Optical sensors, such as the Thematic Mapper (TM) (Landsat 5), Enhanced Thematic Mapper Plus (ETM+) (Landsat 7), High Resolution Visible (HRV) (SPOT 3), High Resolution Visible and Infrared (HRVIR) (SPOT 4), and High Resolution Geometric (HRG) (Spot 5) sensors; the new Chinese Gaofen (GF-1, -2, and -4) sensors; and synthetic aperture radar (SAR) sensors like RADARSAT-1/2, ENVI-SAT ASAR, ALOS-1/2, Terra, COSMO-SkyMed, and GF-3 SAR sensors, have been used to map and monitor coastal zones for more than 20 years [5-7].
GF-1. Five GF-1 optical imagery scenes were also collected for analysis.
First, the optical parameter was selected for both SAR and optical imagery based on the observed performance of C-band Sentinel-1 and L-band ALOS-2 SAR and GF-1 high-resolution optical imagery.
Prior to imagery fusion, the hazen-intensity-saturation (HIS) transforms were respectively applied for GF-1 and Sentinel-1 SAR imagery to decompose the imagery into H, I, S spaces.
Compared with pseudo RGB composite imagery from the GF-1 image (Figure 6(a)), the HIS fusion result (Figure 6(b)) contained the most texture details, especially for mountainous areas.
Compared with traditional HIS fusion results, although the Std of our proposed fusion results was much larger, the other features were superior to the GF-1 and HIS fusion results.
Based on this point, the SR model is focused on to extract the residential regions using GF-1 satellite images in this paper, and more details are described in next section.
In Section 2, the SR model for extracting the residential regions using GF-1 satellite imagery is presented, including band combinations and threshold selection.
In this section, the SR model is introduced to extract rural residential regions using GF-1 satellite imagery.
In order to find the optimal band combinations to produce the best result, several band combinations of GF-1 satellite images, including PAN_SR, MS_SR, RGB_SR, MS_SRs, and RGB_SRs, are considered in this paper.
(a) PAN_SR: in Step 1 of the program given in Section 2.1, the panchromatic band of GF-1 satellite image is used as the gray image, replacing the gray image in original SR model.
(b) MS_SR: in Step 1, the mean of four multispectral bands of GF-1 satellite image is used as the gray image to replace the original gray image.