Garzón-Machado Víctor, Otto Rüdiger, del Arco Aguilar Marcelino José
Departamento de Biología Vegetal (Botánica), Universidad de La Laguna, C/Astrofísico Francisco Sánchez s/n, 38071 La Laguna, Tenerife, Canary Islands, Spain,
Int J Biometeorol. 2014 Jul;58(5):887-99. doi: 10.1007/s00484-013-0670-y. Epub 2013 May 19.
Different spatial interpolation techniques have been applied to construct objective bioclimatic maps of La Palma, Canary Islands. Interpolation of climatic data on this topographically complex island with strong elevation and climatic gradients represents a challenge. Furthermore, meteorological stations are not evenly distributed over the island, with few stations at high elevations. We carried out spatial interpolations of the compensated thermicity index (Itc) and the annual ombrothermic Index (Io), in order to obtain appropriate bioclimatic maps by using automatic interpolation procedures, and to establish their relation to potential vegetation units for constructing a climatophilous potential natural vegetation map (CPNV). For this purpose, we used five interpolation techniques implemented in a GIS: inverse distance weighting (IDW), ordinary kriging (OK), ordinary cokriging (OCK), multiple linear regression (MLR) and MLR followed by ordinary kriging of the regression residuals. Two topographic variables (elevation and aspect), derived from a high-resolution digital elevation model (DEM), were included in OCK and MLR. The accuracy of the interpolation techniques was examined by the results of the error statistics of test data derived from comparison of the predicted and measured values. Best results for both bioclimatic indices were obtained with the MLR method with interpolation of the residuals showing the highest R2 of the regression between observed and predicted values and lowest values of root mean square errors. MLR with correction of interpolated residuals is an attractive interpolation method for bioclimatic mapping on this oceanic island since it permits one to fully account for easily available geographic information but also takes into account local variation of climatic data.
不同的空间插值技术已被应用于构建加那利群岛拉帕尔马岛的客观生物气候图。在这个地形复杂、海拔和气候梯度强烈的岛屿上对气候数据进行插值是一项挑战。此外,气象站在岛上分布不均,高海拔地区的站点很少。我们对补偿热指数(Itc)和年雨量指数(Io)进行了空间插值,以便通过自动插值程序获得合适的生物气候图,并建立它们与潜在植被单元的关系,从而构建一个适生潜在自然植被图(CPNV)。为此,我们使用了地理信息系统(GIS)中实现的五种插值技术:反距离加权法(IDW)、普通克里金法(OK)、普通协同克里金法(OCK)、多元线性回归(MLR)以及对回归残差进行普通克里金法处理的MLR。OCK和MLR中纳入了从高分辨率数字高程模型(DEM)得出的两个地形变量(海拔和坡向)。通过将预测值与测量值进行比较得出的测试数据的误差统计结果,检验了插值技术的准确性。两种生物气候指数的最佳结果均通过MLR方法获得,对残差进行插值显示出观测值与预测值之间回归的最高R2以及最低的均方根误差值。对插值残差进行校正的MLR是该海洋岛屿生物气候制图的一种有吸引力的插值方法,因为它既能充分考虑容易获取的地理信息,又能考虑气候数据的局部变化。