wdc-climate.de:5282084 eng; USA collection QTP Dr. Tianyun Wang Shenyang University of Technology https://www.sut.edu.cn pointOfContact 2025-02-03T10:02:57 ISO 19115 ISO 19115-2:2009 Spatialization of near-surface air temperature and updating based on thermal infrared remote sensing information in the Qinghai-Tibet Plateau 2025-02-21 publication 1 QTP doi:10.26050/WDCC/QTP Dr. Tianyun Wang Shenyang University of Technology https://www.sut.edu.cn Email: tywang_iem@163.com principalInvestigator Dr. Tianyun Wang Shenyang University of Technology https://www.sut.edu.cn Email: tywang_iem@163.com author Prof. Dr. Lu Yang Shenyang University of Technology https://www.sut.edu.cn Email: yanglu515@163.com author Dr. Deyuan Zhang Shenyang Aerospace University not filled Email: dyzhang@sau.edu.cn author WDCC publisher The Qinghai-Tibet Plateau, known for its high altitude, cold climate, and fragile ecosystem, presents unique challenges and opportunities for the implementation of an intelligent sponge urban system. The heat island effect, a phenomenon where urban areas experience higher temperatures compared to surrounding rural areas, can be particularly problematic in such a sensitive environment. Predicting and mitigating heat island intensity is crucial for improving urban livability and environmental sustainability. To develop a procedure for predicting heat island intensity in an intelligent sponge urban system, ensuring accurate and real-time predictions through a series of steps. Collect parameter information of the underlying surface using meteorological observation data from the sponge city, field observation data, and investigation data of the sponge city. Gather comprehensive data on the physical and environmental characteristics of the urban surface. Establish a set of digital labels with feature data derived from the collected information. Add the labeled data to the training sample set for the prediction model of sponge city surface heat island intensity. A crucial input for establishing a real-time prediction model. Train the prediction model function for sponge city surface heat island intensity using the data. This Experiment contains 2 datasets, corrected surface air temperature data and training data. The corrected surface air temperature data has been processed using meteorological observation data and thermal infrared remote sensing data. The data covers a high-altitude area of the Qinghai-Tibet Plateau, with a spatial resolution of 30 meters. The original temperature data were obtained from multiple sources, including thermal infrared remote sensing data from Landsat 8(L8) and Landsat 9 (L9) Collection 2 (C2) Level 2 (L2) products, as well as ground station measurements from National Tibetan Plateau/Third Pole Environment Data Center. The regression algorithms in supervised learning was trained to correct for biases and inaccuracies in updating the spatialized data of near-surface air temperature. This dataset is suitable for climate research, environmental monitoring, and other applications requiring relatively accurate surface air temperature data. Dr. Tianyun Wang Shenyang University of Technology https://www.sut.edu.cn pointOfContact NetCDF Temperature machine learning surface air temperature thermal infrared remote sensing CC-BY-4.0: Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ eng; USA 73.0 105.0 25.0 40.0 gregorian 2019-01-02 2019-11-25 info:eu-repo/grantAgreement/SUT//LJ200080773/CN//Intelligent Urban Rainwater Collection Module System Application surface_bidirectional_reflectance The surface called "surface" means the lower boundary of the atmosphere. "Bidirectional_reflectance" depends on the angles of incident and measured radiation. Reflectance is the ratio of the energy of the reflected to the incident radiation. A coordinate variable of radiation_wavelength or radiation_frequency can be used to specify the wavelength or frequency, respectively, of the radiation. [CF-Standard Name]; unit: 0.01 altitude Altitude is the (geometric) height above the geoid, which is the reference geopotential surface. The geoid is similar to mean sea level. [CF-Standard Name]; unit: m air_temperature Air temperature is the bulk temperature of the air, not the surface (skin) temperature. [CF-Standard Name]; unit: degC NetCDF 74414 https://www.wdc-climate.de/ui/entry?acronym=QTP information collection n/a None n/a None