burnedarea/burned_area at main · dehdutra/burnedarea · GitHub

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import ee
import geemap

ee.Authenticate()
ee.Initialize(project='ee-seuusuario')

grid = ee.FeatureCollection('seuasset')

# Definir o conjunto de dados MODIS
dataset = ee.ImageCollection('MODIS/061/MCD64A1')\
    .filter(ee.Filter.date('2023-01-01', '2023-12-31'))

# Selecionar a camada de data de queimadas
burned_area = dataset.select('BurnDate')

# Definir visualização
burned_area_vis = {
    'min': 30.0,
    'max': 341.0,
    'palette': ['4e0400', '951003', 'c61503', 'ff1901']
}

# Criar o mapa
Map = geemap.Map()
Map.setCenter(6.746, 46.529, 2)

# Recortar a área de queimadas ao grid do Brasil
burned_area_clipped = burned_area.map(lambda img: img.clip(grid))

# Adicionar camada recortada de queimadas
Map.addLayer(burned_area_clipped, burned_area_vis, 'Burned Area')

# Carregar o grid do Brasil
Map.addLayer(grid, {}, 'Brasil Grid')

# Carregar o grid do Brasil
Map.addLayer(grid, {}, 'Brasil Grid')

# Exibir o mapa
Map

import datetime
# Função para adicionar camadas mensais
def add_monthly_layers(start_year, start_month, end_year, end_month):
    for year in range(start_year, end_year + 1):
        for month in range(start_month, end_month + 1):
            start_date = f"{year}-{month:02d}-01"

            # Usar datetime para pegar o último dia do mês
            if month == 12:
                end_date = f"{year}-{month:02d}-31"
            else:
                next_month = month + 1
                next_month_first_day = datetime.date(year, next_month, 1)
                last_day_of_month = next_month_first_day - datetime.timedelta(days=1)
                end_date = last_day_of_month.strftime("%Y-%m-%d")

            dataset = ee.ImageCollection('MODIS/061/MCD64A1')\
                .filter(ee.Filter.date(start_date, end_date))

            burned_area = dataset.select('BurnDate')

            # Recortar a área de queimadas ao grid do Brasil
            burned_area_clipped = burned_area.map(lambda img: img.clip(grid))

            burned_area_vis = {
                'min': 30.0,
                'max': 341.0,
                'palette': ['4e0400', '951003', 'c61503', 'ff1901']
            }

            layer_name = f'{year}-{month:02d}'
            Map.addLayer(burned_area_clipped, burned_area_vis, layer_name)

# Chamar a função para adicionar camadas mensais
add_monthly_layers(2023, 1, 2023, 12)

# Carregar o grid do Brasil novamente
Map.addLayer(grid, {}, 'Brasil Grid')

# Exibir o mapa
Map

import datetime
# Recortar a área de queimadas ao grid do Brasil
burned_area_clipped = burned_area.map(lambda img: img.clip(grid))

# Função para adicionar camadas mensais e exportar como TIF
def add_monthly_layers_and_export(start_year, start_month, end_year, end_month):
    for year in range(start_year, end_year + 1):
        for month in range(start_month, end_month + 1):
            start_date = f"{year}-{month:02d}-01"

            # Usar datetime para pegar o último dia do mês
            if month == 12:
                end_date = f"{year}-{month:02d}-31"
            else:
                next_month = month + 1
                next_month_first_day = datetime.date(year, next_month, 1)
                last_day_of_month = next_month_first_day - datetime.timedelta(days=1)
                end_date = last_day_of_month.strftime("%Y-%m-%d")

            dataset = ee.ImageCollection('MODIS/061/MCD64A1')\
                .filter(ee.Filter.date(start_date, end_date))

            burned_area = dataset.select('BurnDate')

            # Recortar a área de queimadas ao grid do Brasil
            burned_area_clipped = burned_area.map(lambda img: img.clip(grid))

            # Exportar a imagem mensal recortada para o Google Drive
            layer_name = f'{year}-{month:02d}'
            export_task = ee.batch.Export.image.toDrive(
                image=burned_area_clipped.median(),  # Usando a mediana para representar o mês
                description=f"Burned_Area_{layer_name}",
                folder='Burned_Area_TIFs',
                fileNamePrefix=f"Burned_Area_{layer_name}",
                region=grid.geometry(),
                scale=500,  # Ajustar a escala conforme necessário
                fileFormat='GeoTIFF',
                maxPixels=1e8
            )

            export_task.start()

# Chamar a função para adicionar camadas mensais e exportar
add_monthly_layers_and_export(2023, 1, 2023, 12)

# Carregar o grid do Brasil novamente
Map.addLayer(grid, {}, 'Brasil Grid')

# Exibir o mapa
Map