Barone Giulio, Domina Gianniantonio, Di Gristina Emilio
Department of Agricultural, Food and Forest Sciences, University of Palermo, Palermo, Italy Department of Agricultural, Food and Forest Sciences, University of Palermo Palermo Italy.
Biodivers Data J. 2021 May 27;9:e66013. doi: 10.3897/BDJ.9.e66013. eCollection 2021.
The survey by foot in the field is compared to the survey from a car, the photo-interpretation of Google Street View (GSV) panoramas continuously and at intervals of 1.5 km and the photo-interpretation of Google Earth aerial images on a 10 km stretch of road in Sicily. The survey by foot was used as reference for the other methods. The interpretation of continuous GSV panoramas gave similar results as the assessment by car in terms of the number of species identified and their location, but with lower cost. The interpretation online of aerial photos allowed the identification of a limited number of taxa, but gave a good localisation for them. Interpretation of GSV panoramas, each of 1.5 km, allowed the recognition of twice as many taxa as the interpretation of aerial photos and taking half the time, but did not allow a complete localisation. None of these methods alone seems sufficient to carry out a complete survey. A mixture of different techniques, which may vary according to the available resources and the goal to be achieved, seems to be the best compromise. To further test the capabilities of the survey using the interpretation of GSV panoramas every 1.5 km along the roads, we proceeded to study the alien plants along 3500 km of the road network on the island of Sicily. This survey identified only 10% of the known species for the region, but allowed us to trace the distribution of invasive species whose distribution is currently poorly recorded.
将实地徒步调查与乘车调查、对谷歌街景(GSV)全景图每隔1.5公里连续进行的照片判读以及对西西里岛10公里路段的谷歌地球航拍图像的照片判读进行了比较。徒步调查被用作其他方法的参照。连续的GSV全景图判读在已识别物种的数量及其位置方面给出了与乘车评估相似的结果,但成本更低。在线航拍照片判读能识别的分类单元数量有限,但能对其进行良好定位。对每隔1.5公里的GSV全景图进行判读,识别出的分类单元数量是航拍照片判读的两倍,且用时减半,但无法进行完整定位。单独使用这些方法似乎都不足以完成全面调查。根据可用资源和要实现的目标,将不同技术结合起来似乎是最佳折衷方案。为了进一步测试沿道路每隔1.5公里对GSV全景图进行判读的调查能力,我们着手研究西西里岛3500公里道路网络沿线的外来植物。这项调查仅识别出该地区已知物种的10%,但让我们能够追踪目前分布记录不完善的入侵物种的分布情况。