Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico

被引:382
作者
Laliberte, AS
Rango, A
Havstad, KM
Paris, JF
Beck, RF
McNeely, R
Gonzalez, AL
机构
[1] USDA ARS, Jornada Expt Range, Las Cruces, NM 88003 USA
[2] DigitalGlobe Inc, Longmont, CO 80501 USA
[3] New Mexico State Univ, Dept Anim & Range Sci, Las Cruces, NM 88003 USA
基金
美国国家科学基金会;
关键词
object-based classification; segmentation; shrub encroachment; desert grassland; aerial photography; satellite image;
D O I
10.1016/j.rse.2004.07.011
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Shrub encroachment into and 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(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. (C) 2004 Elsevier Inc. All rights reserved.
引用
收藏
页码:198 / 210
页数:13
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