No abstract

Wildfire are increasingly frequent events on a planet undergoing climate change. With more favourable climate conditions for their occurrence, like prolonged periods of drought, the frequency and intensity of these catastrophes continue to increase. Protected areas are important territories for conserving ecosystems and biodiversity around the world and serve as a key management tool in national environmental policies. Many studies have been developed around the world to assess the conditions, frequency, and intensity of fires, and, on the other hand, protected areas are intensively studied to understand whether conservation actions are effective in keeping the ecosystem balanced. However, there are few studies that contemplate these two themes together. Consequently, this study offers a bibliometric analysis of the wildfires and its occurrence in protected areas, aiming to understand the spatial and temporal relation between them, characteristics of the research studies, and trending issues to be worked on. We used the Bibliometrix package in R language, which provides the option of different methods for analysing bibliometric data to understand the temporal evolution of the published documents about wildfires and protected areas. In total, 1116 publications were analysed, ranging from 1970 to 2022. The findings show that the terms “fires” (185 occurrences), “fire” (117), “wildfire” (101), and “forest fire” (92) are more frequently used and associated with studies on topics including biodiversity (304), conservation (221), environmental protection (188), deforestation (148), ecosystems (138), forestry (133), and climate change (126) as well as protected areas (399). The highest growth of research has been registered since 2002. The majority of the publications were published by authors from universities in the USA (77), South Africa (72), the United Kingdom (22), and Brazil (19). The USA leads all other countries with 7 of the top 10 international collaborations, followed by Brazil, Australia, and South Africa. However, only the United Kingdom continues to maintain an increased number of external (inter-country) collaborations, whereas the other nine continue to maintain an increased number of internal (intra-country). Considering the top 10 authors in terms of production, only 1 was active from 1999 to 2019, and the other 9 only have been active since 2009. The topics that stand out were subjected to a coupling analysis, which revealed that environmental protection is a motor theme, endangered species, Australia, and savannah are niche themes, and protected area, biodiversity, and fire management are basic themes.

Utilização do Land Change Modeler® na modelação prospetiva do uso e cobertura do solo na microrregião de Santos, Brasil para o ano de 2022 Land use and land cover model for the Santos microregion in 2022, Brazil, using the Land Change Modeler Referência: Folharini, Saulo; Oliveira, Regina (2020). Utilização do Land Change Modeler® na modelação prospetiva do uso e cobertura do solo na microrregião de Santos, Brasil para o ano de 2022. Revista de Geografia e Ordenamento do Território (GOT), n.º 19 (Junho). Centro de Estudos de Geografia e Ordenamento do Território, p. 57-73, dx.doi.org/10.17127/got/2020.19.003 RESUMO A análise da dinâmica de uso e cobertura do solo deve ser uma etapa fundamental nos procedimentos de ordenamento territorial. No presente estudo apresenta-se o resultado da aplicação de um processo de modelação prospetiva da ocupação do solo na microrregião de Santos (Brasil) tendo como horizonte temporal o ano de 2022. Os dados de referência utilizados no modelo dizem respeito a classificações da ocupação do solo para os anos de 2010 e 2016, elaboradas a partir de imagens de satélite LANDSAT 5 (TM) e 8 (OLI). A etapa de modelagem foi desenvolvida no Land Change Modeler do IDRISI®. Como resultados foram obtidos o mapeamento de tendência espacial de mudança indicando as principais alterações de uso e cobertura e onde elas se concentram espacialmente, além do mapeamento síntese de uso e cobertura do solo para 2022.

The study proposes a methodology to calculate the C-factor using remote sensing data: NDVI from LANDSAT image and MAPBIOMAS Land Use (LU) classification to Atibaia river watershed, Brazil, to improve the estimation of risk of soil loss using equations such as USLE and RUSLE. The methodology follows the procedures: first the NDVI was calculated, then the resulting image was rescaled to the range 0 to 1, applying the Near, Gaussian and Symmetric Linear transformation functions, with value below threshold 1, value above threshold 0 and scale 1 in the Rescale by function tool. Among the three models presented the Symmetric Linear model showed the best results for the distribution of C-factor values between the LU classes, while in the Gaussian model the same value was recorded, 0.70, for the Pasture and Rocky Outcrop classes and the average of the values was low 0.22 (Near) and 0.31 (Gaussian).