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首页> 外文会议>International symposium on spatial accuracy assessment in natural resources and environmental science >Integrating Landsat-TM data with environmental data for classifying forest cover types and estimating their biomass
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Integrating Landsat-TM data with environmental data for classifying forest cover types and estimating their biomass

机译：将Landsat-TM数据与环境数据集成，以分类森林覆盖类型并估算其生物质

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Landsat-TM data (bands 3, 4, and 5) were integrated with environmental data (degree-day, vapour pressure deficit, precipitation, and soil water holding capacity) for classifying forest cover types and estimating their biomass at the resolution of approximately one ha. The study area presents a changing topography at its northern part, and a high variability in the stand structure and species composition at its southern part. It is composed of balsam fir, black spruce, intolerant hardwood, tolerant hardwood, mixed with hardwood dominance, mixed with coniferous dominance, and coniferous stands. The accuracy of these cover types classification by discriminant analysis varied from 15% (mixed with coniferous dominance) to 82% (tolerant hardwood). When these cover types were aggregated into mixed, hardwood, and coniferous stands, the accuracy of the classification increased to respectively 30, 80, and 93%. By reducing the area fragmentation, this aggregation increases the cover type areas so the greater the area involved in the forest parameter to be estimated, the greater becomes the proportion of explained variation. Regression models for estimating biomass by cover type are unbiased, but the proportions of explained variation are low varying from 11% to 30%.
机译：Landsat-TM数据（带3,4和5）与环境数据（学位，蒸汽压力缺陷，降水和土壤含水量）一体化，用于对森林覆盖类型进行分类并以大约一个分辨率估算它们的生物质哈。该研究领域在其北部的地形上提出了改变的地形，以及在其南部的实体结构和物种组成的高度变化。它由Balsam FIR，黑云杉，不宽容硬木，容忍硬木，与硬木优势混合，与针叶土的主导地位混合，并对面的立场。通过判别分析的这些覆盖物种分类的准确性从15％（与针叶酸层混合）变化至82％（耐受硬木）。当将这些覆盖物簇生聚集到混合，硬木和针叶树级时，分类的准确性分别增加到30,80和93％。通过减小区域碎片化，该聚集增加了覆盖类型区域，因此估计森林参数所涉及的面积越大，解释变化的比例越大。通过覆盖类型估计生物质的回归模型是无偏的，但解释的变化的比例从11％到30％都很平。

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