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Yıl 2022, Cilt: 7 Sayı: 3, 283 - 293, 15.10.2022
https://doi.org/10.26833/ijeg.978990

Öz

Kaynakça

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  • Alexander C, Korstjens A H, Usher G, Nowak M G, Fredriksson G & Hill R A (2018a). LiDAR patch metrics for object-based clustering of forest types in a tropical rainforest. International Journal of Applied Earth Observation and Geoinformation, 73, 253-261.
  • Alexander C, Korstjens A H & Hill R A (2018b). Influence of micro-topography and crown characteristics on tree height estimations in tropical forests based on LiDAR canopy height models. International journal of applied earth observation and geoinformation, 65, 105-113.
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  • Asase A, Ofori‐Frimpong K & Ekpe P K (2010). Impact of cocoa farming on vegetation in an agricultural landscape in Ghana. African Journal of Ecology, 48(2), 338-346.
  • Arcos R, Ruiz A, Altamirano M & Albuja Viteri L H (2013). Uso del estrato vertical por el mono aullador (Alouatta palliata) (Primates: Atelidae) en un bosque subtropical del Noroccidente de Ecuador.
  • Aristizábal-Borja J (2013). Estrategias de forrajeo y características nutricionales de la dieta del mono aullador negro (Alouatta pigra) en un ambiente fragmentado. Xalapa, Veracruz: MSc dissertation, Instituto de Ecología, A. C.
  • Ballesteros J, Reyes K & Racero J (2009). Estructura poblacional y etología de Bradypus variegatus en fragmento de bosque seco tropical, Córdoba-Colombia. Revista MVZ Córdoba, 14(3), 1812-1819.
  • Bisseleua D H B, Missoup A D & Vidal S (2009). Biodiversity conservation, ecosystem functioning, and economic incentives under cocoa agroforestry intensification. Conservation biology, 23(5), 1176-1184.
  • Bombi P, Gnetti V, D’Andrea E, De Cinti B, Taglianti A V, Bologna M A & Matteucci G (2019). Identifying priority sites for insect conservation in forest ecosystems at high resolution: the potential of LiDAR data. Journal of Insect Conservation, 1-10.
  • Bhagwat S A, Willis K J, Birks H J B & Whittaker R J (2008). Agroforestry: a refuge for tropical biodiversity. Trends in ecology & evolution, 23(5), 261-267.
  • Buján S, González-Ferreiro E, Barreiro-Fernández L, Santé I, Corbelle E & Miranda D (2013). Classification of rural landscapes from low-density lidar data: is it theoretically possible? International journal of remote sensing, 34(16), 5666-5689.
  • Cabrera J, Lamelas M T, Montealegre A L & Riva J D L (2014). Estimación de variables dasométricas a partir de datos LiDAR PNOA en masas regulares de Pinus halepensis Mill.
  • Caudill S A, Vaast P & Husband T P (2014). Assessment of small mammal diversity in coffee agroforestry in the Western Ghats, India. Agroforestry systems, 88(1), 173-186.
  • Cassano C R, Barlow J & Pardini R (2014). Forest loss or management intensification? Identifying causes of mammal decline in cacao agroforests. Biological Conservation, 169, 14-22.
  • Cottontail V M, Wellinghausen N & Kalko E K V (2009). Habitat fragmentation and haemoparasites in the common fruit bat, Artibeus jamaicensis (Phyllostomidae) in a tropical lowland forest in Panamá. Parasitology, 136(10), 1133-1145.
  • Cicuzza D, Kessler M, Clough Y, Pitopang R, Leitner D & Tjitrosoedirdjo S S (2011). Conservation value of cacao agroforestry systems for terrestrial herbaceous species in central Sulawesi, Indonesia. Biotropica, 43(6), 755-762.
  • Daily G C, Ceballos G, Pacheco J, Suzán G & Sánchez‐Azofeifa A (2003). Countryside biogeography of neotropical mammals: conservation opportunities in agricultural landscapes of Costa Rica. Conservation biology, 17(6), 1814-1826.
  • De La Ossa J & Lacayo A D L O (2014). Densidad poblacional de Saguinus oedipus (Primates Callitrichidae) y disponibilidad de alimento vegetal, Colosó, Sucre-Colombia. Revista UDCA Actualidad & Divulgación Científica, 17(2).
  • Estrada A & Coates-Estrada R (2002). Bats in continuous forest, forest fragments and in an agricultural mosaic habitat-island at Los Tuxtlas, Mexico. Biological Conservation, 103(2), 237-245.
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  • Flaherty S S, Lurz P W & Patenaude G (2014). Use of LiDAR in the conservation management of the endangered red squirrel (Sciurus vulgaris L.). Journal of Applied Remote Sensing, 8(1), 083592.
  • Fidalgo-González L, Arellano-Pérez S, Álvarez-González J G, Castedo-Dorado F, Ruiz-González A D & González-Ferreiro E (2019). Estimación de la distribución vertical de combustibles finos del dosel de copas en masas de Pinus sylvestris empleando datos LiDAR de baja densidad. Revista de Teledetección, (53), 1-16.
  • Funes P A, Camacho C J N, Calcerrada R R, Jiménez, R V, Bernal R N R & Rojas W R (2017). Evaluación de la correlación entre variables métricas derivadas de tecnología LiDAR y variables del sensor MISR, mediante modelos de regresión con redes neuronales. XXV congreso de la AGE 50 años de congresos de geografía, naturaleza, territorio y ciudad en un mundo global, Madrid, España.
  • García Mayoral L E, Valdez Hernández J I, Luna Cavazos M & López Morgado R (2015). Estructura y diversidad arbórea en sistemas agroforestales de café en la Sierra de Atoyac, Veracruz. Madera y bosques, 21(3), 69-82.
  • Gamage S, Liyanage W K D D, Weerakoon D & Gunwardena A (2009). Habitat quality and availability of the Sri Lanka red slender Loris Loris tardigradus tardigradus (Mammalia: Primates: Lorisidae) in the Kottawa Arboretum. Journal of Threatened Taxa, 1(2), 65-71.
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LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife

Yıl 2022, Cilt: 7 Sayı: 3, 283 - 293, 15.10.2022
https://doi.org/10.26833/ijeg.978990

Öz

Agrosystems have different canopy strata due to shade trees that serve as available habitats for endangered species such as birds, reptiles, and mammals. LiDAR is a technology used to assess habitat quality as a support for designing conservation strategies. The objective of this research was to develop a model with data derived from LiDAR to obtain the height of the shade canopy in cocoa agrosystems, as a habitat available for wildlife species. Through the data of the height of the vegetation taken in the field and the data obtained from a LiDAR point cloud, the Canopy Height Model was generated. The data from the mapping of the canopy height model of the agrosystems taken as study sites were validated using the coefficient of determination (R2), mean absolute error (MAE), and the RMSE. The mean canopy height at the study sites was 14.63, 13.84, and 13.95 m, and the results of the validation using the model predicted canopy height shows good agreement with the actual value with an R2 of 0.86, and very low values of MAE=1.88, MSE=5.64, and RMSE=2.37, which indicates that they have an acceptable degree regarding the canopy height model between the LiDAR data and the data taken in the field. Research using LiDAR provides useful information to determine the height of the canopy, in the cocoa agrosystems up to 3 strata are found, this is due to the diversity of tree species used as shade, ranging from timber, fruit, ornamental, which are used as feeding, nesting, and resting of wildlife, in the study area populations of howler monkey species that are listed as endangered by the International Union for Conservation of Nature (IUCN), in addition to other species such as bats and birds, with the presence of these species indicate that the cocoa agrosystems, serve as a habitat for a diversity of species, which is why it is important to conserve these agrosystems in the humid tropics.

Kaynakça

  • Aguilar-Barojas S (2005). Fórmulas para el cálculo de la muestra en investigaciones de salud. Salud en Tabasco, 11(1-2), 333-338.
  • Alexander C, Korstjens A H, Usher G, Nowak M G, Fredriksson G & Hill R A (2018a). LiDAR patch metrics for object-based clustering of forest types in a tropical rainforest. International Journal of Applied Earth Observation and Geoinformation, 73, 253-261.
  • Alexander C, Korstjens A H & Hill R A (2018b). Influence of micro-topography and crown characteristics on tree height estimations in tropical forests based on LiDAR canopy height models. International journal of applied earth observation and geoinformation, 65, 105-113.
  • Allinne C, Savary S & Avelino J (2016). Delicate balance between pest and disease injuries, yield performance, and other ecosystem services in the complex coffee-based systems of Costa Rica. Agriculture, Ecosystems & Environment, 222, 1-12.
  • Asase A, Ofori‐Frimpong K & Ekpe P K (2010). Impact of cocoa farming on vegetation in an agricultural landscape in Ghana. African Journal of Ecology, 48(2), 338-346.
  • Arcos R, Ruiz A, Altamirano M & Albuja Viteri L H (2013). Uso del estrato vertical por el mono aullador (Alouatta palliata) (Primates: Atelidae) en un bosque subtropical del Noroccidente de Ecuador.
  • Aristizábal-Borja J (2013). Estrategias de forrajeo y características nutricionales de la dieta del mono aullador negro (Alouatta pigra) en un ambiente fragmentado. Xalapa, Veracruz: MSc dissertation, Instituto de Ecología, A. C.
  • Ballesteros J, Reyes K & Racero J (2009). Estructura poblacional y etología de Bradypus variegatus en fragmento de bosque seco tropical, Córdoba-Colombia. Revista MVZ Córdoba, 14(3), 1812-1819.
  • Bisseleua D H B, Missoup A D & Vidal S (2009). Biodiversity conservation, ecosystem functioning, and economic incentives under cocoa agroforestry intensification. Conservation biology, 23(5), 1176-1184.
  • Bombi P, Gnetti V, D’Andrea E, De Cinti B, Taglianti A V, Bologna M A & Matteucci G (2019). Identifying priority sites for insect conservation in forest ecosystems at high resolution: the potential of LiDAR data. Journal of Insect Conservation, 1-10.
  • Bhagwat S A, Willis K J, Birks H J B & Whittaker R J (2008). Agroforestry: a refuge for tropical biodiversity. Trends in ecology & evolution, 23(5), 261-267.
  • Buján S, González-Ferreiro E, Barreiro-Fernández L, Santé I, Corbelle E & Miranda D (2013). Classification of rural landscapes from low-density lidar data: is it theoretically possible? International journal of remote sensing, 34(16), 5666-5689.
  • Cabrera J, Lamelas M T, Montealegre A L & Riva J D L (2014). Estimación de variables dasométricas a partir de datos LiDAR PNOA en masas regulares de Pinus halepensis Mill.
  • Caudill S A, Vaast P & Husband T P (2014). Assessment of small mammal diversity in coffee agroforestry in the Western Ghats, India. Agroforestry systems, 88(1), 173-186.
  • Cassano C R, Barlow J & Pardini R (2014). Forest loss or management intensification? Identifying causes of mammal decline in cacao agroforests. Biological Conservation, 169, 14-22.
  • Cottontail V M, Wellinghausen N & Kalko E K V (2009). Habitat fragmentation and haemoparasites in the common fruit bat, Artibeus jamaicensis (Phyllostomidae) in a tropical lowland forest in Panamá. Parasitology, 136(10), 1133-1145.
  • Cicuzza D, Kessler M, Clough Y, Pitopang R, Leitner D & Tjitrosoedirdjo S S (2011). Conservation value of cacao agroforestry systems for terrestrial herbaceous species in central Sulawesi, Indonesia. Biotropica, 43(6), 755-762.
  • Daily G C, Ceballos G, Pacheco J, Suzán G & Sánchez‐Azofeifa A (2003). Countryside biogeography of neotropical mammals: conservation opportunities in agricultural landscapes of Costa Rica. Conservation biology, 17(6), 1814-1826.
  • De La Ossa J & Lacayo A D L O (2014). Densidad poblacional de Saguinus oedipus (Primates Callitrichidae) y disponibilidad de alimento vegetal, Colosó, Sucre-Colombia. Revista UDCA Actualidad & Divulgación Científica, 17(2).
  • Estrada A & Coates-Estrada R (2002). Bats in continuous forest, forest fragments and in an agricultural mosaic habitat-island at Los Tuxtlas, Mexico. Biological Conservation, 103(2), 237-245.
  • Espinosa-García J A, Uresti-Gil J, Vélez-Izquierdo A, Moctezuma-López G, Inurreta-Aguirre H D & Góngora-González S F (2015). Productividad y rentabilidad potencial del cacao (Theobroma cacao L.) en el trópico mexicano. Revista mexicana de ciencias agrícolas, 6(5), 1051-1063.
  • Flaherty S S, Lurz P W & Patenaude G (2014). Use of LiDAR in the conservation management of the endangered red squirrel (Sciurus vulgaris L.). Journal of Applied Remote Sensing, 8(1), 083592.
  • Fidalgo-González L, Arellano-Pérez S, Álvarez-González J G, Castedo-Dorado F, Ruiz-González A D & González-Ferreiro E (2019). Estimación de la distribución vertical de combustibles finos del dosel de copas en masas de Pinus sylvestris empleando datos LiDAR de baja densidad. Revista de Teledetección, (53), 1-16.
  • Funes P A, Camacho C J N, Calcerrada R R, Jiménez, R V, Bernal R N R & Rojas W R (2017). Evaluación de la correlación entre variables métricas derivadas de tecnología LiDAR y variables del sensor MISR, mediante modelos de regresión con redes neuronales. XXV congreso de la AGE 50 años de congresos de geografía, naturaleza, territorio y ciudad en un mundo global, Madrid, España.
  • García Mayoral L E, Valdez Hernández J I, Luna Cavazos M & López Morgado R (2015). Estructura y diversidad arbórea en sistemas agroforestales de café en la Sierra de Atoyac, Veracruz. Madera y bosques, 21(3), 69-82.
  • Gamage S, Liyanage W K D D, Weerakoon D & Gunwardena A (2009). Habitat quality and availability of the Sri Lanka red slender Loris Loris tardigradus tardigradus (Mammalia: Primates: Lorisidae) in the Kottawa Arboretum. Journal of Threatened Taxa, 1(2), 65-71.
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Toplam 74 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Articles
Yazarlar

Baltazar Sanchez Diaz 0000-0003-4165-4302

Ena Edith Mata-zayas Bu kişi benim

Lilia Maria Gama-campillo Bu kişi benim

Joaquin Alberto Rincon-ramirez Bu kişi benim

Francisca Vidal-garcia Bu kişi benim

Cristobal Daniel Rullan-silva Bu kişi benim

Facundo Sanchez-gutierrez Bu kişi benim

Yayımlanma Tarihi 15 Ekim 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 7 Sayı: 3

Kaynak Göster

APA Sanchez Diaz, B., Mata-zayas, E. E., Gama-campillo, L. M., Rincon-ramirez, J. A., vd. (2022). LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife. International Journal of Engineering and Geosciences, 7(3), 283-293. https://doi.org/10.26833/ijeg.978990
AMA Sanchez Diaz B, Mata-zayas EE, Gama-campillo LM, Rincon-ramirez JA, Vidal-garcia F, Rullan-silva CD, Sanchez-gutierrez F. LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife. IJEG. Ekim 2022;7(3):283-293. doi:10.26833/ijeg.978990
Chicago Sanchez Diaz, Baltazar, Ena Edith Mata-zayas, Lilia Maria Gama-campillo, Joaquin Alberto Rincon-ramirez, Francisca Vidal-garcia, Cristobal Daniel Rullan-silva, ve Facundo Sanchez-gutierrez. “LiDAR Modeling to Determine the Height of Shade Canopy Tree in Cocoa Agrosystems As Available Habitat for Wildlife”. International Journal of Engineering and Geosciences 7, sy. 3 (Ekim 2022): 283-93. https://doi.org/10.26833/ijeg.978990.
EndNote Sanchez Diaz B, Mata-zayas EE, Gama-campillo LM, Rincon-ramirez JA, Vidal-garcia F, Rullan-silva CD, Sanchez-gutierrez F (01 Ekim 2022) LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife. International Journal of Engineering and Geosciences 7 3 283–293.
IEEE B. Sanchez Diaz, “LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife”, IJEG, c. 7, sy. 3, ss. 283–293, 2022, doi: 10.26833/ijeg.978990.
ISNAD Sanchez Diaz, Baltazar vd. “LiDAR Modeling to Determine the Height of Shade Canopy Tree in Cocoa Agrosystems As Available Habitat for Wildlife”. International Journal of Engineering and Geosciences 7/3 (Ekim 2022), 283-293. https://doi.org/10.26833/ijeg.978990.
JAMA Sanchez Diaz B, Mata-zayas EE, Gama-campillo LM, Rincon-ramirez JA, Vidal-garcia F, Rullan-silva CD, Sanchez-gutierrez F. LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife. IJEG. 2022;7:283–293.
MLA Sanchez Diaz, Baltazar vd. “LiDAR Modeling to Determine the Height of Shade Canopy Tree in Cocoa Agrosystems As Available Habitat for Wildlife”. International Journal of Engineering and Geosciences, c. 7, sy. 3, 2022, ss. 283-9, doi:10.26833/ijeg.978990.
Vancouver Sanchez Diaz B, Mata-zayas EE, Gama-campillo LM, Rincon-ramirez JA, Vidal-garcia F, Rullan-silva CD, Sanchez-gutierrez F. LiDAR modeling to determine the height of shade canopy tree in cocoa agrosystems as available habitat for wildlife. IJEG. 2022;7(3):283-9.