diff --git a/dbt_project.yml b/dbt_project.yml
index 01175af6..b893b960 100644
--- a/dbt_project.yml
+++ b/dbt_project.yml
@@ -156,7 +156,10 @@ models:
       +schema: br_inep_saeb
     br_inmet_bdmep:
       +materialized: table
-      +schema: br_inmet_bdmep     
+      +schema: br_inmet_bdmep
+    br_inpe_prodes:
+      +materialized: table
+      +schema: br_inpe_prodes
     br_jota:
       +materialized: table
       +schema: br_jota
diff --git a/models/br_inpe_prodes/br_inpe_prodes_desmatamento_municipio.sql b/models/br_inpe_prodes/br_inpe_prodes_desmatamento_municipio.sql
new file mode 100644
index 00000000..e0e5529d
--- /dev/null
+++ b/models/br_inpe_prodes/br_inpe_prodes_desmatamento_municipio.sql
@@ -0,0 +1,16 @@
+{{
+    config(
+        alias='desmatamento_municipio',
+        schema='br_inpe_prodes'
+    )
+}}
+SELECT
+SAFE_CAST(ano AS INT64) ano,
+SAFE_CAST(id_municipio AS STRING) id_municipio,
+SAFE_CAST(bioma AS STRING) bioma,
+SAFE_CAST(area AS INT64) area,
+SAFE_CAST(desmatamento AS FLOAT64) desmatamento,
+SAFE_CAST(floresta AS FLOAT64) floresta,
+SAFE_CAST(nao_floresta AS FLOAT64) nao_floresta,
+SAFE_CAST(hidrografia AS FLOAT64) hidrografia
+FROM basedosdados-staging.br_inpe_prodes_staging.desmatamento_municipio AS t
diff --git a/models/br_inpe_prodes/code/clean_data.py b/models/br_inpe_prodes/code/clean_data.py
new file mode 100644
index 00000000..1ac01ffc
--- /dev/null
+++ b/models/br_inpe_prodes/code/clean_data.py
@@ -0,0 +1,35 @@
+import os
+import pandas as pd
+
+
+def gerar_individual_table(file_name: str):
+    df = pd.read_csv(file_name, encoding="ISO-8859-1")
+    file_name = file_name.split("/")[-1]
+    file_name = file_name[:-4]
+    bioma, year = file_name.split("_")
+    df["bioma"] = bioma
+    df["ano"] = int(year)
+    df["desmatamento"] = (df[df.columns[7:-5]].sum(axis=1)).round(1)
+    df = df[df.columns[[4, 6]].to_list() + df.columns[-6:].to_list()]
+
+    columns_order = ['ano', 'CodIbge', 'bioma', 'AreaKm2', 'desmatamento'] + df.columns[2:5].to_list()
+    df = df[columns_order]
+
+    columns_name = ['ano', 'id_municipio', 'bioma', 'area', 'desmatamento', 'floresta', 'nao_floresta', 'hidrografia']
+    df.columns = columns_name
+
+    df["floresta"] = (df['area'].values - df[['desmatamento', 'nao_floresta', 'hidrografia']].sum(axis=1)).round(1)
+
+    return df
+
+
+def get_clean_data() -> None:
+
+    files = os.listdir(os.getcwd().replace("code", "input"))
+    files = [f"../input/{file}" for file in files]
+    df = pd.concat(map(gerar_individual_table, files))
+    df.to_csv("../output/br_inpe_prodes_desmatamento.csv", index=False)
+
+
+if __name__ == "__main__":
+    get_clean_data()
diff --git a/models/br_inpe_prodes/code/download_data.py b/models/br_inpe_prodes/code/download_data.py
new file mode 100644
index 00000000..1c037991
--- /dev/null
+++ b/models/br_inpe_prodes/code/download_data.py
@@ -0,0 +1,47 @@
+import requests
+import concurrent.futures
+from itertools import product
+
+
+class DownloaderBrInpeProdes:
+
+    def __init__(self, year: int):
+        self.year = year
+        url_base = f"http://www.dpi.inpe.br/prodesdigital/tabelatxt.php?ano={self.year}"
+        self.biomas_urls = {
+            "Amazônia": f"{url_base}&estado=&bioma=Amaz%C3%B4nia&ordem=municipio&type=tabela&output=txt&",
+            "Caatinga": f"{url_base}&estado=&bioma=Caatinga&ordem=municipio&type=tabela&output=txt&",
+            "Cerrado": f"{url_base}&estado=&bioma=Cerrado&ordem=municipio&type=tabela&output=txt&",
+            "Mata Atlântica": f"{url_base}&estado=&bioma=Mata%20Atl%C3%A2ntica&ordem=municipio&type=tabela&output=txt&",
+            "Pampa": f"{url_base}&estado=&bioma=Pampa&ordem=municipio&type=tabela&output=txt&",
+            "Pantanal": f"{url_base}&estado=&bioma=Pantanal&ordem=municipio&type=tabela&output=txt&"
+        }
+
+    def url(self, bioma: str) -> str:
+        return self.biomas_urls[bioma]
+
+    def download_data(self, bioma: str, format="csv") -> None:
+        url = self.url(bioma)
+        response = requests.get(url)
+        response.raise_for_status()
+
+        with open(f"../input/{bioma}_{self.year}.{format}", "w") as f:
+            content_as_string = response.content.decode()
+            f.write(content_as_string)
+
+        print(f"Successfully downloaded for bioma {bioma} year {self.year}")
+
+
+def start_downloader(info: tuple) -> None:
+    DownloaderBrInpeProdes(info[0]).download_data(info[1])
+
+
+def download_all_biomas_data() -> None:
+    years = range(2000, 2023)
+    biomas_names = ['Amazônia', 'Caatinga', 'Cerrado', 'Mata Atlântica', 'Pampa', 'Pantanal']
+    with concurrent.futures.ThreadPoolExecutor() as executor:
+        executor.map(start_downloader, product(years, biomas_names))
+
+
+if __name__ == "__main__":
+    download_all_biomas_data()
diff --git a/models/br_inpe_prodes/schema.yaml b/models/br_inpe_prodes/schema.yaml
new file mode 100644
index 00000000..494e9d74
--- /dev/null
+++ b/models/br_inpe_prodes/schema.yaml
@@ -0,0 +1,22 @@
+version: 2
+
+models:
+  - name: desmatamento_municipio
+    description: Apresenta o desmatamento dos municipios e outras variáveis na Amazônia Legal a partir do ano 2000
+    columns:
+      - name: ano
+        description: Ano
+      - name: id_municipio
+        description: ID Município - IBGE 7 Dígitos
+      - name: bioma
+        description: Bioma
+      - name: area
+        description: Área
+      - name: desmatamento
+        description: Área Desmatada Total
+      - name: floresta
+        description: Área de Floresta
+      - name: nao_floresta
+        description: Área de Não-Floresta
+      - name: hidrografia
+        description: Área de Hidrografia