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GIS-based modeling of Javan Hawk-Eagle distribution using logistic and autologistic regression models

机译:使用Logistic和AutoLogistic回归模型的Javan Hawk-Eagle分布基于GIS的建模

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Few attempts have been made to model the distribution of the Javan Hawk-Eagle (Spizaetus bartelsi) based on predictions formulated from habitat requirements in West Java or throughout Java Island. This paper proposes a new approach to predicting probability models of Javan Hawk-Eagle (JHE) distribution using the application of logistic regression (LR) and autologistic regression (ALR) coupled with RAMAS GIS, and creating pseudo-absence data using a normalized difference vegetation index from remote sensing data. Habitat requirements of 11 nest-sites in Gunung Gede-Pangrango National Park (TNGP) and its surrounding areas were analyzed and quantified, and the model was validated in southern parts of West Java. The final LR model was used as the starting point for fitting ALR models that account for spatial autocorrelation through the addition of an autocovariate variable using several different neighborhood sizes ranging from 450m (15x15 moving window size, or equal to 20.25ha) to 1500m (50x50 moving window size, or equal to 225ha) using 300m interval. The best model was the ALR model with a 1500m autocovariate that agreed with the distance between nests in TNGP and the mean home range size in Java. This model showed a significant increase in overall accuracy and successfully removed misclassified pixels. Based on our results, we recommend five strategies for the management and conservation of JHE habitat, including integrated conservation management and increased regulation of wildlife reserves.
机译:基于根据西爪哇或整个爪哇岛的栖息地需求制定的预测,很少有人尝试对爪哇鹰(Spizaetus bartelsi)的分布进行建模。本文提出了一种利用逻辑回归(LR)和自动回归(ALR)结合RAMAS GIS预测Javan Hawk-Eagle(JHE)分布概率模型的新方法,并使用归一化差异植被创建伪缺失数据遥感数据的索引。分析并量化了Gunung Gede-Pangrango国家公园(TNGP)及其周围地区11个巢穴的栖息地需求,并在西爪哇南部验证了该模型。最终的LR模型用作拟合ALR模型的起点,该模型通过添加自协变量来解决空间自相关问题,这些自变量使用几种不同的邻域大小,范围从450m(15x15移动窗口大小,等于20.25ha)到1500m(50x50)以300m的间隔移动窗口大小,或等于225ha)。最好的模型是ALR模型,其自变量为1500m,该变量与TNGP中的嵌套之间的距离和Java中的平均起始范围大小一致。该模型显示出整体准确性的显着提高,并成功去除了错误分类的像素。根据我们的结果,我们推荐了五种JHE生境的管理和保护策略,包括综合保护管理和加强对野生动植物保护区的监管。

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