Haolu Shang

Dr. Haolu Shang


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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12 February 2022 in Remote Sensing
Verified
Journal Article
Open access
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JWJIE WU
JIE WU
HGHuadong Guo
Huadong Guo
YDYixing Ding
Yixing Ding
HSHaolu Shang
Haolu Shang
TLTong Li
Tong Li
MLMingyang Lv
Mingyang Lv
The variation in the radiation budget at Earth’s top of the atmosphere (TOA) represents the most fundamental metric defining the status of global climate change. The accurate estimation of Earth’s shortwave radiant exitance is of critical importance to study Earth’s radiation budget (ERB) at TOA. Measuring Earth’s outgoing shortwave radiance (OSR) is a key point to estimate Earth’s shortwave radiant exitance. Compared with space-borne satellite systems, Moon-based sensors (MS) could provide large-scale, continuous, and long-term data for Earth radiation observations, bringing a new perspective on ERB. However, the factors affecting the estimation of Earth’s OSR in the lunar direction have not yet been fully explored, for example, anisotropic surface reflection and the effects of clouds and aerosols on radiation budget. In this work, we only focused on the influence of anisotropic surface reflection. To evaluate the extent of this influence, we constructed a model to estimate Earth’s OSR in the lunar direction (EOSRiLD), integrating the variables of anisotropic surface reflection (scene types, solar zenith angles, viewing zenith angles, and relative azimuth angles) and radiant flux in Moon-viewed sunlit regions. Then, we discussed it over three time periods (Earth’s rotation, revolution period, and synodic month cycle) and analyzed the impact of three variables (area of the Moon-viewed sunlit region, scene types, and incident-viewing angular bins) on anisotropic EOSRiLD. Our results indicate that EOSRiLD based on the assumptions of anisotropic and isotropic reflection is different but they all show the same monthly cycle change, which is related to the area of the Moon-viewed sunlit region. At the beginning and end of the lunar month, the differences between anisotropy and isotropy are greatest in each cycle; when it is close to the first half of each cycle, there is a small difference peak. Both anisotropy and isotropy are caused by the relative azimuth angles between the Sun and Moon. In conclusion, even if the Moon-based platform has a wider scope than space-borne satellites, the difference is still large between anisotropy and isotropy. Therefore, we still need to consider the anisotropic surface reflection based on the Moon-based observation.

1 May 2021 in Sensors
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Journal Article
Open access
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PLPeng Liang
Peng Liang
Wenzhong ShiWenzhong Shi
Wenzhong Shi
YDYixing Ding
Yixing Ding
ZLZhiqiang Liu
Zhiqiang Liu
HSHaolu Shang
Haolu Shang
Accurate and up-to-date road network information is very important for the Geographic Information System (GIS) database, traffic management and planning, automatic vehicle navigation, emergency response and urban pollution sources investigation. In this paper, we use vector field learning to extract roads from high resolution remote sensing imaging. This method is usually used for skeleton extraction in nature image, but seldom used in road extraction. In order to improve the accuracy of road extraction, three vector fields are constructed and combined respectively with the normal road mask learning by a two-task network. The results show that all the vector fields are able to significantly improve the accuracy of road extraction, no matter the field is constructed in the road area or completely outside the road. The highest F1 score is 0.7618, increased by 0.053 compared with using only mask learning.

29 October 2021 in Sensors
Verified
Journal Article
Open access
PDF file
GCGuoqiang Chen
Guoqiang Chen
HGHuadong Guo
Huadong Guo
YDYixing Ding
Yixing Ding
HSHaolu Shang
Haolu Shang
MLMingyang Lv
Mingyang Lv
KZKe Zhang
Ke Zhang
The Moon provides a long-term, stable, and unique location for Earth observation. Several space agencies, such as NASA, ESA, and CNSA, have conducted lunar explorations. To build a Moon-based observation station, site selection is the first step. The time coverage of Earth observation, e.g., the whole Earth disc observation or Earth-related plasmasphere and magnetosphere, the duration of sunlight coverage, and topography (i.e., slope) are the three major factors influencing site selection, especially in the Moon’s south pole region. In this study, we used the Chang’E digital elevation model (DEM) together with Earth, Moon, and Sun positions deduced from JPL ephemeris for site selection. Two craters, Faustini and Shoemaker, were chosen for the fuzzy evaluation of these three factors based on a multiple-input single-output (MISO) model during a 19-year period. The results show that the edge regions of craters and small hills, potholes, or uplifts inside craters are unsuitable for a Moon-based observation station. The south pole area, including these two craters, has relatively low time coverage of sunlight and some unevenly distributed, permanent shadow areas. This indicates a low thermal environment for radiation protection, whereas the relatively flat topography and the ability to cover a field of view several times the Earth’s radius enable observations of the plasmasphere and magnetosphere.