[Objective] The study aimed to explore the degradation law and trend of artificial grassland. [Method] Taking the ryegrass （Lolium perenne） - white clover （ Trifolium repens） artificial grassland in Maiping Townsh...[Objective] The study aimed to explore the degradation law and trend of artificial grassland. [Method] Taking the ryegrass （Lolium perenne） - white clover （ Trifolium repens） artificial grassland in Maiping Township, Guizhou Province as the research object, the grassland vegetation of 40 quadrate from different areas （area around the sheep shed, hilltop, hillside, flatland at the foot of the hill） were analyzed by comparing the dominance and richness index. [ Result] Degradation of different degrees appeared in various areas of this artificial grassland. To be specific, the degradation of grassland around the sheep shed was not serious for less consumption by the sheep; however, the areas on the hilltop and hillside degenerated to the grassland types of dallis grass （ Paspalum dilatatum Poir. ） -Indian lovegrass （ Eragrostis pilosa） and dallis grass - cogongrass [ Imperata cylindrica （ Linn. ） Beauv. ], respectively, and the area at the foot of the hill degenerated to the grassland type dominated by garland chrysanthetnum （ Chrysanthemum coronarium L. ） and knotgrass （ Paspalum distichum L. ）. [ Conclusion ] This study provided a basis for grassland improvement as well as the efficient and sustainable utilization of grazing-type artificial grassland in South China.展开更多
An advanced edge-based method of feature detection and extraction is developed for object description in digital images. It is useful for the comparison of different images of the same scene in aerial imagery, for des...An advanced edge-based method of feature detection and extraction is developed for object description in digital images. It is useful for the comparison of different images of the same scene in aerial imagery, for describing and recognizing categories, for automatic building extraction and for finding the mutual regions in image matching. The method includes directional filtering and searching for straight edge segments in every direction and scale, taking into account edge gradient signs. Line segments are ordered with respect to their orientation and average gradients in the region in question. These segments are used for the construction of an object descriptor. A hierarchical set of feature descriptors is developed, taking into consideration the proposed straight line segment detector. Comparative performance is evaluated on the noisy model and in real aerial and satellite imagery.展开更多
基金Supported by National Key Technology R & D Program(2006BAD16B07) Fund of Science and Technology in Guizhou Province ([2008]2074)~~
文摘[Objective] The study aimed to explore the degradation law and trend of artificial grassland. [Method] Taking the ryegrass （Lolium perenne） - white clover （ Trifolium repens） artificial grassland in Maiping Township, Guizhou Province as the research object, the grassland vegetation of 40 quadrate from different areas （area around the sheep shed, hilltop, hillside, flatland at the foot of the hill） were analyzed by comparing the dominance and richness index. [ Result] Degradation of different degrees appeared in various areas of this artificial grassland. To be specific, the degradation of grassland around the sheep shed was not serious for less consumption by the sheep; however, the areas on the hilltop and hillside degenerated to the grassland types of dallis grass （ Paspalum dilatatum Poir. ） -Indian lovegrass （ Eragrostis pilosa） and dallis grass - cogongrass [ Imperata cylindrica （ Linn. ） Beauv. ], respectively, and the area at the foot of the hill degenerated to the grassland type dominated by garland chrysanthetnum （ Chrysanthemum coronarium L. ） and knotgrass （ Paspalum distichum L. ）. [ Conclusion ] This study provided a basis for grassland improvement as well as the efficient and sustainable utilization of grazing-type artificial grassland in South China.
文摘An advanced edge-based method of feature detection and extraction is developed for object description in digital images. It is useful for the comparison of different images of the same scene in aerial imagery, for describing and recognizing categories, for automatic building extraction and for finding the mutual regions in image matching. The method includes directional filtering and searching for straight edge segments in every direction and scale, taking into account edge gradient signs. Line segments are ordered with respect to their orientation and average gradients in the region in question. These segments are used for the construction of an object descriptor. A hierarchical set of feature descriptors is developed, taking into consideration the proposed straight line segment detector. Comparative performance is evaluated on the noisy model and in real aerial and satellite imagery.
