Enhancement of Ecological Field Experimental Research by Means of UAV Multispectral Sensing

摘要

Although many climate research experiments are providing valuable data, long-termmeasurements are not always affordable. In the last decades, several facilities have secured long-termexperiments, but few studies have incorporated spatial and scale effects. Most of them have beenimplemented in experimental agricultural fields but none for ecological studies. Scale effects can beassessed using remote sensing images from space or airborne platforms. Unmanned aerial vehicles(UAVs) are contributing to an increased spatial resolution, as well as becoming the intermediatescale between ground measurements and satellite/airborne image data. In this paper we assessthe applicability of UAV-borne multispectral images to provide complementary experimental datacollected at point scale (field sampling) in a long-term rain manipulation experiment located at theKiskun Long-Term Socio-Ecological Research (LTSER) site named ExDRain to assess the effects ongrassland vegetation. Two multispectral sensors were compared at different scales, the Parrot Sequoiacamera on board a UAV and the portable Cropscan spectroradiometer. The NDVI values were usedto assess the effect of plastic roofs and a proportional reduction effect was found for Sequoia-derivedNDVI values. Acceptable and significant positive relationships were found between both sensors atdifferent scales, being stronger at Cropscan measurement scale. Differences found at plot scale mightbe due to heterogeneous responses to treatments. Spatial variability analysis pointed out a morehomogeneous response for plots submitted to severe and moderate drought. More investigation isneeded to address the possible effect of species abundance on NDVI at plot scale contributing to amore consistent representation of ground measurements. The feasibility of carrying out systematicUAV flights coincident or close to ground campaigns will certainly reveal the consistency of theobserved spatial patterns in the long run.