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Down scaling vegetation fraction by fusing multi-temporal MODIS and Landsat data

机译:通过融合多时相MODIS和Landsat数据降低植被比例

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Vegetation fraction is an important indicator of ecosystem change, a high spatial and temporal resolution vegetation fraction product was essential in many spatially distributed models. Recent developments of coarse resolution remote sensing (e.g. MODIS) provide the potential to estimate the vegetation fraction with a high temporal resolution. However, coarse resolution products usually provide insufficient spatial resolution to fully characterize the heterogeneity of vegetation fraction at the local scale. Successful downscaling of vegetation fraction to high spatial resolution would be indispensable for describing the vegetation fraction difference in regional studies. A new downscaling approach is developed by fusing multitemporal MODIS and Landsat TM data based on the assumption that a simple scale-invariant linear relationship exist between vegetation fraction and NDVI. Land cover map was incorporated for refining Landsat scale pixels to determine the transformation coefficients. The downscaled vegetation fraction was validated through the comparison with field measured vegetation fraction. The results shows that the new proposed downscaling method was effective, the accuracy of the result was significantly improved, while the vegetation type information was took into consideration.
机译:植被分数是生态系统变化的重要指标,在许多空间分布模型中,高时空分辨率的植被分数乘积是必不可少的。粗分辨率遥感技术(例如MODIS)的最新发展提供了以高时间分辨率估算植被比例的潜力。然而,粗分辨率产品通常无法提供足够的空间分辨率来充分表征局部尺度上植被部分的异质性。成功地将植被比例缩小到高空间分辨率对于描述区域研究中的植被比例差异将是必不可少的。通过在植被比例和NDVI之间存在简单的尺度不变线性关系的假设下,通过融合多时间MODIS和Landsat TM数据,开发了一种新的降尺度方法。合并了土地覆盖图以完善Landsat比例像素,以确定变换系数。通过与实地测得的植被比例进行比较来验证缩小的植被比例。结果表明,提出的新的降尺度方法是有效的,结果的准确性得到了显着提高,同时考虑了植被类型信息。

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