Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images

Proisy, Christophe; Couteron, Pierre; Fromard, François

doi:10.1016/j.rse.2007.01.009

Cited by 174 publications

(188 citation statements)

References 52 publications

Supporting

Mentioning

169

Contrasting

Unclassified

Order By: Relevance

“…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%

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

et al. 2015

View full text Add to dashboard Cite

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.

show abstract

Section: Introductionmentioning

confidence: 99%

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

et al. 2015

View full text Add to dashboard Cite

show abstract

“…In particular, the development of textural approaches to very high spatial resolution imageries has led to an accurate retrieval of forest structural parameters (Couteron et al 2005;Barbier et al 2012) and has been shown to improve land cover classification in complex forested environment (Lu et al 2014). For instance, the Fourier Transform Textural Ordination (Couteron et al 2005) has been shown to retrieve accurate forest biomass estimates, even in a high biomass context (Proisy et al 2007;Ploton et al 2012;Bastin et al 2014). However, a major limitation of such an approach, which should be overcome before any large-scale mapping, is the systematic biases generated by the varying acquisition angles and by the atmospheric pollution (Barbier et al 2011).…”

Section: Very High-resolution Optical Imagerymentioning

confidence: 99%

An overview of existing and promising technologies for national forest monitoring

Henry

Réjou‐Méchain

Cifuentes-Jara

et al. 2015

Annals of Forest Science

View full text Add to dashboard Cite

show abstract

“…FOTO is a well-established method to quantify image textural properties [19,20,22]. A brief introduction to the main steps of the method is given below, while more details can be found in [20].…”

Section: Canopy Grain Analysis (Foto)mentioning

confidence: 99%

“…A brief introduction to the main steps of the method is given below, while more details can be found in [20]. The image data is first divided into continuous unit windows, fixed here to 100 m by 100 m. A 2D Fast Fourier Transform is then applied to each unit window, and the resulting amplitudes are squared to yield a 2-D periodogram providing information about the variability in pixels according to spatial frequencies.…”

Section: Canopy Grain Analysis (Foto)mentioning

confidence: 99%

“…For instance, texture analysis of VHRI (1-2 m resolution) of forest canopies that exploits the contrast between sunlit and shadowed part of tree crowns, not only improved details of the outer canopy structure but correlated well with crown size and stand density [18,19]. High potential for biomass mapping was also seen with methods like Fourier Textural Ordination (referred as FOTO [20]) or Gaussian variogram model [21] applied on IKONOS imagery as such textural Indices did not saturate in high biomass ranges of unstratified forest [20][21][22]. Although important, such image-based techniques describe only the horizontal distribution of biomass, thus lacking any insight into vertical description of the canopy structure, a complex issue in multi-layered forests.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar

et al. 2015

Self Cite

View full text Add to dashboard Cite

Light Detection and Ranging (Lidar) is a state of the art technology to assess forest aboveground biomass (AGB). To date, methods developed to relate Lidar metrics with forest parameters were built upon the vertical component of the data. In multi-layered tropical forests, signal penetration might be restricted, limiting the efficiency of these methods. A potential way for improving AGB models in such forests would be to combine traditional approaches by descriptors of the horizontal canopy structure. We assessed the capability and complementarity of three recently proposed methods for assessing AGB at the plot level OPEN ACCESSRemote Sens. 2015, 7 10608 using point distributional approach (DM), canopy volume profile approach (CVP), 2D canopy grain approach (FOTO), and further evaluated the potential of a topographical complexity index (TCI) to explain part of the variability of AGB with slope. This research has been conducted in a mountainous wet evergreen tropical forest of Western Ghats in India. AGB biomass models were developed using a best subset regression approach, and model performance was assessed through cross-validation. Results demonstrated that the variability in AGB could be efficiently captured when variables describing both the vertical (DM or CVP) and horizontal (FOTO) structure were combined. Integrating FOTO metrics with those of either DM or CVP decreased the root mean squared error of the models by 4.42% and 6.01%, respectively. These results are of high interest for AGB mapping in the tropics and could significantly contribute to the REDD+ program. Model quality could be further enhanced by improving the robustness of field-based biomass models and influence of topography on area-based Lidar descriptors of the forest structure.

show abstract

Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images

Cited by 174 publications

References 52 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

An overview of existing and promising technologies for national forest monitoring

Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar

Contact Info

Product

Resources

About