Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

Dash, Jonathan P.; Watt, Michael S.; Pearse, Grant D.; Heaphy, Marie; Dungey, Heidi S.

doi:10.1016/j.isprsjprs.2017.07.007

Cited by 296 publications

(265 citation statements)

References 80 publications

Supporting

Mentioning

246

Contrasting

Unclassified

Order By: Relevance

“…Recent studies have reported the use of UAS in various analyses, including forestry applications [27,28]. Collecting aerial photos by UAS and processing them with the structure from motion (SfM) method is one of the major new approaches to analyzing forest structures [29,30].…”

Section: Introductionmentioning

confidence: 99%

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

et al. 2017

View full text Add to dashboard Cite

Methods for accurately measuring biophysical parameters are a key component for quantitative evaluation regarding to various forest applications. Conventional in situ measurements of these parameters take time and expense, encountering difficultness at locations with heterogeneous microtopography. To obtain precise biophysical data in such situations, we deployed an unmanned aerial system (UAS) multirotor drone in a cypress forest in a mountainous area of Japan. The structure from motion (SfM) method was used to construct a three-dimensional (3D) model of the forest (tree) structures from aerial photos. Tree height was estimated from the 3D model and compared to in situ ground data. We also analyzed the relationships between a biophysical parameter, diameter at breast height (DBH), of individual trees with canopy width and area measured from orthorectified images. Despite the constraints of ground exposure in a highly dense forest area, tree height was estimated at an accuracy of root mean square error = 1.712 m for observed tree heights ranging from 16 to 24 m. DBH was highly correlated with canopy width (R 2 = 0.7786) and canopy area (R 2 = 0.7923), where DBH ranged from 11 to 58 cm. The results of estimating forest parameters indicate that drone-based remote-sensing methods can be utilized to accurately analyze the spatial extent of forest structures.

show abstract

Section: Introductionmentioning

confidence: 99%

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The use of small UAS has been shown to be helpful in tropical communities to manage and conserve forests [8]. Very high temporal and spatial resolution imagery obtained from the UAS provide a new tool for improved forest health monitoring during disease outbreaks [9]. With commercial availability of high spatial resolution visible and small active sensors, data can be provided for high precision forestry applications such as three-dimensional tree measurements, assessment of tree competition measurements, and growth [10].…”

Section: Introductionmentioning

confidence: 99%

Post-Logging Estimation of Loblolly Pine (Pinus taeda) Stump Size, Area and Population Using Imagery from a Small Unmanned Aerial System

Samiappan

Turnage

McCraine

et al. 2017

Drones

View full text Add to dashboard Cite

Abstract:This study describes an unmanned aerial system (UAS) method for accurately estimating the number and diameters of harvested Loblolly Pine (Pinus taeda) stumps in a final harvest (often referred as clear-cut) situation. The study methods are potentially useful in initial detection, quantification of area and volume estimation of legal or illegal logging events to help estimate the volumes and value of removed pine timber. The study sites used included three adjacent pine stands in East-Central Mississippi. Using image pattern recognition algorithms, results show a counting accuracy of 77.3% and RMSE of 4.3 cm for stump diameter estimation. The study also shows that the area can be accurately estimated from the UAS collected data. Our experimental study shows that the proposed UAS survey method has the potential for wide use as a monitoring or investigation tool in the forestry and land management industries.

show abstract

“…An example of surface reconstruction has been in forest structure [29]. Studies have shown that UAVs can help with species identification [30,31], tree height [26,32], crown delineation [26,33,34], and forest health [35][36][37]. The use of UAVs has great potential for analyzing tree branch conditions as an early detection of tree health [35].…”

Section: Introductionmentioning

confidence: 99%

“…Studies have shown that UAVs can help with species identification [30,31], tree height [26,32], crown delineation [26,33,34], and forest health [35][36][37]. The use of UAVs has great potential for analyzing tree branch conditions as an early detection of tree health [35]. Besides this potential, most of the studies applying UAV imagery to forest health are based in multispectral bands, as near infrared and red edge, in addition to the traditional visible light bands [35][36][37] as presented in this paper.…”

Section: Introductionmentioning

confidence: 99%

Cicada (<i>Magicicada</i>) Tree Damage Detection Based on UAV Spectral and 3D Data

Hentz¹,

Strager²

2018

View full text Add to dashboard Cite

The periodical cicadas appear in regions of the United States in intervals of 13 or 17 years. During these intervals, deciduous trees are often impacted by the small cuts and eggs they lay in the outer branches which soon die off. Because this is such an infrequent occurrence and it is so difficult to assess the damage across large forested areas, there is little information about the extent of this impact. The use of remote sensing techniques has been proven to be useful in forest health management to monitor large areas. In addition, the use of Unmanned Aerial Vehicles (UAVs) has become a valuable tool for analysis. In this study, we evaluated the impact of the periodical cicada occurrence on a mixed hardwood forest using UAV imagery. The goal was to evaluate the potential of this technology as a tool for forest health monitoring. We classified the cicada impact using two Maximum Likelihood classifications, one using only the high resolution spectral derived from leaf-on imagery (MLC 1), and in the second we included the Canopy Height Model (CHM)-derived from leaf-on Digital Surface Model (DSM) and leaf-off Digital Terrain Model (DTM)-information in the classification process (MLC 2). We evaluated the damage percentage in relation to the total forest area in 15 circular plots and observed a range from 1.03% -22.23% for MLC 1, and 0.02% -10.99% for MLC 2. The accuracy of the classification was 0.35 and 0.86, for MLC 1 and MLC 2, based on the kappa index. The results allow us to highlight the importance of combining spectral and 3D information to evaluate forest health features. We believe this approach can be applied in many forest monitoring objectives in order to detect disease or pest impacts.

show abstract

Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

Cited by 296 publications

References 80 publications

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

Post-Logging Estimation of Loblolly Pine (Pinus taeda) Stump Size, Area and Population Using Imagery from a Small Unmanned Aerial System

Cicada (<i>Magicicada</i>) Tree Damage Detection Based on UAV Spectral and 3D Data

Contact Info

Product

Resources

About

Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak

Cited by 296 publications

References 80 publications

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

Estimating Tree Height and Diameter at Breast Height (DBH) from Digital Surface Models and Orthophotos Obtained with an Unmanned Aerial System for a Japanese Cypress (Chamaecyparis obtusa) Forest

Post-Logging Estimation of Loblolly Pine (Pinus taeda) Stump Size, Area and Population Using Imagery from a Small Unmanned Aerial System

Cicada (&lt;i&gt;Magicicada&lt;/i&gt;) Tree Damage Detection Based on UAV Spectral and 3D Data

Contact Info

Product

Resources

About

Cicada (<i>Magicicada</i>) Tree Damage Detection Based on UAV Spectral and 3D Data