scholarly journals Fire Regime of Landscapes in the Volgograd Region According to Remote Sensing Data

Author(s):  
Stanislav Shinkarenko ◽  
Valeriya Doroshenko ◽  
Asel Berdengalieva
2020 ◽  
pp. 44-53
Author(s):  
Stanislav Shinkarenko ◽  
◽  
Asel Berdengalieva ◽  
Valeriya Doroshenko ◽  
Kseniya Oleynikova ◽  
...  

The aim of the work is to determine the spatial characteristics of the distribution of the burnt areas of natural zonal landscapes of the Volgograd region with different duration of pyro-factor successions, taking into account the frequency of fires. Based on the previously developed thematic geo-information layers of the steppe fires in the region using overlay operations, the duration of post-pyrogenic periods in the municipal districts of the region was determined, taking into account the total number of fires from 1998–2018. The largest areas covered by fire have a succession duration of 2–3 years and 12–14 years at the beginning of 2019, which corresponds to the fires of 2016–2017 and 2005–2007, respectively. Large areas after the fires of 2001–2002 are located in Ilovlinsky, Kletsky, Pallasovsky and Surovikinsky districts. The largest area of land covered by fire in 2004–2006 is located in the Danilovsky, Ilovlinsky, Olkhovsky and Pallas districts. In our opinion, landscapes affected by fire no more than 5–7 years ago are suitable for the analysis of pyrogenic shifts. These territories are located in Frolovsky, Chernyshkovsky, Kotovsky, Ilovlinsky, Pallasovsky, Leninsky, Kamyshinsky, Staropoltavsky districts. The results will serve as the basis for field studies and the analysis of the spectral characteristics of overgrowing burns from remote sensing materials.


2002 ◽  
Vol 8 (1) ◽  
pp. 15-22
Author(s):  
V.N. Astapenko ◽  
◽  
Ye.I. Bushuev ◽  
V.P. Zubko ◽  
V.I. Ivanov ◽  
...  

2011 ◽  
Vol 17 (6) ◽  
pp. 30-44
Author(s):  
Yu.V. Kostyuchenko ◽  
◽  
M.V. Yushchenko ◽  
I.M. Kopachevskyi ◽  
S. Levynsky ◽  
...  

2017 ◽  
Vol 6 (1) ◽  
pp. 2246-2252 ◽  
Author(s):  
Ajay Roy ◽  
◽  
Anjali Jivani ◽  
Bhuvan Parekh ◽  
◽  
...  

Author(s):  
Rupali Dhal ◽  
D. P. Satapathy

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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