IRS AND MODIS IMAGE FUSION FOR ENHANCEMENT OF LAND USE AND LAND COVER CLASSIFICATION ACCURACY

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ALIMOHAMMADI SARAB A.; ZEAIEAN FIROUZABADI P.; MATKAN A.A.; SHERAFAT JAHROMI M.N.

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Journal: JOURNAL OF GEOGRAPHICAL SCIENCES Year:2008 | Volume:8 | Issue:11 Page(s): 171-190

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Title

IRS AND MODIS IMAGE FUSION FOR ENHANCEMENT OF LAND USE AND LAND COVER CLASSIFICATION ACCURACY

Author(s)

ALIMOHAMMADI SARAB A. | ZEAIEAN FIROUZABADI P. | MATKAN A.A. | SHERAFAT JAHROMI M.N. | Issue Writer Certificate

Keywords

IMAGE FUSIONQ3

CLASSIFICATIONQ3

ACCURACYQ2

LINEAR UNMIXING MODELQ2

IRSQ2

MODISQ2

Abstract

High spatial resolution data, such as IRS images are used to derive land cover information from the local to regional scales.However, acquisition of multi-temporal data of these images is costly and also limited. At the other hand, MODIS provides daily data in 36 bands with different spatial resolutions of 250, 500 and 1000 meters, which may not be so sufficient to capture the details of highly fragmented landscapes. For this reason, the synergetic use of IRS and MODIS imagery can be useful.The aim of this research is to use the linear mixing model for the fusion of IRS and MODIS images acquired over a suburban area of Tehran, Iran.First, IRS image was classified, and then the classified data were aggregated to match the resolution of the MODIS image. From the degraded data, data of weights, representing the proportions of cover types within the mixed pixels of the coarse spatial/fine temporal resolution image (MODIS), were produced.Computing the radiance values of the low resolution pixels in each image of MODIS, the spectral signatures of each land cover type were retrieved by inverting the linear mixing model. So, fused images were created. Then, IRS and fused image were classified to produce the maps of main land cover types of the study area.By assessing and comparing the classified images, the CLASSIFICATION results showed a good correlation with IRS estimates on a regional scale. The fused data definitely permit a better exploitation of the temporal resolution of MODIS data for object separation over the heterogeneous areas. Furthermore, such methodology can be improved by better registration of low and high resolution imagery.

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APA: Copy

ALIMOHAMMADI SARAB, A., ZEAIEAN FIROUZABADI, P., MATKAN, A.A., & SHERAFAT JAHROMI, M.N.. (2008). IRS AND MODIS IMAGE FUSION FOR ENHANCEMENT OF LAND USE AND LAND COVER CLASSIFICATION ACCURACY. JOURNAL OF GEOGRAPHICAL SCIENCES, 8(11), 171-190. SID. https://sid.ir/paper/102398/en

Vancouver: Copy

ALIMOHAMMADI SARAB A., ZEAIEAN FIROUZABADI P., MATKAN A.A., SHERAFAT JAHROMI M.N.. IRS AND MODIS IMAGE FUSION FOR ENHANCEMENT OF LAND USE AND LAND COVER CLASSIFICATION ACCURACY. JOURNAL OF GEOGRAPHICAL SCIENCES[Internet]. 2008;8(11):171-190. Available from: https://sid.ir/paper/102398/en

IEEE: Copy

A. ALIMOHAMMADI SARAB, P. ZEAIEAN FIROUZABADI, A.A. MATKAN, and M.N. SHERAFAT JAHROMI, “IRS AND MODIS IMAGE FUSION FOR ENHANCEMENT OF LAND USE AND LAND COVER CLASSIFICATION ACCURACY,” JOURNAL OF GEOGRAPHICAL SCIENCES, vol. 8, no. 11, pp. 171–190, 2008, [Online]. Available: https://sid.ir/paper/102398/en

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