Integrating Remote Sensing and Street View Images to Quantify Urban Forest Ecosystem Services
Integrating Remote Sensing and Street View Images to Quantify Urban Forest Ecosystem Services
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基于遥感和街景影像的城市森林生态系统服务量化研究
DOI：
10.3390/rs12020329
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发表时间：
2020-01-01
期刊：
影响因子：
5
通讯作者：
Saragosa, Claudio
中科院分区：
文献类型：
--
作者：
Barbierato, Elena;Bernetti, Iacopo;Saragosa, Claudio
迫切需要有综合工具来评估与增加公共绿色空间有关的减缓和适应气候变化政策对健康的影响。城市植被在当地范围内提供了许多生态系统服务，因此是一种潜在的适应战略，可用于全球变暖时代，以抵消人类活动对城市环境日益增加的影响。在这项研究中，我们提出了一套城市绿色生态指标，可用于评估城市绿色生态系统服务。这些指标来自两项互补的调查：一项是对多光谱图像和激光成像探测和测距数据进行的传统遥感调查，另一项是通过谷歌街景数据库提供的图像进行的近距离遥感调查。根据之前的研究，计算了两类指标：比建筑立面海拔更低和更高的绿化。在工作的最后阶段，指标被应用到城市街区，并采用空间约束聚类方法。根据城市绿化特征确定了均匀区域。拟议的方法是开发一个地理信息系统，公共行政人员和城市绿色设计人员可以使用该系统来创建和维护城市公共森林。
There is an urgent need for holistic tools to assess the health impacts of climate change mitigation and adaptation policies relating to increasing public green spaces. Urban vegetation provides numerous ecosystem services on a local scale and is therefore a potential adaptation strategy that can be used in an era of global warming to offset the increasing impacts of human activity on urban environments. In this study, we propose a set of urban green ecological metrics that can be used to evaluate urban green ecosystem services. The metrics were derived from two complementary surveys: a traditional remote sensing survey of multispectral images and Laser Imaging Detection and Ranging (LiDAR) data, and a survey using proximate sensing through images made available by the Google Street View database. In accordance with previous studies, two classes of metrics were calculated: greenery at lower and higher elevations than building facades. In the last phase of the work, the metrics were applied to city blocks, and a spatially constrained clustering methodology was employed. Homogeneous areas were identified in relation to the urban greenery characteristics. The proposed methodology represents the development of a geographic information system that can be used by public administrators and urban green designers to create and maintain urban public forests.