首页> 外文会议>Geoscience and Remote Sensing Symposium, 1996. IGARSS '96. 'Remote Sensing for a Sustainable Future.', International >Seasonal NDVI trajectories in response to disturbance: toward a spectral-temporal mixing model for tallgrass prairie
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Seasonal NDVI trajectories in response to disturbance: toward a spectral-temporal mixing model for tallgrass prairie

机译:响应扰动的季节性NDVI轨迹:建立高草草原的频谱-时间混合模型

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Natural and anthropogenic disturbance in tallgrass prairie communities can induce changes in plant species composition, including shifts in abundance of C/sub 3/ vs. C/sub 4/ lifeforms. The asynchronous seasonalities in greenness that C/sub 3/ and C/sub 4/ species exhibit should enable monitoring of their relative abundance using sensor derived vegetation indices, such as NDVI. The authors used close-range measurements made over 22 experimental. Plots at the Konza Prairie Research Natural Area (KPRNA) to evaluate seasonal trajectories in canopy greenness as a function of C/sub 3//C/sub 4/ ratio. NDVI data were collected from each plot at approximately ten day intervals throughout the 1995 growing season. Temporal trajectories were used to develop discriminant functions to model relative C/sub 3//C/sub 4/ abundances. The discriminant model yielded values of Kendall's /spl tau//sub b/ and Cohen's /spl kappa/ statistic of 0.794 and 0.781, indicating strong agreement between classes and an overall classification significantly better than random assignment. Results suggest the possibility of applying spectral-temporal mixture models derived from close-range sensing to larger scale monitoring of tallgrass prairie.
机译:高草草原社区的自然和人为干扰可以诱导植物物种组成的变化,包括C / sub 3 /与C / sub 4 /生物形式的丰度变化。 C / sub 3 /和C / sub 4 /物种表现出的绿色非同步季节应该能够使用传感器得出的植被指数(例如NDVI)来监视其相对丰度。作者使用了超过22个实验的近距离测量。在Konza Prairie Research Natural Area(KPRNA)上绘制图,以评估冠层绿色度随C / sub 3 // C / sub 4 /比率变化的季节性轨迹。在1995年整个生长季节中,大约每隔10天从每个地块收集NDVI数据。时间轨迹被用来发展判别函数,以模拟相对C / sub 3 // C / sub 4 /丰度。判别模型得出Kendall的/ spl tau // sub b /和Cohen的/ spl kappa /统计值分别为0.794和0.781,这表明类别之间的一致性强,总体分类明显优于随机分配。结果表明,有可能将近距离感测得到的光谱-时间混合模型应用于高草草原的大规模监测。

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