Cross-Comparison Between China HJ1A-CCD and Landsat TM Data Guoqing Li, Xiaobing Li*, Hong Wang, Lihong Chen, Wanyu Wen State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Resources Science and Technology, Beijing Normal University, Beijing, China, 100875
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CROSS-COMPARISON BETWEEN CHINA HJ1A-CCD AND LANDSAT TM DATA(Guoqing Li).ppt
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Cross-Comparison Between China HJ1A-CCD and Landsat TM Data
Guoqing Li, Xiaobing Li*, Hong Wang, Lihong Chen, Wanyu Wen
State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Resources Science and Technology, Beijing Normal University,
Beijing, China, 100875
• 1. Introduction
• 2. Selection of Image Test Zone
• 3. Methodology
• 4. Results and Discussion
1. Introduction
• With the increasing service life of Landsat 5, the stability of over-life operation of sensor is facing important challenges. In addition, many currently used data outcomes directly or indirectly come from TM or ETM+ data. It is especially necessary to choose a remote sensing data source similar to Landsat TM data which can replace TM in a certain degree.
• The HJ-1 satellite was launched successfully in 2008, and carried two satellites: HJ-1A and HJ-1B. HJ-1A carries two CCD sensors with 30 m spatial resolution and a hyper-spectral sensor with 100 m spatial resolution. HJ-1B carries two identical CCD sensors and an infrared sensor with two kinds of spatial resolution (150 m at near, short-wave and middle-infrared band scope and 300 m at far-infrared band). The return period of the HJ-1 satellite is two days, with synergistic operation of HJ-1A and HJ-1B. The scan width exceeds 700 km with the two satellite CCD sensors working together. This enables HJ-1 CCD remote sensing images covering all lands of China to be captured every two to three days.
Satellite Altitude(km) Inclination
( °)Repetition cycle(d) Cycles/d
HJ1A 、 1
B
649.09 97.996 31 14+23/31
Landsat5 705 98.2 16 14.5
Tab1. Orbital characteristics of Landsat5 and HJ satellites
Tab2 Contrasting between HJ-CCD and Landsat TM imaging parameters
• 3.1 Radiation Precision Analysis• Radiation precision is the index which reflects the
information richness of the image. Many scholars have adopted grayscale mean-value and grayscale variance to evaluate radiation precision, and they believe that for different images of the area, the bigger is the distribution range of grayscale, the bigger the variance, and the richer the image information (Franke2006 , LI Shi-hua 2009).
3. Methodology
3.1 Radiation Precision Analysis
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3.2 Calculation of Texture and Definition
• Information entropy is a measurement of the information amount that the image possesses. The higher complexity the texture has, the bigger the image information amount is, and the bigger its information entropy is.
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