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Artificial Intelligence for Agriculture and Climate

Type: Paper
Sponsor Groups: Rural Geography Specialty Group
Poster #:
Day: 4/8/2020
Start / End Time: 1:45 PM / 3:00 PM (MDT)
Room: Virtual Track 3
Organizers: Ziheng Sun, Manzhu Yu
Chairs: Ziheng Sun


Human geography is historically at some level dominated by agricultural environment and climate factors. Even today the agricultural environment and climate still have a wider and more direct effect on the human society. Farming on different types of soils in various climates requires different set of knowledge and skills to secure the yield and quality. Also, human factors, policy, costs, and prices cannot be ignored in explaining the farming activities in today’s world agriculture landscape. The environmental and human factors interfere with each other and results in the current crop distribution, food chain, agricultural market distribution and pricing. To get a better understanding of agricultural geography, we must build models/tools/systems to help estimate the impacts of the changes of each component in the agriculture-climate-human networks. However, the mutual interfering is very difficult to simulate by traditional numeric modeling methods due to the lack of fine-resolution observations and the complexity of the underlying mechanisms. Artificial intelligence, however, lets us see some possibility to simulate these relationships without diving into the ultra-complicated numeric models. We have seen several successful application of using the state-of-art AI techniques in accomplishing difficult tasks in agriculture, e.g., automatically crop mapping at large scale, which can only imagine before. We would like to invite community geographers to attend us to talk about your opinions/experiences/visions on using artificial intelligence in analyzing/monitoring/predicting the relationships and consequences in agriculture and climate-related geographical factors.


Type Details Minutes Start Time
Presenter Chris Burney*, West Virginia University, Building Production Ecosystems from the Soil Up: Using Ecological Site Descriptions to Map Agroforestry Feasibility in Southern West Virginia 10 1:45 PM
Introduction Sadia Alam Shammi Mississippi State University 8 1:55 PM
Presenter Bing Lu*, University of Toronto - Mississauga, Yuhong He, University of Toronto Mississauga, Jiali Shang, Agriculture and Agri-Food Canada, Jiangui Liu, Agriculture and Agri-Food Canada, Cameron Proctor, University of Windsor, Phuong Dao, University of Toronto Mississauga, Ali Al Wafi, University of Toronto Mississauga, Monitoring Crop Physiological Status Using Airborne Hyperspectral and Thermal Images 10 2:03 PM
Presenter John V. Cotter*, St. Edward's University, It's Not Always About Climate Change: The Development of the Texas Olive OIl Industry 10 2:13 PM
Presenter Rohit Mukherjee*, The Ohio State University, Desheng Liu, The Ohio State University, Fusion of Landsat 8 and Sentinel-2 Imagery using a Deep Generative Model 10 2:23 PM
Introduction Pouyan Hatami Department of Geography 7 2:33 PM
Presenter Diego Pons*, Columbia University, Connecting the Next Generation of Seasonal and Sub-seasonal Forecasts to Vegetation Stress Indices 10 2:40 PM
Presenter Ziheng Sun*, George Mason University, Liping Di, George Mason University, Hui Fang, George Mason University, AI-Augmented Agricultural Geography and Remote Sensing 10 2:50 PM

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