TY - GEN
T1 - Use of satellite imagery to radiometrically calibrate digital airborne multispectral imagery
AU - Maas, Stephan
AU - Torrion, Jessica
AU - Rajapakse, Sepalika
AU - Guo, Wenxuan
PY - 2006
Y1 - 2006
N2 - Detailed spatial and temporal assessment of agricultural fields is crucial in site specific management of agricultural crops. Satellite imagery is limited in its application to many site-specific applications due to its typically coarse spatial resolution. Airborne imaging systems are capable of acquiring remote sensing data with spatial resolutions that satisfy the requirements for site specific crop management. Unlike satellite imagery, the radiometric characteristics of airborne imagery are usually not known. Thus, it is difficult to perform temporal analysis using airborne imagery since it is typically not known if the radiometric characteristics of the imagery have changed between acquisitions. This document describes a procedure based on histogram matching to calibrate aerial imagery to a standard radiometric level established by satellite imagery acquired near the time of the airborne image acquisition. Normalized Landsat TM and ETM+ imagery were used as reference images. The technique was tested for two dates during the cotton growing season. Two techniques of histogram matching were compared: matching histograms by automatic histogram matching in ENVI, and matching histograms based on the ratio of the pixel distribution means. Automatic histogram matching produced better results, since it not only translated the histogram distributions but also balanced the gray values with respect to the reference image. Histogram matching of aerial photos is a promising technique for calibrating multi-temporal remote sensing.
AB - Detailed spatial and temporal assessment of agricultural fields is crucial in site specific management of agricultural crops. Satellite imagery is limited in its application to many site-specific applications due to its typically coarse spatial resolution. Airborne imaging systems are capable of acquiring remote sensing data with spatial resolutions that satisfy the requirements for site specific crop management. Unlike satellite imagery, the radiometric characteristics of airborne imagery are usually not known. Thus, it is difficult to perform temporal analysis using airborne imagery since it is typically not known if the radiometric characteristics of the imagery have changed between acquisitions. This document describes a procedure based on histogram matching to calibrate aerial imagery to a standard radiometric level established by satellite imagery acquired near the time of the airborne image acquisition. Normalized Landsat TM and ETM+ imagery were used as reference images. The technique was tested for two dates during the cotton growing season. Two techniques of histogram matching were compared: matching histograms by automatic histogram matching in ENVI, and matching histograms based on the ratio of the pixel distribution means. Automatic histogram matching produced better results, since it not only translated the histogram distributions but also balanced the gray values with respect to the reference image. Histogram matching of aerial photos is a promising technique for calibrating multi-temporal remote sensing.
UR - http://www.scopus.com/inward/record.url?scp=84867812004&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84867812004
SN - 9781604236057
T3 - American Society for Photogrammetry and Remote Sensing - 20th Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment 2005
SP - 388
EP - 396
BT - American Society for Photogrammetry and Remote Sensing - 20th Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment 2005
T2 - 20th Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment 2005
Y2 - 4 October 2005 through 5 October 2005
ER -