J Integr Plant Biol. ›› 2003, Vol. 45 ›› Issue (10): 1146-1156.

• Research Articles • Previous Articles     Next Articles

Detecting Vegetation Fractional Coverage of Typical Steppe in Northern China Based on Multi-scale Remotely Sensed Data

LI Xiao-Bing, CHEN Yun-Hao*, SHI Pei-Jun, CHEN Jin   

Abstract:

One of the study objectives of global change is land use/cover change (LUCC) by using multi-scale remotely sensed data on global and regional scale. In this paper, field sample, digital camera, Landsat-ETM+ (ETM+, Enhanced Thematic Mapper) image and the National Oceanic and Atmospheric Administra-tion/the advanced very high resolution radiometer (NOAA/AVHRR) image were integrated to detect, simulate and analyze the vegetation fractional coverage of typical steppe in northern China. The results show: (1) Vegetation fractional coverage measured by digital camera is more precise than results mea-sured by other methods. It can be used to validate other measuring results. (2) Vegetation fractional coverage measured by 1 m2 field sample change fluctuantly for different observers and for different sample areas. In this experiment, the coverage is generally high compared with the result measured by digital camera, and the average absolute error is 9.92%, but two groups measure results, correlation coefficient r2 = 0.89. (3) Three kinds of methods using remotely sensed data were adopted to simulate the vegetation fractional coverage. Average absolute errors of the vegetation fractional coverage, measured by ETM+ and NOAA, are respectively 7.03% and 7.83% compared with the result measured by digital camera. When NOAA pixel was decomposed by ETM+ pixels after geometrical registry, the average absolute errors measured by this method is 5.68% compared with the digital camera result. Correction coefficients of three results with digital camera result r2 are respectively 0.78, 0.61and 0.76. (4) The result of statistic model established by NOAA-NDVI (NDVI, Normalized Difference Vegetation Index) and the vegetation fractional coverage mea-sured by digital camera show lower precision (r2 = 0.65) than the result of statistic model established by ETM+-NDVI and digital camera coverage then converted to NOAA image (r2 = 0.80). Pixel decomposability method improves the precision of measuring the vegetation fractional coverage on a large scale. This is a significant practice on scaling by using remotely sensed data. Integrated application of multi-scale re-motely sensed data in earth observation will be an important approach to promoting measuring precision of ecological parameters.

多尺度遥感综合监测我国北方典型草原区植被盖度
李晓兵  陈云浩  史培军  陈 晋

(1 . 北京师范大学资源科学研究所,北京师范大学环境演变与自然灾害教育部重点实验室,北京 1 0 0 8 7 5;2 . 日本国立环境研究所,筑波,日本)


摘要: 利用多尺度遥感影像综合进行全球和区域尺度的土地利用/覆盖变化(LUCC)研究是最近全球变化研究的重要方向之一。本文综合利用野外群落样方、数字相机、ETM+影像、NOAA/AVHRR影像,在遥感、GIS和GPS支持下,对我国北方典型草原区植被盖度进行了综合监测、模拟与分析。结果表明:(1) 利用经处理后的数字相机影像测量盖度的结果准确性较高,可以作为植被盖度测量的标准结果,反映真实的覆盖特征,并用以验证利用其它方法测量结果的精度。(2) 利用野外1 m2样方网格法目视估测的植被盖度结果变化较大,不稳定。本次实验中,与数字相机测量结果相比,样方估测的盖度普遍偏高,平均偏差为9.92%;但两者相关性较好(r 2=0.89)。(3) 采用Gutman模型ETM+影像、NOAA/AVHRR影像反演植被盖度的结果与数字相机测量结果偏差分别为7.03%、7.83%,ETM+像元分解NOAA像元后得到的植被盖度与数字相机测量结果偏差5.68%。三者与数字相机测量结果的相关系数r2分别为0.78、0.61和0.76。(4)利用野外实测植被盖度数据直接与NOAA-NDVI影像建立统计模型估算植被盖度的精度较低(r 2=0.65),而通过空间分辨率介于两者之间的ETM+影像进行转换后,该精度得到一定的提高(r 2=0.80)。利用像元分解的方法提高了大尺度植被盖度监测的精度,是利用遥感数据进行尺度转换研究的重要实践。多尺度遥感影像的综合对地观测对大区域上反演植被盖度有很好的促进作用。
关键词: 多尺度遥感;典型草原;植被盖度

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Key words: multi-scale remote sensing, typical steppe, vegetation fractional coverage

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