*3.2. Image Fusion*

Figure 5 shows the Gram–Schmidt (GS) and principal component analysis (PCA) image fusion results by color compositing of the fused bands compared with the original Sentinel-1 data. In general, there were few differences between Sentinel-1 VH and VV results using GS or PCA. In contrast, the effects of image fusion methods seemed to be greater on the color composite images. The GS enhanced the colors of the residential areas (yellow) and the mangrove (red) (C and D) more clearly than the PCA (E and F). However, these differences were in the color composites and might not affect the later mangrove classification results. The spatial resolution of the fused images (all polarization, GS, and PCA) was improved from the 10 m resolution of Sentinal-1, and 6 m resolution of the multispectral SPOT-7 to 1.5 m, as can be seen in the zoomed-in pink polygons (C and E clearly distinguish between aquaculture and mangrove, D and F distinguish between river and mangrove) compared to the same areas using original Sentinel-1 data (A and B). Another advantage of the band sharpening is the capacity to minimize cloud effects in optical images. However, in this study, we collected a cloud-free SPOT-7 scene.

**Figure 5.** Demonstrations of SPOT-7 and Sentinel-1 (S1) image fusion processes where (**A**) is the original Sentinel-1 VH layer and (**B**) is Sentinel-1 VV layer (sigma0 in decibel); and (**C**–**F**) depict the results of the fused images using VH–GS, VV–GS, VH–PCA, and VV–PCA, respectively.

#### *3.3. Mangrove Species Maps*

Three main mangrove species were classified using the fused images and SVM classifier: the *Sonneratia caseolaris* locally called "Ban", the *Aegiceras corniculatum*, local name "Su", and *Kandelia obovata*, local name "Vet" (Figure 6). Su was present in the forest core, close to the river channel in the middle of all maps, and accounted for around 50 percent of the total mangrove area. Nonetheless, there was some mixture of Su with Ban in the core forest in the VV\_GS and VV\_PCA maps. Vet (26% of total mangroves) was distributed more in the southwest of the study site and it was categorized similarly in all maps. The main differences between using VH and VV S1 polarizations was the young Ban mangrove in the east of the map (C and D) was incorrectly classified as Vet in the VH\_GS and VH\_PCA maps according to the ground-truth investigation. In general, the use of different image fusion methods affected the mangrove species classifications less than the use of different SAR polarizations. A comparison of map A with C, and B with D, and the VV polarization fused with the SPOT-7 bands indicated a good performance for mangrove type categorization. The VH might nevertheless be more suitable for mangrove forests where the mixture of species is low. The classification of the original SPOT-7 (E) showed large areas of Vet (4.06%) were mis-classified to Su (75.83%). While percentage of Ban areas (20.11%) seemed to be similar to those of other images, the distribution was incorrect for the outer forest edge. The use of the Sentinel-1 VH layer generated mangrove species (F), and their distribution was considered accurate and agreed well with fused-image based classifications. However, the resulting resolution (10 m) was much lower than the fused images (1.5 m) and that was why the small areas of Vet and Ban were combined into the Su mangrove type.

**Figure 6.** Maps of classified mangrove species; GS and PCA indicate Gram–Schmidt and principal component analysis image fusion methods; V and H are vertical and horizontal, respectively and coupled letters of VH and VV indicate SAR cross-polarizations. VH\_GS, VH\_PCA, VV\_GS, and VV\_PCA are combinations of fused images of SPOT-7 acquired on 17 May 2019 and Sentinel-1 polarization data (VH or VV) and the image fusion methods (GS or PCA).

#### *3.4. Mangrove Extent Changes*

Extracting mangrove extents over a long period of time (1975–2019) showed the expansion, approximately 80 m/year, of the mangrove forest to about 3.5 km seaward in Thuy Truong commune and surroundings (Figure 7). The mangrove expansion of the results of the ISODATA classifications was slower between 1975 and 1993, and slightly decreased in 1993 compared to 1988. Nonetheless, the forest has been rapidly and continuously increasing in extent for 31 years from 1998 to 2019. Based on the in situ investigation data, the mangrove forest was mostly planted when the accumulated sediment from the river was high and the base well-founded. There is a small area of mangrove fragmentation due to aquaculture ponds and the mangrove there was degraded until 2019, by which time it had mostly disappeared (see the red rectangle in years 1993 and 2019). We also tested classifying the mangrove extents using the K-means classifier. However, no significant di fferences between the two methods were found. Hence, we only present the ISODATA results.

**Figure 7.** Changes in mangrove extent from 1975 to 2019 classified from a time series of Landsat images missions 2 to 8 (described in the Table 2) using the iterative self-organizing data analysis technique (ISODATA) classification, an unsupervised image classification approach (detailed in Section 2.3.1). The red rectangle denotes the same area of intensive aquaculture in 1993 and 2019.

Changes in mangrove extent (including all mangrove species) in ha were quantified and graphed (Figure 8). In the first 11 years, the forest expanded approximately 150 ha (1988), but had decreased by slightly over 100 ha five years later (1993). Forest extent recovered slightly by 1998, and then increased by more than 220 ha in the five years until 2003. Afterward, there was a gradually increase over the subsequent 15 years (2003–2018). A remarkable increase was found in the last year of the assessment time. It is noted that all estimates were not validated except for 2019, for which ground-truth data were available. However, the mangrove in this region grows in sediment deposits and does not mix with other vegetation, therefore unsupervised classifications are considered su fficiently accurate.

**Figure 8.** Total mangrove area (orange line) and changes in extent (blue line) (ha) from 1975–2019 in Thuy Truong commune.
