Regression and analytical models for estimating mangrove wetland biomass in South China using Radarsat images

Li, X.; Yeh, Ago; Wang, S.; Liu, K.; Liu, Xingcheng; Qian, Jiajia; Chen, X.

doi:10.1080/01431160701227638

Cited by 44 publications

(33 citation statements)

References 31 publications

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“…As a result, remote sensing-based mangrove biomass study, different mangrove species exhibit significant spectral signature differences in the electromagnetic spectrum independent of AGB [21,24]. In fact, biomass inversion processes based on traditional optical satellite data mainly consider the vegetation spectrum, such as normalized difference vegetation index (NDVI) or simple ratio index (SRI), etc.…”

Section: Introductionmentioning

confidence: 99%

“…Remote sensing-based models commonly utilize field survey data (diameter at breast height (DBH), tree height, and density) and allometric equations to acquire biomass estimations for developing biomass models [15,16]. Remote sensing models for estimating mangrove vegetation biomass have been established in LandSat [17], IKONOS [18], QuickBird [19], SAR [20], Rardarsat [21], SRTM [22] (coupled with ICEsat/GLAS, Landsat ETM+) and LiDAR [23] data, etc. Optical images are the most widely used and available sensor types, which is important for AGB estimations.…”

Section: Introductionmentioning

confidence: 99%

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Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images

et al. 2015

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Abstract:Previous research studies have demonstrated that the relationship between remote sensing-derived parameters and aboveground biomass (AGB) could vary across different species types. However, there are few studies that calibrate reliable statistical models for mangrove AGB. This study quantifies the differences of accuracy in AGB estimation between the results obtained with and without the consideration of species types using Worldview-2 images and field surveys. A Back Propagation Artificial Neural Network (BP ANN) based model is developed for the accurate estimation of uneven-aged and dense mangrove forest biomass. The contributions of the input variables are further quantified using a "Weights" method based on BP ANN model. Two types of mangrove species, Sonneratia apetala (S. apetala) and Kandelia candel (K. candel), are examined in this study. Results show that the species type information is the most important variable for AGB estimation, and the red edge band and the associated vegetation indices from WorldView-2 images are more sensitive to mangrove AGB than other bands and vegetation indices. The RMSE of biomass estimation at the incorporation of species as a dummy variable is 19.17% OPEN ACCESSRemote Sens. 2015, 7 12193 lower than that of the mixed species level. The results demonstrate that species type information obtained from the WorldView-2 images can significantly improve of the accuracy of the biomass estimation.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images

et al. 2015

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“…Accuracy tests used correlation coefficient (r) and Root Mean Square Error (RMSE) [14], [15], [16], [17], [5]. Equation :…”

Section: Test Accuracy With Rmsementioning

confidence: 99%

“…Regression was having values of R 2 >0.8, exponential regression for vegetation index NDVI, NDVI2, NNIP, SVI, MTV2, RDVI, MSR; regression of power/geometry for vegetation index of GNDVI, NDVI, NDVI2, NNIP, SVI, RDVI, MSR (Table 1). SPOT 5 and Landsat TM images obtained the best vegetation index was NDVI with non-linear regression [32], [5]. Worldview-2's best index is DVI, EVI, MRE-SR with allometric equations and 80.9% accuracy [6].…”

Section: Biomass Carbon Content Estimation Modelingmentioning

confidence: 99%

“…The assessment of carbon stocks with remote sensing was expected to reduce destructive ways or mangrove destruction. The estimated share of mangrove carbon with remote sensing imagery has been done using various images, such Quickbird [3], ALOS, Landsat [4], and, RADARSAT [5]. Different image resolutions resulted in different model accuracy.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Mangrove Carbon Stock With Hybrid Method Using Image Sentinel-2

Muhsoni¹

2018

GEOMATE

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ABSTRACT:Field survey data combined with remote sensing data were an ideal and practical method for estimating carbon stocks. The objective of this research was to get an estimation model of mangrove carbon stock with good accuracy. Modeling used hybrid methods, by combining satellite image analysis and field data. The result of this research was to get the mangrove carbon estimation model. Model 1 merging between NNIP vegetation index equation using regression of power/geometry and six variables multiple regression (NDRE or WVVI vegetation index, sediment depth, soil density,% C soil depth 0-15 cm, 15-50 cm and >50 cm). RMSE test resulted 0.4778 t 100 m -2 and % RMSE 16.12%. Model 2 NNIP vegetation index and three variable regression (VIRRE vegetation index, sediment depth, soil density). RMSE test resulted 0.5639 t 100 m -2 and % RMSE 19.03%. Model 3 uses NNIP vegetation index and two variable regression (NDRE vegetation index and sediment depth). RMSE test resulted 0.7295 t 100 m -2 and RMSE % 24.63%. Model 4 incorporation of NNIP vegetation index and multiple regression of 3 variables (VIRRE vegetation index, average sediment depth value 100.63 cm, soil density value 1.02 g cm -3 ). RMSE test resulted 1.0043 t 100 m -2 and % RMSE 33.89%.

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Remote Sensing Technology: Recent Advancements for Mangrove Ecosystems

Suratman

2013

Mangrove Ecosystems of Asia

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Regression and analytical models for estimating mangrove wetland biomass in South China using Radarsat images

Cited by 44 publications

References 31 publications

Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images

Retrieval of Mangrove Aboveground Biomass at the Individual Species Level with WorldView-2 Images

Estimation of Mangrove Carbon Stock With Hybrid Method Using Image Sentinel-2

Remote Sensing Technology: Recent Advancements for Mangrove Ecosystems

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