Resolution Enhancement of Remotely Sensed Land Surface Temperature: Current Status and Perspectives

Mao, Qi; Peng, Jian; Wang, Yanglin

doi:10.3390/rs13071306

Cited by 28 publications

(17 citation statements)

References 110 publications

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“…The crucial problem is to attain a fused image with enhanced target regions and suppressed backgrounds from the spaceborne and airborne SAR images, in order to increase the target-to-clutter ratio (TCR) and improve the vessel target detection performance. Considering the issue of image fusion, some works have been carried out in the existing literature [10][11][12][13][14][15][16][17][18][19][20][21][22][23]. The most straightforward and computationally efficient fusion methods are arithmetic-based fusion approaches, such as addition fusion and multiplication fusion, but this class of fusion approaches might maintain a high level of background clutter, resulting in false alarms, or excessively suppress relatively weak targets, resulting in missed detections [10].…”

Section: Related Workmentioning

confidence: 99%

Vessel Target Detection in Spaceborne–Airborne Collaborative SAR Images via Proposal and Polarization Fusion

et al. 2021

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This paper focuses on vessel detection through the fusion of synthetic aperture radar (SAR) images acquired from spaceborne–airborne collaborative observations. The vessel target detection task becomes more challenging when it features inshore interferences and structured and shaped targets. We propose a new method, based on target proposal and polarization information exploitation (TPPIE), to fuse the spaceborne–airborne collaborative SAR images for accurate vessel detection. First, a new triple-state proposal matrix (TSPM) is generated by combining the normed gradient-based target proposal and the edge-based morphological candidate map. The TSPM can be used to extract the potential target regions, as well as filtering out the sea clutter and inshore interference regions. Second, we present a new polarization feature, named the absolute polarization ratio (APR), to exploit the intensity information of dual-polarization SAR images. In the APR map, the vessel target regions are further enhanced. Third, the final fused image with enhanced targets and suppressed backgrounds (i.e., improved target-to-clutter ratio; TCR) is attained by taking the Hadamard product of the intersected TSPM from multiple sources and the composite map exploiting the APR feature. Experimental analyses using Gaofen-3 satellite and unmanned aerial vehicle (UAV) SAR imagery indicate that the proposed TPPIE fusion method can yield higher TCRs for fused images and better detection performance for vessel targets, compared to commonly used image fusion approaches.

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Section: Related Workmentioning

confidence: 99%

Vessel Target Detection in Spaceborne–Airborne Collaborative SAR Images via Proposal and Polarization Fusion

et al. 2021

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“…Some scholars chose urban lakes as their research object, while other scholars chose urban rivers [27][28][29][30][31]. The most widely used method was field measurement, although lacking comprehensiveness and integrity of data [32][33][34][35][36][37]. It was found that the water had an obvious "cold island" effect on the surrounding area.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Mechanisms of Summer Thermal Environment of Waterfront Space in China’s Cold Regions

2022

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Water is an essential part of the urban ecosystem and plays a vital role in alleviating urban heat island (UHI) problems. The contribution toward UHI mitigation made by bodies of water needs to be ascertained to establish waterfront thermal environment construction standards. In this study, the thermal environment of the waterfront space of Tianjin in the cold regions of China was the research object. Through a survey including 141 valid questionnaires and the field measurement of four typical waterfront spaces in Tianjin, the thermal demand characteristics of recreational use for the waterfront environment and the influence of water on microclimate are discussed, supplemented by results from low-altitude infrared remote sensing technology, which was mainly used to obtain a wider range of infrared thermal images with higher accuracy. To improve the urban heat island effect and the quality of the ecological environment, this paper used outdoor thermal environment simulation software to quantitatively analyze the thermal environmental impact of outdoor public activity spaces around the representative urban body of water and proposes the optimization scheme of the waterfront space’s thermal environment. The results show that, based on the factors of water itself, the most economical water width was 70–80 m, and the cooling effect intensity of water had an essential correlation with the distance between the measured site and the water center. In terms of the environmental factors around the water, when the green lawn of the waterfront space was 12 m and the water shore’s geometric form was S-shaped, this could improve the cooling effect of water significantly. Waterfront activity spaces should focus on thermal comfort on the east and south water shores. It is expected that this study could provide practical implications and useful guidance for the planning and design of urban waterfront space in China’s cold regions.

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“…Additionally, the relationship of fine and coarse resolution data varies diurnally, which could not be captured adequately using a static downscaling approach. Comprehensive reviews of advancement in LST downscaling methods (both spatially and temporally) along with their advantages and limitations were recently outlined by Mao et al [32] and Wu et al [33].…”

Section: Introductionmentioning

confidence: 99%

Spatial Downscaling of GOES-R Land Surface Temperature over Urban Regions: A Case Study for New York City

et al. 2022

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The surface urban heat island (SUHI) effect is among the major environmental issues encountered in urban regions. To better predict the dynamics of the SUHI and its impacts on extreme heat events, an accurate characterization of the surface energy balance in urban regions is needed. However, the ability to improve understanding of the surface energy balance is limited by the heterogeneity of surfaces in urban areas. This study aims to enhance the understanding of the urban surface energy budget through an innovation in the use of land surface temperature (LST) observations from remote sensing satellites. A LST database with 5–min temporal and 30–m spatial resolution is developed by spatial downscaling of the Geostationary Operational Environmental Satellites—R (GOES–R) series LST product over New York City (NYC). The new downscaling method, known as the Spatial Downscaling Method (SDM), benefits from the fine spatial resolution of Landsat–8 and high temporal resolution of GOES–R, and considers the temporal variation in LST for each land cover type separately. Preliminary results show that the SDM can reproduce the temporal and spatial variability of LST over NYC reasonably well and the downscaled LST has a spatial root mean square error (RMSE) of the order of 2 K as compared to the independent Landsat–8 observations. The SDM shows smaller RMSE of 1.93 K over the tree canopy land cover, whereas RMSE is 2.19 K for built–up areas. The overall results indicate that the SDM has potential to estimate LST at finer spatial and temporal scales over urban regions.

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Resolution Enhancement of Remotely Sensed Land Surface Temperature: Current Status and Perspectives

Cited by 28 publications

References 110 publications

Vessel Target Detection in Spaceborne–Airborne Collaborative SAR Images via Proposal and Polarization Fusion

Vessel Target Detection in Spaceborne–Airborne Collaborative SAR Images via Proposal and Polarization Fusion

Assessment of the Mechanisms of Summer Thermal Environment of Waterfront Space in China’s Cold Regions

Spatial Downscaling of GOES-R Land Surface Temperature over Urban Regions: A Case Study for New York City

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