Zhang Dianjun

Dr. Zhang Dianjun


Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

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

Representative Publications

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17 August 2016 in Sensors
Verified
Journal Article
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ZDZhang Dianjun
Zhang Dianjun
Guoqing ZhouGuoqing Zhou
Guoqing Zhou
As an important parameter in recent and numerous environmental studies, soil moisture (SM) influences the exchange of water and energy at the interface between the land surface and atmosphere. Accurate estimate of the spatio-temporal variations of SM is critical for numerous large-scale terrestrial studies. Although microwave remote sensing provides many algorithms to obtain SM at large scale, such as SMOS and SMAP etc., resulting in many data products, they are almost low resolution and not applicable in small catchment or field scale. Estimations of SM from optical and thermal remote sensing have been studied for many years and significant progress has been made. In contrast to previous reviews, this paper presents a new, comprehensive and systematic review of using optical and thermal remote sensing for estimating SM. The physical basis and status of the estimation methods are analyzed and summarized in detail. The most important and latest advances in soil moisture estimation using temporal information have been shown in this paper. SM estimation from optical and thermal remote sensing mainly depends on the relationship between SM and the surface reflectance or vegetation index. The thermal infrared remote sensing methods uses the relationship between SM and the surface temperature or variations of surface temperature/vegetation index. These approaches often have complex derivation processes and many approximations. Therefore, combinations of optical and thermal infrared remotely sensed data can provide more valuable information for SM estimation. Moreover, the advantages and weaknesses of different approaches are compared and applicable conditions as well as key issues in current soil moisture estimation algorithms are discussed. Finally, key problems and suggested solutions are proposed for future research.

9 April 2014 in Remote Sensing
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Journal Article
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ZDZhang Dianjun
Zhang Dianjun
Ronglin TangRonglin Tang
Ronglin Tang
Wei ZhaoWei Zhao
Wei Zhao
Bo-Hui TangBo-Hui Tang
Bo-Hui Tang
Hua WuHua Wu
Hua Wu
ZLZhao-Liang Li
Zhao-Liang Li
Soil water content (SWC) is a crucial variable in the thermal infrared research and is the major control for land surface hydrological processes at the watershed scale. Estimating the surface SWC from remotely sensed data using the triangle method proposed by Price has been demonstrated in previous studies. In this study, a new soil moisture index (Temperature Rising Rate Vegetation Dryness Index—TRRVDI) is proposed based on a triangle constructed using the mid-morning land surface temperature (LST) rising rate and the vegetation index to estimate the regional SWC. The temperature at the dry edge of the triangle is determined by the surface energy balance principle. The temperature at the wet edge is assumed to be equal to the air temperature. The mid-morning land surface temperature rising rate is calculated using Meteosat Second Generation—Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) LST products over 4 cloud-free days (day of year: 206, 211, 212, 242) in 2007. The developed TRRVDI is validated by in situ measurements from 19 meteorological stations in Spain. The results indicate that the coefficient of determination (R2) between the TRRVDI derived using the theoretical limiting edges and the in situ SWC measurements is greater than that derived using the observed limiting edges. The R2 values are 0.46 and 0.32; respectively (p < 0.05). Additionally, the TRRVDI is much better than the soil moisture index that was developed using one-time LST and fractional vegetation cover (FVC) with the theoretically determined limiting edges.

25 August 2020 in Neural Computing and Applications
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Journal Article
Closed access
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ZDZhang Dianjun
Zhang Dianjun
JZJie Zhan
Jie Zhan
LTLifeng Tan
Lifeng Tan
YGYuhang Gao
Yuhang Gao
RŽRobert Župan
Robert Župan

17 November 2023 in Science of The Total Environment
Verified
Journal Article
Closed access
PHPingping Hong
Pingping Hong
JXJingen Xiao
Jingen Xiao
HLHongtao Liu
Hongtao Liu
ZNZhiguang Niu
Zhiguang Niu
YMYini Ma
Yini Ma
YMYongzheng Ma
Yongzheng Ma

Verified
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ZOZhuxin Ouyang
Zhuxin Ouyang
JQJiawei Qi
Jiawei Qi
XZXuefeng Zhang
Xuefeng Zhang
XWXiangyu Wu
Xiangyu Wu
ZDZhang Dianjun
Zhang Dianjun
Significant Wave Height (SWH) is a crucial parameter in ocean wave dynamics, impacting coastal safety, maritime transportation, and meteorological research. Building upon the TimesNet neural network, a recent advancement in the realm of time series prediction in deep learning, this study proposes an integrated approach combining Empirical Mode Decomposition (EMD) with TimesNet, introducing the EMD-TimesNet model for SWH forecasting. The TimesNet model’s multidimensional spatial mapping guarantees effective historical information extraction, while the EMD approach makes it easier to decompose subsequence characteristics inside the original SWH data. The predicted Root Mean Square Error (RMSE) and Correlation Coefficient (CC) values of the EMD-TimesNet model are 0.0494 m and 0.9936; 0.0982 m and 0.9747; and 0.1573 m and 0.9352 at 1 h, 3 h, and 6 h, respectively. The results indicate that the EMD-TimesNet model outperforms existing models, including the TimesNet, Autoformer, Transformer, and CNN-BiLSTM-Attention models, both in terms of overall evaluation metrics and prediction performance for diverse sea states. This integrated model represents a promising advancement in enhancing the accuracy of SWH predictions.

14 September 2020 in IEEE Access
Verified
Journal Article
Open access
HZHao Zhang
Hao Zhang
ZDZhang Dianjun
Zhang Dianjun
AZAnmin Zhang
Anmin Zhang
The Tianjin port plays a relevant role in driving both ship navigation and the weather and climate of the area. To better understand the underlying peculiarities of this area, several in-service coastal ocean system and facilities have been constructed, at present, the whole coastal ocean systems at Tianjin port have been improved, however, they cannot meet the safety requirements of traffic management and navigational safety. Marine buoys have the unreplaceable advantages of long-term, real-time, reliable capabilities and trivial environmental restrictions to monitor the marine dynamics. Here an innovative multifunctional buoy prototype is proposed to continuously measure meteorological and oceanographic parameters at a high spatial and temporal resolution, which can ensure navigation safety at Tianjin Port. Solar panels and battery module are personalized to ensure electric supply to the buoy system. An independent ARM (Advanced RISC Machine)-based module is affiliated to maintain the stability of the data acquisition and communication module. Buoy platform based on Beidou difference is proved to be an effective approach for the tide measurement. Additionally, a web-designed software for data acquisition is integrated for the visualization purpose. Finally, in-field recording test at Tianjin port will be performed to verify effectiveness of our system on monitoring environment dynamics. It turns out that our buoy prototype functions as a reliable and energy favorable electrical device and shed light on the development of effective measurement instruments working under unpredictable and harsh marine environment.