基于MODIS NDVI、SPOT NDVI数据的GIMMS NDVI性能评价
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摘要
以MODIS NDVI和SPOT NDVI数据为基准对2000—2015年重叠时段的GIMMS NDVI数据进行评价.在全国尺度以及水田、旱地、林地、草地4种土地类型上对比分析3种数据的数值差异、动态一致性、变化趋势差异和两两间相关性.结果表明:GIMMS NDVI在数值上整体高于MODIS NDVI和SPOT NDVI,3种数据在反映植被月动态方面能力相当;研究期内3种NDVI数据在全国大部分区域均呈增加趋势,GIMMS的增加幅度最小,且在我国西北、东北、中南、青藏高原及云贵高原的部分地区与另两套数据差异较大,表明在研究该区域时应对GIMMS NDVI数据的使用有所保留;各数据间两两相关性较强,在全国尺度上MODIS NDVI与SPOT NDVI的相关性更好,旱地GIMMS NDVI与MODIS NDVI的相关性更好,水田、林地、草地MODIS NDVI与SPOT NDVI的相关性更好.
The study evaluated GIMMS NDVI based on MODIS NDVI and SPOT NDVI over the same period from 2000 to 2015. We assessed their absolute values,dynamics,trends and cross-relationships between any two of the NDVIs for the national scale,as well as four separate land use types,i.e.,paddy field,dry land,forest,and grassland. GIMMS NDVI was numerically greater than MODIS NDVI and SPOT NDVI. The three NDVIs exhibited equal capability of capturing monthly phenological variations. During the study period,the three NDVIs showed increasing trends in most regions,with GIMMS NDVI showing the smallest increment. Pronounced differences were identified in trends between GIMMS NDVI and MODIS NDVI or SPOT NDVI in the northwest,northeast,south-central China, Tibetan Plateau and Yunnan-Guizhou Plateau, implying that GIMMS NDVI trends in these regions should be interpreted with caution. High correlations existed between the three datasets. MODIS NDVI and SPOT NDVI showed stronger correlations at national scale. The GIMMS NDVI and MODIS NDVI were in highest accordance for dry land,while MODIS NDVI and SPOT NDVI were in higher accordance for the paddy field,forest,and grassland than dry lands.
The study evaluated GIMMS NDVI based on MODIS NDVI and SPOT NDVI over the same period from 2000 to 2015. We assessed their absolute values,dynamics,trends and cross-relationships between any two of the NDVIs for the national scale,as well as four separate land use types,i.e.,paddy field,dry land,forest,and grassland. GIMMS NDVI was numerically greater than MODIS NDVI and SPOT NDVI. The three NDVIs exhibited equal capability of capturing monthly phenological variations. During the study period,the three NDVIs showed increasing trends in most regions,with GIMMS NDVI showing the smallest increment. Pronounced differences were identified in trends between GIMMS NDVI and MODIS NDVI or SPOT NDVI in the northwest,northeast,south-central China, Tibetan Plateau and Yunnan-Guizhou Plateau, implying that GIMMS NDVI trends in these regions should be interpreted with caution. High correlations existed between the three datasets. MODIS NDVI and SPOT NDVI showed stronger correlations at national scale. The GIMMS NDVI and MODIS NDVI were in highest accordance for dry land,while MODIS NDVI and SPOT NDVI were in higher accordance for the paddy field,forest,and grassland than dry lands.
引文
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[22] Guo XY,Zhang HY,Wu ZF,et al. Comparison and evaluation of annual NDVI time series in China derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 products. Sensors,2017,17:1298-1309
[23] Wang JB,Dong JW,Liu JY,et al. Comparison of gross primary productivity derived from GIMMS NDVI3g,GIMMS,and MODIS in Southeast Asia. Remote Sensing,2014,6:2108-2133
[24] Fensholt R,Rasmussen K,Nielsen TT,et al. Evaluation of earth observation based long term vegetation trends:Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS,Terra MODIS and SPOT VGT data. Remote Sensing of Environment,2009,113:1886-1898
[25] Gallo K,Ji L,Reed B,et al. Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data. Remote Sensing of Environment,2005,99:221-231
[26] Liu S(刘爽),Gong P(宫鹏). Change of surface cover greenness in China between 2000 and 2010. Chinese Science Bulletin(科学通报),2012,57(16):1423-1434(in Chinese)
[27] Pettorelli N,Vik JO,Mysterud A,et al. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution,2005,20:503-510
[28] An YZ,Gao W,Gao ZQ,et al. Trend analysis for evaluating the consistency of Terra MODIS and SPOT VGT NDVI time series products in China. Frontiers of Earth Science,2015,9:125-136
[29] Yang J(杨嘉),Guo N(郭铌),Huang L-N(黄蕾诺),et al. Analyses on MODIS-NDVI index saturation in northwest China. Plateau Meteorology(高原气象),2008,27(4):896-903(in Chinese)
[30] Chen Y-H(陈艳华),Zhang W-C(张万昌). Effects of vegetation types on TVDI:A case study of Heihe Oasis. Remote Sensing Technology and Application(遥感技术与应用),2007,22(6):700-706(in Chinese)
[2] Guo N(郭铌). Vegetation index and its research progress. Arid Meteorology(干旱气象),2003,21(4):71-75(in Chinese)
[3] Suo Y-X(索玉霞),Wang Z-X(王正兴),Liu C(刘闯),et al. Correlation analysis between vegetation index and air temperature and precipitation in Central Asia from 1982 to 2002. Resources Science(资源科学),2009,31(8):1422-1429(in Chinese)
[4] Fabio F,Christian R,Tobias J,et al. Alpine grassland phenology as seen in AVHRR, VEGETATION, and MODIS NDVI time series:A comparison with in situ measurements. Sensors,2008,8:2833-2853
[5] Wang Z-P(王志鹏),Zhang X-Z(张宪洲),He Y-T(何永涛),et al. Responses of normalized difference vegetation index(NDVI)to precipitation changes on the grassland of Tibetan Plateau from 2000 to 2015. Chinese Journal of Applied Ecology(应用生态学报),2018,29(1):75-83(in Chinese)
[6] Zuo L(左璐),Wang H-J(王焕炯),Liu R-G(刘荣高),et al. Differences of vegetation phenology monitoring by remote sensing based on different spectral vegetation indices. Chinese Journal of Applied Ecology(应用生态学报),2018,29(2):599-606(in Chinese)
[7] Liu Y(刘远),Zhou M-C(周买春). Comparative analysis of AVHRR,SPOT-VGT and MODIS NDVI remote sensing data in Hanjiang River Basin. Journal of South China Agricultural University(华南农业大学学报),2015,36(1):106-112(in Chinese)
[8] Beck HE,McVicar TR,Dijk A,et al. Global evaluation of four AVHRR-NDVI data sets:Intercomparison and assessment against Landsat imagery. Remote Sensing of Environment,2011,115:2547-2563
[9] Zhang G,Zhang Y,Dong J,et al. Green-up dates in the Tibetan Plateau have continuously advanced from1982 to 2011. Proceedings of the National Academy of Sciences of the United States of America,2013,110:4309-4314
[10] Fensholt R,Langanke T,Rasmussen K,et al. Greenness in semi-arid areas across the globe 1981-2007:An earth observing satellite based analysis of trends and drivers. Remote Sensing of Environment,2012,121:144-158
[11] Fensholt R,Proud SR. Evaluation of earth observation based global long term vegetation trends:Comparing GIMMS and MODIS global NDVI time series. Remote Sensing of Environment,2012,119:131-147
[12] Hou M-T(侯美亭),Zhao H-Y(赵海燕),Wang Z(王筝),et al. Comparative analysis of vegetation index in eastern China between GIMMS,VGT and MODIS. Remote Sensing Technology and Application(遥感技术与应用),2013,28(2):290-299(in Chinese)
[13] Du J-Q(杜加强),Shu J-M(舒俭民),Wang Y-H(王跃辉),et al. Comparison of MODIS,NDVI and GIMMS NDVI in the Tibetan Plateau. Chinese Journal of Applied Ecology(应用生态学报),2014,25(2):533-544(in Chinese)
[14] Steven MD,Malthus TJ,Baret F,et al. Intercalibration of vegetation indices from different sensor systems. Remote Sensing of Environment,2003,88:412-422
[15] Huete A,Didan K,Miura T,et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment,2002,83:195-213
[16] Zhang Y,Song C,Band LE,et al. Reanalysis of global terrestrial vegetation trends from MODIS products:Browning or greening? Remote Sensing of Environment,2017,191:145-155
[17] Yan X-Y(严晓瑜),Dong W-J(董文杰),He Y(何勇). Suitability analysis of different sensor data in monitoring wetland vegetation change in Ruoergai. Remote Sensing Technology and Application(遥感技术与应用),2008,23(3):300-304(in Chinese)
[18] Song F-Q(宋富强),Kang M-Y(康慕谊),Yang P(杨朋),et al. Difference analysis of normalized difference vegetation index between GIMMS,SPOT-VGT and MODIS in Northern Shaanxi Province. Journal of Beijing Forestry University(北京林业大学学报),2010,32(4):72-80(in Chinese)
[19] van Leeuwen WJD,Orr BJ,Marsh SE,et al. Multi-sensor NDVI data continuity:Uncertainties and implications for vegetation monitoring applications. Remote Sensing of Environment,2006,100:67-81
[20] Tucker CJ,Pinzon JE,Slayback DA,et al. An extended AVHRR 8-km NDVI dataset,compatible with MODIS and SPOT vegetation NDVI data. International Journal of Remote Sensing,2005,26:4485-4498
[21] Brown ME,Pinzon JE,Didan K,et al. Evaluation of the consistency of long-term NDVI time series derived from AVHRR,SPOT-Vegetation, Sea Wi FS, MODIS,and Land SAT ETM+sensors. IEEE Transactions on Geoscience and Remote Sensing,2006,44:1787-1793
[22] Guo XY,Zhang HY,Wu ZF,et al. Comparison and evaluation of annual NDVI time series in China derived from the NOAA AVHRR LTDR and Terra MODIS MOD13C1 products. Sensors,2017,17:1298-1309
[23] Wang JB,Dong JW,Liu JY,et al. Comparison of gross primary productivity derived from GIMMS NDVI3g,GIMMS,and MODIS in Southeast Asia. Remote Sensing,2014,6:2108-2133
[24] Fensholt R,Rasmussen K,Nielsen TT,et al. Evaluation of earth observation based long term vegetation trends:Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS,Terra MODIS and SPOT VGT data. Remote Sensing of Environment,2009,113:1886-1898
[25] Gallo K,Ji L,Reed B,et al. Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data. Remote Sensing of Environment,2005,99:221-231
[26] Liu S(刘爽),Gong P(宫鹏). Change of surface cover greenness in China between 2000 and 2010. Chinese Science Bulletin(科学通报),2012,57(16):1423-1434(in Chinese)
[27] Pettorelli N,Vik JO,Mysterud A,et al. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution,2005,20:503-510
[28] An YZ,Gao W,Gao ZQ,et al. Trend analysis for evaluating the consistency of Terra MODIS and SPOT VGT NDVI time series products in China. Frontiers of Earth Science,2015,9:125-136
[29] Yang J(杨嘉),Guo N(郭铌),Huang L-N(黄蕾诺),et al. Analyses on MODIS-NDVI index saturation in northwest China. Plateau Meteorology(高原气象),2008,27(4):896-903(in Chinese)
[30] Chen Y-H(陈艳华),Zhang W-C(张万昌). Effects of vegetation types on TVDI:A case study of Heihe Oasis. Remote Sensing Technology and Application(遥感技术与应用),2007,22(6):700-706(in Chinese)