草业学报 ›› 2020, Vol. 29 ›› Issue (12): 5-16.DOI: 10.11686/cyxb2020240
赵慧芳1,2(), 李晓东1,2(), 张东1,2, 校瑞香1,2
收稿日期:
2020-05-26
修回日期:
2020-08-05
出版日期:
2020-12-28
发布日期:
2020-12-28
通讯作者:
李晓东
作者简介:
Corresponding author. E-mail: lixd16@lzu.edu.cn基金资助:
Hui-fang ZHAO1,2(), Xiao-dong LI1,2(), Dong ZHANG1,2, Rui-xiang XIAO1,2
Received:
2020-05-26
Revised:
2020-08-05
Online:
2020-12-28
Published:
2020-12-28
Contact:
Xiao-dong LI
摘要:
利用EOS/MODIS植被指数产品(NDVI)、实测草地地上生物量和气象监测资料,结合实测资料和NDVI之间的关系建立了青海省草地地上生物量卫星遥感估算模型,并通过研究青海省气温和降水量变化特征分析了影响草地地上生物量的主要因素。结果表明:在草地生长季,生态监测站草地地上生物量与NDVI之间具有较好的正相关关系(P<0.01)。利用模型估算的青海省草地地上生物量在2003-2017年表现出弱的增加态势,2003年平均草地地上生物量最低,仅为2622 kg·hm-2,2010年最大,达3252 kg·hm-2; 2003-2017年,青海省草地地上生物量变化表现出明显的空间分布特征,从东南向西北逐渐递减;其中,青海省果洛州东南部、玉树州南部、黄南州东南部和海北州东南部草地地上生物量最高;西北部的柴达木盆地最低;2003-2017年青海省绝大多数地区草地地上生物量均呈现保持不变或者趋好的变化特征,其中曲麻莱、都兰以及甘德等地区部分草地地上生物量明显减少。气温升高热量条件充足的背景下,青海省草地受降水量增多带来的水分条件趋好的有利影响,对高寒地区草地植被的生长发育起到了促进作用,最终导致草地NDVI升高,地上生物量增加。
赵慧芳, 李晓东, 张东, 校瑞香. 基于MODIS数据的青海省草地地上生物量估算及影响因素研究[J]. 草业学报, 2020, 29(12): 5-16.
Hui-fang ZHAO, Xiao-dong LI, Dong ZHANG, Rui-xiang XIAO. Aboveground biomass in grasslands in Qinghai Province estimated from MODIS data and its influencing factors[J]. Acta Prataculturae Sinica, 2020, 29(12): 5-16.
草地类型 Grassland type | 高寒草甸 Alpine meadow steppe | 高寒草原 Alpine steppe | 温性草原 Temperate steppe | |||
---|---|---|---|---|---|---|
NDVI | NDVI-9 | NDVI | NDVI-9 | NDVI | NDVI-9 | |
相关系数Correlation coefficient | 0.710* | 0.825** | 0.638 | 0.778** | 0.696 | 0.763** |
样本数Sample number | 203 | 200 | 50 | 29 | 42 | 28 |
表1 各种草地类型地上生物量与植被指数的相关分析
Table 1 Correlation analysis between various grassland types and vegetation index
草地类型 Grassland type | 高寒草甸 Alpine meadow steppe | 高寒草原 Alpine steppe | 温性草原 Temperate steppe | |||
---|---|---|---|---|---|---|
NDVI | NDVI-9 | NDVI | NDVI-9 | NDVI | NDVI-9 | |
相关系数Correlation coefficient | 0.710* | 0.825** | 0.638 | 0.778** | 0.696 | 0.763** |
样本数Sample number | 203 | 200 | 50 | 29 | 42 | 28 |
草地类型 Grassland type | 地上生物量遥感监测 模型Biomass model | 样本容量 Sample size | 相关系数 Correlation coefficient | F值 F value | 显著性 Significance |
---|---|---|---|---|---|
高寒草甸Alpine meadow steppe | Y=13.37e4.75X | 200 | 0.825** | 935.798 | 0.000 |
高寒草原Alpine steppe | Y=28.31e2.71X | 29 | 0.778** | 94.745 | 0.000 |
温性草原Temperate steppe | Y=7.49e4.61X | 28 | 0.763** | 83.914 | 0.000 |
表 2 各种草地类型地上生物量遥感监测模型
Table 2 Remote sensing monitoring model for aboveground biomass of various grassland types
草地类型 Grassland type | 地上生物量遥感监测 模型Biomass model | 样本容量 Sample size | 相关系数 Correlation coefficient | F值 F value | 显著性 Significance |
---|---|---|---|---|---|
高寒草甸Alpine meadow steppe | Y=13.37e4.75X | 200 | 0.825** | 935.798 | 0.000 |
高寒草原Alpine steppe | Y=28.31e2.71X | 29 | 0.778** | 94.745 | 0.000 |
温性草原Temperate steppe | Y=7.49e4.61X | 28 | 0.763** | 83.914 | 0.000 |
图6 研究区2003-2017年各类型草地(a)、温性草原(b)、高寒草原(c)和高寒草甸(d)地上生物量和NDVI变化特征
Fig.6 Characteristics of aboveground biomass and NDVI of various grassland types (a), temperate steppe (b), alpine steppe (c), and alpine meadow steppe (d) from 2003 to 2017 in study area
1 | Zhang L Y, Wang G, Bao L R. Temporal changes of MODIS-NDVI vegetation index and forge biomass in Xilinguole grassland-taking the change from April to September in 2005 as a sample. Pratacultural Science, 2008, 25(3): 6-11. |
张连义, 王刚, 宝路如. 锡林郭勒盟草地MODIS-NDVI植被指数和估产草地产量季节变化特征: 以2005年4-9月的变化为例. 草业科学, 2008, 25(3): 6-11. | |
2 | Li F X, Li X D, Zhou B R, et al. Effects of grazing intensity on biomass and soil physical and chemical characteristics in alpine meadow in the source of three rivers. Pratacultural Science, 2015, 32(1): 11-18. |
李凤霞, 李晓东, 周秉荣, 等. 放牧强度对三江源典型高寒草甸生物量和土壤理化特征的影响. 草业科学, 2015, 32(1): 11-18. | |
3 | Hou Y Y, Mao L X, Qian S, et al. Pasture production and its spatio-temporal distribution pattern in Qinghai Province: An estimations with remote sensing. Chinese Journal of Ecology, 2006, 25(11): 1428-1434. |
侯英雨, 毛留喜, 钱拴, 等. 青海省草地产量的遥感估算及其时空分布规律. 生态学杂志, 2006, 25(11): 1428-1434. | |
4 | Dong Y P, Wu X H, Rong Y P, et al. Grassland remote sensing monitoring technology. Beijing: Chemical Industry Press, 2005 |
董永平, 吴新宏, 戎郁萍, 等. 草原遥感监测技术. 北京: 化学工业出版社, 2005. | |
5 | Mao L X, Hou Y Y, Qian S, et al. Estimation of pasture output and livestock carrying capacity using remote sensing. Transactions of the Chinese Society of Agricultural Engineering, 2008, 24(8): 147-151. |
毛留喜, 侯英雨, 钱拴, 等. 草地产量的遥感估算与载畜能力研究. 农业工程学报, 2008, 24(8): 147-151. | |
6 | Yan L D, Yin Q J, Zhang H Z, et al. The applied research of remote sensing material in Qinghai grassland. Journal of Natural Resources, 2007, 22(4): 640-648. |
颜亮东, 殷青军, 张海珍, 等. 遥感资料在青海草地资源监测及评价中的应用研究. 自然资源学报, 2007, 22(4): 640-648. | |
7 | Ge J, Meng B P, Yang S X, et al. Monitoring of above-ground biomass in alpine grassland based on agricultural digital camera and MODIS remote sensing data: A case study in the Yellow River Headwater Region. Acta Prataculturae Sinica, 2017, 26(7): 23-34. |
葛静, 孟宝平, 杨淑霞, 等. 基于ADC和MODIS遥感数据的高寒草地地上生物量监测研究-以黄河源区为例. 草业学报, 2017, 26(7): 23-34. | |
8 | Chen Q, Zhao J, Yang J Y, et al. Remote sensing monitoring of biomass on desert grassland: A case study of Alxa League in Inner Mongolia. Chinese Journal of Grassland, 2020, 42(2): 105-116. |
陈琪, 赵健, 杨九艳, 等. 荒漠草场地上生物量的遥感监测-以内蒙古阿拉善盟为例. 中国草地学报, 2020, 42(2): 105-116. | |
9 | Liu M Y. Change of grassland aboveground biomass in the Three-River Headwater Region and analysis of its response to climate factors. Beijing: China University of Geosciences, 2019. |
刘美扬. 三江源区草地地上生物量变化及气候因素影响分析. 北京: 中国地质大学, 2019. | |
10 | Du Y E, Liu B K, Guo Z G. Changes of forage biomass of grasslands during the growing season in the Qinghai-Tibetan Plateau based on MODIS data. Pratacultural Science, 2011, 28(6): 1117-1123. |
杜玉娥, 刘宝康, 郭正刚. 基于MODIS的青藏高原牧草生长季草地生物量动态. 草业科学, 2011, 28(6): 1117-1123. | |
11 | Huang J F, Wang X Z, Cai C X, et al. Natural grassland production monitoring using NOAA/AVHHRR data in the Northern part of Xingjiang Uygur Autonomous Region. Transactions of the Chinese Society of Agricultural Engineering, 2000, 16(2): 123-127. |
黄敬峰, 王秀珍, 蔡承侠, 等. 利用气象卫星AVHRR资料监测新疆北部天然草地产量. 农业工程学报, 2000, 16(2): 123-127. | |
12 | Li C, Cao Z Z, Li L X, et al. The research of remote sensing dynamic monitoring on grassland vegetation index seasonal variation. Desert and Oasis Meteorology, 2007(3): 26-29. |
李聪, 曹占洲, 李良序, 等. 草地植被指数季节变化的遥感动态监测研究. 沙漠与绿洲气象, 2007(3): 26-29. | |
13 | Chao Z H. Monitoring grassland in Aletai prefecture by using remote sensing. Lanzhou: Lanzhou University, 2004. |
钞振华. 阿勒泰地区天然草地的遥感监测, 兰州: 兰州大学, 2004. | |
14 | Fan J W, Shao Q Q, Liu J Y, et al. Assessment of effects of climate change and grazing activity on grassland yield in the Three River Headwaters Region of Qinghai-Tibet Plateau, China. Environmental Monitoring and Assessment, 2010, 170(1/2/3/4): 571-581. |
15 | Shao Q Q, Liu J Y, Fan J W, et al. Integrated assessment on the effectiveness of ecological conservation in Sanjiangyuan National Nature Reserve. Geographical Research, 2013, 32(9): 1645-1656. |
16 | Myneni R B, Keeling C D, Tucker C J, et al. Increased plat growth in the northern high latitudes from 1981 to 1991. Nature, 1997, 386(17): 698-702. |
17 | Guo Q, Hu Z M, Li S G, et al. Spatial variations in aboveground net primary productivity along a climate gradient in Eurasian temperate grassland: Effects of mean annual precipitation and its seasonal distribution. Global Change Biology, 2012, 18(12): 3624-3631. |
18 | Zhang Y X, Fan J W, Cao W, et al. Spatial and temporal dynamics of grassland yield and its response to precipitation in the Three River Headwater Region from 2006 to 2013. Acta Prataculturae Sinica, 2017, 26(10): 10-19. |
张雅娴, 樊江文, 曹巍, 等. 2006-2013年三江源草地产草量的时空动态变化及其对降水的响应. 草业学报, 2017, 26(10): 10-19. | |
19 | Zhang G S, Yan L D. The dynamic model of meadow grassland natural herbages yield forming in Qinghai Plateau and its application. Pratacultural Science, 1997, 14(2): 36-38. |
张国胜, 颜亮东. 青海高原草甸草场天然牧草产量形成的动态模式及应用. 草业科学, 1997, 14(2): 36-38. | |
20 | Yan L D. The yield forecasting model of natural herbage in Qinghai Highland. Meteorological Monthly, 1997(12): 53-55. |
颜亮东. 青海高原天然牧草产量预报方法及模式. 气象, 1997(12): 53-55. | |
21 | Zhong Z B, Yang L C, Liu H C, et al. The main shrubs aboveground biomass and effect factors in Yushu, Qinghai, China. Mountain Research, 2014, 32(6): 678-684. |
钟泽兵, 杨路存, 刘何春, 等. 青海玉树地区主要灌丛类型地上生物量及其影响因素. 山地学报, 2014, 32(6): 678-684. | |
22 | Yang S X, Feng Q S, Meng B P, et al. Temporal and spatial dynamics of alpine grassland biomass in the Three-River Headwaters Region. Pratacultural Science, 2018, 35(5): 956-968. |
杨淑霞, 冯琦胜, 孟宝平, 等. 三江源地区高寒草地地上生物量时空动态变化. 草业科学, 2018, 35(5): 956-968. | |
23 | Han B, Cao Y N, Guo Y, et al. Modeling aboveground biomass of alpine grassland in the Three-River Headwaters Region based on remote sensing data. Research of Environmental Sciences, 2017, 30(1): 67-74. |
韩波, 高艳妮, 郭杨, 等. 三江源区高寒草地地上生物量遥感反演模型研究. 环境科学研究, 2017, 30(1): 67-74. | |
24 | National Animal Husbandry and Veterinary General Station, Department of Animal Husbandry and Veterinary, Ministry of Agriculture of the People's Republic of China. Grassland resources in China. Beijing: China Science and Technology Press, 1996: 347-382. |
中华人民共和国农业部畜牧兽医司全国畜牧兽医总站. 中国草地资源. 北京: 中国科学技术出版社, 1996: 347-382. | |
25 | Wang Q C. Researches on the relationship between grass growth and meteorological condition and climatic situation evaluation. Chinese Journal of Agrometeorology, 1998, 19(3): 1-7. |
汪青春. 牧草生长发育与气象条件的关系及气候年景研究. 中国农业气象, 1998, 19(3): 1-7. | |
26 | Wei F Y. Modern climate statistical diagnosis and prediction technology. Beijing: China Meteorological Press, 2007. |
魏凤英. 现代气候统计诊断与预测技术. 北京: 气象出版社, 2007. | |
27 | Liu Y J, Yang Z D. Principles and algorithms of remote sensing information processing of MODIS. Beijing: Science Press, 2001. |
刘玉洁, 杨忠东. MODIS遥感信息处理原理与算法. 北京: 科学出版社, 2001. | |
28 | Liang Y, Wei Y R, Liu A J. Based on MODIS-NDVI of the application of remote sensing in natural grassland of Inner Mongolia grassland vegetatron conditions. Inner Mongolia Prataculture, 2009, 21(9): 40-44. |
梁燕, 魏玉荣, 刘爱军. 基于MODIS-NDVI的草地遥感在内蒙古天然草原植被状况中的应用. 内蒙古草业, 2009, 21(9): 40-44. | |
29 | Aerts R, Cornelissen J H C, Dorrepaal E, et al. Plant performance in a warmer world: General responses of plants from cold, northern biomes and the importance of winter and spring events. Plants and Climate Change, 2006, 41: 65-78. |
30 | Hu M Q, Mao F, Sun H, et al. Study of normalized difference vegetation index variation and its correlation with climate factors in the Three-River-Source Region. International Journal of Applied Earth Observation and Geoinformation, 2011, 13(1): 24-33. |
31 | Li C Y, Fan W T, Li G M, et al. Driving force analysis of changes in grassland coverage on the Qinghai-Tibet Plateau based on NDVI in 2000-2016. Acta Prataculturae Sinica, 2019, 28(10): 25-32. |
李重阳, 樊文涛, 李国梅, 等. 基于NDVI的2000-2016年青藏高原牧户草场覆盖度变化驱动力分析. 草业学报, 2019, 28(10): 25-32. |
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