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The green space information extraction is significant for study on urban remote sensing because of its ecological and socioeconomic functions. And with the traditional methods the precision is very low, we educe decision tree of extraction to raise the accuracy rate. We take Shanghai as a case study area from QUICKBIRD imagery, analyzing spectral characteristics of 4 multi-spectral bands. And we also...
We present a method of a hierarchical classification technique to distinguish street trees from the neighboring grasslands and roads based on high resolution remote sensing images. Street trees information is obtained based on full use of the spectral and textural characteristics of different objects with the help of available corresponding methods on the fused image of QuickBird panchromatic and...
Existing classification methods which are based on the homogeneous-region mostly involve the best segmentation scale choice. Using the so-called best segmentation scale to respond the subjective defined objects, it would not be the best way for classification. Therefore we propose a simple classification method with high precision. It is a new kind of multi-scale homogeneous-region model, fully uses...
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