Abstract
Monitoring agricultural sustainability requires careful summarising of indicators collected over time into indices representing facets of sustainability. When the number of variables exceeds the number of observations, interpretation of components from ordinary principal component analysis is usually difficult because of minimal or absence of sparsity among the loadings. This is also true for time series indicators that exhibit non-stationarity. A framework for the assessment of agricultural sustainability in a regional context is proposed. Sparse principal component analysis is used in constructing indices of agricultural sustainability that are then used to characterise the state of agricultural development and the dynamics of agricultural growth in Southeast Asia.
Original language | English |
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Pages (from-to) | 95-102 |
Number of pages | 8 |
Journal | International Journal of Sustainable Development & World Ecology |
Volume | 15 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Apr 2008 |
Externally published | Yes |
Keywords
- Monitoring
- Principal component analysis
- Southeast asia
- Sparse principal component analysis
- Sustainable agriculture