Modelagem Dinâmica Espacial Como Ferramenta Para Simulação De Cenários Da Paisagem Na Região Portuária Da Baixada Santista

Kawashima, Renata Sayuri; Giannotti, Mariana Abrantes; Almeida, Cláudia Maria de; Quintanilha, José Alberto

doi:10.1590/s1982-21702016000400040

Cited by 5 publications

(3 citation statements)

References 11 publications

(8 reference statements)

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“…According to Kawashima et al (2016), scenarios are alternative images of the future that help decisionmaking processes, as well as outline political-economic, socio-demographic, legal, institutional, environmental and technological conjectures, among others, that enable viewing multiple future deforestation trajectories.…”

Section: Th Stage: Creating and Simulating The Scenariomentioning

confidence: 99%

Tendential Modeling of Deforestation in Caatinga Biome in Piauí State

Santos

Juvanhol

Aguiar³

2022

RCG

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The work aims to simulate the dynamics of deforestation in the area that covers the caatinga biome in the state of Piauí for the next five decades. In the simulation, the program Dinamica EGO was used. Were acquired deforestation data for 2002 and 2008 and spatial data of the explanatory variables of deforestation in the area. Five steps were performed: calculating the transition matrices, determining the weights of evidence, adjusting, validating and projecting the model in the trend scenario. Transition rates for total and annual deforestation resulted in 4.6% and 0.8%, respectively. The weights of evidence revealed that distances up to 600 m from deforested areas influence in the process of transition to deforestation. The variables with the highest weights were altitude, up to 100 meters; areas closer to urban patch and sustainable use units, in addition to land use and cover classes: urban influence, agriculture, livestock. With the simulated images it was observed a reduction of the forest remnants of caatinga area in the state, from 69% in 2008 to 43% in 2070. These results serve as a warning to the public authorities and the population. The proposed methodology can be applied to other Brazilian biomes with different approaches.

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Section: Th Stage: Creating and Simulating The Scenariomentioning

confidence: 99%

Tendential Modeling of Deforestation in Caatinga Biome in Piauí State

Santos

Juvanhol

Aguiar³

2022

RCG

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“…In addition to the intense urban occupation, the beaches of the river Pará are in an area of a greater influence of port facilities, which (MOSBAHI et al, 2019). Physical facilities, such as support and mooring structures, and pipelines, can alter local hydrodynamic patterns and sediment characteristics, which can include a decrease in local sedimentation (KAWASHIMA et al, 2016). Besides that, contamination of the environment can occur due to oil and fuel leaks from vessels or loss of materials (organic and inorganic) during loading and unloading these vessels (MOREIRA et al, 2019).…”

Section: Variation Sourcementioning

confidence: 99%

Benthic macroinvertebrates as bioindicators of environmental quality of Pará River estuary, a wetland of Eastern Amazon

Pinto

Tavares

Pinheiro

et al. 2020

Rev. Bras. Ciênc. Ambient. (Online)

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The study characterized and evaluated the use of the benthic macroinvertebrate community as an indicator of impacts in different estuarine environments around the Industrial Port Complex (IPC) of Vila do Conde (Pará State, Amazon region). Fauna of beaches and rivers, in sectors of the estuary under different degrees of environmental impact (high, medium, and low), was compared in different seasonal periods. Macrofauna was composed of typically fresh-water and estuarine groups. Beaches presented sediment with a texture ranging from medium to coarse sand, with a less rich macrofauna ( = 4.5 ± SE 0.3 taxa/sample) and dense ( = 1,838.1 ± 164.8 ind./m2) of organisms when compared to rivers ( = 5.9 ± 0.3 taxa/sample, and 3,248.9 ± 77.0 ind./m2), which were environments more muddy. For both environments, sites in the high-impact sector were less rich ( = 4.7 ± 0.3 taxa/sample) and dense ( = 2,812.9 ± 232.7 ind./m2) when compared to those in the low-impact sector ( = 7.6 ± 0.4 taxa/sample, and 3,314.3 ± 230.1 ind./m2). Richness ( = 6.4 ± 0.3 taxa/sample) and density ( = 3,859.4 ± 190.2 ind./m2) were higher in the rainier season when compared to the less rainy season ( = 4.8 ± 0.3 taxa/sample, and 1,933.0 ± 172.1 ind./m2). However, there were no significant seasonal changes in composition. Results indicated that the structure of the benthic macroinvertebrate community surrounding the IPC responds to the loss of environmental quality, with extreme effects of a drop in abundance and diversity. Taxa that are more tolerant (Namalycastis caetensis, Cirolana sp., Pseudosphaeroma sp., Tubificidae, and Chironomidae) and sensitive (Hydropsychidae and Eteone sp.) to impact conditions were identified and evaluated as potential bioindicators.

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“…The coastal regions can be considered one of the most threatened areas on the planet, because they are constantly undergoing anthropic transformations and used for natural resources (MELO, 2014). Approximately two thirds of the world's population live in these regions, where the main metropolises are established (KAWASHIMA et al, 2016). Coastal zones, including mangroves, are important areas of transition between terrestrial and marine environments that have significant social, environmental and ecological importance, providing fundamental environmental services (KRUG, LEÃO AND AMARAL, 2007;SOUZA, et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Evolution of Environmental Dynamics in Guaratiba State Biological Reserve and Its Surroundings, Rio De Janeiro, Brazil

Santos

Vargas²,

Carvalho³

et al. 2022

RCG

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Mangrove is a coastal ecosystem that suffers from the growth of urban areas. We aim to study the environmental dynamics of the State Biological Reserve of Guaratiba-RJ and its surroundings, between 1990 and 2019, when there was great development in the region. Landsat images from 1990 and 2019, orthophotos from the Brazilian Institute of Geography and Statistics (IBGE), and field research were used. The methodology used the Normalized Difference Vegetation Index (NDVI), Normalized Difference Index on Built-up Areas (NDBI), and the Anthropic Transformation Index (ITA). The results showed that the mangrove area that was 16.07 km² in 1990 increased to 19.95 km² in 2019, the hypersaline areas went from 10.49 km² in 1990 to 7.08 km², and the built-up areas from 9.40 km² in 1990 to 24.73 km² in 2019. Variations occurred between mangrove areas (24.14%) and hypersaline areas (-32.51%), where there was migration of mangrove to these areas. The ITA was 4.13 in 1990 and 4.15 in 2019, varying 0.02, classified as Low Degraded. Geotechnologies showed good results in monitoring the reserve. The study showed the importance of the protection area, which mainly enabled the growth of the mangrove area and creation of barrier for built-up areas.

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Modelagem Dinâmica Espacial Como Ferramenta Para Simulação De Cenários Da Paisagem Na Região Portuária Da Baixada Santista

Cited by 5 publications

References 11 publications

Tendential Modeling of Deforestation in Caatinga Biome in Piauí State

Tendential Modeling of Deforestation in Caatinga Biome in Piauí State

Benthic macroinvertebrates as bioindicators of environmental quality of Pará River estuary, a wetland of Eastern Amazon

Spatio-Temporal Evolution of Environmental Dynamics in Guaratiba State Biological Reserve and Its Surroundings, Rio De Janeiro, Brazil

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