Spatial-Temporal Analysis of the Forest Fragments Surrounding a Conservation Unit in the Southern Region of Brazil †
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Image Processing
2.3. Landscape Analysis
3. Results
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Calegari, L.; Martins, S.V.; Gleriani, J.M.; Silva, E.; Busato, L.C. Análise da dinâmica de fragmentos florestais no município de Carandaí, MG, para fins de restauração florestal. Rev. Árvore 2010, 34, 871–880. [Google Scholar] [CrossRef]
- Abdalla, L.D.S.; Madureira, C. Análise de fragmentação florestal no município de Silva Jardim, APA do Rio São João, RJ. Rev. Bras. Cartogr. 2015, 67, 169–184. [Google Scholar]
- Cemin, G.; Schneider, V.E.; Finotti, A.R.; Reginato, P.A.R. Análise estrutura da paisagem da sub-bacia do Arroio Boa Vista, RS: uma abordagem em Ecologia de Paisagem; Anais do XIII Simpósio Brasileiro de Sensoriamento Remoto: Florianópolis, Brasil, 2007; pp. 3821–382. [Google Scholar]
- Herrmann, B.C.; Rodrigues, E.; Lima, A.D. A paisagem como condicionadora de bordas de fragmentos florestais. Floresta 2005, 35, 13–22. [Google Scholar] [CrossRef]
- Molina, J.M.P. Orchidaceae Juss. No Parque Estadual Mata dos Godoy e Entorno, Paraná, Brasil; Mathesis, Universidade Estadual de Londrina: Londrina, Brazil, 2014. [Google Scholar]
- Torezan, J.M.D.; Souza, R.F.d.; Ruas, P.M.; Ruas, C.d.F.; Camargo, E.H.; Vanzela, A.L.L. Genetic variability of pre and post-fragmentation cohorts of Aspidosperma polyneuron Muell. Arg. (Apocynaceae). Braz. Arch. Biol. Technol. 2005, 48, 171–180. [Google Scholar] [CrossRef]
- Santos, P.M.; Bailey, L.L.; Ribeiro, M.C.; Chiarello, A.G.; Paglia, A.P. Living on the edge: Forest cover threshold effect on endangered maned sloth occurrence in Atlantic Forest. Biol. Conserv. 2019, 240. [Google Scholar] [CrossRef]
- Klinga, P.; Mikolas, M.; Smolko, P.; Tejkal, M.; Hoglund, J.; Paule, L. Considering landscape connectivity and gene flow in the Anthropocene using complementary landscape genetics and habitat modelling approaches. Landsc. Ecol. 2019, 34, 521–536. [Google Scholar] [CrossRef]
- Jaafari, S.; Sakieh, Y.; Shabani, A.A.; Danehkar, A.; Akbar Nazarisamani, A. Landscape change assessment of reservation areas using remote sensing and landscape metrics (case study: Jajroud reservation, Iran). Environ. Dev. Sustain. 2016, 18, 1701–1717. [Google Scholar] [CrossRef]
- Richards, J.A.; Jia, X. Remote Sensing Digital Image Analysis: An Introduction, 4th ed.; Springer: New York, NY, USA, 2006. [Google Scholar]
- Congalton, R.G. A review of assessing the accuracy of classifications of remotely sensed data. Remote. Sens. Environ. 1991, 37, 35–46. [Google Scholar] [CrossRef]
- Esch, T.; Bachofer, F.; Heldens, W.; Hirner, A.; Marconcini, M.; Palacios-Lopez, D.; Roth, A.; Üreyen, S.; Zeidler, J.; Dech, S.; et al. Where We Live—A Summary of the Achievements and Planned Evolution of the Global Urban Footprint. Remote. Sens. 2018, 10. [Google Scholar] [CrossRef]
- McGarigal, K.; Cushman, S.; Neel, M.; Ene, E. FRAGSTATS –—Spatial Pattern Analysis Program for Categorical Maps; University of Massachusetts: Amherst, MA, USA, 2002. [Google Scholar]
- Jensen, J. Introductory Digital Image Processing; Prentice Hall: Upper Saddle River, NJ, USA, 1986. [Google Scholar]
- Landis, J.R.; Koch, G.G. The Measurement of Observer Agreement for Categorical Data. Biometrics 1977, 33, 159–174. [Google Scholar] [CrossRef] [PubMed]
- Almeida, C.G. Análise Espacial dos Fragmentos Florestais na área do Parque Nacional dos Campos Gerais, Paraná; Mathesis, Universidade Estadual de Ponta Grossa: Ponta Grossa, Brazil, 2008. [Google Scholar]
- Pinheiro, E.A.L.; Camini, N.A.; Soares, M.R.S.; Sumida, S.S. Cellular Automata Model—Landscape Dynamics Simulation Tool in the Process of Change in Land Use and Cover in the City of GaÚCha Do Norte—Mt. In Proceedings of the 2020 IEEE Latin American GRSS ISPRS Remote Sensing Conference (LAGIRS), Santiago, Chile, 22–26 March 2020; pp. 225–229. [Google Scholar] [CrossRef]
- Pascoal, L.M.L.; Parente, L.L.; Sérgio Nogueira, H.M.; Júnior, L.G.F. Deforestation Polygon Assessment Tool: Providing Comprehensive Information On Deforestation In The Brazilian Cerrado Biome. In Proceedings of the 2020 IEEE Latin American GRSS ISPRS Remote Sensing Conference (LAGIRS), Santiago, Chile, 22–26 March 2020; 428–433. [Google Scholar] [CrossRef]
- Silva Junior, C.H.L.; Aragão, L.E.O.C.; Anderson, L.O.; Fonseca, M.G.; Shimabukuro, Y.E.; Vancutsem, C.; Achard, F.; Beuchle, R.; Numata, I.; Silva, C.A.; et al. Persistent collapse of biomass in Amazonian forest edges following deforestation leads to unaccounted carbon losses. Sci. Adv. 2020, 6. [Google Scholar] [CrossRef] [PubMed]
- Wang, X.; Blanchet, F.G.; Koper, N. Measuring habitat fragmentation: An evaluation of landscape pattern metrics. Methods Ecol. Evol. 2014, 5, 634–646. [Google Scholar] [CrossRef]
- Lechner, A.M.; Reinke, K.J.; Wang, Y.; Bastin, L. Interactions between landcover pattern and geospatial processing methods: Effects on landscape metrics and classification accuracy. Ecol. Complex. 2013, 15, 71–82. [Google Scholar] [CrossRef]
Name | Definition | Units |
---|---|---|
Mean patch size (Area_MN) | Mean area of the patches | ha |
Total class area (CA) | Sum of the area of all patches | ha |
Total Core Area (TCA) | Sum of total core area of patches | ha |
Edge Density (ED) | Sum of edge lengths in relation to total area | m/ha |
Distance (ENN_MN) | Average of euclidean distance to the nearest patch | m |
Percentage of landscape (PLAND) | Percentage of the vegetation in landscape | Percent |
Shape Index (SHAPE_MN) | Mean shape index of patches | dimensionless |
Number of Patches (NP) | Number of vegetation patches | dimensionless |
Patch density (PD) | Number of patches by 100 ha | dimensionless |
Method | 1998 | 2008 | 2018 | |||
---|---|---|---|---|---|---|
OA | Kappa | OA | Kappa | OA | Kappa | |
Maximum likelihood | 98.76% | 0.98 | 95.51% | 0.93 | 100.00% | 1 |
Minimum distance | 97.19% | 0.96 | 96.88% | 0.95 | 100.00% | 1 |
Spectral Angle Mapping | 95.93% | 0.94 | 96.25% | 0.94 | 95.06% | 0.92 |
Metrics | 1998 | 2008 | 2018 |
---|---|---|---|
CA (ha) | 91,016.73 | 105,298.02 | 106,384.14 |
PLAND (%) | 16.16 | 18.70 | 18.89 |
AREA_MN (ha) | 9.99 | 12.74 | 15.39 |
ED (m/ha) | 34.1 | 38.45 | 35.96 |
TCA (ha) | 54,460.71 | 63,160.65 | 66,908.34 |
SHAPE_MN | 1.76 | 1.83 | 1.86 |
NP | 9170 | 8267 | 6913 |
PD (nº/100 ha) | 1617 | 1468 | 1228 |
ENN_MN (m) | 155.41 | 144.61 | 149.72 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Fernandes, B.; Batista, L. Spatial-Temporal Analysis of the Forest Fragments Surrounding a Conservation Unit in the Southern Region of Brazil. Environ. Sci. Proc. 2021, 3, 48. https://doi.org/10.3390/IECF2020-07876
Fernandes B, Batista L. Spatial-Temporal Analysis of the Forest Fragments Surrounding a Conservation Unit in the Southern Region of Brazil. Environmental Sciences Proceedings. 2021; 3(1):48. https://doi.org/10.3390/IECF2020-07876
Chicago/Turabian StyleFernandes, Bianca, and Ligia Batista. 2021. "Spatial-Temporal Analysis of the Forest Fragments Surrounding a Conservation Unit in the Southern Region of Brazil" Environmental Sciences Proceedings 3, no. 1: 48. https://doi.org/10.3390/IECF2020-07876
APA StyleFernandes, B., & Batista, L. (2021). Spatial-Temporal Analysis of the Forest Fragments Surrounding a Conservation Unit in the Southern Region of Brazil. Environmental Sciences Proceedings, 3(1), 48. https://doi.org/10.3390/IECF2020-07876