A Remote Sensing Method for Retrieving Chlorophyll-a Concentration from River Water Body

Weihua LIU; Siyuan WANG; Yuanxu MA; Ming SHEN; Yongfa YOU; Kai HAI; Linlin WU

doi:10.12082/dqxxkx.2020.190547

Journals >Journal of Geo-information Science >Volume 22 >Issue 10 >Page 2062 > Article

Journal of Geo-information Science
Vol. 22, Issue 10, 2062 (2020)

A Remote Sensing Method for Retrieving Chlorophyll-a Concentration from River Water Body

Weihua LIU^1、2, Siyuan WANG^1、*, Yuanxu MA^1、2, Ming SHEN^1、2, Yongfa YOU^1、2, Kai HAI³, and Linlin WU⁴

Author Affiliations

¹Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

²University of Chinese Academy of Sciences, Beijing 100049, China

³Fuzhou University, Fuzhou 350002, China

⁴East China University of Technology, Nanchang 330013, China

show less

DOI: 10.12082/dqxxkx.2020.190547 Cite this Article

Weihua LIU, Siyuan WANG, Yuanxu MA, Ming SHEN, Yongfa YOU, Kai HAI, Linlin WU. A Remote Sensing Method for Retrieving Chlorophyll-a Concentration from River Water Body[J]. Journal of Geo-information Science, 2020, 22(10): 2062 Copy Citation Text

show less

Fig. 1. Sampling point location in the Bayanbulak wetland grassland in Xinjiang

Download full size | View in the Article

Fig. 2. Remote sensing reflectance above water surface of valid samples

Download full size | View in the Article

Fig. 3. Framework for Chl-a estimation based on concentration classification

Download full size | View in the Article

Fig. 4. Correlation coefficient between single-band remote sensing reflectance and in situ Chl-a

Download full size | View in the Article

Fig. 5. Correlation coefficient between in situ Chl-a and the three kinds of Rrsλ combination

Download full size | View in the Article

Fig. 6. Correlation between D3B and measured Chl-a

Download full size | View in the Article

Fig. 7. Retrieval errors of the optimal statistical model X6 and 11 existing models

Download full size | View in the Article

Fig. 8. In situ Chl-a versus estimated Chl-a of X6, OC₂V4 and D3B in the two level Chl-a datasets

Download full size | View in the Article

Fig. 9. Scatterplot of estimated and measured Chl-a value obtained from the leave-one-out procedure

Download full size | View in the Article

Fig. 10. In situ Chl-a versus estimated Chl-a of X6, OC₂V4, D3B and OC₂-D3B in the all in situ datasets

Download full size | View in the Article

Fig. 11. Spatial distribution of estimated Chl-a using the OC₂V4, D3B, and OC₂-D3B

Download full size | View in the Article

Fig. 12. Estimated Chl-a versus in situ Chl-a of matchup samples

Download full size | View in the Article

Fig. 13. Temporal variation of monthly average Chl-a concentration in wetland river water bodies from 2016 to 2019 and monthly average Chl-a concentration over the years

Download full size | View in the Article

Fig. 14. The variation trend of Chl-a concentration with meteorological factors and correlation analysis

Download full size | View in the Article

水质参数		最小值	最大值	平均值	标准差	变异系数	采样数
叶绿素a/(mg/m³)	总体	2.53	8.72	4.29	1.65	0.39	38
	干流	2.78	8.06	4.16	1.37	0.33	12
	湖泊	2.53	8.72	5.33	1.98	0.37	13
	支流	2.67	5.24	3.37	0.67	0.20	13
浊度(NTU)	总体	2.57	93.42	34.23	26.56	0.78	38
	干流	4.33	93.42	49.54	29.81	0.60	12
	湖泊	2.57	44.71	25.77	13.92	0.54	13
	支流	2.89	75.38	28.56	16.36	0.57	13

Table 1. Descriptive statistics of the concentration of water constituents in July 2018

算法	描述
T_Chl-a^[11]	$R = R_{rs} (433) / R_{rs} (555) \times (R_{rs} (412) / R_{rs} {(490))}^{C_{0}}$ $Chl - a = 10^{(c_{1} + c_{2} Lo g_{10} (R) + C_{3} Lo g_{10}^{2} (R))}$ $C_{0} = - 0.935, C_{1} = 0.342, C_{2} = - 2.511, C_{3} = - 0.277$
OC₂V4^[2]	$R = Lo g_{10} (\max (R_{rs} (443), R_{rs} (490)) / R_{rs} (560))$ $Chl - a = 10^{(c_{0} + c_{1} R + c_{2} R^{2} + c_{3} R^{3} + c_{4} R^{4})}$ $\begin{array}{l} C_{0} = 0.2975, C_{1} = - 21.502, C_{2} = - 215.53, C_{3} = - 784.5, \\ C_{4} = - 859.7 \end{array}$
OC₄V4^[2]	$R = Lo g_{10} (\max (R_{rs} (443), R_{rs} (490), R_{rs} (510)) / R_{rs} (560))$ $Chl - a = 10^{(c_{0} + c_{1} R + c_{2} R^{2} + c_{3} R^{3} + c_{4} R^{4})}$ $\begin{array}{l} C_{0} = - 0.599, C_{1} = - 50.54, C_{2} = - 578.38, C_{3} = - 2525.7, \\ C_{4} = - 376.2 \end{array}$
NDCI^[46]	$NDCI = (R_{rs} (708) - R_{rs} (665)) / (R_{rs} (708) + R_{rs} (665))$ $Chl - a = 4.0448 + 10.301 \times (NDCI)$
FLH^[21]	$FLH = R_{rs} (λ_{2}) - [R_{rs} (λ_{3}) + \frac{λ_{2} - λ_{3}}{λ_{1} - λ_{3}} * (R_{rs} (λ_{1}) - R_{rs} (λ_{3}))]$ $λ_{1} : 665 nm, λ_{2} : 681 nm, λ_{3} : 708 nm$ $Chl - a = 3.6268 - 11.289 \times (FLH) - 17.743 \times {(FLH)}^{2}$
MCI^[22]	$MCI = L_{w} (λ_{2}) - [L_{w} (λ_{1}) + \frac{λ_{2} - λ_{1}}{λ_{3} - λ_{1}} * (L_{w} (λ_{3}) - L_{w} (λ_{1}))]$ $λ_{1} : 681 nm, λ_{2} : 708 nm, λ_{3} : 753 nm$ $Chl - a = 5.6122 - 2.1844 \times (MCI) + 0.6641 \times {(MCI)}^{2}$
SCI^[23]	$H_{Chl} = [R_{rs} (λ_{4}) + \frac{λ_{4} - λ_{3}}{λ_{4} - λ_{2}} (R_{rs} (λ_{2}) - R_{rs} (λ_{4}))] - R_{rs} (λ_{3})$ $H_{△} = R_{rs} (λ_{2}) - [R_{rs} (λ_{4}) + \frac{λ_{4} - λ_{2}}{λ_{4} - λ_{1}} (R_{rs} (λ_{1}) - R_{rs} (λ_{4}))]$ $SCI = H_{Chl} - H_{△}$ $λ_{1} : 560 nm, λ_{2} : 620 nm, λ_{3} : 665 nm, λ_{4} : 681 nm$ $Chl - a = 5.7457 - 7.9685 \times (SCI) + 5.7043 \times {(SCI)}^{2}$
G2B^[14]	$G 2 B = \frac{R_{rs} (λ_{2})}{R_{rs} (λ_{1})}$ $λ_{1} : 659 nm, λ_{2} : 692 nm$ $Chl - a = 49.739 - 124.14 \times (G 2 B) + 82.754 \times {(G 2 B)}^{2}$
D3B^[15]	$D 3 B = [R_{rs} {(λ_{1})}^{- 1} - R_{rs} {(λ_{2})}^{- 1}] \times R_{rs} (λ_{3})$ $λ_{1} : 659 nm, λ_{2} : 692 nm, λ_{3} : 748 nm$ $Chl - a = 6.9756 + 73.431 \times (D 3 B) + 344.53 \times {(D 3 B)}^{2}$
L4B^[7]	$L 4 B = [R_{rs} {(λ_{1})}^{- 1} - R_{rs} {(λ_{2})}^{- 1}] / [R_{rs} {(λ_{4})}^{- 1} - R_{rs} {(λ_{3})}^{- 1}]$ $λ_{1} : 659 nm, λ_{2} : 692 nm, λ_{3} : 705 nm, λ_{4} : 748 nm$ $Chl - a = 5.5923 + 11.566 \times (L 4 B) + 15.472 \times {(L 4 B)}^{2}$
G_Chl-a^[29]	$b_{b} = 1.61 \times R_{rs} (779) / (0.082 - 0.6 \times R_{rs} (779))$ $Chl - a = (R_{rs} (709) / R_{rs} (665) \times (0.7 + b_{b}) - 0.4 - b_{b}^{1.06}) / 0.016$

Table 2. Brief descriptions of the 11 types of Chl-a retrieval algorithms used in this study

模型简写	自变量	拟合方程	R²
X1	$x = R_{n} (537)$	$y = 3.2765 x^{2} - 0.3799 x + 3.1175$	0.56
X2	$x = (R_{n} (537) - R_{n} (428)) / (R_{n} (537) + R_{n} (428))$	$y = 14.681 x^{2} + 17.266 x + 8.1809$	0.48
X3	$x = R_{n} (537) / R_{n} (678)$	$y = 8.5277 x^{2} - 0.2788 x + 3.3603$	0.36
X4	$x = (R_{n} (537) - R_{n} (678)) / (R_{n} (537) + R_{n} (678))$	$y = 8.6092 x^{2} + 14.272 x + 9.3707$	0.34
X5	$x = (R_{rs} (384) - R_{rs} (385)) * 100$	$y = 75435 x^{2} + 1063.9 x + 6.896$	0.63
X6	$x = R_{rs} (689) / R_{rs} (613)$	$y = 107.82 x^{2} - 166.85 x + 67.757$	0.82
X7	$x = (R_{rs} (625) - R_{rs} (624)) / (R_{rs} (625) + R_{rs} (624)) \times 100$	$y = 105.97 x^{2} + 45.711 x + 8.2691$	0.73

Table 3. The optimal fitting equation between reflectance and Chl-a concentration based on regression analysis

D3B分组	Chl-a最小值	Chl-a最大值	Chl-a均值	标准差	变异系数	采样点数
D3B≤-0.051	2.53	4.25	3.40	0.50	0.15	24
D3B>-0.051	2.67	8.72	6.05	1.73	0.28	12
Chl-a分组	D3B最小值	D3B最大值	D3B均值	标准差	变异系数	采样点数
Chl-a ≤4.50 mg/m³	-0.092	-0.041	-0.072	0.014	-0.19	26
Chl-a>4.50 mg/m³	-0.047	0.026	-0.014	0.023	-1.69	10

Table 4. Descriptive statistics of the water samples with D3B=-0.051 and Chl-a=4.5 mg/m³as hierarchical threshold

Download Citation

Save the article for my favorites

Paper Information