PROTOLIDAR-package: PRocess TOol LIdar DAta in R.

In PROTOLIDAR: PRocess TOol LIdar DAta in R

Description

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

Details

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.

Author(s)

Monica Fernanda Rinaldi<[e-mail]>

Emilio Gil<[e-mail]>

Jordi Llorens<[e-mail]>

Maintainer: Monica Fernanda Rinaldi<[e-mail]>

References

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 Unpublished PhD diss.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.

See Also

PROTOLIDAR-package

Examples

## 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')

Example output

PROTOLIDAR documentation built on May 2, 2019, 6:08 a.m.