Comparison of UAV and WorldView-2 imagery for mapping leaf area index of mangrove forest

Tian, Jing; Wang, Le; Li, Xiaojuan; Gong, Huili; Shi, Chuang; Zhong, Rugang; Liu, Xiaomeng

doi:10.1016/j.jag.2017.05.002

Cited by 149 publications

(105 citation statements)

References 72 publications

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“…From 2013 to 2015, field survey methods were employed to measure these three parameters. Recently, unmanned aerial vehicle (UAV) remote sensing has opened the door to new sources of data to effectively characterize vegetation metrics at very high spatial resolutions [41,42] and with very high accuracy [43]. LiDAR data were used to test tree height and canopy cover measured from a field survey (in only three GLAS footprints).…”

Section: Field Biomassmentioning

confidence: 99%

Canopy Height Layering Biomass Estimation Model (CHL-BEM) with Full-Waveform LiDAR

Tian

Wang

et al. 2019

Remote Sensing

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Forest biomass is an important descriptor for studying carbon storage, carbon cycles, and global change science. The full-waveform spaceborne Light Detection And Ranging (LiDAR) Geoscience Laser Altimeter System (GLAS) provides great possibilities for large-scale and long-term biomass estimation. To the best of our knowledge, most of the existing research has utilized average tree height (or height metrics) within a GLAS footprint as the key parameter for biomass estimation. However, the vertical distribution of tree height is usually not as homogeneous as we would expect within such a large footprint of more than 2000 m 2 , which would limit the biomass estimation accuracy vastly. Therefore, we aim to develop a novel canopy height layering biomass estimation model (CHL-BEM) with GLAS data in this study. First, all the trees with similar height were regarded as one canopy layer within each GLAS footprint. Second, the canopy height and canopy cover of each layer were derived from GLAS waveform parameters. These parameters were extracted using a waveform decomposition algorithm (refined Levenberg-Marquardt-RLM), which assumed that each decomposed vegetation signal corresponded to a particular canopy height layer. Third, the biomass estimation model (CHL-BEM) was established by using the canopy height and canopy cover of each height layer. Finally, the CHL-BEM was compared with two typical biomass estimation models of GLAS in the study site located in Ejina, China, where the dominant species was Populus euphratica. The results showed that the CHL-BEM presented good agreement with the field measurement biomass (R 2 = 0.741, RMSE = 0.487, %RMSE = 24.192) and achieved a significantly higher accuracy than the other two models. As a whole, we expect our method to advance all the full-waveform LiDAR development and applications, e.g., the newly launched Global Ecosystem Dynamics Investigation (GEDI).

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Section: Field Biomassmentioning

confidence: 99%

Canopy Height Layering Biomass Estimation Model (CHL-BEM) with Full-Waveform LiDAR

Tian

Wang

et al. 2019

Remote Sensing

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“…In addition, based on the population density in districts of Krakow and the cubic capacity of buildings, the anthropogenic heat flux was estimated (Xie et al 2016a, b). The leaf area index, LAI, was estimated based on the normalized difference vegetation index (Tian et al 2017). The morphometric parameters were calculated twice: firstly for squares of 0.01 km 2 , the same as the mesh of the CALMET model domain (Fig.…”

Section: The Monit-air Morphometric Databases (Bdm and Bdr)mentioning

confidence: 99%

Testing Various Morphometric Methods for Determining the Vertical Profile of Wind Speed Above Krakow, Poland

Godlowska

Kaszowski

2019

Boundary-Layer Meteorol

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Various morphometric methods used for wind-speed determination in urban areas inside the roughness sublayer have been tested in Krakow, Poland, using a hybrid modelling system. The hybrid modelling system combines the classic numerical meteorological modelling using ALADIN, MM5, and CALMET models with empirical, non-logarithmic relations determined on the basis of a wind-tunnel experiment. In the hybrid modelling system, the horizontally-averaged wind speed is determined using the displacement height d, roughness length z 0 , and an attenuation coefficient α. These parameters are determined using laser scanning data obtained in the MONIT-AIR project. The variability of the selected morphometric parameters in Krakow, the role of the size of the area from which they are determined and the consequences of replacing the frontal area index by the plan area index are analyzed. The different methods used to determine d, z 0, and α are compared and the correctness of the procedures describing the wind profile are verified by comparisons with wind-speed data from road stations, with the wind speed measured between the traffic lanes or at the roadside at a height of 4 m, at standard meteorological stations, and from masts situated on buildings. It is shown that the use of a parametrization based on large-eddy simulations prepared for explicitly resolved buildings in Tokyo and Nagoya in Japan, and taking the maximum instead of the average height of building in empirical relations, significantly improves the modelling results, especially above the average height of buildings.

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“…The system contains an eight-channel multispectral camera with 1.84 m resolution and a panchromatic camera with 0.46 m resolution. Scientific studies presented in recent publications demonstrate that WorldView-2 images can be used effectively to determine various characteristics of stands, in particular, their leaf area index [1] and species composition [2].…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images

et al. 2019

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A method for automated processing high spatial resolution satellite images is proposed to retrieve inventory and bioproductivity parameters of forest stands. The method includes effective learning classifiers, inverse modeling, and regression modeling of the estimated parameters. Spectral and texture features are used to classify forest species. The results of test experiments for the selected area of Savvatievskoe forestry (Russia, Tver region) are presented. Accuracy estimates obtained using ground-based measurements demonstrate the effectiveness of using the proposed techniques to automate the process of updating information for the State Forest Inventory program of Russia.

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Comparison of UAV and WorldView-2 imagery for mapping leaf area index of mangrove forest

Cited by 149 publications

References 72 publications

Canopy Height Layering Biomass Estimation Model (CHL-BEM) with Full-Waveform LiDAR

Canopy Height Layering Biomass Estimation Model (CHL-BEM) with Full-Waveform LiDAR

Testing Various Morphometric Methods for Determining the Vertical Profile of Wind Speed Above Krakow, Poland

Remote Sensing Methods for the Retrieval of Inventory and Bioproductivity Parameters of Forests Using High Resolution Satellite Images

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