Irrigation Science

, Volume 31, Issue 4, pp 851–869 | Cite as

A review of potential image fusion methods for remote sensing-based irrigation management: part II

Review

Abstract

Satellite-based sensors provide data at either greater spectral and coarser spatial resolutions or lower spectral and finer spatial resolutions due to complementary spectral and spatial characteristics of optical sensor systems. In order to overcome this limitation, image fusion has been suggested to obtain higher spatial and spectral resolution images at the same time. Image fusion has been a valuable technique in digital image analysis and comparison because of the availability of multi-spatial and multispectral images from satellite and airborne sensors. It has been applied to merge coarser spatial resolution of multispectral images with a finer spatial resolution panchromatic image to enhance visual apprehension and to provide images that are more informative. Part I companion paper presented and discussed the image downscaling methods. In this paper (part II), the main objective is to review existing image fusion methods for their capability to downscale coarser spatial resolution images for irrigation management applications. A literature review indicated that image fusion methods have not been actively used in obtaining high-resolution land surface temperature (LST) and evapotranspiration (ET) images for irrigation management. However, there is a great potential for applying image fusion methods to retrieve finer LST and ET images from coarser thermal images by fusing them with finer non-thermal color or panchromatic images for irrigation scheduling and management purposes.

Keywords

Image Fusion Land Surface Temperature Laplacian Pyramid Image Fusion Method High Spatial Resolution Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations

ARSIS

Amélioration de la résolution spatiale par injection de structures meaning improvement of the spatial resolution by injection of structures

ASTER

Advanced spaceborne thermal emission and reflection radiometer

BDF

Bayesian data fusion

CS

Component substitution

DFB

Directional filter bank

DI

Disturbance index

DN

Digital number

DSCK

Downscaling co-kriging

DWT

Discrete wavelet transform

ENVI

ENvironment for Visualizing Images

ERGAS

Erreur relative globale adimensionelle de synthése meaning relative dimensionless global error in synthesis

ET

Evapotranspiration

ETM+

Enhanced thematic mapper plus

GLP

Generalized Laplacian pyramid

GP

Gaussian pyramid

GS

Gram–Schmidt

H

Hue

HPF

High-pass filter

HWT

Haar wavelet transform

I

Intensity

IHS

Intensity, hue, and saturation

LHS

Lightness, hue, and saturation

LP

Laplacian pyramid

LPF

Low pass filter

LST

Land surface temperature

MODIS

Moderate resolution imaging spectroradiometer

MRA

Multi-resolution analysis

MS

Multispectral

NDVI

Normalized difference vegetation index

PAN

Panchromatic

PBIM

Pixel block intensity modulation

PCA

Principal component analysis

PFS

Pyramidal in Fourier space

PL

Pyramidal Laplacian

PSF

Point spread function

RASE

Relative average spectral error

RGB

Red, green, and blue

RMSE

Root mean square error

ROLPP

Ratio of low pass pyramid

S

Saturation

SAM

Spectral angle mapper

SFIM

Smoothing filter-based intensity modulation

SNR

Signal-to-noise ratio

SPOT

Systeme pour l’observation de la terre

STAARCH

Spatial temporal adaptive algorithm for mapping reflectance change

STARFM

Spatial and temporal adaptive reflectance fusion model

TM

Thematic mapper

WT

Wavelet transform

Notes

Acknowledgments

Funding for this study was provided by USDA-ARS and NASA Terrestrial Hydrology Program (Proposal No. 08-THP07-0053). Authors are grateful to reviewers who provided valuable comments.

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Wonsook Ha
    • 1
  • Prasanna H. Gowda
    • 1
  • Terry A. Howell
    • 1
  1. 1.Conservation and Production Research LaboratoryUSDA-ARSBushlandUSA

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