利用无人机提供的高分辨率多光谱数据评估亚热带气候下的植被动态

Víctor González-Jaramillo, Julio Rodríguez-Cabrera
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摘要

植被状况研究非常重要,因为它揭示了环境因素及其与水资源可用性之间的关系,而这些因素与众多土木工程项目的规划、起草和执行息息相关。检测植被变化通常需要天基平台提供的数据,这些数据在空间或时间分辨率方面可能存在局限性,而且获取高分辨率数据的成本很高。对于相对较小的区域,无人飞行器(UAV)的使用提供了一种解决方案。通过使用照相机或专用传感器,这些设备有助于获取高空间和时间分辨率的土地覆盖信息。本研究分析了一个研究区域内的植被状况,该区域属于温暖的亚热带气候,气候四季分明(干燥和潮湿)。主要重点是检测植被覆盖的变化和评估植被的整体状况。为实现这一目标,部署了一架配备多光谱相机的多旋翼无人机,该相机可捕捉红光和近红外波段。应用基于距离和坡度的各种植被指数来获取植被状况。结果分析表明,使用 VANT 方法(每个像素 10 厘米)获得的高分辨率数据可以评估植被覆盖动态。值得注意的是,基于距离的植被指数在描述植被状况和干旱与潮湿季节过渡期间因水资源匮乏而造成的压力方面显示出卓越的功效。
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EVALUATION OF VEGETATION COVER DYNAMICS IN A SUB-TROPICAL CLIMATE USING HIGH-RESOLUTION MULTISPECTRAL DATA FROM UAVS
The study of vegetation status is of great importance as it reveals environmental factors and their relationship with the availability of water resources, components that are relevant in the planning, drafting and execution of numerous civil engineering projects. Detecting changes in vegetation cover often requires data from space-based platforms, which may have limitations in terms of spatial or temporal resolution and high costs for acquiring high-resolution data. For relatively small areas, the use of Unmanned Aerial Vehicles (UAVs) provides a solution. These devices facilitate the acquisition of land cover information with high spatial and temporal resolution through the use of photographic cameras or specialized sensors. This research analyzes the vegetation status within a study area characterized by distinct climatic seasons (dry and humid) within a warm sub-tropical climate. The primary focus lies in detecting changes in vegetation cover and evaluating the overall state of the vegetation. To accomplish this objective, a multirotor UAV equipped with a multispectral camera that captures RED and NIR bands is deployed. Various vegetation indices based on distance and slope are applied to access the vegetation’s condition. The analysis of the results indicates that it is possible to evaluate the vegetation cover dynamics using the very high-resolution data obtained with the VANT approach (10 cm per pixel). Notably, the distance-based vegetation indices demonstrate superior efficacy in delineating the vegetation status and the stress induced by the scarcity of water resources during the transition between dry and humid seasons.
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