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A model-based approach to estimating forest area

机译:基于模型的森林面积估算方法

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摘要

A logistic regression model based on forest inventory plot data and transformations of Landsat Thematic Mapper satellite imagery was used to predict the probability of forest for 15 study areas in Indiana, USA, and 15 in Minnesota, USA. Within each study area, model-based estimates of forest area were obtained for circular areas with radii of 5 km, 10 km, and 15 km and were compared to design-based estimates based on inventory plot data. Precision estimates for the circular areas were also obtained using variance formulae developed for this application that incorporated spatial correlation among model predictions for individual pixels. The model-based estimates were generally comparable to the design-based estimates. The advantages of the model-based approach are that maps and small areas estimates may be obtained and the necessity of releasing exact plot locations for user-specific applications is alleviated. (c) 2006 Elsevier Inc. All rights reserved.
机译:基于森林清查样地数据和Landsat Thematic Mapper卫星图像变换的逻辑回归模型用于预测美国印第安纳州15个研究区和美国明尼苏达州15个研究区的森林概率。在每个研究区域内,针对半径分别为5 km,10 km和15 km的圆形区域,获得基于模型的森林面积估计值,并将其与基于盘点数据的基于设计的估计值进行比较。还使用为此应用程序开发的方差公式获得了圆形区域的精度估计,该方差公式在各个像素的模型预测之间合并了空间相关性。基于模型的估计通常可以与基于设计的估计相比。基于模型的方法的优点是可以获得地图和小面积估计,并且减轻了为特定于用户的应用发布精确的绘图位置的必要性。 (c)2006 Elsevier Inc.保留所有权利。

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