Relationship between spatial heterogeneity and wavelength in multisensor airborne images

Variogram has been utilized to exploring the spatial heterogeneity of remote sensing images,especially its association with spatial resolution.However,very few attentions have been drawn on evaluating the spatial heterogeneity of multisensor airborne imagery and its relationship with spectral wavelength.Therefore,an investigation was carried out on multisensor airborne images to determine the relation between spatial heterogeneity and spectral wavelength for woodland,grass,and urban landscapes by applying variogram modeling.The airborne thematic mapper(ATM),compact airborne spectrographic imager(CASI),and Specim AISA Eagle airborne images at Harwood Forest,Monks wood,Cambridge,and River Frome areas,UK,were utilized.Results revealed that(1)the red band contained greater spatial variability than near-infrared wavelengths and other visible wavebands;(2)there was a steep gradient at the red edge in reference to its spatial variability of multisensor airborne images;(3)only for natural landscape such as woodland and grass,near-infrared waveband contains greater within-scene variations than the blue and green bands;(4)compared with the discrepancy of spatial resolution introduced by multisensor images(ATM,CASI,and Eagle),the specific landscape and spectral bands were more important in determining heterogeneity by means of original visible,near-infrared bands,and normalized difference vegetation index(NDVI).These findings remained us to be caution when combining and interpreting spatial variability and spatial structures derived from airborne images with different spatial resolution and spectral wavelength.Additionally,the outcomes of this study also have considerable implications in terms of designing and choosing suitable images for different applications.

A two-step rectification algorithm for airborne linear images with POS data

Rectification for airborne linear images is an indispensable preprocessing step. This paper presents in detail a two-step rectification algorithm. The first step is to establish the model of direct georeference position using the data provided by the Po- sitioning and Orientation System (POS) and obtain the mathematical relationships between the image points and ground reference points. The second step is to apply polynomial distortion model and Bilinear Interpolation to get the final precise rectified images. In this step, a reference image is required and some ground control points (GCPs) are selected. Experiments showed that the final rectified images are satisfactory, and that our two-step rectification algorithm is very effective.

SIFT-based automatic tie-points extraction for airborne InSAR images

The scale-invariant feature transform (SIFT) is often applied to extract tie-points for airborne SAR images. When a pair of airborne SAR images differs with look angles obviously, shadow sizes and shapes of same objects will differ obviously. In main and slave SAR images, key-points around shadows often match as tie-points, although they are not homologous points. The phenomenon worsens the performance of SIFT on SAR images. On the basis of SIFT, a modified matching method is proposed to decrease the number of incorrect tie-points. High-resolution airborne SAR images are used in Experiments. Experiment results show that the proposed method is very effective to extract correct tie-points for SAR images.

An airborne pushbroom hyperspectral imager with wide field of view

An airborne pushbroom hyperspectrai imager （APHI） with wide field （42° field of view） is presented. It is composed of two 22° field of view （FOV） imagers and can provide 1304 pixels in spatial dimension, 124 bands in spectral dimension in one frame. APHI has a bandwidth ranging from 400 to 900 nm. The spectral resolution is 5 nm and the spatial resolution is 0.6 m at 1000-m height. The implementation of this system is helpful to overcome the restriction of FOV in pushbroom hyperspectral imaging in a more feasible way. The electronic and optical designs axe also introduced in detail.

Hydrocarbon Micro-Seepage Detection by Altered Minerals Mapping from Airborne Hyper-Spectral Data in Xifeng Oilfield,China

Hydrocarbon micro-seepage can cause oxidation reduction reactions and produce altered minerals in surface sediments and soft. The typical altered minerals mapping by their diagnostic spectral features on hyper-spectral images is an important tool for the petroleum exploration industry. In this study, the airborne hyper-spectral data were used to investigate the altered minerals induced by hydrocarbon micro-seepages by spectral feature fitting （SFF） in the loess coverage area of Xifeng Oflfield. The results re- veal that the distribution region of the altered minerals induced by hydrocarbon micro-seepage is larger than the known oilfield exploration area. The potential hydrocarbon micro-seepage region was also re- vealed by the distribution of altered minerals besides the known hydrocarbon area. A fast index was pro- posed by the absorption depths of clay and carbonate minerals for assessment of hydrocarbon micro- seepage. And it gave much clearer boundaries for the hydrocarbon micro-seepage in the loess coverage area than those by the altered mineral mapping. In addition, some field samples were analyzed by X-ray diffrac- tion （XRD） and atomic absorption spectrophotometer to validate the results. Within the extents of hydro- carbon micro-seepage, there are lower contents of ferric iron and higher contents of carbonate minerals in these samples. Therefore, it is satisfactory to have the airborne hyper-spectral data to outline the extents of hydrocarbon micro-seepage for further hydrocarbon exploration in the loess coverage area.

Analysis of vegetation indices derived from aerial multispectral and ground hyperspectral data

Aerial multispectral images are a good source of crop,soil,and ground coverage information.Spectral reflectance indices provide a useful tool for monitoring crop growing status.A series of aerial images were obtained by an airborne MS4100 multispectral imaging system on the cotton and soybean field.Ground hyperspectral data were acquired with a ground-based integration system at the same time.The Normalized Difference Vegetative Index(NDVI),Simple Ratio(SR),and Soil Adjusted Vegetation Index(SAVI)calculated from both systems were analyzed and compared.The information derived from aerial multispectral images has shown the potential to monitor the general growth status of crop field.The vegetation indices derived from both systems were significantly different(p-value was 0.073 atα=0.1 level)at the early growing stage of crops.The correlation coefficients of the image NDVI and ground NDVI were 0.3029 for soybean field and 0.338 for cotton field.SAVI and SR were not correlated.

Spectral characteristics of plant communities from salt marshes:A case study from Chongming Dongtan,Yangtze estuary,China

The spectral reflectance of recently formed salt marshes at the mouth of the Yangtze River,which are undergoing invasion by Spartina alterniflora,were assessed to determine the potential utility of remotely sensed data in assessing future invasion and changes in species composition.Following a review of published research on remote sensing of salt marshes,53 locations along three transects were sampled for paired data on plant species composition and spectral reflectance using a FieldSpecTM Pro JR Field Portable Spectroradiometer.Spectral data were processed concerning reflectance,and the averaged reflectance values for each sample were reanalysed to correspond to a 12-waveband bandset of the Compact Airborne Spectral Imager.The spectral data were summarised using principal components analysis(PCA)and the relationships between the vegetation composition,and the PCA axes of spectral data were examined.The first PCA axis of the reflectance data showed a strong correlation with variability in near infrared reflectance and‘brightness’,while the second axis was correlated with visible reflectance and‘greenness’.Total vegetation cover,vegetation height,and mudflat cover were all significantly related to the first axis.The implications of this in terms of the ability of remote sensing to distinguish the various salt marsh species and in particular the invasive species S.alterniflora were discussed.Major differences in species with various physiognomies could be recognised but problems occurred in separating early colonising S.alterniflora from other species at that stage.Further work using multi-seasonal hyperspectral data might assist in solving these problems.