# Monitoring Biennial Bearing Effect on Coffee Yield Using MODIS Remote Sensing Imagery

^{*}

## Abstract

**:**

## 1. Introduction

## 2. Methodology

#### 2.1. Selection of Pixels with Coffee Fields

#### 2.2. Filtering the Time Series

#### 2.3. Metrics Derived from Vegetation Indices

#### 2.4. Yield Data

#### 2.5. Correlations

_{i}: yield variation for the year (i); Pw

_{i}: weighed yield for the year (i); Pw

_{i}

_{−1}: weighed yield for the previous year (i−1); ΔIV

_{i}: vegetation index variation for the year (i); IVw

_{i}: weighed vegetation index for the year (i); IVw

_{i}

_{−1}: weighed vegetation index for the previous year (i−1); ΔP

_{i+}

_{1}: yield variation for the following year (i+1); Pw

_{i}

_{+1}: weighed yield for the following year (i+1); Pw

_{i}: weighed yield for the year (i).

## 3. Results

#### 3.1. Annual Variation of Vegetation Indices

#### 3.2. Yield Data and Vegetation Index Variation for Each Two Years

_{i}vs. ΔP

_{i}) from 2003 to 2009 are presented in Tables 2 and 3.

_{i}

_{+1}vs. ΔVI

_{i}) from 2003 to 2008.

## 4. Discussion

## 5. Conclusions

## Acknowledgments

## References

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**Figure 2.**Overlap of the limits of MODIS pixels with coffee fields in TM/Landsat 5 image, false color composite color 3B4R5G, (

**A**) pixels fully occupied by coffee crop and (

**B**) crop variability within a MODIS pixel in Landsat images.

**Figure 4.**Annual variation of vegetation indices for the selected pixels (

**A**). Standard crop with the maximum vegetation index value for March (

**B**) and minimum vegetation index for August (

**C**) on Image TM/Landsat 3B4R5G.

**Figure 5.**Filtered EVI and NDVI time series for coffee crop and the original data (without filtering process).

**Figure 6.**Correlation between variation on coffee yield and variation on minimum values of vegetation indices (minEVI and minNDVI) for the same year.

**Figure 7.**Correlation between variation on minimum values of vegetation indices (minEVI and minNDVI) and variation on coffee yield the following year.

**Figure 8.**Water balance for Guaxupé location and Pearson correlation coefficients from 2002 to 2009.

**Table 1.**Number of yield data samples collected for each year (n

_{i}) and number of valid samples when we calculated the difference between 2 years (n

_{i}–n

_{i}

_{−1}).

Table | 2002 | 2003 | 2004 | 2005 | 2006 | 2007 | 2008 | 2009 |
---|---|---|---|---|---|---|---|---|

n_{i} | 20 | 25 | 27 | 32 | 37 | 37 | 37 | 35 |

n_{i}–n_{i}_{−1} | - | 20 | 25 | 27 | 32 | 37 | 37 | 35 |

**Table 2.**Correlation coefficients between variation on coffee yield and variation on EVI metrics in the same year for each metric assessed.

Metric | 2002/03 | 2003/04 | 2004/05 | 2005/06 | 2006/07 | 2007/08 | 2008/09 | |
---|---|---|---|---|---|---|---|---|

N ^{a} | 20 | 25 | 27 | 32 | 37 | 37 | 35 | |

ampEVI | r ^{b} | 0.56 | 0.50 | 0.48 | 0.32 | 0.40 | 0.20 | 0.41 |

r-sq ^{c} | 0.32 | 0.25 | 0.23 | 0.10 | 0.16 | 0.04 | 0.17 | |

p-value ^{d} | 0.01 | 0.01 | 0.01 | 0.07 | 0.01 | 0.23 | 0.01 | |

SE ^{e} | 0.50 | 0.48 | 0.50 | 0.52 | 0.51 | 0.49 | 0.55 | |

sumEVI | r ^{b} | −0.33 | 0.12 | −0.06 | −0.20 | −0.49 | −0.40 | −0.47 |

r-sq ^{c} | 0.11 | 0.01 | 0.00 | 0.04 | 0.24 | 0.16 | 0.22 | |

p-value ^{d} | 0.15 | 0.59 | 0.78 | 0.26 | <0.01 | 0.01 | <0.01 | |

SE ^{e} | 0.57 | 0.55 | 0.57 | 0.53 | 0.48 | 0.46 | 0.53 | |

maxEVI | r ^{b} | 0.29 | 0.34 | 0.24 | 0.12 | −0.05 | −0.15 | −0.10 |

r-sq ^{c} | 0.08 | 0.11 | 0.06 | 0.01 | 0.00 | 0.02 | 0.01 | |

p-value ^{d} | 0.22 | 0.11 | 0.22 | 0.53 | 0.78 | 0.38 | 0.56 | |

SE ^{e} | 0.58 | 0.52 | 0.55 | 0.54 | 0.55 | 0.49 | 0.60 | |

minEVI | r ^{b} | −0.46 | −0.38 | −0.50 | −0.45 | −0.65 | −0.54 | −0.55 |

r-sq ^{c} | 0.21 | 0.14 | 0.25 | 0.20 | 0.42 | 0.30 | 0.31 | |

p-value ^{d} | 0.04 | 0.07 | 0.01 | 0.01 | <0.01 | <0.01 | <0.01 | |

SE ^{e} | 0.54 | 0.51 | 0.49 | 0.49 | 0.42 | 0.42 | 0.51 | |

avrgEVI | r ^{b} | −0.33 | 0.12 | −0.06 | −0.20 | −0.49 | −0.40 | −0.47 |

r-sq ^{c} | 0.11 | 0.01 | 0.00 | 0.04 | 0.24 | 0.16 | 0.22 | |

p-value ^{d} | 0.15 | 0.59 | 0.78 | 0.26 | <0.01 | 0.01 | <0.01 | |

SE ^{e} | 0.57 | 0.55 | 0.57 | 0.53 | 0.48 | 0.46 | 0.53 |

^{a}samples;

^{b}pearson’s coefficient;

^{c}coefficient of determination;

^{d}significance.;

^{e}standard error

**Table 3.**Correlation coefficients between variation on coffee yield and variation on NDVI metrics in the same year for each metric assessed.

Metric | 2002/03 | 2003/04 | 2004/05 | 2005/06 | 2006/07 | 2007/08 | 2008/09 | ||
---|---|---|---|---|---|---|---|---|---|

N ^{a} | 20 | 25 | 27 | 32 | 37 | 37 | 35 | ||

ampNDVI | r ^{b} | 0.44 | 0.33 | 0.10 | 0.41 | 0.42 | 0.26 | 0.11 | |

r-sq ^{c} | 0.20 | 0.11 | 0.01 | 0.17 | 0.18 | 0.07 | 0.01 | ||

p-value ^{d} | 0.05 | 0.11 | 0.61 | 0.02 | 0.01 | 0.12 | 0.52 | ||

SE ^{e} | 0.54 | 0.52 | 0.57 | 0.50 | 0.50 | 0.48 | 0.60 | ||

sumNDVI | r ^{b} | −0.15 | 0.25 | 0.10 | 0.07 | −0.36 | −0.40 | −0.23 | |

r-sq ^{c} | 0.02 | 0.06 | 0.01 | 0.01 | 0.13 | 0.16 | 0.05 | ||

p-value ^{d} | 0.52 | 0.23 | 0.61 | 0.69 | 0.03 | 0.01 | 0.18 | ||

SE ^{e} | 0.60 | 0.54 | 0.57 | 0.54 | 0.51 | 0.46 | 0.59 | ||

maxNDVI | r ^{b} | 0.11 | 0.07 | 0.07 | 0.37 | −0.20 | −0.30 | −0.19 | |

r-sq ^{c} | 0.01 | 0.00 | 0.00 | 0.14 | 0.04 | 0.09 | 0.04 | ||

p-value ^{d} | 0.64 | 0.75 | 0.73 | 0.03 | 0.23 | 0.07 | 0.28 | ||

SE ^{e} | 0.60 | 0.55 | 0.57 | 0.51 | 0.54 | 0.48 | 0.60 | ||

minNDVI | r ^{b} | −0.45 | −0.52 | −0.30 | −0.36 | −0.66 | −0.45 | −0.21 | |

r-sq ^{c} | 0.20 | 0.27 | 0.09 | 0.13 | 0.43 | 0.20 | 0.04 | ||

p-value ^{d} | 0.05 | 0.01 | 0.12 | 0.04 | <0.01 | <0.01 | 0.23 | ||

SE ^{e} | 0.54 | 0.48 | 0.54 | 0.51 | 0.42 | 0.44 | 0.59 | ||

avrgNDVI | r ^{b} | −0.15 | 0.25 | 0.10 | 0.07 | −0.36 | −0.40 | −0.23 | |

r-sq ^{c} | 0.02 | 0.06 | 0.01 | 0.01 | 0.13 | 0.16 | 0.05 | ||

p-value ^{d} | 0.52 | 0.23 | 0.61 | 0.69 | 0.03 | 0.01 | 0.18 | ||

SE ^{e} | 0.60 | 0.54 | 0.57 | 0.54 | 0.51 | 0.46 | 0.59 |

^{a}samples;

^{b}pearson’s coefficient;

^{c}coefficient of determination;

^{d}significance.;

^{e}standard error.

**Table 4.**Correlation coefficients between variation on EVI metrics and variation on coffee yield the following year for each metric assessed.

Metric | 2002/03 | 2003/04 | 2004/05 | 2005/06 | 2006/07 | 2007/08 | |
---|---|---|---|---|---|---|---|

N ^{a} | 20 | 25 | 27 | 32 | 37 | 37 | |

ampEVI | r ^{b} | −0.57 | −0.55 | −0.56 | −0.33 | −0.48 | −0.24 |

r-sq ^{c} | 0.33 | 0.30 | 0.31 | 0.11 | 0.23 | 0.06 | |

p-value ^{d} | 0.01 | 0.01 | <0.01 | 0.06 | <0.01 | 0.17 | |

SE ^{e} | 0.61 | 0.51 | 0.57 | 0.55 | 0.55 | 0.45 | |

sumEVI | r ^{b} | 0.52 | 0.06 | 0.10 | 0.18 | 0.49 | 0.47 |

r-sq ^{c} | 0.27 | 0.00 | 0.01 | 0.03 | 0.24 | 0.22 | |

p-value ^{d} | 0.02 | 0.79 | 0.61 | 0.31 | <0.01 | <0.01 | |

SE ^{e} | 0.61 | 0.57 | 0.58 | 0.55 | 0.48 | 0.44 | |

maxEVI | r ^{b} | −0.17 | −0.29 | −0.27 | −0.16 | 0.01 | 0.20 |

r-sq ^{c} | 0.03 | 0.08 | 0.07 | 0.02 | 0.00 | 0.04 | |

p-value ^{d} | 0.49 | 0.17 | 0.18 | 0.39 | 0.93 | 0.25 | |

SE ^{e} | 0.61 | 0.57 | 0.59 | 0.55 | 0.54 | 0.48 | |

minEVI | r ^{b} | 0.62 | 0.55 | 0.53 | 0.29 | 0.74 | 0.62 |

r-sq ^{c} | 0.39 | 0.30 | 0.28 | 0.09 | 0.55 | 0.39 | |

p-value ^{d} | <0.01 | 0.01 | <0.01 | 0.10 | <0.01 | <0.01 | |

SE ^{e} | 0.61 | 0.48 | 0.57 | 0.55 | 0.46 | 0.42 | |

avgEVI | r ^{b} | 0.52 | 0.06 | 0.10 | 0.18 | 0.49 | 0.47 |

r-sq ^{c} | 0.27 | 0.00 | 0.01 | 0.03 | 0.24 | 0.22 | |

p-value ^{d} | 0.02 | 0.79 | 0.61 | 0.31 | <0.01 | <0.01 | |

SE ^{e} | 0.61 | 0.57 | 0.58 | 0.55 | 0.48 | 0.44 |

^{a}samples;

^{b}pearson’s coefficient;

^{c}coefficient of determination;

^{d}significance.;

^{e}standard error.

**Table 5.**Correlation coefficients between variation on NDVI metrics and variation on coffee yield the following year for each metric assessed.

Metric | 2002/03 | 2003/04 | 2004/05 | 2005/06 | 2006/07 | 2007/08 | |
---|---|---|---|---|---|---|---|

N ^{a} | 20 | 25 | 27 | 32 | 37 | 37 | |

ampNDVI | r ^{b} | −0.63 | −0.47 | −0.26 | −0.34 | −0.40 | −0.30 |

r-sq ^{c} | 0.39 | 0.22 | 0.07 | 0.12 | 0.16 | 0.09 | |

p-value ^{d} | <0.01 | 0.02 | 0.19 | 0.06 | 0.01 | 0.08 | |

SE ^{e} | 0.59 | 0.48 | 0.57 | 0.54 | 0.52 | 0.47 | |

sumNDVI | r ^{b} | 0.34 | 0.03 | −0.04 | −0.12 | 0.38 | 0.42 |

r-sq ^{c} | 0.12 | 0.00 | 0.00 | 0.01 | 0.14 | 0.17 | |

p-value ^{d} | 0.14 | 0.91 | 0.83 | 0.53 | 0.02 | 0.01 | |

SE ^{e} | 0.60 | 0.55 | 0.59 | 0.54 | 0.50 | 0.48 | |

maxNDVI | r ^{b} | 0.00 | −0.08 | −0.12 | −0.33 | 0.24 | 0.30 |

r-sq ^{c} | 0.00 | 0.01 | 0.01 | 0.11 | 0.06 | 0.09 | |

p-value ^{d} | 1.00 | 0.70 | 0.56 | 0.67 | 0.15 | 0.08 | |

SE ^{e} | 0.60 | 0.52 | 0.59 | 0.55 | 0.53 | 0.48 | |

minNDVI | r ^{b} | 0.65 | 0.68 | 0.46 | 0.27 | 0.63 | 0.48 |

r-sq ^{c} | 0.43 | 0.46 | 0.21 | 0.07 | 0.39 | 0.23 | |

p-value ^{d} | <0.01 | <0.01 | 0.02 | 0.14 | <0.01 | <0.01 | |

SE ^{e} | 0.61 | 0.46 | 0.56 | 0.55 | 0.45 | 0.48 | |

avgNDVI | r ^{b} | 0.34 | 0.03 | −0.04 | −0.12 | 0.38 | 0.42 |

r-sq ^{c} | 0.12 | 0.00 | 0.00 | 0.01 | 0.14 | 0.17 | |

p-value ^{d} | 0.14 | 0.91 | 0.83 | 0.53 | 0.02 | 0.01 | |

SE ^{e} | 0.60 | 0.55 | 0.59 | 0.54 | 0.50 | 0.48 |

^{a}samples;

^{b}pearson’s coefficient;

^{c}coefficient of determination;

^{d}significance.;

^{e}standard error.

## Share and Cite

**MDPI and ACS Style**

Bernardes, T.; Moreira, M.A.; Adami, M.; Giarolla, A.; Rudorff, B.F.T.
Monitoring Biennial Bearing Effect on Coffee Yield Using MODIS Remote Sensing Imagery. *Remote Sens.* **2012**, *4*, 2492-2509.
https://doi.org/10.3390/rs4092492

**AMA Style**

Bernardes T, Moreira MA, Adami M, Giarolla A, Rudorff BFT.
Monitoring Biennial Bearing Effect on Coffee Yield Using MODIS Remote Sensing Imagery. *Remote Sensing*. 2012; 4(9):2492-2509.
https://doi.org/10.3390/rs4092492

**Chicago/Turabian Style**

Bernardes, Tiago, Maurício Alves Moreira, Marcos Adami, Angélica Giarolla, and Bernardo Friedrich Theodor Rudorff.
2012. "Monitoring Biennial Bearing Effect on Coffee Yield Using MODIS Remote Sensing Imagery" *Remote Sensing* 4, no. 9: 2492-2509.
https://doi.org/10.3390/rs4092492