Description Details Author(s) References See Also Examples

PROTOLIDAR package contains functions for analyze the LIDAR scan of plants (grapevine) and make with the outputs 3D maps in GRASS-GIS.

Package: | PROTOLIDAR |

Type: | Package |

Version: | 1.0 |

Date: | 2012-12-14 |

License: | GPL(>=2) |

LazyLoad: | yes |

This package help to analyze the LIDAR scan and extract the grapevine plant for see the plant in 3D GRASS GIS maps.

The package contains the following dataset and functions:

LIDAR_data is the dataset of the LIDAR scan. Represent the grapevine plant (BBCH 65).

Extract_plant_grapevine_function: which cuts the excess data.

Extract_plant_3D_function: helps to position the axis in the center of the plant.

Height_canopy_function: to measure the height of canopy from the LIDAR scan.

Width_canopy_function:to measure the width of canopy from the LIDAR scan.

Number_LIDAR_points_function: to calculate the number of points into the canopy.

LAI_function: to calculate the leaf area index.

LWA_lidar_function:to calculate the leaf wall area.

TRV_lidar_function: to calculate tree row volume in m^3*ha^-1.

Rotate_function: to rotate plants to match with the planting line.

Replicate_plants_function: to replicate plants.

Monica Fernanda Rinaldi<[email protected]>

Emilio Gil<[email protected]>

Jordi Llorens<[email protected]>

Maintainer: Monica Fernanda Rinaldi<[email protected]>

Rinaldi, M. F.,2012. Modelling the impact of climate change on the Interaction between host and pest/pathogen phenologies at regional level: Trentino - Italy. Unpublished PhD diss. Doctoral School on the Agro-food System - Agrisystem - Cycle XXIV - Universita Cattolica del Sacro Cuore -UNICATT - Piacenza- Italy.

PROTOLIDAR-package

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## Should be DIRECTLY executable !!
## For example:
data (LIDAR_data)
x <- LIDAR_data [,1]
y <- LIDAR_data [,2]
z <- LIDAR_data [,3]
zdistance <- 190 # total LIDAR scan distance measured in cm.
miny <- 0 # minimum height of the plant measured in cm.
maxy <- 2000 # maximum height of the plant measured in cm.
minx <- 450 # minimum width from where LIDAR starts to measure (cm).
maxx <- 1470# maximum width from where LIDAR starts to measure (cm).
minz <- 0 # the beginning of the LIDAR scan measured in cm.
maxz <- 186 # the end of the LIDAR scan measured in cm (length of interest).
## The function is currently defined as
Extract_plant_grapevine_function <- function(x,y,z,zdistance,miny,maxy,minx,maxx,minz,maxz){
y <- -y
y <- y-min(y)
z<- (z*zdistance)/max(z)
x_cm <- 0
y_cm <- 0
z_cm <- 0
for (i in 1:length(x)){
if (x[i] >= minx && x[i] <= maxx && y[i] >= miny && y[i] <= maxy && z[i] >= minz && z[i] <= maxz) {
y_cm[i] <- y[i]
x_cm[i] <- x[i]
z_cm[i] <- z[i]
}
}
y_cm <- na.omit(y_cm[2:length(y_cm)])
y_cm <- as.numeric((y_cm-min(y_cm))/1000)
x_cm <- as.numeric(na.omit(x_cm[2:length(x_cm)])/1000)
z_cm <- as.numeric(na.omit(z_cm[2:length(z_cm)])/100)
return <- data.frame(x_cm,y_cm,z_cm)
}
out <- Extract_plant_grapevine_function(x,y,z,zdistance,miny,maxy,minx,maxx,minz,maxz)
x = out[,1]
y = out[,2]
z = out[,3]
# plot
par(mfcol=c(2,2))
plot(x,y,pch=20,cex=.4,xlab='Width (m)', ylab='Height (m)', main='Grapevine BBCH')
plot(x,z,pch=20,cex=.4,xlab='Width (m)', ylab='Front (m)', main='Grapevine BBCH')
plot(z,y,pch=20,cex=.4,xlab='Front (m)', ylab='Height (m)', main='Grapevine BBCH')
``` |

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