Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index(NDVI) products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l'observation de la Terre(SPOT), Advanced Spaceborne Thermal Emission and Reflection Radiometer(ASTER) and Landsat Thematic Mapper(TM) images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor images. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical semivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisensor images with consideration of their nominal spatial resolution, image size and spectral bands.
The scale-location specific control on vegetation distribution was investigated through continuous wavelet transforms approaches in subtropical mountain-hill region, Fujian, China. The Normalized Difference Vegetation Index (NDVI) was calculated as an indicator of vegetation greenness using Chinese Environmental Disaster Reduction Satellite images along latitudinal and longitudinal transects. Four scales of variations were identified from the local wavelet spectrum of NDVI, with much stronger wavelet variances observed at larger scales. The characteristic scale of vegetation distribution within mountainous and hilly regions in Southeast China was around 20 km. Significantly strong wavelet coherency was generally examined in regions with very diverse topography, typically characterized as small mountains and hills fractured by rivers and residents. The continuous wavelet based approaches provided valuable insight on the hierarchical structure and its corresponding characteristic scales of ecosystems, which might be applied in defining proper levels in multilevel models and optimal bandwidths in Geographically Weighted Regression.
Knowledge of both vegetation distribution pattern and phenology changes is very important.Their complicated relationship with elevation and accessibility were explored through a geographically weighted regression(GWR) framework in Fujian province,China.The 16-day time series of 250 m Moderate Resolution Imaging Spectroradiometer(MODIS) Enhanced Vegetation Index(EVI) dataset from 2000 to 2010 was applied.Wavelet transform method was adopted to decompose the original time series and construct the annual maximum EVI and amplitude of the annual phenological cycle(EVI).Candidate explaining factors included topographic conditions,accessibility variables and proportions of primary vegetation types.Results revealed very strong positive influence from parameters of elevation and accessibility to big rivers and negative effect from accessibility to resident on both maximum EVI and phenological magnitude through ordinary linear least square(OLS) regression analysis.GWR analysis revealed that spatially,the parameters of topography and accessibility had a very complex relationship with both maximum EVI and phenology magnitude,as a result of the various combinations of environmental factors,vegetation composition and also intensive anthropogenic impact.Apart from the continuously increasing trend of phenology magnitude with increasing altitude,the influence of topography and accessibility on maximum EVI and phenological magnitude generally decreased,even from strongly positive to negative,with increasing altitude or distance.Specially,the most rapid change of correlation coefficient between them was observed within a low elevation or close distance;less variation was discovered within a certain range of medium altitude or distance and their relationship might change above this range.Non-stationary approaches are needed to better characterize the complex vegetation dynamic pattern in Mountain-hill Region.
Knowledge of spatio-spectral heterogeneity within multisensor remote sensing images across visible,near-infrared and short wave infrared spectra is important.Till now,little comparative research on spatio-spectral heterogeneity has been conducted on real multisensor images,especially on both multispectral and hyperspectral airborne images.In this study,four airborne images,Airborne Thematic Mapper,Compact Airborne Spectrographic Imager,Specim AISA Eagle and AISI Hawk hyperspectral airborne images of woodland and heath landscapes at Harwood,UK,were applied to quantify and evaluate the differences in spatial heterogeneity through semivariogram modelling.Results revealed that spatial heterogeneity of multisensor airborne images has a close relationship with spatial and spectral resolution and wavelength.Within the visible,near-infrared spectra and short wave infrared spectra,greater spatial heterogeneity is generally observed from the relatively longer wavelength in short wave infrared spectra.There are dramatic changes across the red and red edge spectra,and the peak value is generally examined in the red middle or red edge wavelength across the visible and near-infrared spectra for vegetation or non-vegetation landscape respectively.In all,for real multisensor airborne images,the change in spatial heterogeneity with spatial resolution will accord with the change of support theory depending on whether dramatic change exists across the corresponding wavelength.Besides,if with close spatial resolution,the spatial heterogeneity of multispectral images might be far from the overall integration of these bands from the hyperspectral images involved.A comparative assessment of spatio-spectral heterogeneity using real hyperspectral and multispectral airborne images provides practical guidance for designing the placement and width of a spectral band for different applications and also makes a contribution to the understanding of how to reconcile spatial patterns generated by multisensors.
