Dynamics of land use in a rural settlement in the Brazilian Legal Amazon

Miqueias Lima Duarte; Jocy Ana Paixão de Sousa; Amazonino Lemos de Castro; Roberto Wagner Lourenço

doi:10.5327/Z217694781005

Authors

Miqueias Lima Duarte Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP) - Brazil https://orcid.org/0000-0001-8232-4655
Jocy Ana Paixão de Sousa Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP) - Brazil https://orcid.org/0000-0003-0937-786X
Amazonino Lemos de Castro Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP) - Brazil https://orcid.org/0000-0002-0065-6144
Roberto Wagner Lourenço Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP) - Brazil https://orcid.org/0000-0002-5234-8944

DOI:

https://doi.org/10.5327/Z217694781005

Keywords:

Amazon biome; agrarian reform; deforestation; CAMarkov model.

Abstract

Deforestation in the Amazon has reached alarming numbers in recent decades. The main factors causing this issue are not only large and medium-sized farmers, land grabbing, and illegal mining but also agrarian reform settlements, which may be contributing to the increase in deforestation rates. In this context, this study aims to evaluate the dynamics of land use in the rural settlement Santo Antônio do Matupi, located in the south of the State of Amazonas. This time-series study analyzed changes in land use and land cover from 1992 to 2018 using supervised classification techniques. In this scenario, simulations were carried out of the dynamics of land use for the period between 2028 and 2038 using the cellular automaton method of Markov (CA-MARKOV). The results show that, in the studied period, the greatest losses were in primary forests and that the most critical period of deforestation rates recorded was from 2004 to 2018 when 63.28% of the area was converted into pastures. Future scenarios based on the period studied indicate losses of up to 5.26% of areas occupied by forests by 2028, and a further 5.60% by 2038, exceeding 80% of the total area deforested in the settlement. This study demonstrates that the current model of land use and occupation practiced in the settlement is unsustainable and that future scenarios are worrying. This situation highlights a need to effectively implement programs that aim a sustainable rural development in the settlement, in addition to monitoring and controlling deforestation, designed for current managers and other sectors of the society concerned with the conservation and preservation of forests.

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References

Ávila, S.R.S.A.; Ávila, M.; Bernardi, J.V.E.; Couto Júnior, A.F., 2019. Estudo exploratório sobre dinâmica do desmatamento em assentamentos localizados no território portal da Amazônia. Retratos de Assentamentos, v. 22, (1), 139-152. http://dx.doi.org/10.25059/2527-2594/retratosdeassentamentos/2019.v22i1.330.

Brasil. 1985. Presidência da República. Decreto nº 91.766, de 10 de outubro de 1985. Aprova o Plano Nacional de Reforma Agrária, e dá outras providências (Accessed January 2, 2019) at: http://www.planalto.gov.br/ccivil_03/Atos/decretos/1985/D91766.html.

Brasil. 2012. Lei 12.651 de 25 de maio de 2012. Dispõe sobre a proteção da vegetação nativa. Congresso Nacional (Accessed February 18, 2021) at: http://www.jusbrasil.com.br/legislacao/1032082/lei-12651-12.

Brasil. 2018. Instituto Nacional de Pesquisas Espaciais. Monitoramento do Desmatamento da Floresta Amazônica Brasileira por Satélite (Accessed November 5, 2020) at: http://www.obt.inpe.br/OBT/assuntos/programas/amazonia/prodes.

Brasil. 2020a. Instituto Nacional de Colonização e Reforma Agrária. Incra nos Estados - Informações gerais sobre os assentamentos da Reforma Agrária (Accessed November 12, 2020) at: https://painel.incra.gov.br/sistemas/index.php.

Brasil. 2020b. Ministério do Meio Ambiente. Plano de ação para a prevenção e controle do desmatamento na Amazônia Legal (Accessed November 8, 2020) at: http://www.mma.gov.br.

Carvalho, T.S.; Domingues, E.P., 2016. Projeção de um cenário econômico e de desmatamento para a Amazônia Legal brasileira entre 2006 e 2030. Nova Economia, v. 26, (2), 585-621. http://dx.doi.org/10.1590/0103-6351/2665.

Congedo, L., 2018. Semi-Automatic Classification Plugin Documentation (Accessed December 12, 2019) at: https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html.

Congilio, C.R.; Moraes, C.S., 2016. Violência agrária e desmatamento: corolários das políticas de Estado e das lutas sociais no sudeste paraense. Lutas Sociais, v. 20, (37), 155-167. 2016.

Dick, G.; Schumacher, M.V., 2015. Relações entre solo e fitofisionomias em florestas naturais. Ecologia e Nutrição Florestal, v. 3, (2), 31-39. http://dx.doi.org/10.5902/2316980X16741.

Duarte, M.L.; Brito, W.B.M.; Silva, T.A.; Casto, A.L., 2020. Padrões e causas do desmatamento no Baixo Acre, região oeste da Amazônia brasileira. Journal of Environmental Analysis and Progress, v. 5, (1), 117-127. https://doi.org/10.24221/jeap.5.1.2020.2790.117-127.

Duarte, M.L.; Silva, T.A., 2019. Avaliação do desempenho de três algoritmos na classificação de uso do solo a partir de geotecnologias gratuitas. Revista de Estudos Ambientais, v. 21, (1), 6-16. http://dx.doi.org/10.7867/1983-1501.2019v21n1p6-16.

Farias, M.H.C.S.; Beltrão, N.E.S.; Cordeiro, Y.E.M.; Santos, C.A., 2018. Impactos dos assentamentos rurais no desmatamento da Amazônia. Mercator, v. 17, 1-20. http://dx.doi.org/10.4215/rm2018.e17009.

Fearnside, P.M., 2017. Deforestation of the Brazilian Amazon. Environmental Science. https://doi.org/10.1093/acrefore/9780199389414.013.102.

Firozjaei, M.K.; Sedighi, A.; Argany, M.; Jelokhani-Niaraki, Arsanjani, J.J., 2019. A geographical direction-based approach for capturing the local variation of urban expansion in the application of CA-Markov model. Cities, v. 93, 120-135. https://doi.org/10.1016/j.cities.2019.05.001.

Fiumi, L.; Congedo, L.; Meoni, C., 2014. Developing expeditious methodology for mapping asbestos-cement roof coverings over the territory of Lazio Region. Applied Geomatics, v. 6, (1), 37-48. https://doi.org/10.1007/s12518-014-0124-1.

Food and Agriculture Organization – FAO. 2017. FAOSTAT Statistical database (Accessed November 1, 2019) at: http://www.fao.org/faostat/en/#data.

Hasan, S.; Shi, W.; Zhu, X.; Abbas, S.; Khan, H.U.A., 2020. Future simulation of land use changes in rapidly urbanizing south China based on land change modeler and remote sensing data. Sustainability, v. 12, (11), 4350. https://doi.org/10.3390/su12114350.

Instituto Brasileiro de Geografia e Estatística – IBGE. 2020. Dados por cidade (Accessed August 12, 2020) at: https://cidades.ibge.gov.br/brasil/am/manicore/panorama.

Instituto de Conservação e Desenvolvimento Sustentável da Amazônia – IDESAM. 2016. Matupi ganha primeira área de pecuária sustentável. IDESAM, Manaus (Accessed February 22, 2021) at: https://idesam.org/conteudo/em-campo/matupi-ganha-primeira-area-de-pecuaria-sustentavel/.

Landis, J.; Koch, G.G., 1977. The measurements of agreement for categorical data. Biometrics, v. 33, (1), 159-179.

Leal, M.L.M.; Silva, V.V.; Furlan, J.Â.; Souza, A.L., 2017. Uso da terra e a legislação florestal no projeto de assentamento Matupi, AM. Boletim de Geografia, v. 35, (1), 122-133. http://dx.doi.org/10.4025/bolgeogr.v35i1.31897.

Leroux, L.; Congedo, L.; Bellón, B.; Gaetano, R.; Bégué, A., 2018. Land Cover Mapping Using Sentinel‐2 Images and the Semi‐Automatic Classification Plugin: A Northern Burkina Faso Case Study. In: BAGHDADI et al. QGIS and Applications in Agriculture and Forest, v. 2, 119-151. https://doi.org/10.1002/9781119457107.ch4.

Ma, Z.; Redmond, R.L., 1995. Tau coefficients for accuracy assessment of classification of remote sensing data. Photogrammetric Engineering and Remote Sensing, v. 61, (4), 435-439.

Mello, N.G.R.; Artaxo, P., 2017. Evolução do Plano de Ação para Prevenção e Controle do Desmatamento na Amazônia Legal. Revista do Instituto de Estudo Brasileiros, (66), 108-126. http://dx.doi.org/10.11606/issn.2316-901x.v0i66p108-129.

Moutinho, P.; Guerra, R.; Azevedo-Ramos, C. 2016. Achieving zero deforestation in the Brazilian Amazon: What is missing? Elementa: Science of the Anthropocene, v. 4, 000125. https://doi.org/10.12952/journal.elementa.000125.

Munthali, M.G.; Mustak, S.; Adeola, A.; Botai, J.; Singh, K.; Davis, N., 2020. Modelling land use and land cover dynamics of Dedza district of Malawi using hybrid Cellular Automata and Markov model. Remote Sensing Applications: Society and Environment, v. 17, 100276. https://doi.org/10.1016/j.rsase.2019.100276.

Olmedo, M.T.C.; Pontius Jr., R.G.; Paegelow, M.; Mas, J.F., 2015. Comparison of simulation models in terms of quantity and allocation of land change. Environmental Modelling & Software, v. 69, 214-221. https://doi.org/10.1016/j.envsoft.2015.03.003.

OSGEO - QGIS Development Team. 2019. QGIS Geographic Information System. Open Source Geospatial Foundation Project (Accessed September 8, 2019) at: http://qgis.osgeo.org.

Rossoni, R.A.; Moraes, M.L., 2020. Agropecuária e desmatamento na Amazônia Legal Brasileira: uma análise espacial entre 2007 e 2017. Geografia em Questão, v. 13, (3), 130-148. https://doi.org/10.48075/geoq.v13i3.23536

Silva, V.V.; Vettorazzi, C.A.; Padovani, C.R., 2011. Assentamento rural e a dinâmica da paisagem. In: XV Simpósio Brasileiro de Sensoriamento Remoto, Curitiba. Anais... INPE, São José dos Campos, pp. 7000-7006.

Souza, A.L.; Silva, V.V.; Schweickardt, K.H.S.; Lucas, M., 2018. Fatores socioeconômicos e ambientais do assentamento Matupi, Manicoré, Amazonas. In: V Seminário Internacional em Ciência do Ambiente e Sustentabilidade na Amazônia. Manaus, pp. 1-11.

Souza, A.L.; Silva, V.V.; Schweickard, K.H.S.; Melo, P.R.U.; Lanua, L., 2019. Questões sociais, econômicas e ambientais em uma área de reforma agrária: projeto de assentamento Matupi. Terceira Margem Amazônia, v. 5, (13), 129-143. https://doi.org/10.36882/2525-4812.2019v5i13p%25p.

Thaler, G.M.; Viana, C.; Toni, F., 2019. From frontier governance to governance frontier: The political geography of Brazil’s Amazon transition. World Development, v. 114, 59-72. https://doi.org/10.1016/j.worlddev.2018.09.022.

Thomaz, E.L.; Nunes, D.D.; Watanabe, M., 2020. Effects of tropical forest conversion on soil and aquatic systems in southwestern Brazilian Amazonia: A synthesis. Environmental Research, v. 183, 109220. https://doi.org/10.1016/j.envres.2020.109220.

Tollefson, J., 2018. Desflorestation ticks up in Brazil’s savannah. Nature. http://dx.doi.org/10.1038/d41586-018-05695-9.

United States Geological Survey – USGS. 2019 (Accessed Nomveber 2, 2019) at: https://earthexplorer.usgs.gov.

Walker, N.F.; Patel, S.A.; Kemel, A.B.K., 2013. From Amazon Pasture to the High Street: Deforestation and the Brazilian Cattle Product Supply Chain. Tropical Conservation Science, v. 6, (3), 446-467. https://doi.org/10.1177/194008291300600309.