Shahid Nawaz Khan
-Remote Sensing -GIS -Machine learning -GeoAI
-Remote Sensing -GIS -Machine learning -GeoAI
Born in a small village in District Swabi, Khyber Pakhtunkhwa, i received my early education from the same village. Later on, I got my Bachelor's degree in Geoinformatics Engineering from School of Civil and Environmental Engineering at National University of Sciences and Technology (Pakistan). My undergraduate studies mainly focused on Geoinformatics, and I was mainly trained in Programming, Geographic Information Systems, and GIS Automation. , I hold a Master's degree in Remote Sensing and GIS from National University of Sciences and Technology (Pakistan). During Master's I focused on several advanced topics in GIS, Remote Sensing, and Web GIS. After completing my Master's I worked as Lecturer of Geoinformatics in National University of Sciences and Technology, Pakistan where i taught several courses.
I was admitted as a PhD student at Department of Geography and Geospatial Sciences, South Dakota State University, Brooking, South Dakota, USA. I spent two and a half years in the Ph.D program where I studied several courses related to remote sensing, GIS, machine learning, and deep learning . I also worked on UAV remote sensing datasets with machine learning for crop yield and seed protein content estimations . In August 2023, I transferred my Ph.D program to The University of Alabama.
Currently, I am working as a Graduate Teaching Assisstant and PhD student at Department of Geography and the Environment, The University of Alabama, Tuscaloosa, AL, USA. During my Ph.D and after, I intend to work in the intesection of remote sensing, machine learning and agriculture. This includes applications of powerful machine learning/deep learning algorithms on remote sensing data for crop yield predictions and other paramaters related to food security and policymaking.
Aug 2023 - present
PhD in Geography
Department of Geography and the Environment
The University of Alabama, Tuscaloosa, AL, USA
Dissertation: Crop Yield Estimation Using Multiscale Remote Sensing and Machine Learning
Advisor: Dr. Dapeng Li
Jan 2021 - Aug 23
PhD in Geospatial Sciences and Engineering, Remote Sensing Specialization
Department of Geography and Geospatial Sciences
South Dakota State University, Brooking, SD, USA
Dissertation: Crop Yield Prediction using Multiscale Remote Sensing and Machine Learning
Advisor: Dr. Dapeng Li
Transferred to: The University of Alabama
2018
MS in Remote Sensing and GIS (Concentration: GIS, Remote Sensing, & Web GIS)
Institute of Geographical Information Systems, School of Civil and Environmental Engineering
National University of Sciences & Technology, Pakistan
Dissertation: Optimizing Allocations Decision in Open and Distance Learning using Agent-based Model and Spatial Decision Support Systems
Advisors: Dr. Ali Tahir
2016
Bachelors in Geoinformatics Engineering (Concentration: GIS, Remote Sensing, Digital Image Processing, & Web GIS)
Institute of Geographical Information Systems, School of Civil and Environmental Engineering
National University of Sciences & Technology, Pakistan
August 2023 - Present
Graduate Teaching Assisstant
Department of Geography and the Environment, The University of Alabama, Tuscaloosa, Alabama
May 2023 - Aug 2023
GIS Developer
Department of Geography and Geospatial Sciences, South Dakota State University, Brooking, South Dakota, 57007
January 2021 - May 2023
Graduate Research Assisstant
Department of Geography and Geospatial Sciences, South Dakota State University, Brooking, South Dakota, 57007
October 2018 - Decemeber 2020
Lecturer of Geoinformatics
Institute of Geographiacal Information Systems, National University of Sciences and Technology, Pakistan
January 2018 - October 2018
Graduate Teaching Assisstant
Institute of Geographiacal Information Systems, National University of Sciences and Technology, Pakistan
Supervisor: Dr. Javed Iqbal
December 2016 - October 2018
GIS Developer
GIS Plus, Technology Incubation Center
National University of Sciences and Technology, Pakistan
Methods:
Machine Learning, Remote Sensing, GIS Development, Spatial Databases, Spatial Data Analysis
Foci:
Agriculture, Natural Resources, Environment, Sustainability
2022
Ketchpaw, R. A., Li, D.,Khan, S.N., Jiang, Y., Li, Y., & Zhang, L. (2022). Using structure location data to map the wildland-urban interface in Montana, USA. Fire, 5(5), 129. IF: 2.726. doi:10.3390/fire5050129 [pdf]
2022
Khan, S.N., Li, D., & Maimaitijiang, M. (2022). A Geographically Weighted Random Forest Approach to Predict Corn Yield in the US Corn Belt. Remote Sensing, 14(12), 2843. IF: 4.848 doi:10.1038/s41598-021-96075-3 [pdf]
2021
Ahmad, W., Iqbal, J., Nasir, M. J., Ahmad, B., Khan, M. T., Khan, S.N., & Adnan, S. (2021). Impact of land use/land cover changes on water quality and human health in district Peshawar Pakistan. Scientific Reports, 11(1), 1-14. IF: 4.379 doi:10.1038/s41598-021-96075-3 [pdf ]
2020
Khan, K., Iqbal, J., Ali, A., & Khan, S.N.. (2020). Assessment of Sentinel-2-Derived Vegetation Indices for The Estimation of Above-Ground Biomass/Carbon Stock, Temporal Deforestation and Carbon Emissions Estimation in the Moist Temperate Forests of Pakistan". Applied Ecology and Environmental Research, 18(1), 783-815. IF: 0.712 doi:10.15666/aeer/1801_783815 [pdf]
2018
Khan, S.N., Mir, K., Tahir, A., Awan, A., Nisa, Z. U., & Gillani, S. A. (2018). Allocation of Tutors and Study Centers in Distance Learning Using Geospatial Technologies". ISPRS International Journal of Geo-Information, 7(5), 185. IF: 2.239 doi:10.3390/ijgi7050185 [pdf]
2023
Khan, S.N., Maimaitijiang, M., Millet, B., Paheding, S., Li, D., Caffé, M., & Kovács, P. (2023). "Simultaneously Estimating Crop Yield and Seed Composition Using Multitask Learning From UAV Multispectral Data". 2023 IEEE International Geoscience and Remote Sensing Symposium IGARSS doi: 10.1109/IGARSS52108.2023.10282273
2023
Maimaitijiang, M., Millet, B., Paheding, S., Khan, S.N., Dilmurat, K., & Kovács, P. (2023). "Estimating Crop Grain Yield and Seed Composition Using Deep Learning from UAV Multispectral Data". 2023 IEEE International Geoscience and Remote Sensing Symposium IGARSS doi: 10.1109/IGARSS52108.2023.10281802
2022
"Drone technology reaches new heights at SDSU". Keloland Media Group, September 05, 2022. (Reporter: Ariana Schumacher). [Video]
2022
"South Dakota State researchers using drones to aid precision agriculture". Dakota News Now, September 15, 2022. (Reporter: Cooper Seamer). [News Link]
Fall 20
Instructor
CS-471 GIS Programming
Fall 20
Instructor
GIE-306 Cartography and Map Production
Fall 20
Instructor
CS-340 Web Technologies
Spring 20
Instructor (Co-taught with Ms. Quratulain)
CS-471 Machine Learning
Spring 20
Instructor
GIE-409 Spatial Databases
Fall 19
Instructor
GIE-471 GIS Programming
Fall 19
Instructor
CS-250 Data Structures and Algorithms
Spring 19
Instructor
CS-212 Object Oriented Programming
Spring 19
Instructor
GIE 409 Spatial Databases
Fall 18
Instructor
CS 110 Fundamentals of Programming
Fall 18
Instructor
GIE 321 Database Management Systems
2019
Khan, S,N. “GeoInformatics Serves the Belt and Road”. International Summer School, Central South University, Changsha, PRC.
2023
Khan, S.N. “Simultaneously Estimating Crop Yield and Seed Composition Using Multitask Learning From UAV Multispectral Data”. International Geoscience and Remote Sensing Symposium (2023) , Pasadena, California, U.S.A.
2022
Khan, S.N.“Spatially explicit machine learning to predict county-level corn yield in US Corn Belt”. Black Hills Digital Mapping Conference (October 17th 2022) , Rapid City, South Dakota, U.S.A.
2022
Khan, S.N.“County-level Crop Yield Prediction Using Machine Learning”. AAG Annual GPRM Meeting (October 15th 2022) , Denver, Colorado, U.S.A.
2022
Khan, S.N, Li, D. Maimaitijiang, M.“Corn yield prediction using geographically weighted machine learning”. 53rd Geography Convention (March 31st - April 1st 2022) , Brookings, South Dakota, U.S.A.
2022
Khan, S.N. Li, D. “County-level Corn and Soybean Yield Prediction Using MODIS-derived Primary Production and Deep Learning”. Earth Resources Observation and Science (EROS), USGS, Poster Competition (Novemeber 16th 2022) , Sioux Falls, South Dakota, U.S.A.
2022
Khan, S.N, Maimaitijiang, M, Li, D.“Corn yield prediction with machine learning using remote sensing, climate, and soil data ”. 53rd Geography Convention (March 31st - April 1st 2022) , Brookings, South Dakota, U.S.A.
2023
First place in Graduate Students Poster Competition, Geography Convention (March 31st to April 01, 2023), South Dakota State University, Brookings, SD
2022
First place in Graduate Students Poster Competition, Geography Convention (March 31st to April 01, 2022), South Dakota State University, Brookings, SD
2023
Graduate School Travel Award (For attending and presenting at 2023 IGARSS Conference in Pasadena, CA)
2023
American Association of Geographers (AAG) Travel Award (For attending AAG 2023 Annual Meeting in Denver, CO)
2019
Young Teacher Travel Award, Central South University, Changsha, China
2021
Higher Education Commission Scholarship for PhD Studies in USA under US Pakistan Knowledge Corridor Program
2021
Graduate Research Assistantship, South Dakota State University, USA
2016
ICT R&D Scholarship for high achieving Master's Students at NUST, Pakistan
2012
Scholarship for Undergraduate studies in NUST, Pakistan
2023
Best Graduate Student of the year, Department of Geography and Geospatial Sciences, South Dakota State University
Programming Languages
Python, C/C++, R
GIS/Remote Sensing Tools
ArcMap, ArcGIS Pro, ArcPy, ENVI, ERDAS IMAGINE, QGIS, Google Earth Engine
Machine Learning/Deep Learning
Scikit-learn, Keras, Pandas, Numpy, GeoPandas
Open Source Geospatial Tools
GDAL/OGR, OpenTools, PROJ.4,RasterIO, ArcPy
WebGIS Development
OpenLayers, Leaflet, GeoServer, PostGIS
Database Skills
PostgreSQL/PostGIS, SQL Server, DB2, MySQL
Agent-Based Modeling
GAMA Platform
Name:
Shahid Nawaz Khan
Email:
shahidnawaz[dot]khan[at]jacks[dot]sdstate[dot]edu
snawaz[at]igis[dot]nust[dot]edu[dot]pk
Mail Address:
324, Farrah Hall (Cartographic Research Lab)
The University of Alabama
Tuscaloosa, AL
Official Websites:
Personal Website:
Webpages
