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《Scandinavian Journal of Forest Research》2012,27(5):446-459
The mean tree height of 73 forest stands in a 1000 ha forest area was determined from canopy heights generated by automatic image matching using a digital photogrammetric workstation and digitized panchromatic aerial photographs with a scale of 1:15 000. First, the mean height of each stand was computed as the arithmetic mean of the quantile corresponding to the 75th percentile of the distribution of the canopy heights from the image matching within square grid cells with cell sizes of 236-400 m2. The mean heights from the image matching underestimated the true heights by 5.42 m. Secondly, field-measured mean tree heights of 165 georeferenced sample plots distributed systematically throughout the 1000 ha forest area were regressed against the mean heights derived from the image matching. The regression equations were used to predict the mean heights of the 73 stands. In very young forest stands, the predicted mean heights overestimated the true heights by 0.4 m and the precision was 0.9-1.0 m. In young and mature stands, the average difference between predicted height and ground-truth ranged between -1.6 and 0.5 m, and the precision ranged from 1.1 to 2.1 m. 相似文献
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黄荣莉 《农业图书情报学刊》2010,22(4):141-144
电子技术的发展,数字图书的出现,形成了阅读资源多元化发展的新趋势,使传统阅读资源受到强烈冲击和影响。虽然阅读的栽体在不断变化,但不变的是读者的需求,只要是有价值的资源,就是读者愿意接受的阅读资源。在相当长的时间内,传统阅读和数字阅读资源会优势互补、各显特色,共生共存。 相似文献
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平缓地带数字土壤制图中,环境协变量的选择是提高制图精度的关键。已有研究证明遥感影像可作为推理制图的辅助因子,而如何确定环境因子推理制图时各自的权重已成为现阶段研究的重点。选取湖北省麻城市乘马岗镇为研究区,采用3种特征筛选方法进行有效环境变量筛选,探索参与平原-丘陵混合区域制图的因子并确定其重要性,依据选择的相对稳定的指标,进一步探索提高土壤类型制图准确性的途径。根据141个野外独立样点的检验结果表明:在推理制图中,遥感因子在平原区域的重要性程度高于丘陵区域,且遥感因子中归一化植被指数(NDVI)和均值(Mean)较为稳定;基于递归特征算法的按地形推理制图精度最高为75.89%,分别高于ReliefF算法和基于Tree的特征筛选算法13.48%和4.97%;此外3种特征筛选算法制图结果中,按地形因子分区制图的精度均高于整体区域制图。因此,遥感因子作为辅助手段参与推理过程可有效提高制图精度。本研究采用的特征挖掘与机器学习算法对提升土壤制图精度具有一定的理论意义。 相似文献
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文章通过对目前图书馆在资源建设中存在的主要问题进行了分析,并对资源整合的现有模式、存在的难点以及对资源整合研究中的问题,应采取推进的措施进行了论述。 相似文献
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Toru Kohama Nobuya Mizoue Satoshi Ito Akio Inoue Kotaro Sakuta Hiroyuki Okada 《Journal of Forest Research》2006,11(4):235-242
We examined the extent to which direct and indirect measures of light and microsite conditions could explain variation in
tree height and diameter at the base of 6-year-old Cryptomeria japonica trees planted in a group selection opening of about 0.32 ha on a steep slope at Shiiba, Miyazaki Prefecture, southern Japan.
We first used the gap light index (GLI) and soil thickness (ST) as directly measured indices. For an indirect measure of light, we used a between-cohort competition index (BCI) estimated from the position and total height of residual trees. For indirect measures of microsite, we examined topographic
indices (slope, plan and profile curvature, average slope gradient, and relative elevation) derived from digital elevation
models (DEMs) with different resolutions ranging from 2 to 10 m. The multiple linear regression using GLI and ST explained about 45% of variation in tree size, while simple regression using only GLI explained about 35%. The contribution of ST was about half of GLI. The multiple regressions using BCI and the topographic indices did not explain any more variation than using BCI alone (R
2 of about 0.26). We conclude that microsite conditions with shallower soil and steeper slope have negative effects on tree
growth in group selection openings, although the relative importance is smaller than light conditions. More comprehensive
studies considering several openings with more heterogeneous topography including different species are needed to generalize
our growth prediction using the indirect measures, which are useful for practical forest management. 相似文献
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