Abstract
This chapter surveys 12 different spatio-temporal statistical methods to determine the start and end of the growing season using a time series of satellite images. In the first section of the chapter, we divided the methods into four categories: thresholds, derivatives, smoothing functions, and fitted models. The general use, advantages, and potential limitations of each method are discussed. In the second section of the chapter, a case study is presented to highlight one method from each category. The four study areas range from the Northwest Territories in Canada to the winter wheat areas in south-central Kansas. We concluded the case study with a discussion of the differences in results for the four methods. The chapter is finished with a synopsis discussing the use of nomenclature, the problems with a lack of statistical error structure from most methods, and the perennial issue of oversmoothing.
Original language | English |
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Title of host publication | Phenological Research |
Subtitle of host publication | Methods for Environmental and Climate Change Analysis |
Editors | Irene L. Hudson, Marie R. Keatley |
Publisher | Springer |
Chapter | 9 |
Pages | 177-208 |
Number of pages | 32 |
ISBN (Electronic) | 9789048133352 |
ISBN (Print) | 9789048133345 |
DOIs | |
Publication status | Published - 2010 |
Externally published | Yes |
Keywords
- Derivatives
- Model fit
- Smoothing functions
- Thermal time
- Thresholds