基本信息

职称：助理研究员
部门：遥感信息部
学历：博士研究生
专业：地球探测与信息技术
邮箱：zhicefang@hnas.ac.cn

毕业院校

中国地质大学（武汉）

地球探测与信息技术专业

工学博士


学术成果

发表论文：

40余篇

授权专利：
研究方向：

灾害时空建模与预测、气候变化影响评估


个人简介

方志策，男，1996年4月生，博士学历，现任河南省科学院空天信息研究所助理研究员。分别于2024、2020年和2017年获得中国地质大学（武汉）博士、硕士和学士学位，于2021年获得国家留学基金委资助前往荷兰特文特大学ITC学院开展联合培养项目。主要从事灾害遥感、地学信息智能处理领域的研究工作，重点研究方向包括基于深度学习的自然灾害时空预测、气象灾害时空演变趋势及气候归因分析。

在《International Journal of Applied Earth Observation and Geoinformation》、《Catena》、《International Journal of Geographical Information Science》、《Journal of Hydrology》和《Landslides》等高水平期刊发表论文40余篇，其中第一/通讯作者论文10余篇，论文总被引用2600余次（Google Scholar，H-Index＝18），8篇入选ESI全球1%高被引论文、1篇入选学术精要高影响力论文。


研究方向

气象灾害时空演变趋势及气候归因分析

研究焦点：量化并评估气候变化对滑坡、山洪等灾害造成的影响

核心方法：

1. 反事实气候变化场景构建

2. 因果推断

3. 未来情景下灾害演变趋势分析


基于深度学习的自然灾害时空预测

研究焦点：结合多源遥感、GIS数据，利用深度学习方法对滑坡、泥石流、山洪等灾害进行时空建模与预测

核心方法：

1. 考虑空间、时间和强度的滑坡危险性动态评估

2. 结合降雨时序特征的降雨型浅层滑坡预警

3. 多模式深度学习空间预测


代表性论文

Long and short-term perspectives on space–time landslide modelling
2025
Wang T, Yin K, Wang Z, Fang Z*

International Journal of Applied Earth Observation and Geoinformation, 142, 104694.

期刊链接
Climate change has increased rainfall-induced landslide damages in central China
2025
Fang Z, Morales A B, Wang Y, Lombardo L, 2025.

International Journal of Disaster Risk Reduction, 119: 105320.

期刊链接
Improved landslide prediction by considering continuous and discrete spatial dependency
2025
Fang Z, Wang J, Wang Y, Du B, Liu G, 2025

 Landslides, 22, 1107-1122.

期刊链接
Landslide hazard spatiotemporal prediction based on data-driven models: Estimating where, when and how large landslide may be
2024
Fang Z, Wang Y, van Westen C, Lombardo L, 2024.

International Journal of Applied Earth Observation and Geoinformation, 126, 103631.

期刊链接
Space-time modeling of landslide size by combining static, dynamic, and unobserved spatiotemporal factors
2024
Fang Z, Wang Y, van Westen C, Lombardo L, 2024.

Catena, 240, 107989.

期刊链接
Space–Time Landslide Susceptibility Modeling Based on Data-Driven Methods
2024
Fang Z, Wang Y, van Westen C, Lombardo L, 2024.

Mathematical Geosciences, 56, 1335-1354.

期刊链接
Speech-recognition in landslide predictive modelling: A case for a next generation early warning system
2023
Fang Z, Tanyas H, Gorum T, Dahal A, Wang Y, Lombardo L, 2023.

Environmental Modelling & Software, 170, 105833.

期刊链接
Comparison of general kernel, multiple kernel, infinite ensemble and semi-supervised support vector machines for landslide susceptibility prediction
2022
Fang Z, Wang Y, Duan H, Niu R, Peng L, 2022.

Stochastic Environmental Research and Risk Assessment, 36, 3535–3556.

期刊链接
Predicting flood susceptibility using LSTM neural networks
2021
Fang Z, Wang Y, Peng L, Hong H, 2021.

ournal of Hydrology, 594, 125734.

期刊链接
A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping
2021
Fang Z, Wang Y, Peng L, Hong H, 2021.

International Journal of Geographical Information Science, 35, 321-347.

期刊链接
Landslide susceptibility prediction based on positive unlabeled learning coupled with adaptive sampling
2021
Fang Z, Wang Y, Niu R, Peng L, 2021.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 11581-11592.

期刊链接
Landslide Susceptibility Mapping Using Rotation Forest Ensemble Technique with Different Decision Trees in the Three Gorges Reservoir Area, China
2021
Fang Z, Wang Y, Duan G, Peng L, 2021.

Remote Sensing, 13, 238

期刊链接
Integration of convolutional neural network and conventional machine learning classifiers for landslide susceptibility mapping
2020
Fang Z, Wang Y, Peng L, Hong H, 2020.

Computers & Geosciences, 139, 104470.

期刊链接
Flood susceptibility mapping by integrating frequency ratio and index of entropy with multilayer perceptron and classification and regression tree
2021
Wang Y, Fang Z, Hong H, Costache R, Tang X, 2021.

Journal of Environmental Management, 289, 112449. 

期刊链接
Flood susceptibility mapping using convolutional neural network frameworks
2020
Wang Y, Fang Z, Hong H, Peng L, 2020.

Journal of Hydrology, 582, 124482.

期刊链接
Comparison of convolutional neural networks for landslide susceptibility mapping in Yanshan County, China
2019
Wang Y, Fang Z, Hong H, 2019.

Science of the Total Environment, 666, 975-993.

期刊链接
基于深度学习的滑坡灾害易发性分析
2021
王毅, 方志策, 牛瑞卿，彭令

地球信息科学学报, 2021, 23(12): 2244-2260.

期刊链接

授权专利