Analiza Geoprostorne i Vremenske Distribucije Klimatskih Katastrofa

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2 L. Davis, Natural Disasters, New York, 2008, . 54.3 Centre for Research on the Epidemiology of Disasters (2003), EM-DAT: the OFDA/CRED International Disaster Database, 05.06.2013. 15,00 .

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,Glajdnamber. . .4 `

. 1900. 2013. 25.552 , (9557), (7149), (3037), (2989) (2820) ( 1).5

1: 1900. 2013. .

($)

7149 2766859 2641153 1742924832 105054916 1850620901 1872273246 3037 5331007 5177147 309279694 45930226 360387067 1522543792

9557 13987140 2655118 6891172180 185223183 7079050481 1200003042 2820 19152311 968153 90325323 0 91293476 460264 2989 23772449 3779656 4532945549 903962 4537629167 471765608

25552 65009766 15221227 13566647578 337112287 13918981092 5067045952: : EM-DAT: The OFDA/CRED International Disaster Database

90, 7.5 0.25 - . , ( 2).6

2: 1900. 2013. , , .

90 7.5 0.25 27 2 0.07

85 7 0.6 24 2 0.06

226 18.5 0.98: : EM-DAT: The OFDA/CRED International Disaster Database

4 -, ,,LaRed. . ,,DesInventar (2010), , - . . P. Bimal, Environmental Hazards and Disasters Contexts, Perspectives and Management, ansas, 2011, . 101.5 V. Cvetkovi; S. Mijalkovi, Spatial and Temporal Distribution of Geophysical Disasters, Journal of the Geographical Institute ,,Jovan Cviji 63/3, Belgrade, 2013, . 346; . ; . ; . -, , , LXVI, /2014, 167.6 . ; , : - ,, , , -, 2014, . 1284.

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, , - , 24,83% , 36.57% 33,41% - ( 1).7

1: 1900. 2013. .

: : EM-DAT: The OFDA/CRED International Disaster Database

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- (CRED). - ,,xcel 25.552 (www.emdat.be). , -7 V. Cvetkovi, Spatial and temporal distribution of floods like natural emergency situations, in: International Scientific Conference Archibald Reiss Days (. 371-389), The Academy f Criminalistic nd Police Studies, Belgrade, 2014, . 373.8 S. Mijalkovi; V. Cvetkovi, Vulnerability of Critical Infrastructure by Natural Disasters, National Critical Infrastructure Protection, Regional Perspective, Belgrade, 2013, . 91.9 . , - , , 2013, . 9.10 . ; . ; . , , , /2012, , . 91.11 . , , , 4/2007, , .108.

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,,IBM SPSS advanced statistics 20.0, - , , ,,MS Word 2013.

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3.1.

- 1900. 2013. - 583, 42. , , , , ( 3).

3: 1900. 2013. , .

($)

583 1694286 0 728889598 0 728889598 5841186A 305 19326778 0 3415632058 40000 3415672058 69044730

263 154 0 138834452 0 138834452 100742278 84 2400004 0 30977538 0 30977538 50962618

42 1320 0 16061654 0 16061654 23006000 1277 23422542 0 4330395300 40000 4330435300 249596812: : EM-DAT: The OFDA/CRED International Disaster Database

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2: 1900. 2013. ,

: EM-DAT: The OFDA/CRED International Disaster Database

1: 1900. 2013.

: : EM-DAT: The OFDA/CRED International Disaster Database)

- , (41.26%), - (39.44%) (50%) , ( 2 1).

, 1900. 2013. , 22.83%, 11.94%, 10.30%, 3.29% 1.64% . , , , ( 2).

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3: 1900. 2013. ,


- , (41.26%), - (39.44%) (50%) . ( 3).

3.2.

, 1900. 2013. , 439, - 12. , , , , , ( 4).

4: 1900. 2013. ,

($)

22 454 210 2015000 0 2015210 95618 206 17894 3649796 6865500 32000 10547296 34529700

291 43163 68788 170379476 466000 170914264 47654666 439 280349 44562 2564504 2680 2611746 32374702

12 740 5568 9200000 0 9205568 400000 970 342600 3768924 191024480 500680 195294084 115054686


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4: 1900. 2013. ,


2: 1900 2013. .


, (45%), (30%), (21%), (3%), - (1%) ( 4 1).

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5: 1900. 2013. ,


, , (45.26%) (1.24%) . (96.84%) (0.15%) . (89.19%) (1.34%) . , (93.07%) (0.54%) ( 3).

3.3.

, - 1900. 2013. , 262, 54. , , , , , ( 5).

5: 1900. 2013. ,

($)

54 548 1516 18570 47658 67744 880000 262 3105 1372 2409871 83386 2494629 51435800

164 1512 1716 6373404 176570 6551690 23807000 196 1150 3978 2569916 17306 2591200 25637622

66 992 2150 154008 38362 194520 5353688 742 7307 10732 11525769 363282 11899783 107114110: : EM-DAT: The OFDA/CRED International Disaster Database

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6: 1900. 2013. ,


3: 1900 2013.


, (35 %), (27 %), (22 %), (9 %), (7 %) ( 6 3).

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7: 1900. 2013. ,


, , (42,49 %), (20,69 %), (15,74 %), (13.58 %), (7.50 %). (37.07 %), (20.03 %), (15.99 %), (14.13%), (12.78%). - (55.30 %), (22.30 %), (20.91 %), (1.34 %), (0.16 %). (48.60 %), (22.95%), (13.12 %), (10.56%), (4.76%). (48.02 %), (23.93 %), (22.23 %), (5.00 %) (0.82 %) ( 7).

4.

4.1.

1900. 2013. 1277 , 23422542, - 4330395300, 40000 . , 11, 0.94, 0.03 ( 6).

6: 1900. 2013. , ,

($)

1900-2013 1277 23422542 0 4330395300 40000 4330435300 249596812 11 207279 0 38322082 354 38322436 2208821 0.94 17.273 0 3193506 294 3193536 184068 0.03 575 0 106450 0.98 106451 6135


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8: 1900. 2013. ,


1960. 5%. - , 2000. 2013. 32.16% . 1950. 1960. , 0,16 % (- 8).

9: 1900. 2013. ,


, 2000 2013. (32.16 %), 1940. 1960. (0,80%) ( 9).

10: 1900. 2013. , : 1900. 1950. 1950. 2013.


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, 1950. 2013. 94,73%, 1900. 1950. (5.27%) ( 10).

11: 1900. 2013. ,


, 1920. 1930. (35.87%), , (0%) 1950. 1960. . , 2000. 2013. (36.05%), 1940. 1960. . 1960. 1970. , 40000 (100%) ( 11).

4.2.

1900. 2013. , 970 , - 342.600, 3.768.924, 191.024.480, 500.680 . , 8.6, 0.7, 0.02 ( 7).

7: 1900. 2013. , ,

($)

1900-2013. 970 342600 3768924 191024480 500680 195294084 115054686 8.6 3031.9 33353.3 1690482.1 4430.8 1728266.2 1018183.1 0.7 252.7 2779.4 140873.5 369.2 144022.2 84848.6 0.02 8.4 92.6 4695.8 12.3 4800.7 2828.3


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12: 1900. 2013. ,


1980. , 6%. , -, 2000. 2013. 59.79% - . 1900. 1930. , ( 12).

13: 1900. 2013. ,


, (59.79%) 2000. 2013. , ( ) 1900. 1920. ( 13).

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14: 1900. 2013. ,


, 1950. . , 1950. 2013. 99.59% . , 1900. 1950. , 0.41% ( 14).

15: 1900. 2013. ,


, , (59.79%) 2000. 2013. , ( ) - 1900. 1930. 1940. 1950. . (99.77%) 2000. 2013. , ( ) - 1900. 1970. . (92.48%) 2000. 2013. , ( ) 1900. 1980 . , (93.07%) 2000. 2013. , ( ) 1900. 1980. ( 15).

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4.3.

1900. 2013. , 742 , 7.037, 10.732, 11.525.769, 363.282 . , 6.5, 0.5, 0.01 ( 8).

8: 1900. 2013. , , .

($)

1900-2013. 742 7307 10732 11525769 363282 11899783 107114110 6,5 64,6 94,9 101998 3214 105307 947912 0,5 2,1 3,16 3399 107 8775 31597 0.01 0,17 0,26 283 8,91 731 2633


16: 1900. 2013. ,

: : EM-DAT: The OFDA/CRED International Disaster Database 1970. ,

, . - 2000. 2013. 268 . 1930. 1940. 2 ( 16).

17: 1900. 2013. ,


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- 1980. 2000. (378) 1920. 1940. (6) ( 17).

18: 1900. 2013. ,


, 1950. . , 1900. 1950. 24 %, 1950. 2013. 76 % ( 18).

19: 1900. 2013. ,


, , (29,37%) 1910. 1920. , ( ) 1900. 1910. . (69.51 %) 2000. 2013. - ( ) 1900. 1960. . (57.93 %) 1990. 2000. , ( ) 1910. 1960. . , (36.45 %) 1990. 2000. , ( ) 1950. 1970. ( 19).

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1900. 2013. , : , -; , , ; , -; , , , , , , ; - , ; , , , , , , .

: 1900. 2013. 1277 , 23422542, 4330395300, 40000 ; 2000 2013. - , 1950 1960. ; - 970 , 342.600, 3.768.924, 191.024.480, 500.680 ; -, , 2000. 2013. ; - 1900. 1930. , 1900. 1970. , 1900. 1980. 1900. 1980. ; 742 , 7.037, 10.732, 11.525.769, 363.282 ; 1910. 1920. -, 2000. 2013. , 1990. 2000. 1990. 2000. . 1900. 1910. , 1900. 1960. , 1910. 1960. , 1950. 1970. .

- . - , .

1. Bimal, P; Environmental Hazards and Disasters Contexts, Perspectives and Management, Wiley Blackwell, ansas, 2011.

2. Centre for Research on the Epidemiology of Disasters (2003), EM-DAT: the OFDA/CRED International Disaster Database, 05.06.2013. 15,00 .

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3. , ; - , , , 2013.

4. Cvetkovi, V; Mijalkovi, S; Spatial and Temporal distribution of geophysical disasters, Journal of the Geographical Institute Jovan Cviji 63/3, 345-360, Belgrade, 2013.

5. Cvetkovi, V; Spatial and temporal distribution of floods like natural emergency situations, in: International Scientific Conference Archibald Reiss Days (. 371-389), The Academy of Criminalistic and Police Studies, Belgrade, 2014.

6. Davis, L; Natural Disasters, Facts on file, New York, 2008.7. Mijalkovi, S; Cvetkovi, V; Vulnerability of Critical Infrastructure by Natural Disasters, Na-

tional Critical Infrastructure Protection, Regional Perspective, Belgrade, 2013.8. , ;

, , 4/2007, .9. , ; , ; , ;

, , /2012, .

10. , ; , : - , , , 2014.

11. . ; , ; , ; , , LXVI, /2014 (166-185), .

ANALYSIS OF GEOSPATIAL AND TEMPORAL DISTRIBUTION OF CLIMATE DISASTERS

Summary: Climate disasters, which include drought, extreme temperatures and wildfires, every day more and more jeopardize the safety of people and their property. As such, they are beginning to attract more attention of researchers in the field of emergency situations who want to better understand it. Consequently, research has been undertaken in order to determine the geospatial and temporal distribution of climate disasters in the world in geographic space period in 1900. till 2013. Given that it is a mass phenomenon, which consists of multiple units, most preferred scientific method for drawing conclusions about climate disasters is a statistical method. In addition, a statistical study was conducted so as to take the first step, the raw data of all natural disasters (25,552) in mind, Excel file from the international database on disasters (CRED) in Brussels, and then analyzed in program for statistical analysis of data SPSS. Within the geospatial distribution analyzed the total number and consequences of climate disasters by continent. By the same token, within the temporal analysis examined the distribution of the total number and consequences of climatic disasters on an annual, monthly and daily. Statistical analysis of the results clearly indicate that the number of climate disasters on the rise, with their recorded maximum in the period since 2000. till 2013.. Then, based on the results it is concluded that most

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of the drought occurred in Africa, extreme temperatures in Europe and the forest fires in America. In contrast, the least drought and extreme temperatures occurred in Oceania, and forest fires in Africa. It can not be said that an international database on natural disasters included absolutely everything that happens in the world, given that it was created thanks to the submitted national reports on natural disasters in the period in 1900. till 2013. So the question that arises is whether the most underdeveloped countries submitted their reports. Bearing in mind the increasing trend in the number and severity of natural disasters in the worlds geographic space, the results are a good argument to launch a serious reform of the system of protection and rescue against natural disasters in countries around the world. Results of research impact on raising awareness among citizens on the severity of the consequences of climatic disasters on people, the environment and their property. In our literature there is no scientific papers on this approach the analysis of climatic disasters. These results are original, bearing in mind the scientific method used to analyze the data obtained from the Center for Research of the Epidemiology of Disaster in Brussels.

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Analiza Geoprostorne i Vremenske Distribucije Klimatskih Katastrofa