@inproceedings {528,
	title = {Design and establishment of multi-scale spatial information system based on regional planning and decision making},
	booktitle = {IEEE Geoscience and Remote Sensing Symposium},
	year = {2001},
	abstract = {<p>Fast development of Geomatics and network integrated technology demonstrates that spatial information are widely used in regional planning and decision making. Existing non-standardized multi-sources and multi-scales data have a shortage of spatial information sharing in both internal and external application departments or units, especially in the network era. A pilot regional planning and decision making spatial information system based on a standardized and network sharing technology is presented in this paper. The research area is composed of eight counties in Jinghong Region and Simao Region of Yunnan Province in China. Spatial information resources such as remote sensing, digital maps, and paper maps are collected from different departments. Statistics data such as agriculture, forest, earthquake hazard, ore, hydrogeology, ecology, transportation, population, tourism, and trade, etc. are the composition of the application system. The system will be mainly used by regional planners and managers in the province and the regions via Internet. The applications of general users are also considered. Geographic Metadata standardization for spatial information is used as an Internet engine between users and datasets. Arc/INFO and ArcView GIS are the basic software for information integration. WebGIS is used for spatial information sharing design and GeoMedia is accepted as a basic web software platform. Other software for multi-dimensional information display and management are designed and applied for virtual reality planning and application in the project</p>
},
	keywords = {agriculture, China, decision making, decision support systems, forest, geographic information system, geographic information systems, geomatics, geophysical measurement technique, geophysical signal processing, geophysical techniques, geophysics computing, GIS, Jinghong, land surface, land use, metadata, multi-dimensional information display, multiscale spatial information system, population, regional planning, Remote Sensing, sharing technology, Simao, tourism, town and country planning, vegetation, WebGIS, Yunnan Province},
	doi = {http://dx.doi.org/10.1109/IGARSS.2001.977131},
	author = {Y Zhao and D A. Clausi}
}
@article {575,
	title = {The effect of speckle filtering on scale-dependent texture estimation of a forested scene},
	journal = {IEEE Transactions on Geoscience and Remote Sensing},
	volume = {38},
	year = {2000},
	pages = {1160 - 1170},
	abstract = {<p>Spatial fluctuations in microwave backscatter may be an important piece of information in discriminating tree stands. However, the presence of speckle in synthetic aperture radar (SAR) image data is a barrier to the exploitation of image texture. The authors explored a new methodology that combines a recent adaptive speckle reduction algorithm by Lopes et al. (1990) with a generic texture estimation scheme. They investigated the claim that this filter was capable of preserving backscatter texture. To understand if speckle reduction was destroying backscatter texture, they compared the strength of the relationship between forest inventory parameters and image texture as a function of spatial scale for both filtered and unfiltered images. They used Radarsat Fine mode image data: single look resolution is approximately 8.5 m, and pixel spacing is 3 m. Their study area was northern Vancouver Island, B.C., on the west coast of Canada. For the unfiltered data, they found that the ability of image texture to predict the forest parameters decreased as the texture scale increased from 3 to 13 m, suggesting greater information content in the small scale texture. For the filtered data, this relationship was much weaker at small scales and was not a function of distance. Their results suggest that the speckle filter was not retaining small scale texture, which is consistent with the theoretical hypotheses underlying its multiplicative noise model. They also show that there is significant information in small state SAR image texture that may be used as an adjunct to other spatial information for discriminating tree stands in the temperate rain forest</p>
},
	keywords = {adaptive signal processing, adaptive speckle reduction algorithm, backscatter texture, forest, forested scene, forestry, generic texture estimation scheme, geophysical measurement technique, geophysical signal processing, geophysical techniques, image texture, land surface, microwave backscatter, radar imaging, radar remote sensing, remote sensing by radar, SAR, scale-dependent texture estimation, spatial fluctuations, speckle, speckle filtering, synthetic aperture radar, tree stand, vegetation mapping},
	issn = {0196-2892},
	author = {M J. Collins and J Wiebe and D A. Clausi}
}
