In the context of global urbanization, unplanned urban expansion renders cities particularly susceptible to the impacts of climate change, natural disasters, and extreme heat and humidity. Monitoring the land surface temperature (LST) in urban areas is crucial for assessing the urban thermal environment. Fine-scale (<100 m) LST products are essential for comprehensively understanding urban environments because of their detailed thermal distribution patterns. The Sustainable Development Science Satellite 1 (SDGSAT-1), launched on November 5, 2021, possesses the capability to capture fine-scale urban LST imagery at a 30-m resolution, both day and night. Based on the characteristics of the SDGSAT-1 thermal infrared data, we implemented two methods (the multiband-based (MBB) method and the two-band-based (TBB) method) to generate 30-m urban LSTs. The derived LSTs are evaluated against the MODIS LST product and in situ measurements. Furthermore, various simulation datasets are constructed based on the spectral characteristics of SDGSAT-1/TIS and utilized to derive LSTs using the MBB and TBB methods to further clarify the feasibility of the two methods. The results indicate that the MBB method exhibits superior performance in urban areas, with an RMSE that is 0.74 K lower than that of the TBB method. In contrast, the TBB method is suitable in areas with lower emissivity fluctuations, such as dense vegetated areas, with an RMSE that is 0.96 K lower than that of the MBB method. These two methods are planned for incorporation into the SDGSAT-1 LST production framework, thereby contributing to the advancement of accurate LST retrieval and achieving sustainable development goals in the future.

中文翻译：

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高空间分辨率SDGSAT-1热红外数据反演城市地表温度


在全球城市化的背景下，无计划的城市扩张使城市特别容易受到气候变化、自然灾害以及极端高温和潮湿的影响。监测城市地区的地表温度（LST）对于评估城市热环境至关重要。精细尺度（<100 m）LST 产品因其详细的热分布模式对于全面了解城市环境至关重要。可持续发展科学卫星一号（SDGSAT-1）于 2021 年 11 月 5 日发射，能够在白天和夜间捕获 30 米分辨率的精细城市地表温度图像。根据SDGSAT-1热红外数据的特点，我们采用了两种方法（基于多波段（MBB）方法和基于双波段（TBB）方法）来生成30米的城市地表温度。根据 MODIS LST 产品和现场测量来评估得出的 LST。此外，基于SDGSAT-1/TIS的光谱特性构建了各种模拟数据集，并利用MBB和TBB方法推导了LST，进一步阐明了两种方法的可行性。结果表明，MBB 方法在城市地区表现出优越的性能，RMSE 比 TBB 方法低 0.74 K。相比之下，TBB方法适用于发射率波动较小的区域，例如植被茂密的地区，其RMSE比MBB方法低0.96 K。这两种方法计划纳入SDGSAT-1地表温度生成框架，从而有助于推进地表温度精确反演，实现未来的可持续发展目标。