基于MODIS NDVI的贵州省植被退化及归因
|
摘要
为了解森林退化的原因,利用2000-2015年的MODIS NDVI数据,在分析贵州省植被变化趋势的基础上识别了归一化植被指数(NDVI)显著下降的区域,并在NDVI显著下降区选取面积大于10 km~2的森林图斑为兴趣区,分析其内气候变化趋势及对森林NDVI值的影响。研究表明:197个兴趣区主要分布在贵州省西北部的赤水—习水、东北部的梵净山和东南部的非喀斯特区域;区内春、夏季NDVI变化趋势与年NDVI值变化趋势一致,下降速率达到-0.01·yr~(-1),冬季与其他季节变化趋势相反,呈不显著升高趋势;区内春季和夏季气温升高显著,降水和日照时间无明显变化,整体气候变化呈暖干趋势;夏季温度升高是NDVI降低的主要驱动因素。
Guizhou Province is located in southwest China, a typical subtropical karst landscape area bordering on Sichuan, Yunnan, Guangxi, Hunan and Chongqing, and is an important ecological barrier in the upper reaches of Pearl River and Yangtze River. Its ecological functions such as water, soil and biodiversity conservations are closely related to the forest ecosystem of the province. The recent years, the forest coverage in Guizhou Province has increased significantly, but in some regions such as Chishui-Xishui area it has decreased drastically. The aim of this study is to examine the major factors that has been driving the forest degradation(expressed in vegetation cover) in the province. In this study, the Mann-kendall change detection method was employed to calculate statistical trends in the Normalized Difference Vegetation Index(NDVI-a spectral index representing vegetation cover), using a 16-year MODIS time series between 2000 and 2015, to identify areas where vegetation cover has significantly decreased(z>2.36,P<0.01). For this purpose, 197 land areas with significant NDVI decrease were selected in the conditions of unchanged forestland type from 2000 to 2015 and each piece of the land size was greater than 10 km~2. Pearson correlation coefficients of climate and forest NDVI values for the 197 land areas of interest were calculated to reflect the response of vegetation NDVI to climate change,which include the mean annual and seasonal values, respectively. The 197 Region Of Interest(ROI) are mainly distributed in Chishui-Xishui in the northwest, Mountain Fanjingshan in the northeast and non-karst areas in the southeast of Guizhou Province.The results showed that the NDVI annual mean decrease rate in the ROI is-0.006 per year and the variation rate of NDVI between grids in the all ROI is small. The trend of NDVI change in spring and summer is consistent with the annual NDVI at a rate of-0.01 per year from 2000 to 2015. However, the trend of NDVI change in winter is not significantly increasing. The temperature increases significantly in spring and summer, whereas the precipitation and sunshine time do not change significantly, and the overall climate change has shown a warm and dry trend in the study area during the last 16 years. The core-density analysis of the correlation coefficient shows that the increase of summer temperature is the main driving factor for the decrease of NDVI, which may be due to the increase in temperature that promotes soil evaporation, resulting in the decrease of soil moisture and thus inhibiting the growth of vegetation.
Guizhou Province is located in southwest China, a typical subtropical karst landscape area bordering on Sichuan, Yunnan, Guangxi, Hunan and Chongqing, and is an important ecological barrier in the upper reaches of Pearl River and Yangtze River. Its ecological functions such as water, soil and biodiversity conservations are closely related to the forest ecosystem of the province. The recent years, the forest coverage in Guizhou Province has increased significantly, but in some regions such as Chishui-Xishui area it has decreased drastically. The aim of this study is to examine the major factors that has been driving the forest degradation(expressed in vegetation cover) in the province. In this study, the Mann-kendall change detection method was employed to calculate statistical trends in the Normalized Difference Vegetation Index(NDVI-a spectral index representing vegetation cover), using a 16-year MODIS time series between 2000 and 2015, to identify areas where vegetation cover has significantly decreased(z>2.36,P<0.01). For this purpose, 197 land areas with significant NDVI decrease were selected in the conditions of unchanged forestland type from 2000 to 2015 and each piece of the land size was greater than 10 km~2. Pearson correlation coefficients of climate and forest NDVI values for the 197 land areas of interest were calculated to reflect the response of vegetation NDVI to climate change,which include the mean annual and seasonal values, respectively. The 197 Region Of Interest(ROI) are mainly distributed in Chishui-Xishui in the northwest, Mountain Fanjingshan in the northeast and non-karst areas in the southeast of Guizhou Province.The results showed that the NDVI annual mean decrease rate in the ROI is-0.006 per year and the variation rate of NDVI between grids in the all ROI is small. The trend of NDVI change in spring and summer is consistent with the annual NDVI at a rate of-0.01 per year from 2000 to 2015. However, the trend of NDVI change in winter is not significantly increasing. The temperature increases significantly in spring and summer, whereas the precipitation and sunshine time do not change significantly, and the overall climate change has shown a warm and dry trend in the study area during the last 16 years. The core-density analysis of the correlation coefficient shows that the increase of summer temperature is the main driving factor for the decrease of NDVI, which may be due to the increase in temperature that promotes soil evaporation, resulting in the decrease of soil moisture and thus inhibiting the growth of vegetation.
引文
[1] 孙红雨,王长耀,牛铮,等.中国地表植被覆盖变化及其与气候因子关系[J].遥感学报,1998(2):204-210.
[2] Eugster W,Rouse W R,Pielke S R A,et al.Land-atmosphere energy exchange in Arctic tundra and boreal forest:Available data and feedbacks to climate[J].Global Change Biology,2000(6):84-115.
[3] Wang J,Meng J J,Cai Y L.Assessing vegetation dynamics impacted by climate change in the southwestern karst region of China with AVHRR NDVI and AVHRR NPP time-series[J].Environmental Geology,2008,54 (6):1185-1195.
[4] Wang J,Wang K L,Zhang M Y,et al.Impacts of climate change and human activities on vegetation cover in hilly southern China[J] Ecological Engineering ,2005,81:451-461.
[5] Nemani R R,Keeling C D,Hashimoto H,et al.Climate-driven increases in global terrestrial net primary production from 1982 to 1999[J].Science ,2003,300(5625):1560-1563.
[6] Myneni R B,Keeling C D,Tucker C J,et al.Increased plant growth in the northern high latitudes from 1981 to 1991[J].Nature 1991,386(6626):698-702.
[7] Tong X W,Wang K L,Brandt M,et al.Assessing Future Vegetation Trends and Restoration Prospects in the Karst Regions of Southwest China[J].Remote Sensing,2016,8(5):357-374.
[8] Pan N,Feng X,Fu B,et al.Increasing global vegetation browning hidden in overall vegetation greening:Insights from time-varying trends[J].Remote Sensing of Environment,2018,214:59-72.
[9] Eklundh L,J?nsson P.Timesat 3.0 Software Manual [M].Lund University,2010.
[10] Tong X.Brandt M,Yue Y,et al.Increased vegetation growth and carbon stock in China karst via ecological engineering[J].Nature Sustainability,2018,1(1):44-50.
[11] 徐建华.现代地理学中的数学方法[M].北京:高等教育出版社,2002:93-94.
[12] Cai H Y,Yang X H ,Wang K J,et al.Is forest restoration in the southwest China Karst promoted mainly by climate change or human-induced factors?[J].Remote Sensing,2014(6):9895-9910.
[13] Tian Y C,Bai X Y,Wang S J,et al.Spatial-temporal changes of vegetation cover in Guizhou Province,Southern China[J].Chinese Geographical Science,2017,27(1):25-38.
[14] Wang J,Meng J J,Cai Y L.Assessing vegetation dynamics impacted by climate change in the southwestern karst region of China with AVHRR NDVI and AVHRR NPP time-series[J].Environmental Geology,2007,54(6):1185-1195.
[15] Lawlor D W,Mitchell R A C.Crop ecosystem responses to climatic change:wheat.In:Reddy K R,Hodges H F,et al .Climate change and global crop productivity[M].Wallingford:CAB International Press,2000:57-80.
[16] Ridolfi L,D’Odorico P,Porporato A,et al.Impact of climate variability on the vegetation water stress[J].Journal of Geophysical Research:Atmospheres,2000,105(D14):18013-18025.
[17] 杨永辉,渡边正孝,王智平,等.气候变化对太行山土壤水分及植被的影响[J].地理学报,2004,59(1):56-63.
[18] Wang J,Wang K L,Zhang M Y,et al.Impacts of climate change and human activities on vegetation cover in hilly southern China[J].Ecological Engineering,2015,81:451-461.
[19] Rodriguez-Itur I,Porporato A,Laion F,et al.Intensive or extensive use of soil moisture:plant strategies to cope with stochastic water availability[J].Geophysical Research Letters,2001,28(23):4495-4497.
[2] Eugster W,Rouse W R,Pielke S R A,et al.Land-atmosphere energy exchange in Arctic tundra and boreal forest:Available data and feedbacks to climate[J].Global Change Biology,2000(6):84-115.
[3] Wang J,Meng J J,Cai Y L.Assessing vegetation dynamics impacted by climate change in the southwestern karst region of China with AVHRR NDVI and AVHRR NPP time-series[J].Environmental Geology,2008,54 (6):1185-1195.
[4] Wang J,Wang K L,Zhang M Y,et al.Impacts of climate change and human activities on vegetation cover in hilly southern China[J] Ecological Engineering ,2005,81:451-461.
[5] Nemani R R,Keeling C D,Hashimoto H,et al.Climate-driven increases in global terrestrial net primary production from 1982 to 1999[J].Science ,2003,300(5625):1560-1563.
[6] Myneni R B,Keeling C D,Tucker C J,et al.Increased plant growth in the northern high latitudes from 1981 to 1991[J].Nature 1991,386(6626):698-702.
[7] Tong X W,Wang K L,Brandt M,et al.Assessing Future Vegetation Trends and Restoration Prospects in the Karst Regions of Southwest China[J].Remote Sensing,2016,8(5):357-374.
[8] Pan N,Feng X,Fu B,et al.Increasing global vegetation browning hidden in overall vegetation greening:Insights from time-varying trends[J].Remote Sensing of Environment,2018,214:59-72.
[9] Eklundh L,J?nsson P.Timesat 3.0 Software Manual [M].Lund University,2010.
[10] Tong X.Brandt M,Yue Y,et al.Increased vegetation growth and carbon stock in China karst via ecological engineering[J].Nature Sustainability,2018,1(1):44-50.
[11] 徐建华.现代地理学中的数学方法[M].北京:高等教育出版社,2002:93-94.
[12] Cai H Y,Yang X H ,Wang K J,et al.Is forest restoration in the southwest China Karst promoted mainly by climate change or human-induced factors?[J].Remote Sensing,2014(6):9895-9910.
[13] Tian Y C,Bai X Y,Wang S J,et al.Spatial-temporal changes of vegetation cover in Guizhou Province,Southern China[J].Chinese Geographical Science,2017,27(1):25-38.
[14] Wang J,Meng J J,Cai Y L.Assessing vegetation dynamics impacted by climate change in the southwestern karst region of China with AVHRR NDVI and AVHRR NPP time-series[J].Environmental Geology,2007,54(6):1185-1195.
[15] Lawlor D W,Mitchell R A C.Crop ecosystem responses to climatic change:wheat.In:Reddy K R,Hodges H F,et al .Climate change and global crop productivity[M].Wallingford:CAB International Press,2000:57-80.
[16] Ridolfi L,D’Odorico P,Porporato A,et al.Impact of climate variability on the vegetation water stress[J].Journal of Geophysical Research:Atmospheres,2000,105(D14):18013-18025.
[17] 杨永辉,渡边正孝,王智平,等.气候变化对太行山土壤水分及植被的影响[J].地理学报,2004,59(1):56-63.
[18] Wang J,Wang K L,Zhang M Y,et al.Impacts of climate change and human activities on vegetation cover in hilly southern China[J].Ecological Engineering,2015,81:451-461.
[19] Rodriguez-Itur I,Porporato A,Laion F,et al.Intensive or extensive use of soil moisture:plant strategies to cope with stochastic water availability[J].Geophysical Research Letters,2001,28(23):4495-4497.