Predicting density of Ixodes pacificus nymphs in dense woodlands in Mendocino County, California, based on geographic information systems and remote sensing versus field-derived data
Predicting density of Ixodes pacificus nymphs in dense woodlands in Mendocino County, California, based on geographic information systems and remote sensing versus field-derived data
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DOI：
10.4269/ajtmh.2006.74.632
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发表时间：
2006-04-01
影响因子：
3.3
通讯作者：
Lane, RS
中科院分区：
文献类型：
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作者：
Eisen, RJ;Eisen, L;Lane, RS
在加州，太平洋硬蜱是莱姆病病原体伯氏疏螺旋体的主要传播媒介。我们使用了一个监督分类模型，基于遥感（RS）数据从多个季节的陆地卫星TM 5图像，以确定在门多西诺县的关键栖息地，人类暴露于I。长满落叶的林地。该模型基于归一化植被指数（NDVI）、亮度和湿度，将若虫风险栖息地（占该县的52.6%）与其他栖息地类型分开，用户和生产者的准确率> 93%。接下来，我们确定了位于整个门多西诺县的62个林地叶区中的寻蛹密度，并创建了前向逐步回归模型，解释了若虫密度的变化，该模型基于外行人在该领域可获得的特征（例如，树木种类、鹿的标志; r（2）= 0.43，P < 0.0001）或基于地理信息系统（GIS）/RS的环境数据（r（2）= 0.50，P < 0.0001）。GIS/RS模型，使用7月NDVI，11月绿色，沿海影响类别，5月太阳辐射，11月日照时数，和主要的水文分组作为输入变量，是22%更准确地预测若虫密度在16个验证站点（r（2）= 0.72）比现场导出的数据模型（r（2）= 0.50）。栖息地分类和GIS/RS模型相结合，创建一个连续的若虫密度表面的整个门多西诺县。该风险面显示，该县11.9%的地区被归类为栖息地，对人类暴露于汞的风险至少为中度（每100米2> 6.4汞）。此外，高风险地区（每100米（2）> 10.5埃;县的1.7%）往往集中在中部内陆和人口最稠密的地区的门多西诺县，但很少在沿海人口中心附近。
Ixodes pacificus nymphs are the primary vectors to humans of Borrelia burgdorferi, the etiologic agent of Lyme disease, in California. We used a supervised classification model, based on remote sensing (RS) data from multi-seasonal Landsat TM 5 images, to identify the key habitat in Mendocino County where humans are exposed to I. pacificus nymphs (woodlands carpeted with leaf litter). The model, based on the normalized difference vegetation index (NDVI), brightness, and wetness, separated the nymphal risk habitat (52.6% of the county) from other habitat types with > 93% user and producer accuracies. Next, we determined the density of questing nymphs in 62 woodland-leaf areas located throughout Mendocino County and created forward-stepwise regression models explaining the variation in nymphal density based on traits attainable by a lay-person in the field (e.g., tree species present, deer signs; r(2) = 0.43, P < 0.0001), or geographic information systems (GIS)/RS-based environmental data (r(2) = 0.50, P < 0.0001). The GIS/RS model, using July NDVI, November greenness, a coastal influence category, May solar insolation, November hours of sunlight, and dominant hydrologic grouping as input variables, was 22% more accurate in predicting nymphal density at 16 validation sites (r(2) = 0.72) than the field-derived data model (r(2) = 0.50). The habitat classification and GIS/RS models were combined to create a continuous nymphal density surface for the entirety of Mendocino County. This risk surface showed that 11.9% of the county was classified as habitat posing at least moderate risk of human exposure to nymphs (> 6.4 nymphs per 100 m(2)). Furthermore, high-risk areas (> 10.5 nymphs per 100 m(2); 1.7% of the county) tended to cluster in the central interior and most heavily populated region of Mendocino County, but were rare in the proximity of coastal population centers.