论文标题
使用远程感知的数据了解城市用水
Understanding Urban Water Consumption using Remotely Sensed Data
论文作者
论文摘要
城市代谢是一个积极的研究领域，涉及城市地区排放和资源消耗的估计。可以通过实施优雅的机器学习算法来通过手动测量师进行分析。在这项探索性工作中，我们估计卫星图像捕获的地区的建筑物的用水量。为此，我们将分析分为三个部分：i）鉴定建筑物像素的识别，然后是ii）从建筑物像素中识别建筑物类型（住宅/非住宅）的识别，最后是使用建筑物像素及其类型的建筑像素，以估算其类型，以使用各单位区域消耗量为不同的建筑物供应，以估算各种单位区域消耗量，从而获得不同的建筑物，从而获得不同的建筑物，从而获得了MuniaiC的不同建筑物。
Urban metabolism is an active field of research that deals with the estimation of emissions and resource consumption from urban regions. The analysis could be carried out through a manual surveyor by the implementation of elegant machine learning algorithms. In this exploratory work, we estimate the water consumption by the buildings in the region captured by satellite imagery. To this end, we break our analysis into three parts: i) Identification of building pixels, given a satellite image, followed by ii) identification of the building type (residential/non-residential) from the building pixels, and finally iii) using the building pixels along with their type to estimate the water consumption using the average per unit area consumption for different building types as obtained from municipal surveys.
