YIN LIU

Phone: +1-734-***-**** Email: adbx2p@r.postjobfree.com

EDUCATION

University of Michigan School for Environment and Sustainability (Ann Arbor, MI) September 2019 Master of Science, Environmental Informatics, August 2019 China University of Geosciences (Wuhan, China) September 2015 Bachelor of Science, Remote Sensing Science and Technology, Information Engineering SKILLS

• Professional Software: ArcGIS, Google Earth Engine, ENVI, Microsoft Visual Studio, Eclipse, MATLAB, MySQL, Microsoft Office

• Computer Languages: R, Python, JavaScript, C++, C#

• Languages: English and Chinese

EXPERIENCE

China University of Geosciences (Wuhan, China)

Faculty of Information Engineering, CUG, Wuhan, Individual Project Spatio-temporal Change Analysis for the Straw Burning in Hubei Province from 2001-2017 December 2017

• Determined the topic and direction of this project

• Consulted literatures online and found the straw burning site through batch processing data and codes

• Extracted the flare point data of MODIS image by adopting ENVI-IDL in secondary development environment and IDL programming language

• Made a spatio-temporal analysis via Mann-Kendall trend analysis method, downloaded DPS for further analysis and evaluation Faculty of Information Engineering, CUG, Wuhan, Planning Project of Innovation for National Undergraduates Tiangong-2 3D Imaging Microwave Altitude to Detect Anomaly Sea Surface Gravity and Explore Marine Gas Reservoir March 2017 - June 2018

• Sought the oil and gas reservoir through altitude data, satellite orbit altitude and anomaly sea level height, and attained the gravity profile through gravity data preprocessing

• Observed the anomaly gravity by contrasting the gravity distribution in the same latitude and longitude and the inversion method of marine microgravity anomaly

• Verified these data by using Tiangong-2 data to extract abnormal height of marine microgravity and find the oil and gas abnormal area in Hainan region

• Obtained the anomaly gravity code by establishing the global gravity model of EGM1996 and EGM2008 with MATLAB and finished the thesis

IA Collaboration Project, Information Engineering Lab, CUG Building Damage Assessment of Compact Polarimetric SAR Using Statistical Model Texture Parameter April 2017 - June 2018

• Extracted the parameters of statistical models from compact polarimetric SAR images within 3 different modes, and recognized the collapsed buildings according to various characteristic values and the parameters of statistical models

• Evaluated the degree of buildings’ damage to three types: light damage, moderate damage and severe damage

• Tested the result and chose the suitable SAR model as well as characteristic parameter in the light of precision evaluation result

• Collated these data and analyzed the result; finished the report and oral defense

• Published the thesis-Building Damage Assessment of Compact Polarimetric SAR Using Statistical Model Texture Parameter on 2017 SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA), IEEE CONFERENCES as the 1st author Mathematical Contest in Modeling / Interdisciplinary Contest in Modeling (MCM/ICM) August 2017 - May 2018

• Distributed the tasks after group discussion: I was engaged in the code programming and data collection mainly

• Decided the resolving idea and prepared for the model building

• Sought the data of vulnerable countries from the United Nations database by visiting foreign website

• Regressed a multitude of variables via logical regression model and analyzed them with PCA

• Analyzed the conclusion after programming with MATLAB, and then wrote the thesis

• Bore the palm of Honorable Mention

University of Michigan, Ann Arbor

YIN LIU

Phone: +1-734-***-**** Email: adbx2p@r.postjobfree.com Meha Jain Lab, Master’s Student (Ann Arbor, MI) December 2019 – Present Mapping zero tillage vs conventional tillage in Arrah, Bihar

• Utilizing high-resolution satellite images including Planet, Sentinel 1 and 2 to classify conventional and conservative tillage in Arrah, Bihar

• Skills: Google Earth Engine (Javascript & Python), R PUBLICATIONS

• Liu, Y.; Li, L.; Chen, Q.; Shu, M.; Zhang, Z.; Liu, X. Building Damage Assessment of Compact Polarimetric Sar Using Statistical Model Texture Parameter. In Proceedings of the SAR in Big Data Era: Models, Methods and Applications (BIGSARDATA), Beijing, China, 13–14 November 2017; IEEE: Piscataway, NJ, USA, 2017; pp. 1–4.

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