Monitoring Brazilian Natural and Human-Modified Landscapes

A special issue of Land (ISSN 2073-445X). This special issue belongs to the section "Landscape Ecology".

Deadline for manuscript submissions: closed (15 February 2023) | Viewed by 23971

Special Issue Editors


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Guest Editor
Department of Oceanography and Limnology - DEOLI, Federal University of Maranhão - UFMA, São Luís 65080-805, Maranhão, Brazil
Interests: climate change; environmental issues; geoprocessing; remote sensing; geoinformation; global environmental changes

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Instituto Federal de Educação Ciência e Tecnologia do Maranhão - IFMA, São Luís 65030-005, Maranhão, Brazil
Interests: geoprocessing; remote sensing; GIS, spatial databases; precision geodesy and coastal monitoring; applied informatics; retrieval and filtering systems

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Guest Editor
Universidade Ceuma- UniCEUMA, Mestrado em Meio Ambiente - MMA, São Luís 65075120, Maranhão, Brazil
Interests: remote sensing; environmental modeling; estimation of environmental biophysical parameters

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Guest Editor
Aeronautics Institute of Technology - ITA, Computer Science Division, São José dos Campos, São Paulo 12228-900, Brazil
Interests: geoinformation; software engineering

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Guest Editor
National Institute for Space Research - INPE, Image Processing Division - DPI, São José dos Campos, 12227-010 São Paulo, Brazil
Interests: remote sensing; geoinformation; biodiversity; urbanization; Brazilian amazon; night-time lights

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Guest Editor
Departamento de Engenharia Agrícola (DEA), Universidade Estadual do Maranhão—UEMA, São Luís 65055-310, MA, Brazil
Interests: remote sensing; Amazon; tropical forests; environmental change; carbon cycle; forest fires; forest fragmentation; fire emissions; deforestation emissions; land use and land cover changes; tropical deforestation; climate change; drought; Lidar
Special Issues, Collections and Topics in MDPI journals

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Aerofotogrametry and Remote Sensing *Lab*- LASERE, Department of Geography, São Paulo University (USP), São Paulo 01322-000, Brazil
Interests: geoprocessing; remote sensing; geoinformation; cybercartography; environmental impacts

Special Issue Information

Dear Colleagues,

Brazil has continental dimensions, being the fifth largest country in the world in extension, which makes its systematic monitoring difficult. Its landscapes include heterogeneous environments, like deserts, savannas, rainforests, mangrove forests, and human-modified environments. The Amazonia, for example, the world's largest continuous rainforest, plays a crucial role in global climate regulation. At the same time, the Brazilian coast has the second largest mangrove area in the world, which is essential for fishing activities and the protection of the coastal zone against the impacts of climate change. However, human activities have negatively modified these environments, compromising their environmental services. In this context, remote sensing and geo-information are indispensable tools for monitoring Brazilian natural and human-modified environments at different spatial and temporal scales. Thus, this Special Issue seeks original and innovative contributions that involve the use of remote sensing and geo-information on the monitoring of Brazilian natural and human-modified landscapes, providing information to directly or indirectly subsidize decision-makers and encourage debate among all social actors in Brazil and abroad.

We invite you to submit articles on topics including, but not limited to the following:

  • Transdisciplinary studies on the vegetation dynamics, climate, water, society, and its relationships;
  • Transdisciplinary studies on forest fires;
  • Transdisciplinary studies on climate changes;
  • Studies on coastal environments;
  • Studies on urban environments;
  • Studies on transition environments (ecotones);
  • Studies on to improve land-use sustainability.

Dr. Denilson da Silva Bezerra
Dr. André Luis Silva dos Santos
Dr. Fabricio Brito Silva
Dr. Karla Donato Fook
Dr. Silvana Amaral
Dr. Celso H. L. Silva-Junior
Mr. Ulisses Denache Vieira Souza
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • GIS
  • geotechnologies
  • land use and land cover change
  • climate change
  • multi-source remote sensing
  • land use sustainability
  • landscape approach
  • forest fragmentation
  • global changes
  • carbon emission
  • ecotones
  • coastal environments

Published Papers (5 papers)

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Research

15 pages, 3767 KiB  
Article
Effects of Deforestation over the Cerrado Landscape: A Study in the Bahia Frontier
by Tainá Oliveira Assis, Maria Isabel Sobral Escada and Silvana Amaral
Land 2021, 10(4), 352; https://0-doi-org.brum.beds.ac.uk/10.3390/land10040352 - 01 Apr 2021
Cited by 6 | Viewed by 2867
Abstract
The losses in the Brazilian Cerrado raise the need to understand the border regions between human activities and Cerrado remnants. This work aims to answer the questions: How does the landscape change in a deforestation area in the Brazilian Cerrado, and where do [...] Read more.
The losses in the Brazilian Cerrado raise the need to understand the border regions between human activities and Cerrado remnants. This work aims to answer the questions: How does the landscape change in a deforestation area in the Brazilian Cerrado, and where do the losses of native Cerrado occur in the landscape context? We chose the Cerrado of Bahia, an area of the agricultural frontier, and used landscape metrics, and land use and land cover data from 2013 and 2020, to quantify the changes in the landscape. We built a typology of landscape patterns to classify and characterize the Cerrado landscapes, based on the landscape metrics, and land use and land cover data from TerraClass Cerrado 2013. From these parameters, a decision tree classifier enabled the classification of the landscape types. Then, we used the yearly deforestation data from PRODES Cerrado to obtain the native cover and the landscape metrics for 2020. The predominant landscape in 2013 was the Intermediate Stage of Fragmentation (32.53%), followed by the Initial Stage of Fragmentation (31.26%), Consolidated Pasture (16.4%), Consolidated Agriculture (9.78%), Mixed Landscapes (5.59%) and Native Cerrado (4.70%). The continuous Cerrado borders on areas in an initial and intermediate stage of fragmentation, putting pressure on the native area. The losses in native cover do not occur in consolidated landscapes or inside the continuous Cerrado. Instead, there is a process of vegetation conversion over the landscapes in the initial and intermediate stages of fragmentation, and landscapes where the matrix is heterogeneous. These factors signal the need to preserve the contiguous fragments of Cerrado. Full article
(This article belongs to the Special Issue Monitoring Brazilian Natural and Human-Modified Landscapes)
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12 pages, 3161 KiB  
Article
Roads in the Southwestern Amazon, State of Acre, between 2007 and 2019
by Eric de Souza Nascimento, Sonaira Souza da Silva, Leandra Bordignon, Antonio Willian Flores de Melo, Amintas Brandão, Jr., Carlos M. Souza, Jr. and Celso H. L. Silva Junior
Land 2021, 10(2), 106; https://0-doi-org.brum.beds.ac.uk/10.3390/land10020106 - 23 Jan 2021
Cited by 15 | Viewed by 4648
Abstract
Over the past 40 years, roads have been the main driver behind the State of Acre’s occupation and development. However, the expansion of roads, has often been associated with the advance of deforestation, habitat fragmentation, and social conflicts. There are no up-to-date data [...] Read more.
Over the past 40 years, roads have been the main driver behind the State of Acre’s occupation and development. However, the expansion of roads, has often been associated with the advance of deforestation, habitat fragmentation, and social conflicts. There are no up-to-date data available on the current extent of Acre’s road network nor its environmental and socioenvironmental impacts. In this study, we updated the State of Acre’s road network map for the period 2007 to 2019 through the visual interpretation of 153 Landsat images (5, 7, and 8) at a scale of 1:50,000. To estimate the impact of roads, we measured the distribution of roads in municipalities and in different land tenure categories and calculated the correlation between roads and annual deforestation. Up to 2019, we estimated 19,620 km of roads, of which 92% were unofficial roads, 6% federal roads, and 2% state roads. The roads increased at an average annual rate of 590 km year−1. The most significant advance in road length between 2007 and 2019 was in protected areas (240%), followed by public lands (68%) and settlement projects (66%). We recommend monitoring of the road network to understand the landscape’s evolution and support actions against illicit environmental and socioenvironmental impacts. Full article
(This article belongs to the Special Issue Monitoring Brazilian Natural and Human-Modified Landscapes)
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24 pages, 4418 KiB  
Article
Drivers of Fire Anomalies in the Brazilian Amazon: Lessons Learned from the 2019 Fire Crisis
by Marcus V. F. Silveira, Caio A. Petri, Igor S. Broggio, Gabriel O. Chagas, Mateus S. Macul, Cândida C. S. S. Leite, Edson M. M. Ferrari, Carolina G. V. Amim, Ana L. R. Freitas, Alline Z. V. Motta, Luiza M. E. Carvalho, Celso H. L. Silva Junior, Liana O. Anderson and Luiz E. O. C. Aragão
Land 2020, 9(12), 516; https://0-doi-org.brum.beds.ac.uk/10.3390/land9120516 - 14 Dec 2020
Cited by 50 | Viewed by 8388
Abstract
The 2019 fire crisis in Amazonia dominated global news and triggered fundamental questions about the possible causes behind it. Here we performed an in-depth investigation of the drivers of active fire anomalies in the Brazilian Amazon biome. We assessed a 2003–2019 time-series of [...] Read more.
The 2019 fire crisis in Amazonia dominated global news and triggered fundamental questions about the possible causes behind it. Here we performed an in-depth investigation of the drivers of active fire anomalies in the Brazilian Amazon biome. We assessed a 2003–2019 time-series of active fires, deforestation, and water deficit and evaluated potential drivers of active fire occurrence in 2019, at the biome-scale, state level, and local level. Our results revealed abnormally high monthly fire counts in 2019 for the states of Acre, Amazonas, and Roraima. These states also differed from others by exhibiting in this year extreme levels of deforestation. Areas in 2019 with active fire occurrence significantly greater than the average across the biome had, on average, three times more active fires in the three previous years, six times more deforestation in 2019, and five times more deforestation in the five previous years. Approximately one-third of yearly active fires from 2003 to 2019 occurred up to 1 km from deforested areas in the same year, and one-third of deforested areas in a given year were located up to 500 m from deforested areas in the previous year. These findings provide critical information to support strategic decisions for fire prevention policies and fire combat actions. Full article
(This article belongs to the Special Issue Monitoring Brazilian Natural and Human-Modified Landscapes)
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16 pages, 4159 KiB  
Article
Identifying Land Use Change Trajectories in Brazil’s Agricultural Frontier
by Adeline M. Maciel, Michelle C. A. Picoli, Lubia Vinhas and Gilberto Camara
Land 2020, 9(12), 506; https://0-doi-org.brum.beds.ac.uk/10.3390/land9120506 - 10 Dec 2020
Cited by 4 | Viewed by 3472
Abstract
Many of the world’s agricultural frontiers are located in the tropics. Crop and cattle expansion in these regions has a strong environmental impact. This paper examines land use and land cover transformations in Brazil, where large swaths of natural vegetation are being removed [...] Read more.
Many of the world’s agricultural frontiers are located in the tropics. Crop and cattle expansion in these regions has a strong environmental impact. This paper examines land use and land cover transformations in Brazil, where large swaths of natural vegetation are being removed to make way for agricultural production. In Brazil, the land use dynamics are of great interest regarding the country’s sustainable development and climate mitigation actions, leading to the formulation and implantation of public policies and supply chain interventions to reduce deforestation. This paper uses temporal trajectory analysis to discuss the patterns of agricultural practices change in the different biomes of Mato Grosso State, one of Brazil’s agricultural frontiers. Taking yearly land use and cover classified images from 2001 to 2017, we identified, quantified, and spatialized areas of stability, intensification, reduction, interchange, and expansion of single and double cropping. The LUC Calculus was used as a tool to extract information about trajectories and trajectories of change. Over two decades, the land use change trajectories uncover the interplay between forest removal, cattle raising, grain production, and secondary vegetation regrowth. We observed a direct relationship between the conversion of forest areas to pasture and of pasture to agriculture areas in the Amazon portion of the Mato Grosso State in different periods. Our results enable a better understanding of trends in agricultural practices. Full article
(This article belongs to the Special Issue Monitoring Brazilian Natural and Human-Modified Landscapes)
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20 pages, 17642 KiB  
Article
Maximum Fraction Images Derived from Year-Based Project for On-Board Autonomy-Vegetation (PROBA-V) Data for the Rapid Assessment of Land Use and Land Cover Areas in Mato Grosso State, Brazil
by Henrique Luis Godinho Cassol, Egidio Arai, Edson Eyji Sano, Andeise Cerqueira Dutra, Tânia Beatriz Hoffmann and Yosio Edemir Shimabukuro
Land 2020, 9(5), 139; https://0-doi-org.brum.beds.ac.uk/10.3390/land9050139 - 02 May 2020
Cited by 11 | Viewed by 3079
Abstract
This paper presents a new approach for rapidly assessing the extent of land use and land cover (LULC) areas in Mato Grosso state, Brazil. The novel idea is the use of an annual time series of fraction images derived from the linear spectral [...] Read more.
This paper presents a new approach for rapidly assessing the extent of land use and land cover (LULC) areas in Mato Grosso state, Brazil. The novel idea is the use of an annual time series of fraction images derived from the linear spectral mixing model (LSMM) instead of original bands. The LSMM was applied to the Project for On-Board Autonomy-Vegetation (PROBA-V) 100-m data composites from 2015 (~73 scenes/year, cloud-free images, in theory), generating vegetation, soil, and shade fraction images. These fraction images highlight the LULC components inside the pixels. The other new idea is to reduce these time series to only six single bands representing the maximum and standard deviation values of these fraction images in an annual composite, reducing the volume of data to classify the main LULC classes. The whole image classification process was conducted in the Google Earth Engine platform using the pixel-based random forest algorithm. A set of 622 samples of each LULC class was collected by visual inspection of PROBA-V and Landsat-8 Operational Land Imager (OLI) images and divided into training and validation datasets. The performance of the method was evaluated by the overall accuracy and confusion matrix. The overall accuracy was 92.4%, with the lowest misclassification found for cropland and forestland (<9% error). The same validation data set showed 88% agreement with the LULC map made available by the Landsat-based MapBiomas project. This proposed method has the potential to be used operationally to accurately map the main LULC areas and to rapidly use the PROBA-V dataset at regional or national levels. Full article
(This article belongs to the Special Issue Monitoring Brazilian Natural and Human-Modified Landscapes)
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