Accuracy evaluation of flood monitoring based on multiscale remote sensing for different landscapes

Figures & data

Figure 1. Location and satellite data of the study area: (A) the intersection between the Heilongjiang River and Songhua River; (B) the Huaihe River downstream canal zone; (C) the Huaihe River Huainan region; (D) the East Taihu Lake region; (E) the Yangtze River Hukou below the mainstream region; (F) the North Poyang Lake region; (G) the South Poyang Lake region; and (H) the Huizhou Dongjiang region.

Table 1. Selected eight study areas and GF-1 satellite images.

Study areas	Landforms	Centre coordinates	Province	Regional flood year	Product serial number	Acquisition time
A: The intersection between Heilongjiang River and Songhua River	Low-altitude alluvial fan plain	132.4000E47.6895N	Heilongjiang	2013	953736	1 August 2015
B: Huaihe River downstream canal zone	Low-altitude alluvial lake plain	119.2880 E33.0237 N	Jiangsu	2007	2497326	20 July 2017
C: Huaihe River Huainan region	Low altitude alluvial plain	116.6770 E32.6732 N	Anhui	2007	2304107	13 April 2017
D: East Taihu Lake region	Low-altitude alluvial lake plain	120.3140 E31.2759 N	Jiangsu	2016	2526241	5 August 2017
E: Yangtze River Hukou below the mainstream region	Low-altitude alluvial fan plain	117.3420 E30.7299 N	Anhui	2017	2386983	28 May 2017
F: North Poyang Lake region	Low-altitude alluvial lake plain	116.5590 E29.1420 N	Jiangxi	2017	2386757	28 May 2017
G: South Poyang Lake region	Low altitude alluvial platform	116.4190 E28.5847 N	Jiangxi	2017	2386755	28 May 2017
H: Huizhou Dongjiang region	Low altitude hills& Low altitude alluvial plain	114.3510 E23.1984 N	Guangdong	2017	2217762	3 March 2017

Source: China's 1:1 million landform type data set is provided by Data Centre for Resources and Environmental Sciences, Chinese Academy of Sciences (RESDC) (http://www.resdc.cn). (Data Centre for Resources and Environmental Sciences).

Figure 2. Flow chart of scaling method based on mechanism.

Figure 3. Different spatial resolution series images of study area C (C-1: 8 m, C-2: 24 m, C-3: 40 m, C-4: 56 m, C-5: 120 m, C-6: 152 m, C-7: 200 m, and C-8: 248 m).

Figure 4. The results of water extraction from different spatial resolution images of C study area (C-1: 8 m, C-2: 24 m, C-3: 40 m, C-4: 56 m, C-5: 120 m, C-6: 152 m, C-7: 200 m, and C-8: 248 m).

Table 2. Descriptions and broad definitions of selected 18 landscape pattern indices.

ID	Landscape pattern indices	Index description/definition
1	Total Water Area (TA)	TA > 0, TA equals the total area (m^2) of the corresponding water patch type
2	Total Edge (TE)	TE ≥ 0, without limit. The total length of all edges; may or may not including landscape boundary
3	Perimeter Area Ratio (PARA)	PARA >0. PARA is the ratio of total patch circumference to total patch area. It reveals the degree of patch type segmentation by the boundary and is a direct reflection of landscape fragmentation. In general, the more complex plaque shape, the higher the value of PARA
4	Number of Patches (NP)	NP ≥ 1, without limit. NP equals the number of patches of the corresponding patch type (class)
5	Largest Patch Index (LPI)	0 < LPI ≤ 100, LPI equals the area (m^2) of the largest patch of the corresponding patch type divided by total landscape area (m^2), multiplied by 100 (to convert to a percentage); in other words, LPI equals the percentage of the landscape comprised by the largest patch
6	Edge Density (ED)	ED ≥ 0, without limit. ED equals the sum of the lengths (m) of all edge segments in the landscape, divided by the total landscape area (m2), multiplied by 10,000 (to convert to hectares). Regardless of whether a landscape border is present or not, ED includes a user-specified proportion of internal background edge
7	Landscape Shape Index (LSI)	LSI ≥ 1, without limit. LSI equals the total length of edge (or perimeter) involving the corresponding class, given in number of cell surfaces, divided by the minimum length of class edge (or perimeter) possible for a maximally aggregated class, also given in number of cell surfaces, which is achieved when the class is maximally clumped into a single, compact patch
8	Patch Area Mean (AREA_MN)	AREA_MN (Mean) equals the sum, across all patches of the corresponding patch type, of the corresponding patch metric values, divided by the number of patches of the same type. MN is given in the same units as the corresponding patch metric
9	Perimeter Area Ratio Mean (PARA_MN)	PARA_MN (Mean) equals the sum, across all patches in the landscape, of the corresponding patch metric values, divided by the total number of patches. MN is given in the same units as the corresponding patch metric
10	Total Core Area (TCA)	TCA ≥ 0, without limit. TCA equals the sum of the core areas of each patch (m^2), divided by 10,000 (to convert to hectares)
11	Number of Disjunct Core Area (NDCA)	NDCA ≥ 0, without limit. NDCA equals the sum of the number of disjunct core areas contained within each patch of the corresponding patch type; that is, the number of disjunct core areas contained within the landscape
12	Clumpiness Index (CLUMPY)	−1 ≤ CLUMPY ≤1. It represents the degree of aggregation of different patch types in the landscape. It equals 0 when the patches are distributed randomly, and approaches 1 when the patch type is maximally aggregated
13	Proportion of Like Adjacency (PLADJ)	0 ≤ PLADJ ≤ 100. The percentage of cell adjacencies involving the corresponding patch type that are like adjacencies. When the patch type is the largest dispersion, and there is no similar adjacency, the PLADJ value is the smallest. When the landscape is composed of only one patch, and all adjacency is the same type, the PLADJ value is the largest
14	Patch Cohesion Index (COHESION)	0 ≤ COHESION < 100. It is the index of measuring the spatial connectivity of landscape types. The larger the COHESION, the higher the spatial connectivity of the landscape
15	Landscape Division Index (DIVISION)	0 ≤ DIVISION < 1. DIVISION equals one minus the sum of patch area (m^2) divided by total landscape area (m^2), quantity squared, summed across all patches of the corresponding patch type. Note, total landscape area (A) includes any internal background present
16	Effective Mesh Size (MESH)	the ratio of cell size to a landscape area ≤ MESH ≤ total landscape area (A). MESH equals the sum of patch area squared, summed across all patches of the corresponding patch type, divided by the total landscape area (m^2), divided by 10,000 (to convert to hectares)
17	Splitting Index (SPLIT)	1 ≤ SPLIT ≤ number of cells in the landscape squared. SPLIT equals the total landscape area (m^2) squared divided by the sum of patch area (m^2) squared, summed across all patches in the landscape
18	Normalized Landscape Shape Index (NLSI)	0 ≤ NLSI < 1.NLSI = 0 when the landscape consists of a single square or maximally compact almost square, it increases when the patch types become increasingly disaggregated and are 1 when the patch type is maximally disaggregated

Source: Gustafson (1998), Haines-Young and Chopping (1996), Kim and Pauleit (2007), McGarigal (2014), McGarigal et al. (2012), McGarigal and Marks (1995), O'Neil and Krummel (1988), O'neill et al. (1996), Turner et al. (1989).

Table 3. Influence of different spatial resolution on the regional accuracy of water extraction.

Resolution (M)	8	24	40	56	120	152	200	248
Water area $A_0$ (km^2)	94.43	88.72	85.14	82.57	74.78	70.93	68.16	63.41
Regional accuracy $P_{\left(s,i\right)}$ (%)	–	93.96	90.16	87.44	79.19	75.11	72.18	67.15

Figure 5. The change of average regional accuracy with different spatial resolutions and spatial extents.

Figure 6. Average regional accuracy changes with different proportion of water body. (a) The average regional accuracy of 1 km². (b) the average regional accuracy of 4 km².

Table 4. Correlation between RE and landscape pattern indices with different resolution.

Landscape pattern indices	Correlation between RE and landscape index of 8 m	Correlation between RE and landscape index of 56 m
Perimeter area ratio (PARA)	0.89	0.91
Normalized landscape shape index (NLSI)	0.81	0.86
Proportion of like adjacency (PLADJ)	−0.89	−0.91
Patch cohesion index (COHESION)	−0.86	−0.91
Clumpiness (CLUMPY)	−0.74	−0.80

Figure 7. The relationship among water extraction error and proportion of water body and PARA.

Figure 8. The relationship among water extraction error and proportion of water body and PLADJ.

Figure 9. The relationship among water extraction error and proportion of water body and COHESION.

Table 5. Results of water body area with different patch shape complexity.

Patch shape complexity	Number of grids	$A_0$	$A_{56}$	Relative error (%)
Low	298	1105.82	1073.6	−2.91
Medium	197	227.36	183.95	−19.09
High	59	35.57	20.58	−42.14

Table 6. A multivariate regression equation parameters.

	Low patch complexity				Medium patch complexity				High patch complexity
	B	Std. err	t	Sig.	B	Std. err	t	Sig.	B	Std. err	t	Sig.
Constant	−452.27	71.66	−6.31	0.00	68.02	23.42	2.90	0.00	213.72	21.06	10.15	0.00
water area with 56M	0.98	0.003	302.48	0.00	0.88	0.03	31.93	0.000	0.72	0.05	15.34	0.00
Number of plaques	1.82	0.25	7.29	0.00	3.24	0.34	9.62	0.000	6.77	0.78	8.71	0.00
PARA	5.87	1.18	4.98	0.00	–	–	–	–	–	–	–	–
PLADJ	2.12	1.02	2.08	0.04	4.11	2.03	2.03	0.04	–	–	–	–
COHESION	3.10	0.90	3.45	0.00	–	–	–	–	–	–	–	–
Boundary perimeter	0.00	0.00	−2.97	0.00	–	–	–	–	–	–	–	–
PARA_mean	–	–	–	–	0.18	0.03	5.68	0.00	–	–	–	–
Average patch area	–	–	–	–	2.29	0.66	3.48	0.00	–	–	–	–
CLUMPY	–	–	–	–	−410.54	172.40	−2.38	0.02	–	–	–	–

Table 7. Regional accuracy of water extraction with the proportion of water body, the landscape pattern indices, and different spatial resolution images.

Study area（30 km × 30 km）	Proportion of water	PARA	NLSI	COHESION	PLADJ	CLUMPY	Regional accuracy of different spatial resolution（%）
	(%)			(%)	(%)		24 m	40 m	56 m	120 m	152 m	200 m	248 m
A: Intersection between Heilongjiang River and Songhua River	10.02	17.32	0.03	99.86	96.53	0.96	96.73	93.56	90.13	77.06	72.37	65.89	60.27
B: Huaihe River downstream canal zone	31.09	21.13	0.04	99.69	95.76	0.94	96.93	94.55	92.46	85.95	83.39	81.13	76.50
C: Huaihe River Huainan region	10.49	28.31	0.06	99.33	94.31	0.94	93.96	90.16	87.44	79.19	75.11	72.18	67.15
D: East Taihu Lake region	70.33	2.06	0.01	99.94	99.57	0.99	99.53	99.29	99.20	97.82	97.44	96.55	95.67
E: Yangtze River Hukou below main stream region	17.23	41.04	0.07	99.13	92.93	0.92	94.78	91.39	88.46	80.43	77.64	75.11	72.54
F: North Poyang Lake region	43.80	9.12	0.02	99.92	98.16	0.97	99.30	98.64	98.09	95.61	94.58	93.17	92.16
G: South Poyang Lake region	24.30	15.48	0.03	99.73	96.90	0.96	97.70	95.62	93.80	87.85	84.97	81.71	77.55
H: Huizhou Dongjiang River	5.93	35.77	0.07	98.06	92.83	0.92	89.95	82.87	77.27	64.09	60.17	55.12	52.51

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