Mapping individual tree health using full-waveform airborne laser scans and imaging spectroscopy: A case study for a floodplain eucalypt forest

Shendryk, Yuri; Broich, Mark; Tulbure, Mirela G.; McGrath, Andrew; Keith, David A.; Alexandrov, Sergey V.

doi:10.1016/j.rse.2016.10.014

Cited by 63 publications

(52 citation statements)

References 70 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Canopy condition of forests has been assessed successfully using remote sensing. Many studies infer changes in vegetation condition from satellite‐derived vegetation indices, such as the normalized difference vegetation index (NDVI), but often (e.g., Maselli, ), although not always (Browning, Maynard, Karl, & Peters, ; Shendryk et al, ), without checks from ground surveys or rigorous statistical analysis (e.g., Vogelmann, Tolk, & Zhu, ). Modelled predictions of forest condition seldom are validated (e.g., Singh, Serbin, McNeil, Kingdon, & Townsend, ), either with ground checks or with subsequent tests of predictions at new, independent locations (Cunningham, Mac Nally, Read et al, ).…”

Section: Introductionmentioning

confidence: 99%

Assessment of ecosystems: A system for rigorous and rapid mapping of floodplain forest condition for Australia's most important river

Cunningham

Griffioen²,

White

et al. 2017

Land Degrad Dev

View full text Add to dashboard Cite

Methods that provide rapid assessments of changing ecosystems at multiple scales are needed to inform management to address undesirable change. We developed a remote-sensing method in partnership with, and for use by, natural resource managers to predict annually stand condition of floodplain forests along Australia's longest river, the Murray River. A measure of stand condition, which was developed in collaboration with responsible natural resource managers, is a function of plant area index, crown extent, and the percentage live basal area. We surveyed a broad range of spatial and temporal variation in condition, built predictive stand-condition models using satellite-derived variables, and validated predictions with surveys of new sites. A multiyear model using data from 2 drought years and a year following extensive floods provided better predictions of stand condition than did models on the basis of the data for individual years.The model provided good predictions for data collected after the build for 50 sites and for resurveys of build sites in later years (R 2 ≥ 0.86). There was limited, temporary improvement in stand condition after the extensive flooding (2010 to late 2010) that followed a 13-year (1997 to early 2010) drought. Forest condition can be mapped accurately and annually at medium resolution (25 × 25 m) for large areas (100,000s ha) if quantitative ground surveys, satellite imagery, machine learning, and future validation are combined. Regular assessments of forest condition can be related to likely causes of change by using regular, rapid assessments and hence can provide important management information.

show abstract

Section: Introductionmentioning

confidence: 99%

Assessment of ecosystems: A system for rigorous and rapid mapping of floodplain forest condition for Australia's most important river

Cunningham

Griffioen²,

White

et al. 2017

Land Degrad Dev

View full text Add to dashboard Cite

show abstract

“…The accuracy of the flight line trajectory was similar as reported for the lidar mission and it is Coupling ALS and HSI technology in airborne remote sensing has a very high potential in understanding landscape processes, but our missions could not have been flown over the same area at that time to demonstrate these benefits. For example, Shendryk et al (2016) successfully used lidar scanning and hyperspectral sensing within a manned airborne mission for assessing health conditions of eucalyptus forest.…”

Section: Results Of Uav-based Hyperspectral Scanningmentioning

confidence: 99%

High Resolution Airborne Laser Scanning and Hyperspectral Imaging With a Small Uav Platform

Gallay

Eck²,

Zgraggen³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

Commission I, WG I/VbKEY WORDS: payload integration, unmanned aerial system, UAV/VTOL, LiDAR, 3D mapping, terrain model, point density ABSTRACT:The capabilities of unmanned airborne systems (UAS) have become diverse with the recent development of lightweight remote sensing instruments. In this paper, we demonstrate our custom integration of the state-of-the-art technologies within an unmanned aerial platform capable of high-resolution and high-accuracy laser scanning, hyperspectral imaging, and photographic imaging. The technological solution comprises the latest development of a completely autonomous, unmanned helicopter by Aeroscout, the Scout B1-100 UAV helicopter. The helicopter is powered by a gasoline two-stroke engine and it allows for integrating 18 kg of a customized payload unit. The whole system is modular providing flexibility of payload options, which comprises the main advantage of the UAS. The UAS integrates two kinds of payloads which can be altered. Both payloads integrate a GPS/IMU with a dual GPS antenna configuration provided by OXTS for accurate navigation and position measurements during the data acquisition. The first payload comprises a VUX-1 laser scanner by RIEGL and a Sony A6000 E-Mount photo camera. The second payload for hyperspectral scanning integrates a push-broom imager AISA KESTREL 10 by SPECIM. The UAS was designed for research of various aspects of landscape dynamics (landslides, erosion, flooding, or phenology) in high spectral and spatial resolution.

show abstract

“…High density lidar pulses can accurately measure the 3D geometric (horizontal plus vertical) information of forest canopies. Therefore, the integration of lidar data into HI analysis could provide critical information on the shadow distribution of a tree crown [29]. The lighting conditions in tree crown pixels of HI were determined using a combination of lidar point cloud and solar geometry at the acquisition time of HI [29].…”

Section: D Shaded and Sunlit Portions Of Tree Crown Modellingmentioning

confidence: 99%

Detection of Pine Shoot Beetle (PSB) Stress on Pine Forests at Individual Tree Level using UAV-Based Hyperspectral Imagery and Lidar

et al. 2019

View full text Add to dashboard Cite

In recent years, the outbreak of the pine shoot beetle (PSB), Tomicus spp., has caused serious shoots damage and the death of millions of trees in Yunnan pine forests in southwestern China. It is urgent to develop a convincing approach to accurately assess the shoot damage ratio (SDR) for monitoring the PSB insects at an early stage. Unmanned airborne vehicles (UAV)-based sensors, including hyperspectral imaging (HI) and lidar, have very high spatial and spectral resolutions, which are very useful to detect forest health. However, very few studies have utilized HI and lidar data to estimate SDRs and compare the predictive power for mapping PSB damage at the individual tree level. Additionally, the data fusion of HI and lidar may improve the detection accuracy, but it has not been well studied. In this study, UAV-based HI and lidar data were fused to detect PSB. We systematically evaluated the potential of a hyperspectral approach (only-HI data), a lidar approach (only-lidar data), and a combined approach (HI plus lidar data) to characterize PSB damage of individual trees using the Random Forest (RF) algorithm, separately. The most innovative point is the proposed new method to extract the three dimensional (3D) shadow distribution of each tree crown based on a lidar point cloud and the 3D radiative transfer model RAPID. The results show that: (1) for the accuracy of estimating the SDR of individual trees, the lidar approach (R2 = 0.69, RMSE = 12.28%) performed better than hyperspectral approach (R2 = 0.67, RMSE = 15.87%), and in addition, it was useful to detect dead trees with an accuracy of 70%; (2) the combined approach has the highest accuracy (R2 = 0.83, RMSE = 9.93%) for mapping PSB damage degrees; and (3) when combining HI and lidar data to predict SDRs, two variables have the most contributions, which are the leaf chlorophyll content (Cab) derived from hyperspectral data and the return intensity of the top of shaded crown (Int_Shd_top) from lidar metrics. This study confirms the high possibility to accurately predict SDRs at individual tree level if combining HI and lidar data. The 3D radiative transfer model can determine the 3D crown shadows from lidar, which is a key information to combine HI and lidar. Therefore, our study provided a guidance to combine the advantages of hyperspectral and lidar data to accurately measure the health of individual trees, enabling us to prioritize areas for forest health promotion. This method may also be used for other 3D land surfaces, like urban areas.

show abstract

Mapping individual tree health using full-waveform airborne laser scans and imaging spectroscopy: A case study for a floodplain eucalypt forest

Cited by 63 publications

References 70 publications

Assessment of ecosystems: A system for rigorous and rapid mapping of floodplain forest condition for Australia's most important river

Assessment of ecosystems: A system for rigorous and rapid mapping of floodplain forest condition for Australia's most important river

High Resolution Airborne Laser Scanning and Hyperspectral Imaging With a Small Uav Platform

Detection of Pine Shoot Beetle (PSB) Stress on Pine Forests at Individual Tree Level using UAV-Based Hyperspectral Imagery and Lidar

Contact Info

Product

Resources

About