{"id":38825,"date":"2025-04-20T00:48:11","date_gmt":"2025-04-20T04:48:11","guid":{"rendered":"https:\/\/studentwork.prattsi.org\/infovis\/?p=38825"},"modified":"2025-04-20T00:48:14","modified_gmt":"2025-04-20T04:48:14","slug":"deforestation-and-wildfires-in-the-brazilian-amazon-forestnatural-and-anthropic-land-use-in-the-past-four-decades","status":"publish","type":"post","link":"https:\/\/studentwork.prattsi.org\/infovis\/visualization\/deforestation-and-wildfires-in-the-brazilian-amazon-forestnatural-and-anthropic-land-use-in-the-past-four-decades\/","title":{"rendered":"Deforestation and wildfires in the Brazilian Amazon Forest:Natural and anthropic land use in the past four decades<\/strong>"},"content":{"rendered":"\n

Context<\/strong><\/h2>\n\n\n\n

The Amazon Forest is one of the largest ecosystems on Earth, spanning an area of about 2.7 million square miles, of which 2.3 million square miles are rainforest. Its boundaries encompass nine Latin American countries and approximately 3,000 indigenous territories. The majority of the land lies in Brazil, which accounts for 60% of the territory. However, despite the forest\u2019s crucial role in mitigating global climate change, its area has been significantly deforested since the 1970s, at the risk of irreversible environmental damage.<\/p>\n\n\n\n

The map focuses on the Brazilian portion of the Amazon rainforest. It aims to visually showcase the deforestation rate, the expansion of anthropic lands\u2014including urban areas and agriculture\u2014and regions burned by wildfires over the past 40 years, documented in five-year increments. The data and subsequent analysis are presented in a chronological series of maps, creating a timeline that overlays the three variables.<\/p>\n\n\n\n

Data<\/strong><\/h2>\n\n\n\n
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Screenshot of Mato Grosso, Brazil, from MapBiomas platform<\/figcaption><\/figure>\n\n\n\n

The primary sources of data on Amazon’s environmental issues include official governmental agencies, international cooperation groups, and independent non-profit institutions. There are two main formats of data: numerical, either as absolute information or incremental proportions, and satellite imagery. The map was designed using tabular (text-based) data and optimized for visualization in Tableau. Furthermore, because the images show the precise location of land types, the information is spatially dispersed (shown above), not aggregated, making proportion comparisons difficult.<\/p>\n\n\n\n

The datasets identified with the most relevant information were sourced from IBGE<\/a> \u2014Brazil’s national statistical institute\u2014 and MapBiomas<\/a>, an organization that unites NGOs, universities, and startups to monitor environmental changes through spatial analysis using satellite-based technology systems. Other considered data sources included the independent organization Global Forest Watch,<\/a> RAISG<\/a>, the Amazon Geo-Referenced Socio-Environmental Information Network, and NASA<\/a>.<\/p>\n\n\n\n

Although considerable data is available regarding Amazon\u2019s transformation over the years, the challenge has been finding information at the municipal level. There are nine states within the legal Amazon limits, each exhibiting distinct patterns of land use. Thus, the state-level analysis proved insufficient for understanding localized patterns. In addition, the aim was to find data from as far back as possible, dating to the 1970s, which is considered the beginning of deforestation, characterized by the inauguration of the Trans Amazonian Highway\u2019s first section (e.g., Laurance<\/a>, Patowari<\/a>). MapBiomas has provided a great deal of information since 1985, and it is documented annually.<\/p>\n\n\n\n

In addition, there were essentially two ways to measure wildfires, by area and by frequency. The decision was made to focus on area, facilitating easier comparisons with the other two datasets, the natural and anthropic regions. Lastly, the data chosen for analysis was derived from tabular information<\/a> and wasn\u2019t managed or aggregated at any level. The solution was to use Python to create a spreadsheet<\/a> for data cleaning.<\/p>\n\n\n\n

The Map<\/strong><\/h2>\n\n\n\n
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The resulting map is a chronological series that can be navigated by the years 1985, 1995, 2005, 2015, and 2022 (the last year with data). Each municipality is colored with a green gradient to indicate the extent of natural vegetation. Areas affected by wildfires are represented as pink translucent circles. The challenge was to overlay the variables, demonstrating a visual correlation without hindering one another.<\/p>\n\n\n\n

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User Impressions<\/strong><\/h2>\n\n\n\n
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Two users \u2014one North American and one Brazilian\u2014 were invited to provide feedback on several versions of the map. The first user made observations about the square shapes, which suggest population density data, while the circles are more likely connected to forest fires. Also, the pink color created a more harmonious combination with the dark green than the orange or yellow, yet it remained related to fires. Moreover, she favored the option with an outlined circle representing anthropic land, which could result in a more visually appealing map and not as busy. <\/p>\n\n\n\n

The second user agreed with some of the first user’s points but disagreed about the square observation. He believes it\u2019s a better way to compare two areas. He also enjoyed the proposal to add anthropic land to the map. However, he was more concerned about having too much information overlaid in different ways of representation at the same time. It was suggested to eliminate the gradient of green in the name to keep the information represented in shapes only. \u201cNot having green in a forest map is a deal breaker,\u201d was the answer. He then suggested varying the color between the outlined circumference and the solid one.<\/p>\n\n\n\n

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Next Steps<\/strong><\/h2>\n\n\n\n
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Taking all the considerations into account, a potential solution would be to create separate maps at different scales: one for a general overview of the Brazilian Amazon and another detailed map focusing on anthropic areas and land use breakdowns. This way, a map of the entire Brazilian Amazon showcases only the wildfires by municipality, overlaid by a gradient of green. The second map could focus on a strategically notorious location, such as the states of Mato Grosso or Par\u00e1, to produce a larger-scale representation. Information about the anthropic area and its proportion of farming lands can be added to this map in a color distinct from the wildfire boundaries, also overlaid by a gradient of lighter green.<\/p>\n\n\n\n

In addition, to provide a more tangible understanding of the impact of a wildfire, several charts illustrating the spatial data shown in the maps could be added as supportive information. Moreover, in conjunction with the maps and secondary charts, the study could benefit from incorporating a timeline of significant political milestones, which could enrich the analysis.<\/p>\n\n\n\n

The final product will be presented in an interactive map, visually showing the changes in the ground patterns over the past four decades. It will be necessary to design the overlayer representation and determine how to control such comparisons.<\/p>\n\n\n\n

References<\/strong><\/h2>\n\n\n\n

Articles and Web Pages<\/strong><\/h4>\n\n\n\n

Our World in Data. \u201cCutting Down Forests: What Are the Drivers of Deforestation?\u201d Our World in Data<\/em>. Accessed April 20, 2025. https:\/\/ourworldindata.org\/drivers-of-deforestation#cutting-down-forests-what-are-the-drivers-of-deforestation.<\/p>\n\n\n\n

Daley, Jim, and Andrea Thompson. \u201cDeforestation Intensifies Warming in the Amazon Rain Forest.\u201d Scientific American<\/em>, 2019. https:\/\/www.scientificamerican.com\/article\/deforestation-intensifies-warming-in-the-amazon-rain-forest1\/.<\/p>\n\n\n\n

InfoAmazonia. \u201cDeforestation in the Amazon: Past, Present, and Future.\u201d InfoAmazonia<\/em>, March 21, 2023. https:\/\/infoamazonia.org\/en\/2023\/03\/21\/deforestation-in-the-amazon-past-present-and-future\/.<\/p>\n\n\n\n

Xu, Yue, Daniel B. Wright, and D. Luke Urban. \u201cIdentifying Predictors of Forest Loss in the Contiguous United States.\u201d Environmental Research Letters 17,<\/em> no. 3 (2022): 034037. https:\/\/doi.org\/10.1088\/1748-9326\/ac4df9.<\/p>\n\n\n\n

Data Sets<\/strong><\/h4>\n\n\n\n

Dados.gov.br. \u201cPortal de Dados Abertos.\u201d Accessed April 20, 2025. https:\/\/dados.gov.br\/dados\/conjuntos-dados<\/a>.<\/p>\n\n\n\n

Global Forest Watch. \u201cBrazil Country Dashboard \u2013 Fires.\u201d Global Forest Watch. Accessed April 20, 2025. https:\/\/www.globalforestwatch.org\/dashboards\/country\/BRA\/?category=fires&location=WyJjb3VudHJ5IiwiQlJBIl0%3D<\/a>.<\/p>\n\n\n\n

Instituto Socioambiental. \u201cRAISG Mapa Online.\u201d Socioambiental.org. Accessed April 20, 2025. https:\/\/www3.socioambiental.org\/geo\/RAISGMapaOnline\/.<\/p>\n\n\n\n

MapBiomas. \u201cMaps and Data.\u201d MapBiomas Brasil.<\/em> Accessed April 20, 2025. https:\/\/brasil.mapbiomas.org\/en\/downloads\/<\/a>.<\/p>\n\n\n\n

NASA Earthdata. \u201cEarthdata Search.\u201d NASA Earth Observing System Data and Information System (EOSDIS). Accessed April 20, 2025. https:\/\/search.earthdata.nasa.gov\/search?gdf=Excel&lat=-22.194090572094453&long=-131.34375&zoom=1<\/a>.<\/p>\n\n\n\n

Podcasts<\/h4>\n\n\n\n

Podcasts<\/strong><\/p>\n\n\n\n

R\u00e1dio Novelo Apresenta. Sob Estresse [Under Stress]<\/em>. 2023. Podcast. https:\/\/open.spotify.com\/episode\/6KUwUHS5nZX1ZeAYH63Ymo?si=ODTrUjfNRXeMDK9S4BlT8g.<\/p>\n\n\n\n

R\u00e1dio Novelo Apresenta. Salles, Jo\u00e3o Moreira. <\/em>2025. Podcast. .<\/em>https:\/\/open.spotify.com\/episode\/5vHfEZoyNUGmVUsnN30rPQ?si=V4sSrrdeRtKWFF_gjAYImw.<\/p>\n","protected":false},"excerpt":{"rendered":"

Context The Amazon Forest is one of the largest ecosystems on Earth, spanning an area of about 2.7 million square miles, of which 2.3 million square miles are rainforest. Its boundaries encompass nine Latin American countries and approximately 3,000 indigenous territories. The majority of the land lies in Brazil, which accounts for 60% of the territory. However, despite the…<\/p>\n","protected":false},"author":4476,"featured_media":38826,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"coauthors":[1896],"class_list":["post-38825","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-visualization"],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/studentwork.prattsi.org\/infovis\/wp-content\/uploads\/sites\/3\/2025\/04\/map-biomas-matogrosso.png?fit=1650%2C1162&ssl=1","jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paBdcV-a6d","_links":{"self":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/38825","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/users\/4476"}],"replies":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/comments?post=38825"}],"version-history":[{"count":2,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/38825\/revisions"}],"predecessor-version":[{"id":38842,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/posts\/38825\/revisions\/38842"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media\/38826"}],"wp:attachment":[{"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/media?parent=38825"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/categories?post=38825"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/tags?post=38825"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/studentwork.prattsi.org\/infovis\/wp-json\/wp\/v2\/coauthors?post=38825"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}