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Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China

BACKGROUND: Liao River basin in Jilin Province is the place of origin of the Dongliao River. This study gives a comprehensive analysis of the vegetation coverage in the region and provides a potential theoretical basis for ecological restoration. METHODS: The seasonal variation of vegetation greenne...

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Detalles Bibliográficos
Autores principales: Lin, Xiao-sheng, Tang, Jie, Li, Zhao-yang, Li, Hai-yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4960087/
https://www.ncbi.nlm.nih.gov/pubmed/27512632
http://dx.doi.org/10.1186/s40064-016-2737-9
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author Lin, Xiao-sheng
Tang, Jie
Li, Zhao-yang
Li, Hai-yi
author_facet Lin, Xiao-sheng
Tang, Jie
Li, Zhao-yang
Li, Hai-yi
author_sort Lin, Xiao-sheng
collection PubMed
description BACKGROUND: Liao River basin in Jilin Province is the place of origin of the Dongliao River. This study gives a comprehensive analysis of the vegetation coverage in the region and provides a potential theoretical basis for ecological restoration. METHODS: The seasonal variation of vegetation greenness and dynamics based on the Normalized Difference Vegetation Index (NDVI) in major land cover types in the region was studied. Analyzing the relationship NDVI, temperature and rainfall, we derived a set of predictor variables from 2001 to 2012 using the MODIS Terra level 1 Product (MOD02QKM). RESULTS: The results showed a general increasing trend in NDVI value in the region, while 34.63 % of the region showed degradation. NDVI values begin to rise from April when plants are regreening and they drop in September when temperature are decreasing and the leaves are falling in the study area and temperature was found decreasing during the period of 2001–2012 while rainfall showed an increasing trend. This model could be used to observe the change in vegetation greenness and the dynamic effects of temperature and rainfall. CONCLUSION: This study provided important data for the environmental protection of the basin area. And we hope to provide scientific analysis for controlling water and soil erosion, maintaining the sustainable productivity of land resources, enhancing the treatment of water pollution and stimulating the virtuous cycle of the ecological system.
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spelling pubmed-49600872016-08-10 Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China Lin, Xiao-sheng Tang, Jie Li, Zhao-yang Li, Hai-yi Springerplus Research BACKGROUND: Liao River basin in Jilin Province is the place of origin of the Dongliao River. This study gives a comprehensive analysis of the vegetation coverage in the region and provides a potential theoretical basis for ecological restoration. METHODS: The seasonal variation of vegetation greenness and dynamics based on the Normalized Difference Vegetation Index (NDVI) in major land cover types in the region was studied. Analyzing the relationship NDVI, temperature and rainfall, we derived a set of predictor variables from 2001 to 2012 using the MODIS Terra level 1 Product (MOD02QKM). RESULTS: The results showed a general increasing trend in NDVI value in the region, while 34.63 % of the region showed degradation. NDVI values begin to rise from April when plants are regreening and they drop in September when temperature are decreasing and the leaves are falling in the study area and temperature was found decreasing during the period of 2001–2012 while rainfall showed an increasing trend. This model could be used to observe the change in vegetation greenness and the dynamic effects of temperature and rainfall. CONCLUSION: This study provided important data for the environmental protection of the basin area. And we hope to provide scientific analysis for controlling water and soil erosion, maintaining the sustainable productivity of land resources, enhancing the treatment of water pollution and stimulating the virtuous cycle of the ecological system. Springer International Publishing 2016-07-26 /pmc/articles/PMC4960087/ /pubmed/27512632 http://dx.doi.org/10.1186/s40064-016-2737-9 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Lin, Xiao-sheng
Tang, Jie
Li, Zhao-yang
Li, Hai-yi
Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China
title Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China
title_full Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China
title_fullStr Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China
title_full_unstemmed Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China
title_short Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China
title_sort vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in liao river basin in jilin province, china
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4960087/
https://www.ncbi.nlm.nih.gov/pubmed/27512632
http://dx.doi.org/10.1186/s40064-016-2737-9
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