Title :
Exploring continuous corn cropping patterns and their relationship with geographic factors
Author :
Weiguo Han ; Liping Di ; Yagci, Ali Levent ; Zhengwei Yang
Author_Institution :
Center for Spatial Inf. Sci. & Syst., George Mason Univ., Fairfax, VA, USA
Abstract :
Continuous cropping is one of main planting methods in the cropping systems. Discovering the continuous planting patterns and their relationship with geographic factors is a very meaningful research subject to support agricultural decision making. The Cropland Data Layer (CDL) data is one of useful land cover data resources to study the crop planting patterns of any area of interest in the Contiguous United States. In this paper, the CDL data of Iowa for the years of 2006-2012 are retrieved directly from CropScape, and planting patterns of continuous corn cropping is discovered from these CDL files. The raster layer of these planting patterns will be overlaid and analyzed in combination with other geospatial datasets, like digital elevation model data, average annual temperature, average annual precipitation data, and soil classification data to identify the important physical factors that impact on the patterns. Spatial relationships between continuous corn planting patterns and these geographic factors are also investigated and presented in this paper.
Keywords :
agricultural engineering; agriculture; crops; vegetation mapping; visual databases; CropScape; Iowa; United States; agricultural decision making; annual precipitation data; annual temperature data; continuous corn cropping patterns; cropland data layer; digital elevation model data; geographic factors; geospatial datasets; land cover data resources; soil classification data; Agriculture; Geospatial analysis; Portals; Soil; Spatial databases; Temperature distribution; Continuous Cropping; CropScape; Cropland Data Layer; Overlay Analysis; Planting Pattern;
Conference_Titel :
Agro-Geoinformatics (Agro-Geoinformatics), 2013 Second International Conference on
Conference_Location :
Fairfax, VA
DOI :
10.1109/Argo-Geoinformatics.2013.6621969