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Parvar Z, Saeidi S, Mirkarimi S. Integrating meteorological and geospatial data for forest fire risk assessment. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2024; 358:120925. [PMID: 38640755 DOI: 10.1016/j.jenvman.2024.120925] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Revised: 03/16/2024] [Accepted: 04/14/2024] [Indexed: 04/21/2024]
Abstract
Understanding the factors that cause fire is crucial for minimizing the fire risk. In this research, a comprehensive approach was adopted to recognize factors influencing forest fires. Golestan National Park (GNP) was considered as a representative area with a humid climate in this study. Initially, using the Multi-Criteria Evaluation Method, a fire risk map was created by analyzing natural and human factors, and vulnerable areas were identified. Then, the relationship between key elements such as meteorological conditions, Land Surface Temperature (LST), and precipitation, with the occurrence of fire in different years was investigated. CHIRPS and Landsat data were utilized to assess LST changes and precipitation. 23-year changes in fire occurrence areas in GNP were acquired using MODIS products. The results of the data analysis showed that the highest number of fires occurred in forest areas, and in the fire risk prediction map, the extremely high-risk class is completely consistent with the ground truth data. The assigned weights, derived from expert opinions, highlight the substantial significance of elevation, and distance from roads and settlements. Additionally, the effectiveness of the model in providing reliable forecasts for fire risks in GNP is highlighted by the ROC curve with an AUC value of 0.83. Forest fires within GNP exhibit a distinct seasonality, predominantly occurring from July to December. During the warmer months, by coinciding with summer excursions, human activities may contribute to the ignition of fires. In 2013 and 2014, rising fire incidents correlated with elevated temperatures, hinting at a potential connection. GNP fires showed an upward trend with higher monthly LST and a downward trend with increased annual precipitation. The results showed that there is a relationship between LST, precipitation, and the occurrence of fire in GNP. Approximately 176.15 ha of GNP's forest areas have been destroyed by fires over the last two decades. This research demonstrated that there is a dynamic interaction between environmental conditions and fire incidents. By considering these factors, managers and environmental planners can develop effective strategies for managing and preventing forest fire risks.
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Affiliation(s)
- Zahra Parvar
- Department of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Golestan, Iran
| | - Sepideh Saeidi
- Department of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Golestan, Iran.
| | - Seyedhamed Mirkarimi
- Department of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Golestan, Iran
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Zhang F, Zhao P, Xu S, Wu Y, Yang X, Zhang Y. Integrating multiple factors to optimize watchtower deployment for wildfire detection. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 737:139561. [PMID: 32569901 DOI: 10.1016/j.scitotenv.2020.139561] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/07/2020] [Revised: 05/18/2020] [Accepted: 05/18/2020] [Indexed: 05/20/2023]
Abstract
Traditional human-vision-based watchtower systems are being gradually replaced by the machine-vision-based watchtower system. The visual range of machine-vision-based watchtower is smaller than the range of traditional human-vision-based watchtower, which has led to a sharp increase in the number of towers that should be deployed. Consequently, the overlapping area between watchtowers is larger and overlaps are more frequent than in conventional watchtower networks. This poses an urgent challenge: identifying the optimal locations for deployment. If the number of required watchtowers must be increased to extend the detection coverage, overlaps among watchtowers are inevitable and result in viewshed redundancy. However, this redundancy of the viewshed resources of the watchtowers has not been utilized in the design of fire detection systems. Moreover, fire ignition factors, such as climatic factors, fuels, and human behaviour, cause the fire occurrence risk to differ among forest areas. Thus, the fire risk map of the area should also be considered in watchtower deployment. A fire risk model is used as the first step in producing the fire risk map, which is used to propose a new watchtower deployment model for optimizing the watchtower system by integrating viewshed analysis, location allocation, and multi-coverage of the high-fire-risk area while considering the budget constraints for providing optimal coverage. We use a real dataset of a forest park to evaluate the applicability of our approach. The proposed approach is evaluated against the FV-NB (Full coVerage with No Budget constraint) algorithm and the XV-B (maXimum possible coVerage with a Budget constraint) algorithm in terms of performance. The evaluation results demonstrate that our approach realizes higher coverage gain and excellent multiple-coverage of the fire risk area by integrating the viewshed and the fire risk level into location allocation while satisfying requirements on the overall coverage and budget. The proposed approach is more suitable in the environments with moderate watchtower density, in which overlapping areas are frequent. It offers as much as 8.9-17.3% improvement of multiple-coverage of the high-fire-risk area.
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Affiliation(s)
- Fuquan Zhang
- College of Information Science and Technology, NanJing Forestry University, NanJing 210037, China.
| | - Pengcheng Zhao
- College of Information Science and Technology, NanJing Forestry University, NanJing 210037, China
| | - Shuwen Xu
- National Laboratory of Radar Signal Processing, Xidian University, Xi'an, China
| | - Yin Wu
- College of Information Science and Technology, NanJing Forestry University, NanJing 210037, China
| | - Xubing Yang
- College of Information Science and Technology, NanJing Forestry University, NanJing 210037, China
| | - Yan Zhang
- College of Information Science and Technology, NanJing Forestry University, NanJing 210037, China
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Sakellariou S, Cabral P, Caetano M, Pla F, Painho M, Christopoulou O, Sfougaris A, Dalezios N, Vasilakos C. Remotely Sensed Data Fusion for Spatiotemporal Geostatistical Analysis of Forest Fire Hazard. SENSORS (BASEL, SWITZERLAND) 2020; 20:E5014. [PMID: 32899393 PMCID: PMC7506779 DOI: 10.3390/s20175014] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Revised: 07/29/2020] [Accepted: 08/31/2020] [Indexed: 11/17/2022]
Abstract
Forest fires are a natural phenomenon which might have severe implications on natural and anthropogenic ecosystems. Future projections predict that, under a climate change environment, the fire season would be lengthier with higher levels of droughts, leading to higher fire severity. The main aim of this paper is to perform a spatiotemporal analysis and explore the variability of fire hazard in a small Greek island, Skiathos (a prototype case of fragile environment) where the land uses mixture is very high. First, a comparative assessment of two robust modeling techniques was examined, namely, the Analytical Hierarchy Process (AHP) knowledge-based and the fuzzy logic AHP to estimate the fire hazard in a timeframe of 20 years (1996-2016). The former technique was proven more representative after the comparative assessment with the real fire perimeters recorded on the island (1984-2016). Next, we explored the spatiotemporal dynamics of fire hazard, highlighting the risk changes in space and time through the individual and collective contribution of the most significant factors (topography, vegetation features, anthropogenic influence). The fire hazard changes were not dramatic, however, some changes have been observed in the southwestern and northern part of the island. The geostatistical analysis revealed a significant clustering process of high-risk values in the southwestern and northern part of the study area, whereas some clusters of low-risk values have been located in the northern territory. The degree of spatial autocorrelation tends to be greater for 1996 rather than for 2016, indicating the potential higher transmission of fires at the most susceptible regions in the past. The knowledge of long-term fire hazard dynamics, based on multiple types of remotely sensed data, may provide the fire and land managers with valuable fire prevention and land use planning tools.
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Affiliation(s)
- Stavros Sakellariou
- NOVA Information Management School, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal; (S.S.); (P.C.); (M.C.); (M.P.)
- Department of Planning and Regional Development, University of Thessaly, 38334 Volos, Greece;
- Department of Agriculture Crop Production and Rural Environment, University of Thessaly, 38446 Volos, Greece;
| | - Pedro Cabral
- NOVA Information Management School, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal; (S.S.); (P.C.); (M.C.); (M.P.)
| | - Mário Caetano
- NOVA Information Management School, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal; (S.S.); (P.C.); (M.C.); (M.P.)
| | - Filiberto Pla
- Institute of New Imaging Technologies (INIT), Universitat Jaume I (UJI), 12071 Castellón, Spain;
| | - Marco Painho
- NOVA Information Management School, Universidade Nova de Lisboa, 1070-312 Lisbon, Portugal; (S.S.); (P.C.); (M.C.); (M.P.)
| | - Olga Christopoulou
- Department of Planning and Regional Development, University of Thessaly, 38334 Volos, Greece;
| | - Athanassios Sfougaris
- Department of Agriculture Crop Production and Rural Environment, University of Thessaly, 38446 Volos, Greece;
| | - Nicolas Dalezios
- Department of Civil Engineering, University of Thessaly, 38334 Volos, Greece
| | - Christos Vasilakos
- Department of Geography, University of the Aegean, University Hill, 81100 Mytilene, Greece;
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Sakellariou S, Parisien MA, Flannigan M, Wang X, de Groot B, Tampekis S, Samara F, Sfougaris A, Christopoulou O. Spatial planning of fire-agency stations as a function of wildfire likelihood in Thasos, Greece. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 729:139004. [PMID: 32498173 DOI: 10.1016/j.scitotenv.2020.139004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 04/21/2020] [Accepted: 04/24/2020] [Indexed: 06/11/2023]
Abstract
Even though wildfires constitute a natural phenomenon, they may have severe implications with respect to the socioeconomic structure of the affected population and the ecological wealth of a territory, especially when they burn under high intensities. Timing of the initial attack is thus crucial to fire control in areas that fires are considered to be under high threat of burning. The aim of this paper is to investigate the combined use of simulation modeling and spatial optimization to assess the pre-positioning of fire-management resources on a small Greek island, Thasos, based on the current and desired fire agency capabilities, maximization of environmental protection, and rationalization of financial resources. The estimation of burn probability (BP) depicted specific areas of high fire hazard in the southern, central, and western part of the island, where essential preventive measures should be undertaken. Based on this result, BP was then used as a primary input for the assessment of optimal locations of fire operation agencies in order to achieve the maximal coverage under certain (already available) and minimum number of fire-fighting vehicles in different time windows. The results generated three differentiated optimal location schemes [8 available vehicles within either 10 (immediate response time) or 31 min (average response time) with the current fire resources; 19 and 2 required vehicles within 10 and 31 min, respectively, based on a minimum number of fire resources]. This type of information enables us to propose a relocation of the current fire agency in a southern town of the island. The flexibility and interaction of the models provide a framework for appropriate decision making under a set of political and financial constraints.
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Affiliation(s)
- Stavros Sakellariou
- Department of Planning and Regional Development, University of Thessaly, Volos, Greece; University of Alberta, Department of Renewable Resources, 51 General Services Building, Edmonton, AB, Canada.
| | - Marc-André Parisien
- Northern Forestry Centre, Canadian Forest Service, Natural Resources Canada, Edmonton, Alberta, Canada
| | - Mike Flannigan
- University of Alberta, Department of Renewable Resources, 51 General Services Building, Edmonton, AB, Canada
| | - Xianli Wang
- Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, 1219 Queen Street East, Sault Ste Marie, ON, Canada
| | - Bill de Groot
- Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, 1219 Queen Street East, Sault Ste Marie, ON, Canada
| | - Stergios Tampekis
- Hellenic Forest Service, Eastern Attica Research Station, Athens, Greece
| | - Fani Samara
- Department of Planning and Regional Development, University of Thessaly, Volos, Greece
| | - Athanasios Sfougaris
- Department of Agriculture Crop Production and Rural Environment, University of Thessaly, Volos, Greece
| | - Olga Christopoulou
- Department of Planning and Regional Development, University of Thessaly, Volos, Greece
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Zhang F, Zhao P, Thiyagalingam J, Kirubarajan T. Terrain-influenced incremental watchtower expansion for wildfire detection. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 654:164-176. [PMID: 30448653 DOI: 10.1016/j.scitotenv.2018.11.038] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2018] [Revised: 11/02/2018] [Accepted: 11/02/2018] [Indexed: 06/09/2023]
Abstract
Optimizing the effectiveness of early wildfire detection systems is of significant interest to the community. To this end, watchtower-based wildfire observations are continuing to be practical, often in conjunction with state-of-the-art technologies, such as automated vision systems and sensor networks. One of the major challenges that the community faces is the optimal expansion of existing systems, particularly in multiple stages due to various practical, political and financial constraints. The notion of incremental watchtower expansion while preserving or making minimal changes to an existing system is a challenging task, particularly while meeting coverage and financial constraints. Conventionally and historically, this problem has been treated as a multi-objective optimization problem, and as such, currently employed methods are predominantly focused on the full-fledged optimization problem, where the problem is re-solved every time during the expansion process. In this paper, for the first time, we propose an alternative approach, by treating the expansion as a submodular set-function maximization problem. By theoretically proving that the expansion problem is a submodular set-function maximization problem, we provide four different models and matching algorithms to handle various cases that arise during the incremental expansion process. Our evaluation of the proposed approach on a practical dataset from a forest park in China, namely, the NanJing forest park, shows that our algorithms can provide an excellent coverage by integrating visibility analysis and location allocation while meeting the stringent budgetary requirements. The proposed approach can be adapted to areas of other countries.
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Affiliation(s)
- Fuquan Zhang
- College of Information and Sciences, NanJing Forestry University, NanJing 210037, China; Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada.
| | - Pengcheng Zhao
- College of Information and Sciences, NanJing Forestry University, NanJing 210037, China
| | - Jeyarajan Thiyagalingam
- Scientific Computing Department, Science and Technologies Facilities Council, Rutherford Appleton Laboratory, Harwell Campus, Oxon, United Kingdom
| | - Thia Kirubarajan
- Department of Electrical and Computer Engineering, McMaster University, Hamilton, Canada
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Sakellariou S, Samara F, Tampekis S, Christopoulou O, Sfougaris A. Optimal Number and Location of Watchtowers for Immediate Detection of Forest Fires in a Small Island. INTERNATIONAL JOURNAL OF AGRICULTURAL AND ENVIRONMENTAL INFORMATION SYSTEMS 2017. [DOI: 10.4018/ijaeis.2017100101] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
A crucial factor for prevention and immediate confrontation of destructive fires and their socioeconomic and environmental consequences constitutes the early detection and spatial localization of fire ignitions, so that the firefighting forces to be activated and act within the critical time of response. Thus, principal objective of the paper constitutes the spatial optimization of the most effective locations of watchtowers developing a constructive network for the immediate and early detection of forest fires. This optimization involves the exploration of the fewest locations for watchtowers with the maximum visible area and reduced degree of overlapping. The results highlighted 4 groups of watchtowers (20 observers in total) determining the optimum locations. The total visibility amounted to 70% of the island, while the visibility percentages per land cover are variable, since they are depended on the spatial structure of them. Definitely, the final selection of the final number and the spatial structure of the watchtowers purely constitute decisions of political nature and will.
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Affiliation(s)
- Stavros Sakellariou
- University of Thessaly, Department of Planning and Regional Development, Volos, Greece
| | - Fani Samara
- University of Thessaly, Department of Planning and Regional Development, Volos, Greece
| | - Stergios Tampekis
- University of Thessaly, Department of Planning and Regional Development, Volos, Greece
| | - Olga Christopoulou
- University of Thessaly, Department of Planning and Regional Development, Volos, Greece
| | - Athanassios Sfougaris
- University of Thessaly, Department of Agriculture Crop Production and Rural Environment, Volos, Greece
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Dos Santos AR, Paterlini EM, Fiedler NC, Ribeiro CAAS, Lorenzon AS, Domingues GF, Marcatti GE, de Castro NLM, Teixeira TR, Dos Santos GMADA, Juvanhol RS, Branco ERF, Mota PHS, da Silva LG, Pirovani DB, de Jesus WC, Santos ACDA, Leite HG, Iwakiri S. Fuzzy logic applied to prospecting for areas for installation of wood panel industries. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2017; 193:345-359. [PMID: 28237845 DOI: 10.1016/j.jenvman.2017.02.049] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Revised: 02/15/2017] [Accepted: 02/17/2017] [Indexed: 06/06/2023]
Abstract
Prospecting for suitable areas for forestry operations, where the objective is a reduction in production and transportation costs, as well as the maximization of profits and available resources, constitutes an optimization problem. However, fuzzy logic is an alternative method for solving this problem. In the context of prospecting for suitable areas for the installation of wood panel industries, we propose applying fuzzy logic analysis for simulating the planting of different species and eucalyptus hybrids in Espírito Santo State, Brazil. The necessary methodological steps for this study are as follows: a) agriclimatological zoning of different species and eucalyptus hybrids; b) the selection of the vector variables; c) the application of the Euclidean distance to the vector variables; d) the application of fuzzy logic to matrix variables of the Euclidean distance; and e) the application of overlap fuzzy logic to locate areas for installation of wood panel industries. Among all the species and hybrids, Corymbia citriodora showed the highest percentage values for the combined very good and good classes, with 8.60%, followed by Eucalyptus grandis with 8.52%, Eucalyptus urophylla with 8.35% and Urograndis with 8.34%. The fuzzy logic analysis afforded flexibility in prospecting for suitable areas for the installation of wood panel industries in the Espírito Santo State can bring great economic and social benefits to the local population with the generation of jobs, income, tax revenues and GDP increase for the State and municipalities involved. The proposed methodology can be adapted to other areas and agricultural crops.
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Affiliation(s)
- Alexandre Rosa Dos Santos
- Federal University of Espírito Santo/UFES, Department of Rural Engineering, Alto Universitário, s/n, 29500-000, Alegre, ES, Brazil.
| | | | - Nilton Cesar Fiedler
- Federal University of Espírito Santo/UFES, PostGraduate Programme in Forest Sciences, Av. Governador Lindemberg, 316, 29550-000, Jerônimo Monteiro, ES, Brazil.
| | | | - Alexandre Simões Lorenzon
- Federal University of Viçosa/UFV, Department of Forest Engineering, Av. Peter Henry Rolfs, s/n, 36570-000, Viçosa, MG, Brazil.
| | - Getulio Fonseca Domingues
- Federal University of Viçosa/UFV, Department of Forest Engineering, Av. Peter Henry Rolfs, s/n, 36570-000, Viçosa, MG, Brazil.
| | - Gustavo Eduardo Marcatti
- Federal University of Viçosa/UFV, Department of Forest Engineering, Av. Peter Henry Rolfs, s/n, 36570-000, Viçosa, MG, Brazil.
| | - Nero Lemos Martins de Castro
- Federal University of Viçosa/UFV, Department of Forest Engineering, Av. Peter Henry Rolfs, s/n, 36570-000, Viçosa, MG, Brazil.
| | - Thaisa Ribeiro Teixeira
- Federal University of Viçosa/UFV, Department of Forest Engineering, Av. Peter Henry Rolfs, s/n, 36570-000, Viçosa, MG, Brazil.
| | | | - Ronie Silva Juvanhol
- Federal University of Espírito Santo/UFES, PostGraduate Programme in Forest Sciences, Av. Governador Lindemberg, 316, 29550-000, Jerônimo Monteiro, ES, Brazil.
| | - Elvis Ricardo Figueira Branco
- Federal University of Espírito Santo/UFES, PostGraduate Programme in Forest Sciences, Av. Governador Lindemberg, 316, 29550-000, Jerônimo Monteiro, ES, Brazil.
| | - Pedro Henrique Santos Mota
- Federal University of Viçosa/UFV, Department of Forest Engineering, Av. Peter Henry Rolfs, s/n, 36570-000, Viçosa, MG, Brazil.
| | | | | | - Waldir Cintra de Jesus
- Federal University of Espírito Santo/UFES, PostGraduate Programme in Forest Sciences, Av. Governador Lindemberg, 316, 29550-000, Jerônimo Monteiro, ES, Brazil.
| | | | - Helio Garcia Leite
- Federal University of Viçosa/UFV, Department of Forest Engineering, Av. Peter Henry Rolfs, s/n, 36570-000, Viçosa, MG, Brazil.
| | - Setsuo Iwakiri
- Federal University of Paraná/UFPR, PostGraduate Programme in Forest engineering, Av. Pref. Lothário Meissner, 632, 80210-170, Jardim Botânico, Campus III, Curitiba, PR, Brazil.
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Santos ARD, Antonio Alvares Soares Ribeiro C, de Oliveira Peluzio TM, Esteves Peluzio JB, de Queiroz VT, Figueira Branco ER, Lorenzon AS, Domingues GF, Marcatti GE, de Castro NLM, Teixeira TR, Dos Santos GMADA, Santos Mota PH, Ferreira da Silva S, Vargas R, de Carvalho JR, Macedo LL, da Silva Araújo C, de Almeida SLH. Geotechnology and landscape ecology applied to the selection of potential forest fragments for seed harvesting. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2016; 183:1050-1063. [PMID: 27692516 DOI: 10.1016/j.jenvman.2016.09.073] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Revised: 09/20/2016] [Accepted: 09/21/2016] [Indexed: 06/06/2023]
Abstract
The Atlantic Forest biome is recognized for its biodiversity and is one of the most threatened biomes on the planet, with forest fragmentation increasing due to uncontrolled land use, land occupation, and population growth. The most serious aspect of the forest fragmentation process is the edge effect and the loss of biodiversity. In this context, the aim of this study was to evaluate the dynamics of forest fragmentation and select potential forest fragments with a higher degree of conservation for seed harvesting in the Itapemirim river basin, Espírito Santo State, Brazil. Image classification techniques, forest landscape ecology, and multi-criteria analysis were used to evaluate the evolution of forest fragmentation to develop the landscape metric indexes, and to select potential forest fragments for seed harvesting for the years 1985 and 2013. According to the results, there was a reduction of 2.55% of the occupancy of the fragments in the basin between the years 1985 and 2013. For the years 1985 and 2013, forest fragment units 2 and 3 were spatialized with a high potential for seed harvesting, representing 6.99% and 16.01% of the total fragments, respectively. The methodology used in this study has the potential to be used to support decisions for the selection of potential fragments for seed harvesting because selecting fragments in different environments by their spatial attributes provides a greater degree of conservation, contributing to the protection and conscious management of the forests. The proposed methodology can be adapted to other areas and different biomes of the world.
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Affiliation(s)
- Alexandre Rosa Dos Santos
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | | | | | | | - Vagner Tebaldi de Queiroz
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | - Elvis Ricardo Figueira Branco
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | | | | | | | | | | | | | | | - Samuel Ferreira da Silva
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | - Rozimelia Vargas
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | - José Romário de Carvalho
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | - Leandro Levate Macedo
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | - Cintia da Silva Araújo
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
| | - Samira Luns Hatum de Almeida
- Federal University of Espírito Santo/UFES, Center of Agricultural Sciences, Alto Universitário, s/n 29500-000, Alegre, ES, Brazil.
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