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Interannual variability and correlation of vegetation cover and precipitation in Eastern China
Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China,...
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Published in: | Theoretical and applied climatology 2014-10, Vol.118 (1-2), p.93-105 |
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description | Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998–2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China. |
doi_str_mv | 10.1007/s00704-013-1054-2 |
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The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China.</description><identifier>ISSN: 0177-798X</identifier><identifier>EISSN: 1434-4483</identifier><identifier>DOI: 10.1007/s00704-013-1054-2</identifier><language>eng</language><publisher>Vienna: Springer-Verlag</publisher><subject>Agricultural development ; Animal and plant ecology ; Animal, plant and microbial ecology ; Aquatic Pollution ; atmospheric precipitation ; Atmospheric Protection/Air Quality Control/Air Pollution ; Atmospheric Sciences ; Biological and medical sciences ; Climate change ; Climate science ; Climatology ; Climatology. Bioclimatology. Climate change ; correlation ; Correlation analysis ; Earth and Environmental Science ; Earth Sciences ; Earth, ocean, space ; Exact sciences and technology ; External geophysics ; Extreme weather ; Fundamental and applied biological sciences. Psychology ; Growing season ; humans ; Hydrologic data ; Meteorology ; Original Paper ; Precipitation ; Precipitation (Meteorology) ; Rainfall intensity ; seasonal variation ; Seasonal variations ; Synecology ; Temperature ; Terrestrial ecosystems ; Vegetation ; Vegetation cover ; Waste Water Technology ; Water Management ; Water Pollution Control</subject><ispartof>Theoretical and applied climatology, 2014-10, Vol.118 (1-2), p.93-105</ispartof><rights>Springer-Verlag Wien 2013</rights><rights>2015 INIST-CNRS</rights><rights>COPYRIGHT 2014 Springer</rights><rights>Springer-Verlag Wien 2014</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c519t-9a6ec389314917a9356425211d8c9a5e99eb13947f159ba697d257e45b7be6853</citedby><cites>FETCH-LOGICAL-c519t-9a6ec389314917a9356425211d8c9a5e99eb13947f159ba697d257e45b7be6853</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28819312$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Jiang, Dejuan</creatorcontrib><creatorcontrib>Zhang, Hua</creatorcontrib><creatorcontrib>Zhang, Yong</creatorcontrib><creatorcontrib>Wang, Kun</creatorcontrib><title>Interannual variability and correlation of vegetation cover and precipitation in Eastern China</title><title>Theoretical and applied climatology</title><addtitle>Theor Appl Climatol</addtitle><description>Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998–2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China.</description><subject>Agricultural development</subject><subject>Animal and plant ecology</subject><subject>Animal, plant and microbial ecology</subject><subject>Aquatic Pollution</subject><subject>atmospheric precipitation</subject><subject>Atmospheric Protection/Air Quality Control/Air Pollution</subject><subject>Atmospheric Sciences</subject><subject>Biological and medical sciences</subject><subject>Climate change</subject><subject>Climate science</subject><subject>Climatology</subject><subject>Climatology. Bioclimatology. Climate change</subject><subject>correlation</subject><subject>Correlation analysis</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth, ocean, space</subject><subject>Exact sciences and technology</subject><subject>External geophysics</subject><subject>Extreme weather</subject><subject>Fundamental and applied biological sciences. 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The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China.</abstract><cop>Vienna</cop><pub>Springer-Verlag</pub><doi>10.1007/s00704-013-1054-2</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural development Animal and plant ecology Animal, plant and microbial ecology Aquatic Pollution atmospheric precipitation Atmospheric Protection/Air Quality Control/Air Pollution Atmospheric Sciences Biological and medical sciences Climate change Climate science Climatology Climatology. Bioclimatology. Climate change correlation Correlation analysis Earth and Environmental Science Earth Sciences Earth, ocean, space Exact sciences and technology External geophysics Extreme weather Fundamental and applied biological sciences. Psychology Growing season humans Hydrologic data Meteorology Original Paper Precipitation Precipitation (Meteorology) Rainfall intensity seasonal variation Seasonal variations Synecology Temperature Terrestrial ecosystems Vegetation Vegetation cover Waste Water Technology Water Management Water Pollution Control |
title | Interannual variability and correlation of vegetation cover and precipitation in Eastern China |
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