TY - GEN
T1 - Empowering Cover Crop Decision Support with Visualization and Provenance Enhancement
AU - Shrestha, Sujan
AU - Sun, Jianxin
AU - Koehler-Cole, Katja
AU - Basche, Andrea
AU - Yu, Hongfeng
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Cover crops offer a range of agricultural and environmental benefits, such as reducing soil erosion, increasing carbon and enhancing water storage, increasing forage production, protecting soil nutrients, and so on. However, adoption of cover crop farming remains limited among Nebraska's farmers. To promote awareness of the value of cover crop farming, we harness modern tools and technology and develop a new web-based tool capable of quantifying potential forage production, forage quality, and environmental benefits when planting cover crops, taking into account factors like climate, soil types, and seeding periods. Our tool incorporates the concept of data provenance to capture simulation configurations and results. This implementation can enhance data integrity and facilitate knowledge sharing within the scientific community, supporting further research and broader public benefits. The tool also includes reporting functions with visualizations illustrating distributions of potential forage, transpiration, nitrogen uptake, and more. Based on factors such as cover crop types, planting and termination dates, locations, and soil types, our tool provides valuable insights, enabling farmers to experiment with different cover crops on their land, ultimately leading to improved environmental outcomes for the broader Nebraska community.
AB - Cover crops offer a range of agricultural and environmental benefits, such as reducing soil erosion, increasing carbon and enhancing water storage, increasing forage production, protecting soil nutrients, and so on. However, adoption of cover crop farming remains limited among Nebraska's farmers. To promote awareness of the value of cover crop farming, we harness modern tools and technology and develop a new web-based tool capable of quantifying potential forage production, forage quality, and environmental benefits when planting cover crops, taking into account factors like climate, soil types, and seeding periods. Our tool incorporates the concept of data provenance to capture simulation configurations and results. This implementation can enhance data integrity and facilitate knowledge sharing within the scientific community, supporting further research and broader public benefits. The tool also includes reporting functions with visualizations illustrating distributions of potential forage, transpiration, nitrogen uptake, and more. Based on factors such as cover crop types, planting and termination dates, locations, and soil types, our tool provides valuable insights, enabling farmers to experiment with different cover crops on their land, ultimately leading to improved environmental outcomes for the broader Nebraska community.
KW - cover crops
KW - environment
KW - provenance
KW - simulation
KW - visualization
UR - http://www.scopus.com/inward/record.url?scp=85184985392&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85184985392&partnerID=8YFLogxK
U2 - 10.1109/BigData59044.2023.10386794
DO - 10.1109/BigData59044.2023.10386794
M3 - Conference contribution
AN - SCOPUS:85184985392
T3 - Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023
SP - 4548
EP - 4556
BT - Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023
A2 - He, Jingrui
A2 - Palpanas, Themis
A2 - Hu, Xiaohua
A2 - Cuzzocrea, Alfredo
A2 - Dou, Dejing
A2 - Slezak, Dominik
A2 - Wang, Wei
A2 - Gruca, Aleksandra
A2 - Lin, Jerry Chun-Wei
A2 - Agrawal, Rakesh
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Conference on Big Data, BigData 2023
Y2 - 15 December 2023 through 18 December 2023
ER -