张智杰

2022.06 ～ 2024.07 亚利桑那大学 博士后研究员

2024.07 ～ 2026.02 犹他州立大学 专职助理教授

张智杰，华东师范大学空间人工智能学院青年研究员，紫江青年学者。入选上海市海外高层次人才计划。以气候变化为背景，对基于深度学习的环境灾害遥感监测与多源数据融合、分布式遥感水文模型开发、以及冰冻圈过程观测模拟等方面进行了较为系统的研究和探索，在Journal of Hydrology、Journal of Remote Sensing、IEEE Transactions on Geoscience and Remote Sensing、Geoscience Frontiers, International Journal of Applied Earth observation and Geoinformation等国际权威期刊以第一/通讯作者发表论文20余篇，Google Scholar被引2000余次。

回国前，在美国犹他州立大学任专职助理教授，并共同主持了由Climate Change AI Innovation Grants，NASA FINESST，Google Cloud Education Fund，以及犹他州立大学资助的四项课题，以主要合作者身份参与了NSF CAREER Award项目一项，以骨干身份参与NASA项目三项，所有获得资助项目都与深度学习，洪涝模拟与遥感监测相关。2024年获邀担任NASA项目评审专家。获得的基于LSTM的遥感变化检测专利被贵州林业局采用，成果直接支撑了《草海流域水生态环境综合保护与修复方案》的编制。博士后导师Beth Tellman受邀参加在白宫举行的“The White House Flood Technology Innovation Roundtable”，并对与申请人联合主持的Climate Change AI项目，以及申请人作为骨干参与的NASA项目成果进行了重点报告。

1. Geospatial Computer Vision (面向多光谱, 高光谱, SAR的CNN, LSTM, Transformer, Geofoundation Model)

2. 环境灾害遥感监测（洪涝，地灾，野火，农业干旱）

3. 分布式遥感水文模型（模型开发，模型驱动数据遥感反演）

4. 冰冻圈观测模拟（冰川，冻土）

华东师范大学：

助教 环境遥感与人工智能

犹他州立大学：
Instructor GEOG5805/6805 Introduction to GeoAI

Instructor GEOG6855 Advanced GeoAI: Geospatial Computer Vision

Instructor GEOG2805 Intro to Geospatial Information Science

主持：

参与：

1. Major Collaborator. “Addressing flood justice and equity impacts of adaptation and urban expansion with satellite observation”. 2024-2029. NSF CAREER Award.  经费：$500,000.

2. Leading Postdoc. "High-resolution imagery to train and validate deep learning models of inundation extent for multiple satellite sensors." NASA

3. Leading Postdoc. "Assessing BlackSky data for surface water detection" NASA

4. Leading Postdoc. "Mapping flood impacts using multi-sensor satellite data fusion in urban areas." NASA

Selected Publications:

1.       Zhang Z., Mukherjee R., Giezendanner J., Tellman B., Melancon A., Purri M., Gurung I., Lall U., Barnard K., Molthan A., 2025. Assessing Deep Learning Models Trained on Public versus Commercial Data using FloodPlanet, a High-Resolution Commercial Imagery Flood Dataset, for Inundation Detection. Journal of Remote Sensing. DOI: 10.34133/remotesensing.0575.

2.       Zhang Z., Ahmad Z.*, Xiong S.*, and Zhang W., Glacier velocity and surge detection in the Karakoram region, Pakistan: using remotely sensed data with cross-correlation feature tracking, International Journal of Digital Earth, 17:1, 2441928, DOI: 10.1080/17538947.2024.2441928.

3.       Zhang Z., Ahmad Z.*, Xiong S.*, and Zhang W., Assessing glacier mass balance variations and climate drivers of Shisper and Muchuhar glaciers in the Karakoram region, Pakistan: a remote sensing and GIS approach. International Journal of Digital Earth. DOI: 10.1080/17538947.2024.2406385.  

4.       Shi C.^†, Zhang Z.^†*, Zhang W., Zhang C., Xu Q., Learning Multiscale Temporal–Spatial–Spectral Features via a Multipath Convolutional LSTM Neural Network for Change Detection with Hyperspectral Images. 2022. IEEE Transactions on Geoscience and Remote Sensing. DOI: 10.1109/TGRS.2022.3176642. 

5.       Zhang Z.*, Arshad A., Zhang C., Hussain S., Li W., Unprecedented temporary reduction in global air pollution associated with COVID-19 forced confinement: A continental and city scale analysis. 2020. Remote Sensing. DOI:10.3390/rs1215242.  

6.    Zhang Z., Zhang C., Li W., Semantic Segmentation of Urban Buildings from VHR Remotely Sensed Imagery Using Attention-Based CNN. Proceeding of IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium; 2020 26 Sept.-2 Oct. 2020. DOI: 10.1109/IGARSS39084.2020.9324528. 【EI】

7.       Arshad A.^†, Zhang Z.^†, Zhang W.*, Dilawar A., Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model: A case study from an agro-urban region of Pakistan. 2019. Geoscience Frontiers. DOI: 10.1016/j.gsf.2019.12.013

8.       Yi Y.^†, Zhang Z.^†, Zhang W.*, Zhang C., Li W., Zhao T., Semantic segmentation of urban buildings from VHR remote sensing imagery using a deep convolutional neural network. Remote Sensing. 2019. DOI:10.3390/rs11151774