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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Comparison of Landsat and Land-Based Phenology Camera Normalized Difference Vegetation Index (NDVI) for Dominant Plant Communities in the Great Basin
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Comparison of Landsat and Land-Based Phenology Camera Normalized Difference Vegetation Index (NDVI) for Dominant Plant Communities in the Great Basin

机译：大盆地主要植物群落的Landsat和基于陆地的物候相机标准化差异植被指数（NDVI）的比较

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Phenology of plants is important for ecological interactions. The timing and development of green leaves, plant maturity, and senescence affects biophysical interactions of plants with the environment. In this study we explored the agreement between land-based camera and satellite-based phenology metrics to quantify plant phenology and phenophases dates in five plant community types characteristic of the semi-arid cold desert region of the Great Basin. Three years of data were analyzed. We calculated the Normalized Difference Vegetation Index (NDVI) for both land-based cameras (i.e., phenocams) and Landsat imagery. NDVI from camera images was calculated by taking a standard RGB (red, green, and blue) image and then a near infrared (NIR) plus RGB image. Phenocam NDVI was calculated by extracting the red digital number (DN) and the NIR DN from images taken a few seconds apart. Landsat has a spatial resolution of 30 m2, while phenocam spatial resolution can be analyzed at the single pixel level at the scale of cm2 or area averaged regions can be analyzed with scales up to 1 km2. For this study, phenocam regions of interest were used that approximated the scale of at least one Landsat pixel. In the tall-statured pinyon and juniper woodland sites, there was a lack of agreement in NDVI between phenocam and Landsat NDVI, even after using National Agricultural Imagery Program (NAIP) imagery to account for fractional coverage of pinyon and juniper versus interspace in the phenocam data. Landsat NDVI appeared to be dominated by the signal from the interspace and was insensitive to subtle changes in the pinyon and juniper tree canopy. However, for short-statured sagebrush shrub and meadow communities, there was good agreement between the phenocam and Landsat NDVI as reflected in high Pearson’s correlation coefficients (r > 0.75). Due to greater temporal resolution of the phenocams with images taken daily, versus the 16-day return interval of Landsat, phenocam data provided more utility in determining important phenophase dates: start of season, peak of season, and end of season. More specific species-level information can be obtained with the high temporal resolution of phenocams, but only for a limited number of sites, while Landsat can provide the multi-decadal history and spatial coverage that is unmatched by other platforms. The agreement between Landsat and phenocam NDVI for short-statured plant communities of the Great Basin, shows promise for monitoring landscape and regional-level plant phenology across large areas and time periods, with phenocams providing a more comprehensive understanding of plant phenology at finer spatial scales, and Landsat extending the historical record of observations.
机译：植物物候学对于生态相互作用很重要。绿叶的时间和发育，植物的成熟度和衰老会影响植物与环境的生物物理相互作用。在这项研究中，我们探索了陆地相机和卫星物候指标之间的一致性，以量化大盆地半干旱沙漠地区的五种植物群落类型中的植物物候和物候日期。分析了三年的数据。我们计算了陆基相机（即现象）和Landsat影像的归一化植被指数（NDVI）。通过拍摄标准RGB（红色，绿色和蓝色）图像，然后拍摄近红外（NIR）加RGB图像来计算摄像机图像的NDVI。通过从相隔数秒拍摄的图像中提取红色数字（DN）和NIR DN来计算Phenocam NDVI。 Landsat的空间分辨率为30 m 2 ，而phenocam的空间分辨率可以在cm 2 的尺度上在单个像素级别进行分析，或者可以使用可以扩展到1 km 2 。在本研究中，使用了感兴趣的苯酚摄像区域，该区域近似至少一个Landsat像素的大小。在状态良好的松树和杜松林地中，即使使用国家农业影像计划（NAIP）图像解释了松树和杜松与分光镜中的空隙之间的比例覆盖率，phenocam和Landsat NDVI之间在NDVI中也没有达成一致数据。 Landsat NDVI似乎受来自空间信号的支配，并且对松树和杜松树冠的细微变化不敏感。但是，对于矮化的鼠尾草灌木和草甸群落，酚醛清漆和Landsat NDVI之间有很好的一致性，这反映在较高的Pearson相关系数（r> 0.75）上。由于每天拍摄的图像对现象的临时分辨率更高，而Landsat的返回天间隔为16天，因此phenocam数据在确定重要的物候期方面提供了更多实用性：季节开始，季节高峰和季节结束。可以通过现象的高时间分辨率获得更具体的物种级信息，但仅适用于有限的站点，而Landsat可以提供其他平台无法比拟的数十年历史和空间覆盖率。 Landsat和phenocam NDVI之间的协议针对大盆地的短期植物群落显示了在大面积和较长时期内监视景观和区域级植物物候的希望，其中酚醛清澈的植物可以在更精细的空间尺度上更全面地了解植物物候和Landsat扩展了观测的历史记录。

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