| Eucalyptus is one of rapid growing species duiring the development of plantations in our country because of strong adaptability, rapid growth, high yield, wide useness, high economic benefit, and so on, which is successedfully introduced and fastly developed in our country. In order to meet the demand of intensive management, we timely, accurately need to know the amount, quanlity, the dynamic information on growth and decline of Eucalyptus. Due to the characteristics of macroscopy, periodicity, advancement, and rapidity, the remote sensing technology is widely used to survey and monitoring of forest resource. The high resolution remote sensing not only gets the spectral information on objects, but can obtain the geometric structure and textural feature. Therefore, it has the unique superiority on survey and monitoring of forest resource.Forest resources have multi-scale hierarchical structre, and multi-scale is one of fundamental characteristics. In general, forest resources information of one level always appears at some scale. Consequently, the optimal scale is needed to search when forest resources information of a level is extracted. We need to ascertain an optimal scale domain, not a single optimal scale due to the complexity of forest species, spatial heterogenicity caused by tree ages and growth density, and so on. Distinct spatial heterogenicity will appear because of the differenent time of cut, and the spatial difference in tree age and growth density of eucalyptus, Spatial heterogenicity is one of primary factors, which results in spatial scale effect. How to changes spatial heterogenicity of information on forest resource with the spatial scale? Can we remove the scale effect and improve the accuracy when forest remote sensing information is extracted if considering spatial heterogenicity?Typical area of eucalyptus forest in Beibu gulf was selected in the paper. In order to discriminate and extract remote sensing information of eucalyptus forest, high resolution remote sensing imagery data of GeoEye-1 was employed. The object oriented method was used to discriminate and extract remote sensing information of eucalyptus forest based on the spectral and spatial textural characteristics of eucalyptus forest. The optimal scale domain of eucalyptus forest remote sensing identification was tried to be found by means of classification accuracy based on the different spatial resolution imageries which modeled by using GeoEye-1 image. The spatial heterogenecity of remote sensing information features of eucalyptus forest was analyzed and discussed. In order that attempte to get more precise mapping of leaf area index of eucalyptus forest, spatial heterogenecity would be considered. Some conclusions as follows were come to:Firstly, the spatial heterogenecity index (SHI) was proposed, which is able to quantificationally describe the spatial heterogenecity of arbitrary area, involved individual pixel. It is defined as the sum of absolute difference between value of a pixel and its eight-neighbour pixels, and the average of spatial heterogenecity index of entire image or local image denote the SHI of those. Each 300 x 300m subset image was selected from residential area, tidal-flat area, eucalyptus forest and natural forest of GeoEye-1 image based on the different spatial resolution imageries which modeled by using GeoEye-1 image, respectively. The spatial heterogenecity of those subset images were quantitatively presented by means of spatial heterogenecity index in the paper proposed. The results showed that SHI of residential area, tidal-flat area and forest at some spatial resolution were declined, respectively, and the SHI of those objects were all decreased as the spatial resolution become coase, but the decreasing extent was not the same. The above research was the same as real world. Therefore it is suggests that SHI can effectively describe spatial heterogenecity feature of land surface.Secondly, there are significant spatial heterogenecity for remote sensing characteristics of eucalyptus. Spatial heterogenecity of spectral, biological and spatial properties of eucalyptus were analysized and the spatial heterogenecity of each feature change with spatial scale were also discussed. The red band reflectance, near infrared band reflectance and NDVI were chosen for spectral characteristics. The spatial heterogenecity of those spectral properties were all decreased, and the coaser spatial resolution, the less decreased extent of spatial heterogenecity. The leaf area index of eucalyptus was analysized for the biological feature, and its spatial heterogenecitywas also declined when the spatial resolution became coaser. Each textural parameters of eculyptus changed as spatial resolution changed, and the change trend didn't agree, but the reason was the same, i.e., when the spatial heterogeneciy became weaker, the texture changed into thinner and simpler. The spatial heterogeneciyt of each textural image became stronger with the spatial heterogenecity coaser.Thirdly, there have potential of discerning and extracting eculyptus by high resolution remote sensing, and the spatial resolution finer, the more accuracy. It was suggested that less than 15 meter for spatial resolution ws best in order to identify eucalyptus by remote sensing approach. The 5m,10m,15m,20m and 30m spatial resolution imageries were modeled by using simple average method based on GeoEye image at 2m spatial resolution, and then their cability to discern and extract typical objects, especial eucalyptus at study area, were assessed. The results showed that the GeoEye image data was able to effectively identify and extract eucalyptus forest. The object oriented method was employed to classify for GeoEye high resolution image, which can make use of spectral and spatial characteristics of objects, and then the cabiltiy of distinguishing eucalyptus were enchanced, which was controlled by the spatial resolution. In addition, when the spatial resolution is less than 15m, the remotely sensened image can effectively discriminate eucalyptus.Finally, considering spatial heterogenecity, the scale transformation models of leaf area index were established and the spatial scale error of eucalyptus leaf area index could be evidently corrected, and this will achieve the precise mapping of leaf area index. The spatial scale effects of reflectance, vegetation index and leaf area index were discussed, respectively, and the spatial scale effects of vegetation index, e.g., DVI and NDVI, and leaf area index were theoretically inferred and modeled. It was found that the spatila heterogenecity is one of primary factors that results in their spatial scle effects except non-linear effect of algorithm by validation using the modeled images at different spatial resolution. Based on the high resolution GeoEye image at spatial resolution, the spatial heterogenecity of eucalyptus forest was depicted by means of spatial heterogenecity index. The paper set up a spatial scale transformation model of leaf area index based on the significant correlation relationship between spatial heterogeneity index and scale error of properties of eucalyptus. The results showed that the model associated with spatial heterogeneity index could effectively correct the scale error of leaf area index of coarse resolution... |
PDF Full Text Request