A5024042979- Remote Sensing in Agriculture
- Flood Risk Assessment and Management
- Precipitation Measurement and Analysis
- Hydrology and Drought Analysis
- Hydrology and Watershed Management Studies
- Climate variability and models
- Plant Water Relations and Carbon Dynamics
- Hydrology and Sediment Transport Processes
- Atmospheric and Environmental Gas Dynamics
- Hydrological Forecasting Using AI
- Psychiatric care and mental health services
- Satellite Image Processing and Photogrammetry
- Complex Systems and Decision Making
- Calibration and Measurement Techniques
- Meteorological Phenomena and Simulations
- Tropical and Extratropical Cyclones Research
- Species Distribution and Climate Change
- Evaluation and Performance Assessment
HKV (Netherlands)
2019-2021
State Key Laboratory of Remote Sensing Science
2016-2019
Institute of Remote Sensing and Digital Earth
2016-2019
Chinese Academy of Sciences
2016-2019
University of Chinese Academy of Sciences
2016
The time lag between anomalies in precipitation and vegetation activity plays a critical role early drought detection as agricultural droughts are caused by shortages. aim of this study is to explore new approach estimate the forcing (precipitation) response (NDVI) signal frequency domain applying cross-spectral analysis. We prepared anomaly series image data on TRMM3B42 (accumulated over antecedent durations 10, 60, 150 days) NDVI, reconstructed interpolated MOD13A2 MYD13A2 daily interval...
It has long been recognized that an effective drought monitoring and early warning system, which provides functions for real-time condition prediction, risk assessment, information dissemination response recommendation, is very important the preparedness mitigation of impacts. In this article, we review currently existing monitor systems, discuss applicable remote sensing datasets indicators present development a web-based quasi-real-time Global Drought Monitoring & Analysis Platform...
The applications of Multi-temporal Normalized Difference Vegetation Index (NDVI), a critical proxy for analysing vegetation dynamics, have been long hindered by prevalent noise. Harmonic ANalysis Time Series (HANTS) has widely applied to reconstruct noise- and cloud-free NDVI time series data set from regional global scales. reconstruction performance HANTS is severely dependent on the inherent parameter settings in HANTS. However, most parameters based users' experience. This study analysed...
The meteorological drought, caused by a shortage of precipitation over certain period, is the root causal chain in drought series agriculture, ecology and hydrology. Different datasets produced inconsistent conclusions characteristics trends events. This study analyzed China using standardized index (SPI) derived from TRMM CMORPH data. annual was increased 1998 to 2014, indicating wetting trend past near twenty years. data showed more significant than mainly occurred northern China, while...
<p>Accurate short-term forecasts, also known as nowcasts, of heavy precipitation are desirable for creating early warning systems extreme weather and its consequences, e.g. urban flooding. In this research, we explore the use machine learning prediction rainfall showers in Netherlands.</p><p>We assess performance a recurrent, convolutional neural network (TrajGRU) with lead times 0 to 2 hours. The is trained on 13-year archive radar images 5-min...
<p>On the world’s fastest urbanizing continent, Africa, urban floods are a real and growing problem. Early warning is first important step in flood risk management. This requires continuous reliable precipitation measurements forecasts, which not always available African cities.</p><p>In this study nowcasting model based on Convolutional Neural Network (TrajGRU) was developed for short-term, 0-2 hours, forecast Ghana, West Africa. The...