Storey Emanuel A, Stow Douglas A, Roberts Dar A
Department of Geography, San Diego State University, San Diego, CA, USA.
Department of Geography, University of California-Santa Barbara, Santa Barbara, CA, USA.
GIsci Remote Sens. 2020;n/a. doi: 10.1080/15481603.2019.1703287. Epub 2019 Dec 17.
Temporal trajectories of apparent vegetation abundance based on the multi-decadal Landsat image series provide valuable information on the postfire recovery of chaparral shrublands, which tend to mature within one decade. Signals of change in fractional shrub cover (FSC) extracted from time-sequential Normalized Difference Vegetation Index (NDVI) data can be systematically biased due to spatial variation in shrub type, soil substrate, or illumination differences associated with topography. We evaluate the effects of these variables in Landsat-derived metrics of FSC and postfire recovery, based upon three chaparral sites in southern California which contain shrub community ecotones, complex terrain, and soil variations. Detailed validations of prefire and postfire FSC are based on high spatial resolution ortho-imagery; cross-stratified random sampling is used for variable control. We find that differences in the composition and structure of shrubs (inferred from ortho-imagery) can substantially influence FSC-NDVI relations and impact recovery metrics. Differences in soil type have a moderate effect on the FSC-NDVI relation in one of the study sites, while no substantial effects were observed due to variation of terrain illumination among the study sites. Arithmetic difference recovery metrics - based on NDVI values that were not normalized with unburned control plots - correlate in a moderate but significant manner with a change in FSC ( values range 0.47-0.59 at two sites). Similar regression coefficients resulted from using Landsat visible reflectance data alone. The lowest correlations to FSC resulted from Soil-Adjusted Vegetation Index (SAVI) and are attributed to the effects of the soil-adjustment factor in sparsely vegetated areas. The Normalized Burn Ratio and Normalized Burn Ratio 2 showed a moderate correlation to FSC. This study confirms the utility of Landsat NDVI data for postfire recovery evaluation and implies a need for stratified analysis of postfire recovery in some chaparral landscapes.
基于数十年的陆地卫星影像序列得出的表观植被丰度的时间轨迹,为山地灌丛群落的火灾后恢复提供了有价值的信息,这类群落往往在十年内成熟。从时间序列归一化植被指数(NDVI)数据中提取的灌木覆盖度分数(FSC)变化信号,可能会因灌木类型、土壤基质的空间变化或与地形相关的光照差异而产生系统性偏差。我们基于南加州的三个山地灌丛地点评估了这些变量对陆地卫星衍生的FSC指标和火灾后恢复的影响,这些地点包含灌木群落交错带、复杂地形和土壤变化。对火灾前和火灾后FSC的详细验证基于高空间分辨率正射影像;采用交叉分层随机抽样进行变量控制。我们发现,灌木的组成和结构差异(从正射影像推断)会显著影响FSC与NDVI的关系,并影响恢复指标。土壤类型差异在其中一个研究地点对FSC与NDVI的关系有中等影响,而在各研究地点之间未观察到因地形光照变化产生的显著影响。基于未用未燃烧对照地块进行归一化的NDVI值的算术差恢复指标,与FSC的变化呈中等但显著的相关性(两个地点的值范围为0.47 - 0.59)。仅使用陆地卫星可见光反射率数据也得到了类似的回归系数。与FSC相关性最低的是土壤调整植被指数(SAVI),这归因于植被稀疏地区土壤调整因子的影响。归一化燃烧比和归一化燃烧比2与FSC呈中等相关性。本研究证实了陆地卫星NDVI数据在火灾后恢复评估中的实用性,并意味着在一些山地灌丛景观中需要对火灾后恢复进行分层分析。