Qiu Bingwen

Comparative spatio-spectral heterogeneity analysis using multispectral and hyperspectral airborne images

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.

Dynamic evaluation of regional land suitability based on GIS and neural networks

Sustainable land use is an important guarantee of sustainable development. Dynamic land suitability assessment can monitor the land quality at different time. A dynamic land suitability assessment research was carried out in Shizi mountain area of Wuhan city in China in 1982, 1994 and 1998. In this research, the plot was taken as the study area and the neural networks as the evaluation method. Relevant criteria for vegetable and orchard and suitability levels were defined. The levels were: very suitable, suitable, moderate suitable, and not suitable. The evaluation procedure was realized through MAPGIS software and C language programming. Results showed that land very suitable for vegetable was very small in 1982, above eighty percents areas were land suitable or moderate suitable for vegetable and they showed considerable increase. From 1982 to 1994, land very suitable for vegetable increased 29.12 hm occupying 66.72 percents. Land moderate suitable for vegetable dropped 62.52 hm, its ratio descended to 21.85%. From 1982 to 1994 and from 1994 to 1998, land well suitable for orchard gained a continuous decrease of 246.78 hm, with fifty percents. Land suitable for orchard showed a successive increase of 137.31 hm. Till 1998, 46.42 hm of land moderate suitable for orchard emerged. The vegetable plot area map and orchard area map was overlaid with its evaluating result map respectively. Results showed that, in vegetable plot area, Very suitable area increased 5.99 hm. Suitable area increased 15.58 hm. Moderate suitable area increased 17.47 hm, but its ratio dropped over thirty percents. In orchard area, well suitable area showed a continuous decrease of 31.87 hm, suitable area first increased then declined sharply, it dropped 22.42 hm. Moderate suitable area had successive increase of 45.90 hm.

Effect of spatial scale on regional land-use pattern analysis in different classification system and data sources

Study of spatial scale effect on regional land-use pattern analysis for construction of spatial model of regional land-use change entails consideration of regional land-use classification system selected and data source used. The effect characteristics of spatial scale on the results of regional land-use pattern analysis was investigated for two different classification systems and different data sources in terms of spatial autocorrelation by empirical study in the Fujian province of China. Fujian province and Longhai County, are selected representing two hierarchical management levels. At County level, two different data sources are used: the 1: 100,000 land use map interpreted from Landsat TM of 2000 and 1:10,000 land use surveying map of 2000. Results showed that all land uses in our study area shows strong positive spatial autocorrelation and VMI of most land uses are scale-dependent. VMI of most land uses decrease with increasing grain size except in Fujian province and VMI of regional land use from more coarse scale land use map decreases more sharply with increasing grain size. Characteristics of fractal dimension are similar to that of spatial autocorrelation in both Counties to a certain extent. When two or three land uses are combined into one, the fractal dimension of it is comparatively larger than the original ones but No general laws in terms of VMI were seen. There may be more variation of VMI of land uses in more detailed classification system. Reducing number of land-use for one classification system may diminish the loss of information of land use area across the range of scale and the effect of spatial scale on regional land-use analysis in certain extent.

Development and application of an agricultural geographic information system of Fujian Southern area

An agricultural geographic information system has been developed to support agricultural resource management, agricultural economic analysis in Zhangzhou area in Fujian Province, the Southeast of China. The system is based on SuperMap GIS technology, mathematics modeling and Visual Basic language. It has functions such as agricultural information displaying, editing, querying, searching, statistic and analysis, the village corporation management, agricultural economic analysis and crop introduction consulting. The paper first outlines its user requirements and system architecture. Then it describes the main functions and implementation technique. Finally, the application of the system is presented. A suitability evaluation of tea tree through multi-criteria evaluation and AHP method was conducted by the system.