GIS applied to location of fires detection towers in domain area of tropical forest

Eugênio, Fernando Coelho; Santos, Alexandre Rosa dos; Fiedler, Nilton César; Ribeiro, Guido Assunção; Silva, Aderbal Gomes da; Juvanhol, Ronie Silva; Schettino, Vítor Roberto; Marcatti, Gustavo Eduardo; Domingues, Getúlio Fonseca; Santos, Gleissy Mary Amaral Dino Alves dos; Pezzopane, José Eduardo Macedo; Pedra, Beatriz Duguy; Banhos, Áureo; Martins, Lima Deleon

doi:10.1016/j.scitotenv.2016.03.231

Cited by 35 publications

(21 citation statements)

References 29 publications

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“…construction and maintenance) and general access purposes. Selecting the candidate sites according to criteria such as altitude and terrain features, as proposed by Eugenio et al (2016), would reduce the number of sites in the Placement Zone. However, there is a risk that high-quality candidate sites may be discarded by this approach, so it was not considered further.…”

Section: Placement Zone Specificationmentioning

confidence: 99%

“…The second candidate site identification approach was proposed by Eugenio et al (2016) using Geographical Information Systems (GIS) software, when they selected sites for manned watchtowers in an area covering 46 000 km 2 . GIS processes were used to identify land within feasible geographical and administrative/municipal boundaries, while terrain feature classification analyses were used to identify ridges on mountains and hills.…”

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confidence: 99%

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Optimisation of tower site locations for camera-based wildfire detection systems

Heyns

Plessis

Kosch

et al. 2019

Int. J. Wildland Fire

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Early forest fire detection can effectively be achieved by systems of specialised tower-mounted cameras. With the aim of maximising system visibility of smoke above a prescribed region, the process of selecting multiple tower sites from a large number of potential site locations is a complex combinatorial optimisation problem. Historically, these systems have been planned by foresters and locals with intimate knowledge of the terrain rather than by computational optimisation tools. When entering vast new territories, however, such knowledge and expertise may not be available to system planners. A tower site-selection optimisation framework that may be used in such circumstances is described in this paper. Metaheuristics are used to determine candidate site layouts for an area in the Nelspruit region in South Africa currently monitored by the ForestWatch detection system. Visibility cover superior to that of the existing system in the region is achieved and obtained in several days, whereas traditional approaches normally require months of speculation and planning. Following the results presented here, the optimisation framework is earmarked for use in future ForestWatch system planning.

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Section: Placement Zone Specificationmentioning

confidence: 99%

mentioning

confidence: 99%

Optimisation of tower site locations for camera-based wildfire detection systems

Heyns

Plessis

Kosch

et al. 2019

Int. J. Wildland Fire

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“…Experiments were undertaken from July 2018 to January 2019 at the Forest Nursery at Universidade Federal do Espirito Santo (DCFM-CCA-UFES), in Jerônimo Monteiro, Espirito Santo State (ES), at 20° 47′ S and 41° 23′ W and an altitude of 120 m. The climate of the Jerônimo Monteiro region based on the Köppen classification is the CWA type, i.e. dry winter and rainy summer (Eugenio et al, 2016).…”

Section: Study Areamentioning

confidence: 99%

MINI-CUTTING TECHNIQUE FOR VEGETATIVE PROPAGATION OF Paratecoma peroba

Araújo

Gibson

Santos

et al. 2019

CERNE

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“…Constituyen una valiosa herramienta de apoyo para la toma de decisiones, y han probado su utilidad en gran diversidad de condiciones geográficas para el monitoreo de muchos ambientes distintos (Shalaby & Tateishi, 2007;Marín, Nahuelhual, Echeverría, & Grant, 2013). Así, la regresión logística realizada en un entorno de SIG, ha permitido la gestión de medidas encaminadas a la protección de ecosistemas (Fagerholm et al, 2016;. Semeraro et al, 2016), y en particular al manejo de bosques (Zambelli et al, 2012;Eugenio et al, 2016;Lin, Thomson, Hung, & Lin, 2012).…”

Section: Introductionunclassified

“…Así, la regresión logística realizada en un entorno de SIG, ha permitido la gestión de medidas encaminadas a la protección de ecosistemas (Fagerholm et al, 2016;. Semeraro et al, 2016), y en particular al manejo de bosques (Zambelli et al, 2012;Eugenio et al, 2016;Lin, Thomson, Hung, & Lin, 2012).…”

Section: Introductionunclassified

Áreas Probables De Degradación-Deforestación De La Cubierta Vegetal en Chihuahua, México. Una Exploración Mediante Regresión Logística Para El Período 1985-2013

et al. 2017

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RESUMENEl objetivo de este trabajo fue identificar las áreas con riesgo de degradación-deforestación de la cubierta forestal en el oeste de Chihuahua, en el norte de México, utilizando un modelo de regresión logística. Se generó la regresión entre once capas de información geográfica (biofísica y socioeconómica) y áreas deforestadas de cuatro municipios del estado durante el período 1985-2013. Los resultados indican un buen poder predictivo del modelo generado (Pseudo-R2 de McFadden de 0.24), e identifican la tenencia de la tierra, el grado de marginación y su comportamiento temporal, la aptitud agrológica del suelo y la pendiente del terreno, como las variables con mayor peso en la predicción de zonas susceptibles de degradación y pérdida de bosques. Estos hallazgos facilitan el manejo ambiental de áreas boscosas y la mitigación de causas en zonas que están sufriendo este proceso. Palabras clave: Deforestación, Chihuahua, Predicción, Regresión Logística. PROBABLE AREAS OF DEGRADATION-DEFORESTATION OF VEGETATION COVERAGE IN CHIHUAHUA, MEXICO. AN EXPLORATION THROUGH LOGISTIC REGRESSION FOR THE PERIOD 1985-2013. ABSTRACTThe objective of this work was to identify the areas with risk of degradation-deforestation of forest cover in the west of Chihuahua, in the north of Mexico, using a logistic regression model. It was generated the regression between eleven layers of geographic information (biophysical and socioeconomic) and deforested areas of four municipalities of the state during the period 1985-2013. The results indicate a good predictive power of the generated model (McFadden's Pseudo-R2 of 0.24), and identify land tenure, degree of marginalization and its temporal behavior, soil agrological suitability and terrain slope, as the variables with the biggest weight in

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GIS applied to location of fires detection towers in domain area of tropical forest

Cited by 35 publications

References 29 publications

Optimisation of tower site locations for camera-based wildfire detection systems

Optimisation of tower site locations for camera-based wildfire detection systems

MINI-CUTTING TECHNIQUE FOR VEGETATIVE PROPAGATION OF Paratecoma peroba

Áreas Probables De Degradación-Deforestación De La Cubierta Vegetal en Chihuahua, México. Una Exploración Mediante Regresión Logística Para El Período 1985-2013

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