Abstract
Vegetation interpretation and classification is the core work of regional ecological monitoring and carbon sinks calculating. Different from traditional remote sensing data, the development of high resolution true colour map provides a new possibility of vegetation interpretation and classification, especially for scattered, small-scale vegetation distributions in city regions. In Hue, Saturation and Value (HSV) colour space, colour model and texture model are combined to extract vegetation features, adjusting weights of the two features as a whole to achieve a better identification effect. Based on the nearest neighbour method, the model matches the features of candidate images with typical training vegetation samples. The main researches and innovations are as fol- lows: (i) The research uses high resolution true colour map images to provide real-time and more convenient data, making the study less limited to low spatial resolution of sensing images. (ii) It explores vegetation cover in city regions in an effective way, which is dispersed in size, variable in type and difficult to be located pre- cisely. (iii) The results of simulation show that this method is feasible and the feature-weighted model im- proves the precision to 83.3 % around by adjusting weight parameters, much better than single feature model.
(iv) Combined with the annual Net primary productivity (NPP) values in different vegetation types, the carbon storage of carbon sinks in one area of 23,373 m2 is calculated, ranging from 9,000 - 12,000 kg, providing a new way to track the carbon footprints in city regions.
