Estudo do uso da terra na bacia hidrográfica do Rio Sorocabuçu, Ibiúna – SP para avaliação de áreas elegíveis em projetos MDL
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Data
2023-02-23
Autores
Toledo, Mayra Vannessa Lizcano
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Universidade Estadual Paulista (Unesp)
Resumo
O crescimento da população ao longo dos anos tem levado a um maior consumo dos recursos naturais para garantir uma boa qualidade de vida, entretanto, tem gerado impactos negativos ao ambiente, especialmente nas florestas, as quais fornecem diversos serviços ambientais fundamentais e necessários para garantir a vida no planeta como, por exemplo, a captura de dióxido de carbono que contribui para atenuar os efeitos da mudança climática. Portanto, o reflorestamento permite garantir a sustentabilidade dos serviços ambientais proporcionados pelas florestas, além da qualidade de vida para as gerações futuras. É importante que os projetos destinados a recuperação e expansão daquela cobertura vegetal sejam desenvolvidos em áreas estratégicas que garantam o investimento realizado. Neste sentido, o objetivo deste estudo foi identificar e avaliar áreas com ausência de atividade econômica que apresentassem potencial para o desenvolvimento de projetos que contribuam ao Mecanismo de Desenvolvimento Limpo (MDL). Para o desenvolvimento deste estudo foi selecionada a bacia hidrográfica do Rio Sorocabuçu, a qual se encontra inserida na Área de Proteção Ambiental (APA) de Itupararanga. A metodologia utilizada consistiu na elaboração de mapas temáticos de uso da terra a partir de imagens do satélite Landsat 5 TM e Landsat 8 OLI para os anos 2000 e 2020, respetivamente; onde a classificação das imagens se deram pelo uso redes neurais artificiais do tipo Multilayer Perceptrón (MLP), além disso, foi realizado o cálculo e análise temporal do estado da vegetação através do Índice de Vegetação por Diferença Normalizada (NDVI). Finalmente, utilizou-se ferramenta Land Change Modeler (LCM) para analisar as mudanças ocorridas no período estudado e calculado o potencial de transição e a identificação e elaboração de um mapa temático das áreas viáveis para o desenvolvimento de projetos que contribuam com o MDL. Foi identificada uma elevada perda de áreas de vegetação natural entre os anos 2000 e 2020, bem como uma expansão das áreas antrópicas, tanto agrícolas quanto não agrícolas; por outra parte, o NDVI calculado mostrou que não há áreas com vegetação saudáveis e que as áreas com maior saúde vegetal estão, principalmente, em áreas com maior declividade. Por fim foi determinado que 1,38% da área de estudo apresenta áreas com alta elegibilidade para implementação de projetos que contribuam com o MDL.
The population growth over the years has led to greater consumption of natural resources to ensure a good quality of life. However, this has had negative impacts on the environment, especially in forests, which provide various fundamental environmental services necessary for life on the planet, such as the capture of carbon dioxide, which helps mitigate the effects of climate change. Therefore, reforestation allows for the sustainability of the environmental services provided by forests, as well as the quality of life for future generations. It is important that projects aimed at recovering and expanding forest cover be developed in strategic areas that ensure the investment made. In this sense, the objective of this study was to identify and evaluate areas with no economic activity that presented potential for the development of projects that contribute to the Clean Development Mechanism (CDM). For the development of this study, the Sorocabuçu River watershed was selected, which is located in the Itupararanga Environmental Protection Area (APA). The methodology used consisted of the preparation of thematic maps of land use based on Landsat 5 TM and Landsat 8 OLI satellite images for the years 2000 and 2020, respectively. The classification of the images was carried out using Multilayer Perceptron (MLP) artificial neural networks. In addition, the calculation and temporal analysis of vegetation status was performed using the Normalized Difference Vegetation Index (NDVI). Finally, the Land Change Modeler (LCM) tool was used to analyze the changes that occurred during the study period, calculate the transition potential, and identify and prepare a thematic map of viable areas for the development of projects that contribute to the CDM. A high loss of natural vegetation areas was identified between 2000 and 2020, as well as an expansion of anthropogenic areas, both agricultural and non-agricultural. The calculated NDVI showed that there are no areas with healthy vegetation and that the areas with the healthiest vegetation are mainly in areas with steeper slopes. Finally, it was determined that 1.38% of the study area presents areas with high eligibility for the implementation of projects that contribute to the CDM.
The population growth over the years has led to greater consumption of natural resources to ensure a good quality of life. However, this has had negative impacts on the environment, especially in forests, which provide various fundamental environmental services necessary for life on the planet, such as the capture of carbon dioxide, which helps mitigate the effects of climate change. Therefore, reforestation allows for the sustainability of the environmental services provided by forests, as well as the quality of life for future generations. It is important that projects aimed at recovering and expanding forest cover be developed in strategic areas that ensure the investment made. In this sense, the objective of this study was to identify and evaluate areas with no economic activity that presented potential for the development of projects that contribute to the Clean Development Mechanism (CDM). For the development of this study, the Sorocabuçu River watershed was selected, which is located in the Itupararanga Environmental Protection Area (APA). The methodology used consisted of the preparation of thematic maps of land use based on Landsat 5 TM and Landsat 8 OLI satellite images for the years 2000 and 2020, respectively. The classification of the images was carried out using Multilayer Perceptron (MLP) artificial neural networks. In addition, the calculation and temporal analysis of vegetation status was performed using the Normalized Difference Vegetation Index (NDVI). Finally, the Land Change Modeler (LCM) tool was used to analyze the changes that occurred during the study period, calculate the transition potential, and identify and prepare a thematic map of viable areas for the development of projects that contribute to the CDM. A high loss of natural vegetation areas was identified between 2000 and 2020, as well as an expansion of anthropogenic areas, both agricultural and non-agricultural. The calculated NDVI showed that there are no areas with healthy vegetation and that the areas with the healthiest vegetation are mainly in areas with steeper slopes. Finally, it was determined that 1.38% of the study area presents areas with high eligibility for the implementation of projects that contribute to the CDM.
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Palavras-chave
Geoprocessamento, Mata Atlântica Conservação, Modelagem, Índice de Vegetação por Diferença Normalizada, Geoprocessing, Index Normalized Difference Vegetation, Modeling