Heritable variation in tree growth and needle vegetation indices of slash pine (Pinus elliottii) using unmanned aerial vehicles (UAVs)

2021 ◽  
Vol 173 ◽  
pp. 114073
Author(s):  
Xueyu Tao ◽  
Yanjie Li ◽  
Weiqi Yan ◽  
Minjuan Wang ◽  
Zifeng Tan ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Tree Growth ◽  
Vegetation Indices ◽  
Pinus Elliottii ◽  
Slash Pine ◽  
Heritable Variation ◽  
Aerial Vehicles

scholarly journals Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard

2020 ◽  
Vol 12 (24) ◽  
pp. 4144
Author(s):  
José Luis Gallardo-Salazar ◽  
Marín Pompa-García
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Vegetation Indices ◽  
Field Measurements ◽  
Tree Level ◽  
Individual Tree ◽  
Basal Diameter ◽  
Crown Diameter ◽  
Aerial Vehicles

Modern forestry poses new challenges that space technologies can solve thanks to the advent of unmanned aerial vehicles (UAVs). This study proposes a methodology to extract tree-level characteristics using UAVs in a spatially distributed area of pine trees on a regular basis. Analysis included different vegetation indices estimated with a high-resolution orthomosaic. Statistically reliable results were found through a three-phase workflow consisting of image acquisition, canopy analysis, and validation with field measurements. Of the 117 trees in the field, 112 (95%) were detected by the algorithm, while height, area, and crown diameter were underestimated by 1.78 m, 7.58 m2, and 1.21 m, respectively. Individual tree attributes obtained from the UAV, such as total height (H) and the crown diameter (CD), made it possible to generate good allometric equations to infer the basal diameter (BD) and diameter at breast height (DBH), with R2 of 0.76 and 0.79, respectively. Multispectral indices were useful as tree vigor parameters, although the normalized-difference vegetation index (NDVI) was highlighted as the best proxy to monitor the phytosanitary condition of the orchard. Spatial variation in individual tree productivity suggests the differential management of ramets. The consistency of the results allows for its application in the field, including the complementation of spectral information that can be generated; the increase in accuracy and efficiency poses a path to modern inventories. However, the limitation for its application in forests of more complex structures is identified; therefore, further research is recommended.

scholarly journals Evaluation of Aboveground Nitrogen Content of Winter Wheat Using Digital Imagery of Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4416 ◽  
Author(s):  
Baohua Yang ◽  
Mengxuan Wang ◽  
Zhengxia Sha ◽  
Bing Wang ◽  
Jianlin Chen ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Unmanned Aerial Vehicles ◽  
Nitrogen Content ◽  
Spatial Information ◽  
Vegetation Indices ◽  
Scale Transformation ◽  
Support Vector ◽  
Spatial Feature ◽  
Aerial Vehicles ◽  
Wavelet Features

Nitrogen (N) content is an important basis for the precise management of wheat fields. The application of unmanned aerial vehicles (UAVs) in agriculture provides an easier and faster way to monitor nitrogen content. Previous studies have shown that the features acquired from UAVs yield favorable results in monitoring wheat growth. However, since most of them are based on different vegetation indices, it is difficult to meet the requirements of accurate image interpretation. Moreover, resampling also easily ignores the structural features of the image information itself. Therefore, a spectral-spatial feature is proposed combining vegetation indices (VIs) and wavelet features (WFs), especially the acquisition of wavelet features from the UAV image, which was transformed from the spatial domain to the frequency domain with a wavelet transformation. In this way, the complete spatial information of different scales can be obtained to realize good frequency localization, scale transformation, and directional change. The different models based on different features were compared, including partial least squares regression (PLSR), support vector regression (SVR), and particle swarm optimization-SVR (PSO-SVR). The results showed that the accuracy of the model based on the spectral-spatial feature by combining VIs and WFs was higher than that of VIs or WF indices alone. The performance of PSO-SVR was the best (R2 = 0.9025, root mean square error (RMSE) = 0.3287) among the three regression algorithms regardless of the use of all the original features or the combination features. Our results implied that our proposed method could improve the estimation accuracy of aboveground nitrogen content of winter wheat from UAVs with consumer digital cameras, which have greater application potential in predicting other growth parameters.

Effects of Fertilization on Healthy and Pitch Canker-Infected Pines

1981 ◽  
Vol 5 (2) ◽  
pp. 77-79 ◽  
Author(s):  
R. F. Fisher ◽  
W. S. Garbett ◽  
E. M. Underhill
Keyword(s):  
Tree Growth ◽  
Pinus Elliottii ◽  
Slash Pine ◽  
Pitch Canker ◽  
Phosphorus Fertilizer ◽  
Calcium Magnesium ◽  
Nitrogen Phosphorus

Abstract The addition of large amounts of nitrogen plus phosphorus fertilizer to a slash pine (Pinus elliottii var. elliottii Engelm.) stand infected with pitch canker increased mortality and decreased tree growth. The addition of nitrogen or phosphorus alone, small amounts of nitrogen plus phosphorus, or nitrogen, phosphorus, potassium, calcium, magnesium and micronutrients together neither increased mortality nor decreased tree growth.

scholarly journals UAV Detection of Sinapis arvensis Infestation in Alfalfa Plots Using Simple Vegetation Indices from Conventional Digital Cameras

2020 ◽  
Vol 2 (2) ◽  
pp. 206-212 ◽  
Author(s):  
Luis Fernando Sánchez-Sastre ◽  
Mª Auxiliadora Casterad ◽  
Mónica Guillén ◽  
Norlan Miguel Ruiz-Potosme ◽  
Nuno M. S. Alte da Veiga ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Vegetation Indices ◽  
Digital Cameras ◽  
Site Specific ◽  
Aerial Vehicles ◽  
Ndvi Index ◽  
Weed Cover

Unmanned Aerial Vehicles (UAVs) offer excellent survey capabilities at low cost to provide farmers with information about the type and distribution of weeds in their fields. In this study, the problem of detecting the infestation of a typical weed (charlock mustard) in an alfalfa crop has been addressed using conventional digital cameras installed on a lightweight UAV to compare RGB-based indices with the widely used Normalized Difference Vegetation Index (NDVI) index. The simple (R−B)/(R+B) and (R−B)/(R+B+G) vegetation indices allowed one to easily discern the yellow weed from the green crop. Moreover, they avoided the potential confusion of weeds with soil observed for the NDVI index. The small overestimation detected in the weed identification when the RGB indices were used could be easily reduced by using them in conjunction with NDVI. The proposed methodology may be used in the generation of weed cover maps for alfalfa, which may then be translated into site-specific herbicide treatment maps.

scholarly journals Remotely Sensed Vegetation Indices to Discriminate Field-Grown Olive Cultivars

2019 ◽  
Vol 11 (10) ◽  
pp. 1242 ◽  
Author(s):  
Giovanni Avola ◽  
Salvatore Filippo Di Gennaro ◽  
Claudio Cantini ◽  
Ezio Riggi ◽  
Francesco Muratore ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Vegetation Indices ◽  
Canopy Reflectance ◽  
Olive Grove ◽  
Linear Discriminant ◽  
Aerial Vehicles ◽  
Olive Cultivars ◽  
Univariate Anova ◽  
Components Analysis ◽  
Statistical Approaches

The application of spectral sensors mounted on unmanned aerial vehicles (UAVs) assures high spatial and temporal resolutions. This research focused on canopy reflectance for cultivar recognition in an olive grove. The ability in cultivar recognition of 14 vegetation indices (VIs) calculated from reflectance patterns (green520–600, red630–690 and near-infrared760–900 bands) and an image segmentation process was evaluated on an open-field olive grove with 10 different scion/rootstock combinations (two scions by five rootstocks). Univariate (ANOVA) and multivariate (principal components analysis—PCA and linear discriminant analysis—LDA) statistical approaches were applied. The efficacy of VIs in scion recognition emerged clearly from all the approaches applied, whereas discrimination between rootstocks appeared unclear. The results of LDA ascertained the efficacy of VI application to discriminate between scions with an accuracy of 90.9%, whereas recognition of rootstocks failed in more than 68.2% of cases.

Small Topographic Differences Affect Slash Pine Response to Site Preparation and Fertilization

1983 ◽  
Vol 7 (3) ◽  
pp. 145-148 ◽  
Author(s):  
James D. Haywood
Keyword(s):  
Tree Growth ◽  
Pinus Elliottii ◽  
Site Preparation ◽  
Slash Pine ◽  
Silt Loam ◽  
Triple Superphosphate

Abstract On a Wrightsville-Vidrine silt loam flatwoods in southwest Louisiana, six-year-old slash pines (Pinus elliottii Engelm. var. elliottii) planted on the better drained Vidrine-pimple mounds and Vidrine-like ridges were nearly four times larger than pines planted in the poorly drained Wrightsville depressions. Site preparation treatments did not affect tree growth on the better drained sites. In the poorly drained depressions pines planted on beds were 37 percent taller and averaged 49 percent more volume per tree than pines planted on harrowed plots. Fertilization did not increase yields on the poorly drained sites. On the better drained sites, pines fertilized with triple superphosphate were 24 percent taller and averaged 84 percent more volume per tree than unfertilized pines.

Triadimefon Controls Fusiform Rust in Young Slash Pine Plantations

1986 ◽  
Vol 10 (2) ◽  
pp. 112-114 ◽  
Author(s):  
S. J. Rowan
Keyword(s):  
Tree Growth ◽  
Pinus Elliottii ◽  
Slash Pine ◽  
Pine Plantations ◽  
Effective Control ◽  
Fusiform Rust ◽  
Foliar Sprays

Abstract Triadimefon (Bayleton®) effectively controlled fusiform rust in a slash pine (Pinus elliottii Engelm. var. elliottii) plantation when three or more foliar sprays containing 600 ppm a.i. were applied annually (March to June) to runoff. Fewer foliar sprays and a top-dip applied at planting did not provide effective control of the disease. From the spray volumes applied over a five-year period, an estimated maximum of 505 mg a.i. triadimefon accumulated per tree. This amount did not reduce tree growth or survival. South. J. Appl. For. 10:112-114, May 1986.

Canopy structure, light penetration and tree growth in a slash pine (Pinus elliottii) silvo-pastoral system at different stand configurations in Florida

1991 ◽  
Vol 67 (3) ◽  
pp. 263-267 ◽  
Author(s):  
W. Sequeira ◽  
H. L. Gholz
Keyword(s):  
Soil Temperature ◽  
Tree Growth ◽  
Volume Growth ◽  
Canopy Structure ◽  
Pinus Elliottii ◽  
Slash Pine ◽  
Stem Volume ◽  
Light Penetration ◽  
Pastoral System ◽  
Structure Light

Canopy structure, light penetration and accumulated stem volume were studied for a one-year-period in an 18-year-old slash pine/native understory silvo-pastoral system at the Withlacoochee State Forest, central Florida. Trees were planted in six different single and double row configurations at a constant stand density. Below-canopy photosynthetically active radiation (PAR) and soil temperature were monitored along transects within the plots on a monthly basis. Above-canopy PAR was continuously recorded as reference. Tree stem dimensions (height, diameter) and crown dimensions (height, width) were measured on trees adjacent to the transects and stem volumes estimated. Results showed that tree crown area and stem volume were highly correlated, and both were also significantly related to light penetration (below-canopy PAR: above-canopy PAR ratio). Soil temperature and light penetration were also correlated. The results suggest that canopy geometry can be significantly managed to optimize both tree growth and light available to an understory. Key words: Canopy, configuration, Florida, light, silvopastoral, slash pine, stem volume growth, understory, PAR

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