Dingrong Wu

Dr. Dingrong Wu


Research Focus & Metrics

Academic Career Length

17Years (2010-Present)

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

Representative Publications

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1 May 2020 in Agricultural and Forest Meteorology
Verified
Journal Article
Closed access
PWPeijuan Wang
Peijuan Wang
DWDingrong Wu
Dingrong Wu
JYJianying Yang
Jianying Yang
YMYuping Ma
Yuping Ma
RFRui Feng
Rui Feng
ZHZhiguo Huo
Zhiguo Huo

5 December 2018 in International Journal of Plant Production
Verified
Journal Article
Closed access
PDF file
DWDingrong Wu
Dingrong Wu
PWPeijuan Wang
Peijuan Wang
CJChaoyang Jiang
Chaoyang Jiang
JYJianying Yang
Jianying Yang
ZHZhiguo Huo
Zhiguo Huo
QYQiang Yu
Qiang Yu

19 March 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
PWPeijuan Wang
Peijuan Wang
YMYuping Ma
Yuping Ma
JTJunxian Tang
Junxian Tang
DWDingrong Wu
Dingrong Wu
HCHui Chen
Hui Chen
ZHZhiguo Huo
Zhiguo Huo
Tea (Camellia sinensis) is one of the most dominant economic plants in China and plays an important role in agricultural economic benefits. Spring tea is the most popular drink due to Chinese drinking habits. Although the global temperature is generally warming, spring frost damage (SFD) to tea plants still occurs from time to time, and severely restricts the production and quality of spring tea. Therefore, monitoring and evaluating the impact of SFD to tea plants in a timely and precise manner is a significant and urgent task for scientists and tea producers in China. The region designated as the Middle and Lower Reaches of the Yangtze River (MLRYR) in China is a major tea plantation area producing small tea leaves and low shrubs. This region was selected to study SFD to tea plants using meteorological observations and remotely sensed products. Comparative analysis between minimum air temperature (Tmin) and two MODIS nighttime land surface temperature (LST) products at six pixel-window scales was used to determine the best suitable product and spatial scale. Results showed that the LST nighttime product derived from MYD11A1 data at the 3 × 3 pixel window resolution was the best proxy for daily minimum air temperature. A Tmin estimation model was established using this dataset and digital elevation model (DEM) data, employing the standard lapse rate of air temperature with elevation. Model validation with 145,210 ground-based Tmin observations showed that the accuracy of estimated Tmin was acceptable with a relatively high coefficient of determination (R2 = 0.841), low root mean square error (RMSE = 2.15 °C) and mean absolute error (MAE = 1.66 °C), and reasonable normalized RMSE (NRMSE = 25.4%) and Nash–Sutcliffe model efficiency (EF = 0.12), with significantly improved consistency of LST and Tmin estimation. Based on the Tmin estimation model, three major cooling episodes recorded in the "Yearbook of Meteorological Disasters in China" in spring 2006 were accurately identified, and several highlighted regions in the first two cooling episodes were also precisely captured. This study confirmed that estimating Tmin based on MYD11A1 nighttime products and DEM is a useful method for monitoring and evaluating SFD to tea plants in the MLRYR. Furthermore, this method precisely identified the spatial characteristics and distribution of SFD and will therefore be helpful for taking effective preventative measures to mitigate the economic losses resulting from frost damage.

19 January 2023 in Ecological Indicators
Verified
Journal Article
Open access
JTJunxian Tang
Junxian Tang
PWPeijuan Wang
Peijuan Wang
XLXin Li
Xin Li
JYJianying Yang
Jianying Yang
DWDingrong Wu
Dingrong Wu
ZHZhiguo Huo
Zhiguo Huo

1 December 2014 in Journal of Meteorological Research
Verified
Journal Article
Closed access
PDF file
Jianping GuoJianping Guo
Jianping Guo
JZJunfang Zhao
Junfang Zhao
DWDingrong Wu
Dingrong Wu
JMJia Mu
Jia Mu
YXYanhong Xu
Yanhong Xu

9 July 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
PWPeijuan Wang
Peijuan Wang
JTJunxian Tang
Junxian Tang
YMYuping Ma
Yuping Ma
DWDingrong Wu
Dingrong Wu
JYJianying Yang
Jianying Yang
ZHZhiguo Huo
Zhiguo Huo
Spring frost damage (SFD), defined as the disaster during the period of newly formed tea buds in spring caused by lower temperature and frost damage, is a particular challenge for tea plants (Camellia sinensis), whose capacity to adapt to extreme weather and climate impacts is limited. In this paper, the region of the Middle and Lower Reaches of the Yangtze River (MLRYR) in China was selected as the major tea plantation study area, and the study period was focused on the concentrated occurrence of SFD, i.e., from March to April. By employing the standard lapse rate of air temperature with elevation, a minimum temperature (Tmin) estimation model that had been previously established was used based on reconstructed MYD11A1 nighttime LST values for 3 × 3 pixel windows and digital elevation model data. Combined with satellite-based Tmin estimates and ground-based Tmin observations, the spatiotemporal characteristics of SFD for tea plants were systematically analyzed from 2003 to 2020 in the MLRYR. The SFD risks at three scales (temporal, spatial, and terrain) were then evaluated for tea plants over the MLRYR. The results show that both SFD days at the annual scale and SFD areas at the daily scale exhibited a decreasing trend at a rate of 2.7 days/decade and 2.45 × 104 ha/day, respectively (significant rates at the 0.05 and 0.01 levels, respectively). The period with the highest SFD risk appeared mainly in the first twenty days of March. However, more attention should be given to the mid-to-late April time period due to the occurrence of late SFD from time to time. Spatially, areas with relatively higher SFD days and SFD risks were predominantly concentrated in the higher altitude areas of northwestern parts of MLRYR for both multi-year averages and individual years. Fortunately, in regions with a higher risk of SFD, the distribution of tea plants was relatively scattered and the area was small. These findings will provide helpful guidance for all kinds of people, including government agencies, agricultural insurance agencies, and tea farmers, in order that reasonable and effective strategies to reduce losses caused by spring frost damage to tea plants may be recommended and implemented.