首个公开的多光谱街景数据集，助力城市气候韧性研究。
The Spectrascapes Dataset: Street-view imagery beyond the visible captured using a mobile platform
- 用自行车搭载RGB、近红外和热成像设备采集街景数据。
- 覆盖荷兰多种城市形态，共17,718张多光谱图像。
- 适合做城市规划、遥感与机器学习研究，数据可复用。
高分辨率时空数据对建设气候韧性城市至关重要。现有城市参数监测数据集主要依赖人工巡查、嵌入式传感、遥感或标准街景图像（RGB），但普遍存在扩展性差、时空分辨率不一致、视角为俯视或光谱信息不足等问题。本文提出一种新方法及开源实现：基于移动平台的多光谱地表影像数据集，有效克服上述限制。该数据集包含17,718张街景多光谱图像，使用自行车搭载的RGB、近红外和热成像传感器，在荷兰不同城市形态（村庄、小镇、小城市和大城市）中采集。数据采集强调严格校准与质量控制，并公开硬件与软件细节。据我们所知，Spectrascapes是首个同类型开源数据集。最后，展示了两个下游应用案例，并提出了机器学习、城市规划与遥感领域的潜在研究方向。
原文摘要 · Abstract (English)
High-resolution data in spatial and temporal contexts is imperative for developing climate resilient cities. Current datasets for monitoring urban parameters are developed primarily using manual inspections, embedded-sensing, remote sensing, or standard street-view imagery (RGB). These methods and datasets are often constrained respectively by poor scalability, inconsistent spatio-temporal resolutions, overhead views or low spectral information. We present a novel method and its open implementation: a multi-spectral terrestrial-view dataset that circumvents these limitations. This dataset consists of 17,718 street level multi-spectral images captured with RGB, Near-infrared, and Thermal imaging sensors on bikes, across diverse urban morphologies (village, town, small city, and big urban area) in the Netherlands. Strict emphasis is put on data calibration and quality while also providing the details of our data collection methodology (including the hardware and software details). To the best of our knowledge, Spectrascapes is the first open-access dataset of its kind. Finally, we demonstrate two downstream use-cases enabled using this dataset and provide potential research directions in the machine learning, urban planning and remote sensing domains.
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