# Mapping forest cover

using tree canopy cover

Question 1

here we import a dateset on tree canopy cover and calculate forest using a 10% tree cover threshold

```// import feature collection with country boundaries
var countries = ee.FeatureCollection("USDOS/LSIB_SIMPLE/2017");
// select Cambodia
var kh = countries.filter(ee.Filter.eq("country_na","Cambodia")).geometry();

// import tree canopy cover data
var tcc2000 = ee.Image("projects/servir-mekong/UMD/tree_canopy/tcc_2000").clip(kh);
var tcc2020 = ee.Image("projects/servir-mekong/UMD/tree_canopy/tcc_2020").clip(kh);

// use 10% as a threshold for forest
var forest2000  = tcc2000.gt(10);
var forest2020  = tcc2020.gt(10);

// add tcc to the map

// add forest layer to the map
```

Question 2

we calculate forest loss now between the years 2020 and 2000. copy the lines below in the existing code

```var forestLoss = forest2000.and(forest2020.eq(0))
```

Question 3

we calculate the pixel area in 2000. copy the lines below to your existing code

```var areaImage = forest2000.rename("forest").multiply(ee.Image.pixelArea());

// Sum the values of forest in 2000
var stats = areaImage.reduceRegion({
reducer: ee.Reducer.sum(),
geometry: kh,
scale: 30,
maxPixels: 1e9
});

print('pixel area in 2000 ', stats.get('forest'), 'square meters');
```

Question 4

we do the same for the year 2020

```var areaImage = forest2020.rename("forest").multiply(ee.Image.pixelArea());

// Sum the values of forest in 2020
var stats = areaImage.reduceRegion({
reducer: ee.Reducer.sum(),
geometry: kh,
scale: 30,
maxPixels: 1e9
});

print('pixel area in 2020 ', stats.get('forest'), 'square meters');
```

Question 5

now we calculate the forest loss for the period 2000 until 2020

```var areaImage = forestLoss.rename("loss").multiply(ee.Image.pixelArea());
// Sum the values of forest loss pixels
var stats = areaImage.reduceRegion({
reducer: ee.Reducer.sum(),
geometry: kh,
scale: 30,
maxPixels: 1e9
});

print('pixels representing loss: ', stats.get('loss'), 'square meters');
```

Question 6

now we calculate the forest loss per province. Copy the code below to your existing script and hit run.

```// define the countries of interest

var chart =
ui.Chart.image.byRegion
({
image:areaImage.divide(10000),
regions: cambodia,
reducer: ee.Reducer.sum(),
scale: 100,
xProperty: 'NAME_1'
})
.setSeriesNames(['loss area'])
.setChartType('ColumnChart')
.setOptions({
title: 'forest loss',
hAxis: {title: 'Date', titleTextStyle: {italic: false, bold: true}},
vAxis: {
title: 'area loss (ha)',
titleTextStyle: {italic: false, bold: true}
},
lineWidth: 5,
colors: ['red'],
curveType: 'function'
});

print(chart);
```

## One comment

1. Ana says:

Thank you for this great contribution!
A question: when in question 6 you use the code: ” xProperty: ‘NAME_1’ “. What variable in your boundaries dataset are you referring with “NAME_1” or what is it implying?

Thank you again for this great help! ðŸ™‚