2001-2008年甘南牧区草地地上生物量与载畜量遥感动态监测

摘要/Abstract

摘要： 草地地上生物量监测是草地资源空间格局动态研究的重要内容,也是草畜平衡综合分析的基础。利用2006-2008年甘南牧区草地调查资料和Terra/MODIS每日地表反射率产品MOD09GA,建立了草地地上生物量遥感反演模型,模拟分析了甘南州及各县市草地资源在2001-2008年期间的各旬、月和年的生物量及理论载畜量变化动态。研究结果表明, MODIS增强型植被指数EVI的乘幂函数可以较好地模拟甘南牧区草地地上的生物量鲜重,拟合模型平均估产精度为76.7%,可很好地模拟牧草生长状况较好时期(5-10月)的草地地上生物量变化动态。甘南牧区草地生长主要集中在5月上旬-10月下旬期间,草地旬最大地上生物量数字图像可以较客观地反映草地植被生长发育的总体规律。但是,个别旬生物量受大范围长时间阴雨多云天气状况及放牧家畜数量有较大变动情况的严重影响。2001-2008年不同草地类型的月最大生物量动态变化曲线均呈单峰抛物线形式,全州平均最大生物量均出现在7月,但不同年份产量达到最大值的月份有所变化,主要集中在7-8月。甘南州草地地上总生物量年度之间存在较大的差异。全州8年平均总地上生物量为109.31亿kg。2005年全州草地植被年总生物量最高,达129.1亿kg,其次为2006,2007和2002年,分别为113.2,110.7和109.0亿kg。由于气候条件和不同县市草地面积及生长状况等存在较大差异,其理论载畜量也存在显著差别。

Abstract: Monitoring grassland aboveground biomass (GAB) is not only an important content for the research of spatial patterns of grassland resources, but is also a basis for the integration analysis of the balance between grassland forage supply and livestock demand. Grassland investigation data from 2006-2008 and Terra/MODIS (Moderate-resolution Imaging Spectroradiometer) daily surface reflectance product of MOD09GA in Gannan pastoral area, were used to establish both a monitoring model of GAB, and the 10-day, monthly and yearly dynamics of biomass and theoretical livestock carrying capacity during 2001-2008 in Gannan Prefecture. And each county was simulated and analyzed. Results suggested that the power function of MODIS-EVI (Enhanced Vegetation Index) can best simulate the green yield of GAB in Gannan pastoral area. The mean precision of the monitoring model was 76.7%, which might simulate the GAB dynamics in the period from May to October when the grassland was at a good growing stage. It mainly concentrated in the period from the first 10-days of May to the third 10-days of October during the grassland growth time. During this period digital images of the maximum GAB in a 10-day period may objectively reflect the general rule of grassland growth, but a few of the digital images of the maximum GAB were severely affected by rainy or cloudy weather condition which lasted a long time and covered a large scale, with a considerable change in the quantity of grazing livestock. The dynamic curve of the monthly maximum GAB for each grassland type during 2001-2008 was characterized by a unimodal parabola form. The average maximum GAB appeared in July, but the month that the GAB reached the maximum value varied from year to year, mainly in the period from July to August. There were great differences in the overall biomasses in different years in the Gannan pastoral area. The average overall biomass during those years in the overall Prefecture was 109.31×10⁸ kg. The highest value appeared in 2005 (129.1×10⁸ kg), followed by 2006 and 2007, which reached 113.2×10⁸, 110.7×10⁸, and 109.0×10⁸ kg, respectively. Due to the differences of weather condition, grassland area and growth situation, there was a significant difference for the theoretical livestock carrying capacity in each county.

中图分类号:

S127
S812

梁天刚,崔霞²,冯琦胜,王莺,夏文韬. 2001-2008年甘南牧区草地地上生物量与载畜量遥感动态监测[J]. 草业学报, 2009, 18(6): 12-22.

LIANG Tian-gang, CUI Xia, FENG Qi-sheng, WANG Ying, XIA Wen-tao. Remotely sensed dynamics monitoring of grassland aboveground biomass and carrying capacityduring 2001-2008 in Gannan pastoral area[J]. Acta Prataculturae Sinica, 2009, 18(6): 12-22.

参考文献

[1] 王正兴, 刘闯, Huete A. 植被指数研究进展: 从AVHRR-NDVI到MODIS-EVI[J]. 生态学报, 2003, 23(5): 979-986.
[2] 王正兴, 刘闯, 陈文波, 等. MODIS增强型植被指数EVI与NDVI初步比较[J]. 武汉大学学报, 2006, 31(5): 407-427.
[3] Huete A, Didan K, Miura T, et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices[J]. Remote Sensing of Environment, 2002, 83: 195-213.
[4] 卢丽萍, 赵成义. 基于MODIS数据不同荒漠植被指数的空间变化研究——以新疆三工河流域为例[J]. 干旱区地理, 2005, 28(3): 381-385.
[5] 邢旗, 刘爱军, 刘永志. 应用MODIS－NDVI对草原植被变化检测研究[J]. 草地学报, 2005, 13(增刊): 15-19.
[6] 赵冰茹, 刘闯, 王晶杰, 等. 锡林郭勒草地MODIS植被指数时空变化研究[J]. 中国草地, 2004, 26(1): 1-8.
[7] 毕晓丽, 王辉, 葛剑平. 植被归一化指数(NDVI)及气候因子相关起伏型时间序列变化分析[J]. 应用生态学报, 2005, 16(2): 284-288.
[8] 王正兴, 刘闯, 赵冰茹, 等. 利用MODIS增强型植被指数反演草地地上生物量[J]. 兰州大学学报, 2005, 41(2): 10-15.
[9] 徐斌, 杨秀春, 陶伟国, 等. 中国草原产草量遥感监测[J]. 生态学报, 2007, 27(2): 405-413.
[10] Yang Y H, Fang J Y, Pan Y D, et al. Aboveground biomass in Tibetan grasslands[J]. Journal of Arid Environments, 2009, 73: 91-95.
[11] Zhao M S, Heinsch F A, Nemani R R, et al. Improvements of the MODIS terrestrial gross and net primary production global data set[J]. Remote Sensing of Environment, 2005, 95: 164-176.
[12] Turner D P, Ritts W D, Cohen W B, et al. Evaluation of MODIS NPP and GPP products across multiple biomes[J]. Remote Sensing of Environment, 2006, 102: 282-292.
[13] Li Z G, Yu G R, Xiao X M, et al. Modeling gross primary production of alpine ecosystems in the Tibetan Plateau using MODIS images and climate data[J]. Remote Sensing of Environment, 2007, 107: 510-519.
[14] Yang F, Ichii K, White M A, et al. Developing a continental-scale measure of gross primary production by combining MODIS and AmeriFlux data through Support Vector Machine approach[J]. Remote Sensing of Environment, 2007, 110: 109-122.
[15] Sims D A, Rahman A F, Cordova V D, et al. A new model of gross primary productivity for North American ecosystems based solely on the enhanced vegetation index and land surface temperature from MODIS[J]. Remote Sensing of Environment, 2008, 112: 1633-1646.
[16] Chasmer L, Barr A, Hopkinson C, et al. Scaling and assessment of GPP from MODIS using a combination of airborne lidar and eddy covariance measurements over jack pine forests[J]. Remote Sensing of Environment, 2009, 113: 82-93.
[17] Prieto B A, North P R, Barnsley M J, et al. Satellite-driven modelling of Net Primary Productivity (NPP): Theoretical analysis[J]. Remote Sensing of Environment, 2009, 113: 137-147.
[18] 姜立鹏, 覃志豪, 谢雯. 基于单时相MODIS 数据的草地退化遥感监测研究[J]. 中国草地学报, 2007, 29(7): 39-43.
[19] 韩爱惠. 用MODIS植被指数的时间序列分析提取荒漠化敏感区域的方法[J]. 林业资源管理, 2004, (1): 57-60.
[20] 刘勇洪, 牛铮. 基于MODIS遥感数据的宏观土地覆盖特征分类方法与精度分析研究[J]. 遥感技术与应用, 2004, 19(4): 217-224.
[21] 刘爱军, 韩建国. 利用遥感技术监测锡林郭勒天然草原利用强度方法初探[J]. 中国草地学报, 2007, 29(2): 70-74.
[22] 宋小宁, 赵英时. 应用MODIS卫星数据提取植被-温度-水分综合指数的研究[J]. 地理与地理信息科学, 2004, 20(2): 13-17.
[23] Cleugh H A, Leuning R, Mu Q Z, et al. Regional evaporation estimates from flux tower and MODIS satellite data[J]. Remote Sensing of Environment, 2007, 106(3): 285-304.
[24] 甘肃省草原总站. 甘肃草地资源[M]. 兰州:甘肃科学技术出版社, 1999.
[25] 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[M]. 北京: 中国科学技术出版社, 1996.
[26] 陈建华. 环境恶化:甘南州如何拉生态建设一把[J]. 执政决策, 2005, (2): 18-19.
[27] 洛桑·灵智多杰. 青藏高原甘南生态经济示范区研究[M]. 兰州:甘肃科学技术出版社, 2005.
[28] 王兮之, 杜国祯, 梁天刚, 等. 基于RS和GIS的甘南草地生产力估测模型构建及其降水量空间分布模式的确立[J]. 草业学报, 2001, 10(2): 95-102.
[29] 赵雪雁. 高寒牧区草地退化的人文因素研究——以甘南牧区玛曲县为例[J]. 草业学报, 2007, 16(6): 113-120.
[30] 仁青吉, 罗燕江, 王海洋, 等. 青藏高原典型高寒草甸退化草地的恢复——施肥刈割对草地质量的影响[J]. 草业学报, 2004, 13(2): 43-49.