Integration of multi-disciplinary geospatial data for delineating agroecosystem uniform management zones.
Understanding agricultural ecosystems and their complex interactions with the environment is important for improving agricultural sustainability and environmental protection. Developing the necessary understanding requires approaches that integrate multi-source geospatial data and interdisciplinary relationships at different spatial scales. In order to identify and delineate landscape units representing relatively homogenous biophysical properties and eco-environmental functions at different spatial scales, a hierarchical system of uniform management zones (UMZ) is proposed. The UMZ hierarchy consists of seven levels of units at different spatial scales, namely site-specific, field, local, regional, country, continent, and globe. Relatively few studies have focused on the identification of the two middle levels of units in the hierarchy, namely the local UMZ (LUMZ) and the regional UMZ (RUMZ), which prevents true eco-environmental studies from being carried out across the full range of scales. This study presents a methodology to delineate LUMZ and RUMZ spatial units using land cover, soil, and remote sensing data. A set of objective criteria were defined and applied to evaluate the within-zone homogeneity and between-zone separation of the delineated zones. The approach was applied in a farming and forestry region in southeastern Ontario, Canada, and the methodology was shown to be objective, flexible, and applicable with commonly available spatial data. The hierarchical delineation of UMZs can be used as a tool to organize the spatial structure of agricultural landscapes, to understand spatial relationships between cropping practices and natural resources, and to target areas for application of specific environmental process models and place-based policy interventions.
College of Natural Resources and the Environment, Northeast Agricultural University, Harbin, 150030, China.
Huanjun
H
Liu
Ted
T
Huffman
Jiangui
J
Liu
Zhe
Z
Li
Bahram
B
Daneshfar
Xinle
X
Zhang
D000383:Agriculture / Q000706:statistics & numerical data*; D003247:Conservation of Natural Resources / Q000379:methods*; D017753:Ecosystem; D004777:Environment; D004784:Environmental Monitoring / Q000379:methods*; D009864:Ontario; D063809:Satellite Imagery; D012987:Soil
D012987:Soil