Mapping pollination types with remote sensing
Mapping pollination types with remote sensing
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DOI：
10.1111/jvs.12421
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发表时间：
2016-09-01
影响因子：
2.8
通讯作者：
Skidmore, Andrew K.
中科院分区：
文献类型：
--
作者：
Feilhauer, Hannes;Doktor, Daniel;Skidmore, Andrew K.
问题：Pollution是一种生态系统功能，在当地的空间尺度上有所不同。遥感可能有助于量化和绘制由此产生的模式，以便更好地了解生态系统的功能。这项任务是具有挑战性的，因为传感器测量的信号是由叶片和冠层的光学特性，确定植被光谱占主导地位。预计授粉类型（即风、昆虫和自花授粉）不会产生直接影响。我们限制问：（1）狮子强烈授粉类型在社区水平与光学性状;（2）这些联系是否允许我们地图的空间格局授粉类型与遥感数据？所在地：沼泽和Molinia grasslar，南部C.ernmany。方法：我们采样维管植物的物种组成，以及性状相关的光谱信号，为100块。授粉类型和额外的光学性状的信息，从已建立的植物性状数据库编译。与现场采样的同时，使用机载传感器阿坝获取研究现场的图像数据。双重。我们测试的相关性授粉类型和光学性状。基于这些结果，我们回归了基于图的授粉类型的信息对相应的光谱信号提取。从图像数据。我们倒置的模型使用的图像，以获得地图的授粉类型分布在整个studysite.Results：在我们的研究网站，授粉类型和光学性状显着相关，高达R = 0.813的情况下，风授粉和叶干物质含量。然而，这些关系并不一定可以转移到其他生态系统、物候阶段和空间尺度，它们的物理解释需要仔细考虑。我们能够对授粉类型的空间分布进行统计建模，RMSE <10.5%。由此产生的地图提供了详细的见解授粉类型的空间分布在community level.Conclusions：结果表明，授粉类型确实与冠层反射率的方式，使他们的映射使用遥感。需要更多的研究，以提高我们的知识，在其他生态系统和不同的物候期授粉类型和植物性状之间的可转移关系。
Questions: Pollination is an ecosystem function that varies at local spatial scales. Remote sensing may help to quantify and map the resulting patterns for a better understanding of ecosystem functioning. This task is challenging because the signal measured by sensors is dominated by leaf and canopy optical traits that determine the vegetation spectrum. No direct influence of pollination types (i.e. wind, insect and self pollination) can be expected. We limits ask: (1) lion strongly are pollination types at the community level linked with optical traits; and (2) do these links allow us to map spatial patterns of pollination types with remote sensing data?Location: Mires arid Molinia grasslar, southern C.ernmany.Methods: We sampled vascular plant species composition, as well as traits related to optical spectral signals, for 100 plots. Information on pollination types and additional optical traits were compiled from established plant trait databases. Simultaneously with the field sampling, image data of the study site were acquired using the airborne sensor ABA. Dual. We tested for correlations between-pollination types and optical traits. Based on these results, we regressed the plot-based information on pollination types against the corresponding spectral signal extracted.from the image data. We inverted the models using the image in order to obtain maps of the pollination type distribution across the study site.Results: In our study site, pollination types and optical traits were significantly correlated, up to R = 0.813 in the case of wind pollination and leaf dry matter content. These relations are, however, not.necessarily transferable to other ecosystems, phenological stages and spatial scales, and their physical interpretation requires careful consideration. We were able to statistically model the spatial distribution of pollination types with a RMSE < 10.5%. The resulting maps provide detailed insights into the spatial distribution of pollination types at the community level.Conclusions: The results show that pollination types are indeed related to canopy reflectance in a way that allows their mapping using remote sensing. More research is needed in order to improve our knowledge about transferable relations between pollination types and plant traits in other ecosystems and at different phenological stages.