DocumentCode
3447485
Title
Spatial analysis of farming viability and its contributing factors in California
Author
Bo Xu ; Ziying Jiang
Author_Institution
Dept. of Geogr., California State Univ., San Bernardino, CA, USA
fYear
2013
fDate
20-22 June 2013
Firstpage
1
Lastpage
7
Abstract
California is the leading agricultural state in the United States. Agricultural production is being threatened by many factors: loss of agricultural land, water shortage, among others. In this paper, we employed an ordinary least square regression (OLS) model and a geographically weighted regression (GWR) model to examine the relationship between farming viability in California and three contributing factors: energy intensification, product diversity, and government support by county. The OLS model revealed that energy intensification and product diversity were significantly related overall to farming viability. Locally, the GWR model demonstrated the significant spatial variation in the relationship between farming viability, product diversity and government support across counties. By taking into account the spatial variation, the GWR model presented a higher explanatory power than the OLS Model. These findings will provide farmers and policy makers a better understanding of the influence of local factors and the variation across space.
Keywords
agriculture; regression analysis; California; GWR model; OLS Model; United States; agricultural land loss; agricultural production; agricultural state; energy intensification; farming viability; geographically weighted regression model; government support; local factors; ordinary least square regression model; policy makers; product diversity; spatial analysis; spatial variation; water shortage; Adaptation models; Agriculture; Analytical models; Government; Indexes; Predictive models; Production; farming viability; geographically weighted regression model; government support; product diversity; technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoinformatics (GEOINFORMATICS), 2013 21st International Conference on
Conference_Location
Kaifeng
ISSN
2161-024X
Type
conf
DOI
10.1109/Geoinformatics.2013.6626184
Filename
6626184
Link To Document