ccrop_zoning {cropZoning}

Climate crop zoning based on monthly air temperature data

Description

This function will calculate the climate crop zoning for the range of air temperature informed. The result will be a raster image with five possible values (values of 1 to 5) according to what is explained below.

• Pixel values = 1, correspond to suitable air temperature (ST);

• Pixel values = 2, correspond to restricted due to low temperature (RLT);

• Pixel values = 3, correspond to restricted due to high temperature (RHT);

• Pixel values = 4, correspond to unsuitable due to low temperature (ULT);

• Pixel values = 5, correspond to unsuitable due to high temperature (UHT).

The thermal suitability ranges established were as follows:

1. ST - Temperature range (range of temp2 to temp3) considered optimal for the growth, development and production of the crop;

2. RLT - Temperature range (range of temp2 to temp1) which the crop is able to develop, however, below its potential due to the air temperature values being slightly lower than those of the suitable range;

3. RHT - Temperature range (range of temp3 to temp4) which the crop is able to develop, however, below its potential due to the temperature values being slightly higher than those of the suitable range;

4. ULT - When temperature values are not suitable for commercial exploitation of the crop due to low air temperature (air temperature below the temp1);

5. UHT - When temperature values are not suitable for commercial exploitation of the crop due to high air temperature (air temperature above the temp4);

Usage

ccrop_zoning(temp_per_month, temp1, temp2, temp3, temp4)

Arguments

temp_per_month

Rasterstack object with a monthly mean air temperature from a period of time

temp1

unsuitable due to low temperature (numeric)

temp2

minimum suitable temperature (numeric)

temp3

maximum suitable temperature (numeric)

temp4

unsuitable due to high temperature (numeric)

Value

Returns a SpatRaster object of climate crop zoning based in air temperature.

Examples

## Not run: 
### Example with Brazil states

see_brazil_states()

image_tmin<-loadROI(variable = "tmin", 
                   region = "brazil", 
                   sub_region = 13) # sub_regions 1:27
                   
image_tmax<-loadROI(variable = "tmax",
                   region = "brazil", 
                   sub_region = 13)
                   
image_tmean <- tmean(tmax_stack = image_tmax, tmin_stack = image_tmin)


start_date <- c('2000-01-01')
end_date <- c('2017-12-01')

tmean_monthly <- tmean_monthly_stack(tmean_stack = img_tmean,
                                    start_date = start_date,
                                    end_date = end_date)
                                    
                    
zoning <- ccrop_zoning(temp_per_month = tmean_monthly,
                       temp1 = 10 , temp2 = 20, 
                       temp3 = 30, temp4 = 40)

## End(Not run)