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ObjecKoriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico

机译:面向对象的图像分析,用于绘制新墨西哥州南部1937年至2003年的灌木丛侵害图

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Shrub encroachment into arid and semi-arid grasslands in the southwestern United States is of concern because increased shrub cover leads to declines in species diversity, water availability, grazing capacity, and soil organic matter. Although it is well known that shrubs have increased over time, we have little quantitative information related to the non-linear nature of this vegetation change over a particular period, On the Jornada Experimental Range (JER; USDA-ARS) and the adjacent Chihuahuan Desert Rangeland Research Center (CDRRC; New Mexico State University) in southern New Mexico, shrub increase has been measured with various ground survey techniques extending back to 1858. For this study, we used 11 aerial photos taken between 1937 and 1996 that covered a 150-ha study area and had sufficient resolution for shrub detection. A QuickBird satellite image provided coverage for 2003. We used image segmentation and object-based classification to monitor vegetation changes over time. Shrub cover increased from 0.9% in 1937 to 13.1% in 2003, while grass cover declined from 18.5% to 1.9%.. Vegetation dynamics reflected changes in precipitation patterns, in particular, effects of the 1951-1956 drought. Accuracy assessment showed that shrub and grass cover was underestimated due to the constraint of the pixel size. About 87% of all shrubs >2 m{sup}2 were detected, The use of object-based classification has advantages over pixel based classification for the extraction of shrubs from panchromatic aerial and high-resolution satellite imagery. Incorporating both spectral and spatial image information approximates the way humans interpret information visually from aerial photos, but has the benefit of an automated classification routine. Combining several scales of analysis in a hierarchical segmentation method is appropriate in an ecological sense and allows for determining shrub density in coarser level classes, Despite encountering difficulties in analyzing a greatly varying aerial photo data set, including variability in spectral and spatial resolutions, moisture conditions, time of year of observation, and appearance of grass cover, aerial photos provide an invaluable historic record for monitoring shrub encroachment into a desert grassland
机译:令人担忧的是,灌木丛被侵蚀进入美国西南部的干旱和半干旱草原,因为灌木丛覆盖面积的增加会导致物种多样性,水的可利用性,放牧能力和土壤有机质的下降。尽管众所周知灌木随时间增加,但是在Jornada试验场(JER; USDA-ARS)和邻近的奇瓦瓦沙漠,我们几乎没有定量信息与该植被在特定时期内的非线性变化有关。在新墨西哥州南部的兰德兰研究中心(CDRRC;新墨西哥州立大学),已通过多种可追溯至1858年的地面调查技术测量了灌木丛的生长。在本研究中,我们使用了1937年至1996年之间拍摄的11张航拍照片,覆盖了150-占研究面积,并具有足够的分辨率进行灌木检测。 QuickBird卫星图像提供了2003年的覆盖范围。我们使用图像分割和基于对象的分类来监视植被随时间的变化。灌木覆盖率从1937年的0.9%增加到2003年的13.1%,草覆盖率从18.5%下降到1.9%。植被动态反映了降水模式的变化,特别是1951-1956年干旱的影响。精度评估表明,由于像素大小的限制,灌木和草皮被低估了。在所有> 2 m {sup} 2的灌木中,大约有87%被检测到。从全色航空和高分辨率卫星图像中提取灌木,使用基于对象的分类优于基于像素的分类。结合光谱和空间图像信息可以使人们从航空照片中直观地理解信息,但具有自动分类程序的优势。从层次上讲,在生态学意义上将几种分析规模结合起来是合适的,并且可以确定较粗级别的灌木密度,尽管在分析变化很大的航空照片数据集时遇到困难,包括光谱和空间分辨率的变化,湿度条件,一年中的观察时间以及草皮的出现,航空照片提供了宝贵的历史记录,可用于监测灌木丛对沙漠草原的侵占

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