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Cover type classification and biomass estimation by spectral analysis

机译:通过光谱分析覆盖类型分类和生物量估计

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This paper was written within the context of scaling up forest attributes, especially cover type and biomass, from ground plot inventory data to near infrared aerial photos. The material used is represented by ground plots georeferenced on aerial photos. Areas of 150 by 150 m are decomposed into proportions of spectrally distinct land cover elements: shadow and sunlit. Pielou's non-randomness index is used as a surrogate of tree spatial distribution. Cover type is predicted with 71% of accuracy by blue, red, and green bands and by Pielou's index. Meanwhile, only the blue and green bands are significant explanatory variables of biomass with a poor accuracy. More intensive use of photo texture information should improve the biomass prediction.
机译:本文在缩放森林属性,尤其是覆盖类型和生物量的范围内写入,从地面绘图库存数据到近红外线照片。所用的材料由航空照片上的地造成的地图表示。 150×150米的区域分解成比例的光谱不同的陆地覆盖元件:阴影和阳光照射。 Pielou的非随机性索引用作树空间分布的代理。通过蓝色,红色和绿色频段和Pielou的指数预测覆盖类型的精度71%。同时,只有蓝色和绿色带是具有较差差的生物质的显着解释变量。更加密集的照片纹理信息应该改善生物质预测。

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