2002 ◽  
Vol 8 (1) ◽  
pp. 15-22
Author(s):  
V.N. Astapenko ◽  
◽  
Ye.I. Bushuev ◽  
V.P. Zubko ◽  
V.I. Ivanov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Market Demand ◽  
Sensing Data ◽  
National Market

A procedure for integrated assessment of landscape fire risk using remote sensing data

2011 ◽  
Vol 17 (6) ◽  
pp. 30-44
Author(s):  
Yu.V. Kostyuchenko ◽  
◽  
M.V. Yushchenko ◽  
I.M. Kopachevskyi ◽  
S. Levynsky ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Integrated Assessment ◽  
Remote Sensing Data ◽  
Fire Risk ◽  
Sensing Data

Estimation of PM10 Distribution using Landsat 7 ETM+ Remote Sensing Data

2017 ◽  
Vol 6 (1) ◽  
pp. 2246-2252 ◽  
Author(s):  
Ajay Roy ◽  
◽  
Anjali Jivani ◽  
Bhuvan Parekh ◽  
◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Sensing Data ◽  
Landsat 7

Evaluation of Capacity of Salandi Reservoir Using Remote Sensing Data Along With Qgis Software

2018 ◽  
Vol 6 (8) ◽  
pp. 339
Author(s):  
Rupali Dhal ◽  
D. P. Satapathy
Keyword(s):  
Remote Sensing ◽  
Satellite Data ◽  
Remote Sensing Data ◽  
Project Work ◽  
Space Technology ◽  
Reservoir Water ◽  
Sediment Distribution ◽  
Sensing Data ◽  
Spread Area ◽  
Water Spread

The dynamic aspects of the reservoir which are water spread, suspended sediment distribution and concentration requires regular and periodical mapping and monitoring. Sedimentation in a reservoir affects the capacity of the reservoir by affecting both life and dead storages. The life of a reservoir depends on the rate of siltation. The various aspects and behavior of the reservoir sedimentation, like the process of sedimentation in the reservoir, sources of sediments, measures to check the sediment and limitations of space technology have been discussed in this report. Multi satellite remote sensing data provide information on elevation contours in the form of water spread area. Any reduction in reservoir water spread area at a specified elevation corresponding to the date of satellite data is an indication of sediment deposition. Thus the quality of sediment load that is settled down over a period of time can be determined by evaluating the change in the aerial spread of the reservoir at various elevations. Salandi reservoir project work was completed in 1982 and the same is taken as the year of first impounding. The original gross and live storages capacities were 565 MCM& 556.50 MCM respectively. In SRS CWC (2009), they found that live storage capacity of the Salandi reservoir is 518.61 MCM witnessing a loss of 37.89 MCM (i.e. 6.81%) in a period of 27 years.The data obtained through satellite enables us to study the aspects on various scales and at different stages. This report comprises of the use of satellite to obtain data for the years 2009-2013 through remote sensing in the sedimentation study of Salandi reservoir. After analysis of the satellite data in the present study(2017), it is found that live capacity of the reservoir of the Salandi reservoir in 2017 is 524.19MCM witnessing a loss of 32.31 MCM (i.e. 5.80%)in a period of 35 years. This accounts for live capacity loss of 0.16 % per annum since 1982. The trap efficiencies of this reservoir evaluated by using Brown’s, Brune’s and Gill’s methods are 94.03%, 98.01and 99.94% respectively. Thus, the average trap efficiency of the Salandi Reservoir is obtained as 97.32%.

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