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  <controlfield tag="008">211115s2020    hu      o     0||   eng d</controlfield>
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   <subfield code="a">2060-467X</subfield>
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  <datafield tag="024" ind1="7" ind2=" ">
   <subfield code="a">10.2478/jengeo-2020-0007</subfield>
   <subfield code="2">doi</subfield>
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  <datafield tag="040" ind1=" " ind2=" ">
   <subfield code="a">SZTE Egyetemi Kiadványok Repozitórium</subfield>
   <subfield code="b">hun</subfield>
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   <subfield code="a">eng</subfield>
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  <datafield tag="100" ind1="2" ind2=" ">
   <subfield code="a">Mendez Garzón Fernando Arturo</subfield>
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  <datafield tag="245" ind1="1" ind2="0">
   <subfield code="a">Environmental armed conflict assessment using satellite imagery</subfield>
   <subfield code="h">[elektronikus dokumentum] /</subfield>
   <subfield code="c"> Mendez Garzón Fernando Arturo</subfield>
  </datafield>
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   <subfield code="c">2020</subfield>
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   <subfield code="a">1-14</subfield>
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  <datafield tag="490" ind1="0" ind2=" ">
   <subfield code="a">Journal of environmental geography</subfield>
   <subfield code="v">13 No. 3-4</subfield>
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  <datafield tag="520" ind1="3" ind2=" ">
   <subfield code="a">Armed conflicts not only affect human populations but can also cause considerable damage to the environment. Its consequences are as diverse as its causes, including; water pollution from oil spills, land degradation due to the destruction of infrastructure, poisoning of soils and fields, destruction of crops and forests, over-exploitation of natural resources and paradoxically and occasionally reforestation. In this way, the environment in the war can be approached as beneficiary, stage, victim or/and spoil of war. Although there are few papers that assess the use of remote sensing methods in areas affected by warfare, we found a gap in these studies, being both outdated and lacking the correlation of remote sensing analysis with the causes-consequences, biome features and scale. Thus, this paper presents a methodical approach focused on the assessment of the existing datasets and the analysis of the connection between geographical conditions (biomes), drivers and the assessment using remote sensing methods in areas affected by armed conflicts. We aimed to find; weaknesses, tendencies, patterns, points of convergence and divergence. Then we consider variables such as biome, forest cover affectation, scale, and satellite imagery sensors to determine the relationship between warfare drivers with geographical location assessed by remote sensing methods. We collected data from 44 studies from international peer-reviewed journals from 1998 to 2019 that are indexed using scientific search engines. We found that 62% of the studies were focused on the analysis of torrid biomes as; Tropical Rainforest, Monsoon Forest / Dry Forest, Tree Savanna and Grass Savanna, using the 64% Moderateresolution satellite imagery sensors as; Landsat 4-5 TM and Landsat 7 ETM+. Quantitative analysis of the trends identified within these areas contributes to an understanding of the reasons behind these conflicts.</subfield>
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  <datafield tag="650" ind1=" " ind2="4">
   <subfield code="a">Természettudományok</subfield>
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  <datafield tag="650" ind1=" " ind2="4">
   <subfield code="a">Föld- és kapcsolódó környezettudományok</subfield>
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  <datafield tag="695" ind1=" " ind2=" ">
   <subfield code="a">Természeti földrajz, Fegyveres konfliktus</subfield>
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  <datafield tag="700" ind1="0" ind2="1">
   <subfield code="a">Valánszki István</subfield>
   <subfield code="e">aut</subfield>
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   <subfield code="u">http://acta.bibl.u-szeged.hu/73881/1/journal_geo_013_003-004_001-014.pdf</subfield>
   <subfield code="z">Dokumentum-elérés </subfield>
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