report-defoliation.Rmd

---
title: "Prediction maps of defoliation at trees"
output: 
  workflowr::wflow_html:
    includes:
      in_header: header.html
editor_options:
  chunk_output_type: console
author: "Patrick Schratz, Marc Becker, Friedrich-Schiller-University Jena"
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(
  fig.retina = 3,
  fig.align = "center",
  out.width = "100%",
  echo = FALSE
)
source(here::here("code/99-packages.R"))
sourceDirectory("R")

# load drake objects
loadd(defoliation_raster,
      defoliation_raster_relative,
      defoliation_df,
      defoliation_df_relative,
      
      tune_xgboost
)
library("rgdal")
```

# Predicted defoliation (absolute)

Predicted defoliation by XGBOOST on 20 m spatial resolution in the Basque Country.

With an RMSE of 36 % (for a range of 0 - 100), the model focuses its prediction to the mean of the response range (0 - 100) to achieve acceptable performance results on the test set.

The following vegetation indices have been used, selected by the internal variable importance rating of XGBOOST:

- EVI
- GDVI4
- GDVI3
- GDVI2
- D1
- mNDVI
- mSR

# Optimization path of hyperparameter tuning

The following shows the optimization path (RMSE) of the hyperparameter tuning for the XGBOOST model using 20 MBO iterations (with a starting design of 30).

```{r}
suppressMessages(getOptPathY(tune_xgboost$opt.path))
```

Some more details on the optimization path are presented below:

```{r}
suppressMessages(plotOptPath(tune_xgboost$opt.path))
```

# Predicted Defoliation (relative)

Since these absolute values do not reflect the truth, we decided to create a relative Index from the predicted absolute values.

This was done by calling 

```{r , eval=FALSE, echo = TRUE}
scale(data$defoliation, center = FALSE,
      scale = max(data$defoliation, na.rm = TRUE)/100)
```

which re-scales the data from 0 - 100. 
The code was adapted from [this](https://stackoverflow.com/a/19462405/4185785) Stackoverflow answer.

# Defoliation evaluation {.tabset .tabset-fade}

## Absolute defoliation {.tabset .tabset-fade}

### Maps

#### 2017

```{r defoliation-map-2017, fig.height = 5.5, fig.width = 8.5}
plot = create_defoliation_map(defoliation_raster[[1]],
                              algorithm = "XGBOOST",
                              limits = c(35, 60), title = "Defoliation of trees [%]"
)
suppressWarnings(suppressMessages(print(plot)))
```

#### 2018

```{r defoliation-map-2018, fig.height = 5.5, fig.width = 8.5}
plot = create_defoliation_map(defoliation_raster[[2]],
                              algorithm = "XGBOOST",
                              limits = c(35, 60), title = "Defoliation of trees [%]"
)
suppressWarnings(suppressMessages(print(plot)))
```

### Histograms

2017 

```{r}
hist = suppressWarnings(suppressMessages(ggplot(defoliation_df[[1]], aes(x = defoliation)) +
  geom_histogram() +
  labs(x = "Defoliation (%)") +
  theme_pubr()
))

suppressMessages(print(hist))
```

2018

```{r}
hist = suppressWarnings(suppressMessages(ggplot(defoliation_df[[2]], aes(x = defoliation)) +
  geom_histogram() +
  labs(x = "Defoliation (%)") +
  theme_pubr()
))
suppressMessages(print(hist))
```

## Relative defoliation {.tabset .tabset-fade}

### Maps

#### 2017

```{r defoliation-map-relative-2017, fig.height = 5.5, fig.width = 8.5}
plot = create_defoliation_map(defoliation_raster_relative[[1]],
                              algorithm = "XGBOOST",
                              limits = c(65, 100), title = "Relative defoliation of trees"
)
suppressWarnings(suppressMessages(print(plot)))
```

#### 2018

```{r defoliation-map-relative-2018, fig.height = 5.5, fig.width = 8.5}
plot = create_defoliation_map(defoliation_raster_relative[[2]],
                              algorithm = "XGBOOST",
                              limits = c(65, 100), title = "Relative defoliation of trees"
)
suppressWarnings(suppressMessages(print(plot)))
```

### Histograms

2017

```{r}
hist = suppressWarnings(suppressMessages(ggplot(defoliation_df_relative[[1]], aes(x = defoliation)) +
                   geom_histogram() +
                   labs(x = "Relative defoliation of trees") +
                   theme_pubr()
))
suppressMessages(print(hist))
```

2018

```{r}
hist = suppressWarnings(suppressMessages(ggplot(defoliation_df_relative[[2]], aes(x = defoliation)) +
                   geom_histogram() +
                   labs(x = "Relative defoliation of trees") +
                   theme_pubr()
))
suppressMessages(print(hist))
```

```{r echo = FALSE}
system("rsync -rlptDivzog --chown=*:www-data --chmod=g+r,o+r /home/patrick/papers/2019-feature-selection/docs/figure/report-defoliation.Rmd/defol* patrick@jupiter.geogr.uni-jena.de:/home/www/life-healthy-forest/action-B1-spatial-mapping/defoliation-maps/"
)
```