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Memorias de investigación
Research Publications in journals:
Derivation of phenological metrics by function fitting to time-series of spectral shape indexes AS1 and AS2: Mapping cotton phenological stages using MODIS time series
Year:2012
Research Areas
  • Physics chemical and mathematical,
  • Natural sciences and health sciences,
  • Engineering,
  • Humanities
Information
Abstract
The availability of high frequency remote sensing time series allows the assessment of crop evolution at different scales. The Spectral Shape Indexes (SSI) represent the shape of a multispectral (MODIS in this case) reflectance profile in a set of three consecutive bands. The aims of this research were: (1) to assess AS1 and AS2 behavior over a cotton crop growing period, (2) to test whether function fitting procedures can be used to model MODIS AS1 and AS2 and NDVI time series and (3) to derive objective AS1 and AS2 phenological metrics that can be used to monitor cotton phenological stages. Phenological stages of a cotton crop in the San Joaquin Valley (CA) were identified by linking local climatic data and producer recorded management practices. An asymmetric Gaussian function was fitted to the time series of each index using TIMESAT software. Then, specific dates in the fitted functions have been related to phenological stages and dates of agricultural practices. Results show that AS1 and AS2 exhibit a consistent pattern clearly different from the temporal evolution of NDVI. The AS2 index shows high values during periods when vegetation is dominant, either photosynthetically active or dry, and lowvalueswhen soil dominates the pixel. The AS1 index time series showed two minima during the cotton growth period.Minima and inflection points derived from the fitted functions are coincident in time with significant crop management dates during the growing period. These results show that function fitting procedures applied to AS1 and AS2 can be used to derive phenological metrics, illustrating the potential for using Spectral Shape Indexes for crop monitoring.
International
Si
JCR
Si
Title
Remote Sensing of Environment
ISBN
0034-4257
Impact factor JCR
5,103
Impact info
Volume
http://dx.doi.org/10.1016/j.rse.2012.08.002
Journal number
126 (2012)
From page
148
To page
159
Month
SIN MES
Ranking
nº 9 en ENVIRONMENTAL SCIENCES nº 1 en IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY nº 1 en REMOTE SENSING
Participants
  • Autor: Alicia Palacios Orueta (UPM)
  • Autor: Jesus Javier Litago Lavilla (UPM)
Research Group, Departaments and Institutes related
  • Creador: Departamento: Estadística y Métodos de Gestión en Agricultura
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