Geoprostorna i Vremenska Distribucija Cunamija

7/24/2019 Geoprostorna i Vremenska Distribucija Cunamija

1/9

,2-3. , 2014.

352

. 1

2

3

:

1900. 2013. .

,

. ,

(25.552) ,,Excel

(CRED) ,

SPSS.

. ,

, .

, , , ,

, .

GEOSPATIAL AND TEMPORAL DISTRIBUTION OF

TSUNAMI AS A NATURAL DISASTER

Abstract:The subject of research is determination of geospatial and temporal distribution of tsunami

in the global geospace in the period from 1900 to 2013. Bearing in mind that this is a mass

phenomenon that consists of multiple units, most preferred scientific method to draw conclusions about

the tsunami is a statistical method. In addition, a statistical study was conducted in such a way that the

first step to take raw data about all natural disasters (25,552) in the form,, Excel "file from the

international database on disasters (CRED) in Brussels, and then analyzed in program for statisticalanalysis SPSS. Within the geospatial distribution analyzed the total number and consequences of the

tsunami across the continents. By the same token, within the temporal analysis examined the

distribution of the total and the consequences of the tsunami on a yearly, monthly and daily.

Key words: security, emergency situations, natural disasters, statistical analysis, geospatial and

temporal distribution, tsunami.

1A, - , , [email protected]. 2, - , , [email protected] , ,[email protected].
mailto:[email protected]:[email protected]


2/9

,2-3. , 2014.

353

1.

, , . [1][2][3][4][5] , .

. [6] . , , . . 950 /

30 . [7] , . , . , . ( ) .[8][9]

(CRED). [10] , ,,Excel

25.552 (www.emdat.be). ,

,,IBM SPSS advancedstatistics 20.0, , , ,,MS Word 2013. , . : - , ; - , ; - , ; - ;

, ; - , .

, , , . .

2.

1900.


3/9

,2-3. , 2014.

354

2014. 671, 36. , , , , ( 1).

1 - 1900. 2013.

, . : .

1. 1900 2013.

. : .

3. 1900. 2013.

, . : .

, , (71,05%), (17,13%), (10,85%), (0,13%). ,

(65,97%), (77,28%) (70,44%). , (0,12%), (0,46%) (0,09%) ( 3).

2. 1900. 2013. . :

.


4/9

,2-3. , 2014.

355

1900. 2013. , 118., , 96, 84, 78, 64 (T 2).

3. 1900. 2013.

. : .

1900. 2013. , - (.) 24.564. , (), 17.068, 10.642, 9.524, 5.928 (T3).

4. 1900. 2013.

. : .

1900. 2013. , 7.058. ,

, 3.374, 1.074, 1.062, 924 ( 4).

5. 1900. 2013.

. : .

1900. 2013. , 8.180.340. , , 4.427.492, 1.561.480,

724.588, 709.592 ( 5). 6.

1900. 2013. . : .

1900. 2013. , 7.232.570. , , 294.200, 160.400, 121.794 102.200 ( 6).


5/9

,2-3. , 2014.

356

7.

1900. 2013. . : .

1900. 2013. , 719.324.800. , , 200.231.414, 98.569.704, 82.083.340, 69.224.140 ( 7).

3.

1900. 2013. , 1226 ,

119.954, 20.672, 18.907.252, 8.467.444 ., 10.8, 0.9, 0.0 (8).

8. 1900. 2013. ,

, . : .

4. 1900. 2013. ,

. : .

1970. 5 %. , , 2000. 2013. 27,94% . 1910. 1920.

, 1,98% ( 4).

5. 1900. 2013. ,

. : .


6/9

,2-3. , 2014.

357

1980. 2000. (37,26%), 1900. 1920. (4,60%)( 5).

6. 1900. 2013. , . : .

, 1950. . , 1900. 1950. 15,54%, 1950. 2013. 84,46% ( 6).

7. 1900. 2013., . : .

, , (27,76%), (51,77%), (53,30%) (52,75%) 2000. 2013. . (1,46 %) 1950. 1960. , (0%) 1900. 1910. , (0%) 1910. 1920. , (0%) 1900. 1910. 1910.1920. ( 7).

8. 1900. 2013.

, . : .

, 2000. 2013. (27,76%), 1920. 1940. (24,05%), 1980. 2000. (6,18%).

. ,


7/9

,2-3. , 2014.

358

, , . 1900. 1920. (0,9%), 2000. 2013. (51,77%). . 1920. 1940. (0,08%), 2000. 2013. (53,30%). 1900. 1920. (0%), 2000. 2013. (52,75%) ( 8).

9. 1900.

2013. . : .

1900. 2013. , 1949. 24.000. 1949., 1941, 1973, 2010, 1963. (T 9).

10. 1900.

2013. . : .

1900. 2013. , 1987. 6.000. 1987, 1988, 1974, 2010, 2003. ( 10).

11. 1900.

2013. . : .

1966.

8.000.000. 1966, 2010, 1983, 2003, 2006. ( 11).

12.

1900. 2013. . : .

1986. 5.000.732. 1986, 1995, 2000, 2006, 1993. ( 12).


8/9

,2-3. , 2014.

359

13.

1900. 2013. . : .

2010. 2.554.156. , 2010, 1983, 1993, 1998, 1999. ( 13).

4.

. . . , . , . , .

, , .

: 671, 36; (71,05%), (0,13%); (118) , (24564) , (7058), (8180340) , (719324800); , 10 ; 2000-2013., (27.94%), ; , 1949. (24.000); 1987. (6000); 1986. (5000);

2010. 2.554.156 .

, .

5.

[1] Cvetkovi, V. (2014): Spatial and temporal distribution of floods like natural

emergency situations. International scientific conference Archibald Reiss days (pp.

371-389). Belgrade: The academy of criminalistics and police studies.


9/9

,2-3. , 2014.

360

[2] Cvetkovi, V., & Mijalkovi, S. (2013): Spatial and temporal distribution ofgeophysical disasters. International conference natural hazards - links between science

and practice (pp. 345-360). Belgrade: Serbian Academy of Sciences and Arts and

Geographical Institute Jovan Cviji, Journal of the Geographical Institute JovanCviji.

[3] Mijalkovi, S., & Cvetkovi, V. (2013): Vulnerability of Critical Infrastructure byNatural Disasters. In: Kekovic, Z., aleta, D., Keetovi, ., & Jevti, Z., (eds.):National Critical Infrastructure Protection Regional Perspective, pp. 91102.Belgrade: University of Belgrade Faculty of Security Studies, Institute forCorporative Security Studies in Ljubljana.

[4] , ., , ., & , . (2014):

. , 275-290.

[5] Cvetkovi, V. (2014). Analysis of spatial and temporal distribution of volcaniceruptions as natural disasters.NBP: Journal of criminalistics and law, 2/2014.

[6] Bryant, E. (2008): Tsunami: the underrated hazard. New York: Springer.

[7] Chadha, R. K., Latha, G., Yeh, H., Peterson, C., & Katada, T. (2005): The tsunami ofthe great Sumatra earthquake of M 9.0 on 26 December 2004: Impact on the east coast

of India. Current Science, 88(8), 1297-1301.

[8] Lavrentyev, M., Titov, V., & Romanenko, A. (2014): Approaches to real-time tsunami

wave parameters evaluation. InEGU General Assembly Conference Abstracts(Vol. 16,

p. 3742).[9] Kanamori, H. (1972): Mechanism of tsunami earthquakes.Physics of the earth and

planetary interiors, 6(5), 346-359.

[10] Centre for Research on the Epidemiology of Disasters (2003): EM-DAT: theOFDA/CRED International Disaster Database, pristupljeno 05.06.2013. godine u15,00 asova

Geoprostorna i Vremenska Distribucija Cunamija

Documents

Transcript of Geoprostorna i Vremenska Distribucija Cunamija