Mapping China’s coastal aquaculture ponds expansion with sentinel-2 images during 2017–2021

Figures & data

Figure 1. Location of the study area and the average number of good quality-observation Sentinel-2 images from 2017 to 2021.

Table 1. Details of Sentinel-2A/2B satellites.

Satellite (Sensor)	Sentinel-2A/2B (MSI)
Revisit time (days)	5
Orbit Altitude (km)	786
Launch Date	23 June 2015/7 March 2017
Wavelength (nm)	443–2202
Swath (km)	290
Number of bands	13
Spatial Resolution (m)	10

Figure 2. The distribution of sample points and sample polygons in this study.

Table 2. The number of sample points in this study from 2017 to 2021.

Date	Aquaculture ponds	Dike	River and Lake	Salt pan	Other types	Total
2017	1980	500	800	300	400	3980
2018	2100	500	800	300	350	4050
2019	2090	500	800	300	380	4070
2020	2120	500	800	300	460	4180
2021	2000	500	800	300	500	4100

Figure 3. Workflow of the study.

Figure 4. Elevation and slope histograms of aquaculture pond distribution based on samples.

Figure 5. Differences in AWEI_nsh and AWEI_sh indices of different feature types.

Table 3. Spectral indices used for the determination of water pixels.

Name	Abbreviation	Equation
Nominalized Difference Vegetation Index	NDVI	NDVI = (NIR – Red) / (NIR + Red)	(1)
Enhanced Vegetation Index	EVI	EVI  = 2.5 × (NIR – Red) / (NIR + 6 × Red−7.5 × Blue + 1)	(2)
Nominalized Difference Water Index	NDWI	NDWI = (NIR – Red)/ (NIR + Red)	(3)
Automated Water Extraction Index	AWEI	AWEInsh = 4 × (Green – SWIR1) – (0.25 × NIR + 2.75 × SWIR2)	(4)
		AWEIsh = Blue + 2.5  × Green – 1.5 × (NIR + SWIR1) – 0.25 × SWIR2	(5)

Figure 6. Trend of the overall accuracy of permanent waterbodies with WF threshold.

Figure 7. Optimal segmentation scale calculation result in Zhejiang Province.

Figure 8. Segmentation results in three typical area. (A) Liaodong Bay, Liaoning Province; (B) Bohai Bay, Shandong Province; (C) Sanmen Bay, Zhejiang Province; (D) Jiao Bay, Guangdong Province.

Table 4. Optimal segmentation scale for each province.

Province	Segmentation Scale	Province	Segmentation Scale
Liaoning	40	Zhejiang	31
Hebei	35	Fujian	32
Tianjin	35	Guangdong	30
Shandong	33	Guangxi	30
Jiangsu	33	Haihan	30
Shanghai	30

Table 5. The specific description and meaning of each classification feature.

Feature/Metric	Description	Formula
LSI	Describes the shape characteristics of an object	${\displaystyle \frac{0.25\ast Perimeter}{\sqrt{\mathrm{Area}}}}$	(7)
Compactness	Describes the compactness of an object	$\sqrt{{\displaystyle \frac{Area}{Bi}}},\mathrm{Bi}={\displaystyle \frac{Perimete{r}^2}{4\pi }}$	(8)
Rectangular fit	Describes the proximity of an object to its external rectangle	${\displaystyle \frac{Area}{Are{a}_R}}$	(9)
Aspect Ratio	Describes the aspect ratio of an object	${\displaystyle \frac{Width}{Height}}$	(10)

Figure 9. Classification thresholds trained from polygon sample data. (OW: other waterbody types; AP: aquaculture ponds.) (a) Statistical results of the area; (b) Statistical results of LSI; (c) Statistical results of the compactness; (d) Statistical results of the rectangular fit.

Figure 10. The spatial distribution of independent reservoirs and aquaculture ponds. (A) and (B): Independent reservoirs; (C): Aquaculture ponds.

Table 6. Confusion matrix and F1 scores for the aquaculture pond map in China during 2017-2021.

Year	Class	Pond	Non-Pond	Recall	Precision	Ove. acc	F1 Score
2017	Pond	1351	161	0.91	0.89	0.90	0.90
	Non-Pond	129	1339
2018	Pond	1468	142	0.92	0.91	0.91	0.92
	Non-Pond	132	1308
2019	Pond	1432	153	0.90	0.90	0.89	0.90
	Non-Pond	158	1327
2020	Pond	1491	122	0.92	0.91	0.92	0.92
	Non-Pond	129	1438
2021	Pond	1369	155	0.91	0.90	0.91	0.90
	Non-Pond	131	1445

Figure 11. Comparison of aquaculture ponds extracted with sample polygons obtained by automated extraction based on Google Earth. (a) Liaodong Bay, Liaoning Province; (b) Bohai Bay, Shandong Province; (c) Sanmen Bay, Zhejiang Province; (d) Jiao Bay, Guangdong Province.

Table 7. Comparison of the aquaculture ponds area in typical areas.

	Liaodong Bay	Bohai Bay	Sanmen Bay	Jiao Bay
Automatic extraction (km^2)	195.03	163.48	154.64	115.78
Visual interpretation (km^2)	201.34	176.54	160.30	119.72
Overlapping area (km^2)	179.21	154.26	145.73	10.46
Proportion of overlapping area	0.89	0.87	0.90	0.92

Figure 12. The spatial distribution of China's coastal aquaculture ponds during 2017-2021. (A) Liaodong Bay, Liaoning Province; (B) Laizhou Bay, Shandong Province; (C) Yancheng City, Jiangsu Province; (D) Sanmen Bay, Zhejiang Province; (E) Changsha Bay, Guangdong Province; (F) Beihai Port, Guangxi Province.

Figure 13. Kernel density analysis map of aquaculture ponds in 2021.

Figure 14. Aquaculture pond area changes in China's coastal zone from 2017 to 2021. (a) Aquaculture pond ACR in coastal provinces during 2017–2021. (b) Changes in the area of aquaculture ponds by province during 2017–2021. (c) National aquaculture pond total area changes during 2017–2021.

Figure 15. Spatial distribution of typical coastal aquaculture ponds in 2017 and 2021. (a) Liaodong Bay, Liaoning Province; (b) Bohai Bay, Shandong Province; (c) Sanmen Bay, Zhejiang Province; (d) Jiao Bay, Guangdong Province.

Figure 16. Percentage of aquaculture ponds converted into land cover types in China’s coastal provinces during 2017–2021.

Figure 17. Comparison of aquaculture ponds extracted results with other 10-m resolution datasets.