Spatial statistical techniques for aggregating point objects extracted from high spatial resolution remotely sensed imagery

被引：2

作者：

Nelson T. ^{[1
]}

Niemann K.O. ^{[2
]}

Wulder M.A. ^{[3
]}

机构：

[1] Wilfrid Laurier University, Dept. of Geography/Environ. Studies, Waterloo

[2] University of Victoria, Department of Geography, Victoria, BC V8W 3P5

[3] Canadian Forest Serv., Natural Resources Canada, Victoria, BC V8Z 1M5

来源：

Journal of Geographical Systems | 2002年 / 4卷 / 4期

关键词：

Aggregation; Feature extraction; Generalisation; Nearest neighbour statistics;

D O I：

10.1007/s101090300092

中图分类号：

学科分类号：

摘要：

Using a local maximum filter, individual trees were extracted from a 1 m spatial resolution IKONOS image and represented as points. The spatial pattern of individual trees was determined to represent forest age (a surrogate for forest structure). Point attributes, based on the spatial pattern of trees, were generated via nearest neighbour statistics and used as the basis for aggregating points into forest structure units. The forest structure units allowed for the mapping of a forested area into one of three age categories: young (1-20 years), intermediate (21-120 years), and mature (>120 years). This research indicates a new approach to image processing, where objects generated from the processing of image data (rather than pixels or spectral values) are subjected to spatial statistical analysis to estimate an attribute relating an aspect of forest structure.

引用

页码：423 / 433

页数：10

共 16 条

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