Time series interpolation

A consistent data acquisition interval among multi-temporal images is necessary to accurate landscape change detection and temporal-series signatures. Orbital images are difficult to maintain a temporal precision due to the different interferences that generate missing data. The correct handling of missing data is a difficult problem in data analysis and often depends on your specific situation. This missing information can be replaced using an interpolation method. In this paper is proposed a new algorithm that interpolates multitemporal images. This new computation method uses the cubic-spline interpolation technique to trace the reflectance and NDVI behaviors along time. The performance of the cubic-spline interpolation technique in the determination of NDVI temporal series is verified in terms of accuracy.

[1]  S. Sader,et al.  Remote sensing of tropical forests : an overview of research and applications using non-photographic sensors , 1990 .

[2]  R. Nelson.  Detecting forest canopy change due to insect activity using Landsat MSS , 1983 .

[3]  Marvin E. Bauer,et al.  Processing of multitemporal Landsat TM imagery to optimize extraction of forest cover change features , 1994, IEEE Trans. Geosci. Remote. Sens..

[4]  Yong Du,et al.  Radiometric normalization, compositing, and quality control for satellite high resolution image mosaics over large areas , 2001, IEEE Trans. Geosci. Remote. Sens..

[5]  Mark W. Brennan,et al.  Multitemporal texture analysis of features computed from remotely sensed imagery , 1993, Other Conferences.

[6]  Ashbindu Singh,et al.  Review Article Digital change detection techniques using remotely-sensed data , 1989 .

[7]  C. Munyati,et al.  Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset , 2000 .

[8]  Franz Mora,et al.  Remote Sensing Using AVHRR , 2006 .

[9]  Steven W. Running,et al.  Community type differentiation using NOAA/AVHRR data within a sagebrush-steppe ecosystem , 1993 .

[10]  Jesslyn F. Brown,et al.  Measuring phenological variability from satellite imagery , 1994 .

[11]  Compton J. Tucker,et al.  Satellite remote sensing of total herbaceous biomass production in the Senegalese Sahel - 1980-1984 , 1985 .

[12]  Frank Veroustraete,et al.  Seasonal variations in leaf area index, leaf chlorophyll, and water content; scaling-up to estimate fAPAR and carbon balance in a multilayer, multispecies temperate forest. , 1999, Tree physiology.

[13]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[14]  Sharon E. Nicholson,et al.  On the use of NDVI for estimating rainfall fields in the Kalahari of Botswana , 1997 .

[15]  S. Goetz,et al.  Radiometric rectification - Toward a common radiometric response among multidate, multisensor images , 1991 .

[16]  C. Woodcock,et al.  An assessment of several linear change detection techniques for mapping forest mortality using multitemporal landsat TM data , 1996 .

[17]  C. Field,et al.  Remote Sensing of Terrestrial Photosynthesis1 , 1995 .

[18]  P. E. Anuta,et al.  Change detection in coastal zone environments , 1977 .

[19]  Steven I. Gordon,et al.  Utilizing LANDSAT imagery to monitor land-use change - A case study in Ohio , 1980 .

[21]  K. K. Mayo,et al.  Monitoring land-cover change by principal component analysis of multitemporal Landsat data. , 1980 .

[22]  K. Rutchey,et al.  Inland Wetland Change Detection in the Everglades Water Conservation Area 2A Using a Time Series of Normalized Remotely Sensed Data , 1995 .

[23]  Christopher O. Justice,et al.  Monitoring the grasslands of the Sahel using NOAA AVHRR data: Niger 1983 , 1986 .

[24]  S. Nicholson,et al.  A comparison of the vegetation response to rainfall in the Sahel and East Africa, using normalized difference vegetation index from NOAA AVHRR , 1990 .

[25]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[26]  S. L Furby,et al.  Calibrating images from different dates to ‘like-value’ digital counts , 2001 .

[27]  E. LeDrew,et al.  Application of principal components analysis to change detection , 1987 .

[28]  R. Lunetta,et al.  A change detection experiment using vegetation indices. , 1998 .

[29]  C. Elvidge,et al.  NALC Land Cover Change Detection Pilot Study , 1998 .

[30]  G. Woodwell,et al.  Map of the vegetation of South America based on satellite imagery , 1994 .

[31]  J. Hill,et al.  Radiometric correction of multitemporal Thematic Mapper data for use in agricultural land-cover classification and vegetation monitoring , 1991 .

[32]  Peng Gong,et al.  Registration-noise reduction in difference images for change detection , 1992 .

[33]  S. Ingebritsen,et al.  Principal components analysis of multitemporal image pairs , 1985 .

[34]  P. Manavalan,et al.  Irrigated crops monitoring through seasons using digital change detection analysis of IRS-LISS 2 data , 1995 .