Three-dimensional estimation of deciduous forest canopy structure and leaf area using multi-directional, leaf-on and leaf-off airborne lidar data

2022 ◽  
Vol 314 ◽  
pp. 108781
Author(s):  
Tiangang Yin ◽  
Bruce D. Cook ◽  
Douglas C. Morton
Author(s):  
Peter Potapov ◽  
Xinyuan Li ◽  
Andres Hernandez-Serna ◽  
Svetlana Turubanova ◽  
Alexandra Tyukavina ◽  
...  

2016 ◽  
pp. 103 ◽  
Author(s):  
J. Guerra-Hernández ◽  
M. Tomé ◽  
E. González-Ferreiro

<p>This study reports progress in forest inventory methods involving the use of low density airborne LiDAR data and an area-based approach (ABA). It also emphasizes the usefulness of the Spanish countrywide LiDAR dataset for mapping forest stand attributes in Mediterranean stone pine forest characterized by complex orography. Lowdensity airborne LiDAR data (0.5 first returns m<sup><span lang="EN-US">–2</span></sup>) was used to develop individual regression models for a set of forest stand variables in different types of forest. LiDAR data is now freely available for most of the Spanish territory and is provided by the Spanish National Aerial Photography Program (Plan Nacional de Ortofotografía Aérea, PNOA). The influence of height thresholds (MHT: Minimun Height Threshold and BHT: Break Height Threshold) used in extracting LiDAR metrics was also investigated. The best regression models explained 61-85%, 67-98% and 74-98% of the variability in ground-truth stand height, basal area and volume, respectively. The magnitude of error for predicting structural vegetation parameters was higher in closed deciduous and mixed forest than in the more homogeneous coniferous stands. Analysis of height thresholds (HT) revealed that these parameters were not particularly important for estimating several forest attributes in the coniferous forest; nevertheless, substantial differences in volume modelling were observed when the height thresholds (MHT and BHT) were increased in complex structural vegetation (mixed and deciduous forest). A metric-by-metric analysis revealed that there were significant differences in most of the explanatory variables computed from different height thresholds (HBT and MHT).The best models were applied to the reference stands to yield spatially explicit predictions about the forest resources. Reliable mapping of biometric variables was implemented to facilitate effective and sustainable management strategies and practices in Mediterranean Forest ecosystems.</p>


2021 ◽  
Author(s):  
Yonghua Qu ◽  
Ahmed Shaker ◽  
Carlos Alberto Silva ◽  
Carine Klauberg ◽  
Ekena Rangel Pinagé

Leaf area index (LAI) is an important parameter to describe the capacity of forests to intercept light and thus affects the microclimate and photosynthetic capacity of canopies. In general, tropical forests have a higher leaf area index and it is a challenge to estimate LAI in a forest with a very dense canopy. In this study, it is assumed that the traditional Light Detection and Ranging (LiDAR)-derived fractional vegetation cover (fCover) has weak relationship with leaf area index in a dense forest. We propose a partial least squares (PLS) regression model using the height percentile metrics derived from airborne LiDAR data to estimate the LAI of a dense forest. Ground inventory and airborne LiDAR data collected in a selectively logged tropical forest area in Eastern Amazonia are used to map LAI from the plot level to the landscape scale. The results indicate that the fCover, derived from the first return or the last return, has no significant correlations with the ground-based LAI. The PLS model evaluated by the leave-one-out validation shows that the estimated LAI is significantly correlated with the ground-based LAI with an R2 of 0.58 and a root mean square error (RMSE) of 1.13. A data comparison indicates that the Moderate Resolution Imaging Spectrometer (MODIS) LAI underestimates the landscape-level LAI by about 22%. The MODIS quality control data show that in the selected tile, the cloud state is not the primary factor affecting the MODIS LAI performance; rather, the LAI from the main radiative transfer (RT) algorithm contributes much to the underestimation of the LAI in the tropical forest. In addition, the results show that the LiDAR-based LAI has a better response to the logging activities than the MODIS-based LAI, and that the leaf area reduction caused by logging is about 13%. In contrast, the MODIS-based LAI exhibits no apparent spatial correlation with the LiDAR-based LAI. It is suggested that the main algorithm of MODIS should be improved with regard to tropical forests. The significance of this study is the proposal of a framework to produce ground-based LAI using forest inventory data and determine the plot-level LAI at the airborne and satellite scale using LiDAR data.


2012 ◽  
Vol 500 ◽  
pp. 511-516 ◽  
Author(s):  
Zhi Ming Hu ◽  
Jian Ping Wu ◽  
Bin Wu ◽  
Song Shu ◽  
Bai Lang Yu

This study utilizes high resolution airborne LiDAR data and topographic solar radiation model to quantify the impacts of three-dimensional morphology on the spatio-temporal variations of solar radiation at the Lujiazui Region, Shanghai, China. Monthly direct and non-direct (diffuse and reflection) plus seasonal total solar radiation distributions are simulated and mapped by using a radiation flux model. The results show that the crowded buildings at the Lujiazui Region have severely changed the spatial pattern of solar radiation intensity and duration. The derived monthly and seasonal solar radiation maps would benefit the understanding of the impacts of urban 3D morphology on the environmental factors and be the scientific basic for the further research.


2012 ◽  
Vol 518-523 ◽  
pp. 5648-5655
Author(s):  
Hui Lin ◽  
Ya Zhou Ji ◽  
Liang Liang ◽  
Wei Liu ◽  
Zhao Ling Hu

The research of Three Dimensional City Model (3DCM) has become a hot topic in GIS field in recent years, and it also has played an important role in traffic, land, mining, surveying and mapping, and other fields, especially in urban planning. However, the difficulty to acquire 3D data is the key obstacle to the further development of 3DCM. Airborne LIDAR, integrating GPS, INS and scanning laser rangefinder, can rapidly acquire the 3D position of ground by airplane, which is very economical, efficient and convenient to acquire 3D data. Because traditional three-dimensional data acquisition method can’t meet the need of the city’s fast development, airborne LIDAR technology is regarded as a convenient, swift, high-efficient three-dimensional data acquisition method. Compared with traditional methods, the airborne LIDAR technology has the following characteristics: 1) High efficiency: in 12 hours, the airborne LIDAR can scan 1000 square kilometers, next, with the help of the related post-processing software, LIDAR cloud data can transform them into GIS format or other receivable format in certain automatic or semiautomatic mode. 2) High precision: because the pulse of laser light isn’t easily subject to shadow and solar angle, it greatly improves the data quality. The flight height limit has no influence on its elevation data precision, which is superior to the conventional photogrammetry. The plane precision may achieve 0.15 to 1 meter, the elevation precision may achieve 10 centimeters. 3) All-weather feature: airborne LIDAR is active remote sensing without considering the digital aerial photogrammetry. 4) Rich information: with the aid of airborne LIDAR ,we can obtains not only the three dimensional coordinate of ground point, but also the three dimensional coordinate of terrain details, such as trees, buildings, roads. If it is integrated with CCD, it could gains image information. We acquired the airborne LIDAR data of 20 square kilometers in the central area of Shanghai using ALTM3100 airborne LIDAR system of the Optech company in 2006.This paper introduces the data processing procedure of the airborne LIDAR data, LIDAR system uses random commercial software to process plane GPS tracking data、plane attitude data、 laser ranging data and the swinging angle data of laser scanning mirror, finally, obtaining the three-dimensional coordinates(X,Y,Z) data of various surveying points. Which three-dimensional discrete dot matrix data is without attribute suspending in the air namely LIDAR original data, named “point cloud”. LIDAR data performs pre-processing to obtain digital surface model (DSM), which is classified and extracted, we acquire topography and object related to modeling, preparing for three-dimensional city model. Data pre-processing includes abnormal point deletion, coordinate transformation and flight strip combination. At present, we used famous business software TerraSolid, developed by Company of Finland to realize the classification and extraction from the LIDAR data TerraSolid depends on MicroStation platform, on the basis of classification and extraction algorithms presented by Axelsson, et al. of Swedish, including a lot of module such as TerraScan, TerraModeler and TerraPhoto. TerraScan is used in the field of LIDAR data classification and extraction, TerraModeler is used for producing and dealing with various planes, TerraPhoto is used for dealing with the primitive image, topography model and building model are got by using this software, complicated artificial building (Oriental Pearl, Jin Mao mansion etc.) need artificial repair and disposal, data processing of 20 sq. km. takes more than one month, efficiency has been improved greatly on the premise of guaranteeing the precision. Topography model and building model can be obtained by using TerraSolid and combining a few manual intervention based on DSM, The topography model is expressed with the triangulated irregular network (TIN), the building model is expressed with 3ds format, three dimensional model of non - texture of Lujiazui region of Shanghai was gained by LIDAR data. In order to achieving better visualization effect, the topography model overlaps orthophoto, and stuck true texture to building model, true city landscape of Lujiazui region of Shanghai is established. This paper has introduce post-processing procedure of airborne LIDAR data systematically, has realized the fast reconstruction of three-dimension urban model based on LIDAR data, enable this technology to serve the information construction of the city better.


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