Advances in Mapping and Modeling of Agricultural Land Management Practices
Advances in Mapping and Modeling of Agricultural Land Management Practices
Session ID#: 283095
Session Description:
Advances in multi-source remote sensing, computing capacity, and AI-based modeling are enabling a shift beyond conventional land cover/use classification and change detection toward improved characterization of specific land management practices, transition processes, production system types, and detailed use regimes. This session will explore the latest developments in mapping, monitoring, and modeling of the management and conservation of agricultural landscapes. Relevant land systems of interest include croplands, grasslands, pasture and rangelands, working forests and woodlots, and various agroforestry systems, along with their associated management including planting, harvest, tillage, grazing, haying, manure/fertilizer application, or implementation of conservation practices such as cover cropping, tile drainage, integrated crop-livestock production, and rotational grazing.
Co-Sponsor(s):
- B - Biogeosciences
Index Terms:
0402 Agricultural systems [BIOGEOSCIENCES]
0480 Remote sensing [BIOGEOSCIENCES]
1615 Biogeochemical cycles, processes, and modeling [GLOBAL CHANGE]
1632 Land cover change [GLOBAL CHANGE]
Primary Convener: Tyler J Lark, Michigan State University, Department of Plant, Soil and Microbial Sciences, East Lansing, MI, United States
Conveners: He Yin, Kent State University, Department of Geography, Kent, United States, Nazli Z Uludere Aragon, University of Montana, Numerical Terradynamic Simulation Group, Missoula, MT, United States and Yanhua Xie, University of Oklahoma, Department of Geography and Environmental Sustainability, Norman, United States
See more of: Global Environmental Change