基于GEE和时序主被动影像的广西北部湾红树林时空动态监测研究

邓建明, 姚航, 付波霖, 顾森, 唐婕, 甘园园

Monitoring the spatiotemporal dynamics of mangrove forests in Beibu Gulf, Guangxi Zhuang Autonomous Region, China, using Google Earth Engine and time-series active and passive remote sensing images

DENG Jianming, YAO Hang, FU Bolin, GU Sen, TANG Jie, GAN Yuanyuan

表3 各类型遥感指数计算公式

Tab.3 Calculation formula of each type of remote sensing index

序号	指数类型	计算公式^①
1	归一化植被指数 (normalized difference vegetation index, NDVI)	$N D V I = (λ_{N I R} - λ_{R E D}) / (λ_{N I R} + λ_{R E D})$
2	比值植被指数(ratio vegetation index, RVI)	$R V I = λ_{R E D} / λ_{N I R}$
3	差值植被指数(difference vegetation index, DVI)	$D V I = λ_{N I R} - λ_{R E D}$
4	增强植被指数(enhanced vegetation index, EVI)	$E V I = 2.5 \times \frac{λ_{N I R} - λ_{R E D}}{λ_{N I R} + 6.0 λ_{R E D} - 7.5 λ_{B L U E} + 1}$
5	校正植被指数(corrected transformed vegetation index, CTVI)	$C T V I = \frac{N D V I + 0.5}{\| N D V I + 0.5 \|} \sqrt{\| N D V I + 0.5 \|}$
6	非线性指数(non-linear vegetation index, NLI)	$N L I = ({λ_{N I R}}^{2} - λ_{R E D}) / ({λ_{N I R}}^{2} + λ_{R E D})$
7	改进简单比值指数(modified simple ratio, MSR_NIR)	$M S R_{N I R} = (\frac{λ_{N I R}}{λ_{R E D}} - 1) / \sqrt{\frac{λ_{N I R}}{λ_{R E D}} + 1}$
8	归一化水体指数(normalized difference water index, NDWI)	$N D W I = (λ_{S W I R} - λ_{N I R}) / (λ_{S W I R} + λ_{N I R})$
9	改进的归一化水体指数(modified normalized difference water index, MNDWI)	$N D W I_{S W I R 1} = (λ_{S W I R 1} - λ_{N I R}) / (λ_{S W I R 1} + λ_{N I R})$ SWIR1(1.55~1.75 μm) $N D W I_{S W I R 2} = (λ_{S W I R 2} - λ_{N I R}) / (λ_{S W I R 2} + λ_{N I R})$ SWIR2(2.08~2.35 μm)
10	自动提取水体指数(automated water extraction index, AWEI)	$A W E I = 4 (λ_{G R E E N} - λ_{S W I R 1}) / (0.25 λ_{N I R} + 0.75 λ_{S W I R 2})$
11	归一化建筑指数(normalized difference built-up index, NDBI)	$N D B I_{S W I R 1} = (λ_{S W I R 1} - λ_{N I R}) / (λ_{S W I R 1} + λ_{N I R})$ SWIR1(1.55~1.75 μm) $N D B I_{S W I R 2} = (λ_{S W I R 2} - λ_{N I R}) / (λ_{S W I R 2} + λ_{N I R})$ SWIR2(2.08~2.35 μm)
12	基于红边波段的改进简单比值指数(modified simple ratio, MSR_RE1,MSR_RE2)	$M S R_{R E 1} = (\frac{λ_{R E 1}}{λ_{R E D}} - 1) / \sqrt{\frac{λ_{R E 1}}{λ_{R E D}} + 1}$ RE1(703.9 nm) $M S R_{R E 2} = (\frac{λ_{R E 2}}{λ_{R E D}} - 1) / \sqrt{\frac{λ_{R E 2}}{λ_{R E D}} + 1}$ RE2(740.2 nm)
13	基于红边波段的非线性指数(non-linear index, NLI_RE1,NLI_RE2)	$N L I_{R E 1} = ({λ_{R E 1}}^{2} - λ_{R E D}) / ({λ_{R E 1}}^{2} + λ_{R E D})$ RE1(703.9 nm) $N L I_{R E 2} = ({λ_{R E 2}}^{2} - λ_{R E D}) / ({λ_{R E 2}}^{2} + λ_{R E D})$ RE2(740.2 nm)
14	基于红边波段的增强植被指数(enhanced vegetation index, EVI_RE1,EVI_RE2)	$E V I_{R E 1} = 2.5 \times \frac{λ_{R E 1} - λ_{R E D}}{λ_{R E 1} + 6.0 λ_{R E D} - 7.5 λ_{B L U E} + 1}$ RE1(703.9 nm) $E V I_{R E 2} = 2.5 \times \frac{λ_{R E 2} - λ_{R E D}}{λ_{R E 2} + 6.0 λ_{R E D} - 7.5 λ_{B L U E} + 1}$ RE2(740.2 nm)
15	微波遥感指数HH/HV	PALSAR HH/HV
16	微波遥感指数VV/VH	Sentinel-1 VV/VH