Remote Sensing Research Priorities in Tropical Dry Forest Environments

Biotropica ◽  
2003 ◽  
Vol 35 (2) ◽  
pp. 134-142 ◽  
Author(s):  
G. A. Sanchez-Azofeifa ◽  
K. L. Castro ◽  
B. Rivard ◽  
M. R. Kalascka ◽  
R. C. Harriss
Biotropica ◽  
10.1646/02072 ◽  
2003 ◽  
Vol 35 (2) ◽  
pp. 134
Author(s):  
G. A. Sánchez-Azofeifa ◽  
K. L. Castro ◽  
B. Rivard ◽  
M. R. Kalascka ◽  
R. C. Harriss

2012 ◽  
Vol 121 ◽  
pp. 132-143 ◽  
Author(s):  
Mauricio Castillo ◽  
Benoit Rivard ◽  
Arturo Sánchez-Azofeifa ◽  
Julio Calvo-Alvarado ◽  
Ralph Dubayah

Author(s):  
Elena Posada ◽  
Héctor Mauricio Ramírez Díaz ◽  
Paola Isaacs Cubides ◽  
Martha Paola Barajas Barbosa

Resumen Se presenta un avance de los resultados del proyecto “Uso de sensores remotos y tecnologías asociadas para estudio de ecosistemas forestales ante el cambio climático global”, realizadas en el marco de la red temática FORCLIM patrocinado por el Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo (Cyted). De dicha red temática hace parte el grupo de Percepción Remota y Aplicaciones Geográficas del Instituto Geográfico Agustín Codazzi, Oficina CIAF. En este contexto, como modelo metodológico se están trabajando datos de presencias del ecosistema páramo y bosque seco tropical, obtenidos de polígonos de cobertura de los ecosistemas continentales costeros y marinos del IDEAM –IGAC et al (2007). Se emplean datos de temperatura, precipitación y alturas descargados del proyecto WorldClim, los cuales se han procesado con ArcGIS y DIVA-GIS, para ser modelados junto con los datos de presencia en el programa MaxEnt. El resultado del modelo expresa el valor de idoneidad como una función de las variables ambientales. Para el trabajo se ha empleado un escenario futuro de incremento en la temperatura de tres y cinco grados Celsius, para determinar el comportamiento de dichas coberturas ante el calentamiento global. Se obtuvieron mapas de idoneidad actuales y futuros presentando una elevada tendencia a la disminución del páramo y aumento de los bosques secos, siendo la altura la variable que más contribuye para el páramo y la precipitación para bosque seco. Se presenta un proceso metodológico el cual sirve como insumo para modelar distribución de especies, en este caso incluyendo algunas variables empleadas para estudiar cambio climático y su integración con los datos obtenidos de sensores remotos. Palabras ClaveCambio climático, Distribución de especies, Red temática FORCLIM, Sensores remotos.   Abstract We present progress in the results of the research “Remote sensing use and associated technologies for ecosystem spatial changes evaluation concerning global climate change, in the frame of the thematic net FORCLIM, sponsored for the Programa Iberoamericano de Ciencia y Tecnología para el Desarrollo (Cyted). The Remote Sensing and Geographic Applications Group of the Instituto Geográfico Agustín Codazzi–CIAF is member of the net. In this sense, as a method we are using paramo and tropical dry forest ecosystem presence data obtained from the geodatabase of the continental and marine ecosystems of IDEAM-IGAC et al (2007). We are using temperature, precipitation and elevation data from WorldClim Project, which were processed with DIVA-GIS software in order to be modeled among the presence data with MaxEnt program. The model result shows the suitable value as a function of the environmental variables. For this work we used two future scenarios, the first with 3°C and the second with 5°C increment. The suitable paramo current models and paramo future models showed a considerable decreasing, for the tropical dry forest the distribution raised. We present a methodology process, which is helpful as an species distribution modeling input; according to the climatic variables, and data recovered from remote sensing techniques (presence data).Keywords Climate change, Remote sensing, Species distributions, Thematic net FORCLIM.


2021 ◽  
Vol 13 (19) ◽  
pp. 3830
Author(s):  
Genping Zhao ◽  
Arturo Sanchez-Azofeifa ◽  
Kati Laakso ◽  
Chuanliang Sun ◽  
Lunke Fei

Accurate estimation of the degree of regeneration in tropical dry forest (TDF) is critical for conservation policymaking and evaluation. Hyperspectral remote sensing and light detection and ranging (LiDAR) have been used to characterize the deterministic successional stages in a TDF. These successional stages, classified as early, intermediate, and late, are considered a proxy for mapping the age since the abandonment of a given forest area. Expanding on the need for more accurate successional forest mapping, our study considers the age attributes of a TDF study area as a continuous expression of relative attribute scores/levels that vary along the process of ecological succession. Specifically, two remote-sensing data sets: HyMap (hyperspectral) and LVIS (waveform LiDAR), were acquired at the Santa Rosa National Park Environmental Monitoring Super Site (SRNP-EMSS) in Costa Rica, were used to generate age-attribute metrics. These metrics were then used as entry-level variables on a randomized nonlinear archetypal analysis (RNAA) model to select the most informative metrics from both data sets. Next, a relative attribute learning (RAL) algorithm was adapted for both independent and fused metrics to comparatively learn the relative attribute levels of the forest ages of the study area. In this study, four HyMap indices and five LVIS metrics were found to have the potential to map the forest ages of the study area, and compared with these results, a significant improvement was found through the fusion of the metrics on the accuracy of the generated forest age maps. By linking the age group mapping and the relative attribute mapping results, a dynamic gradient of the age-attribute transition patterns emerged.


Mycotaxon ◽  
2018 ◽  
Vol 133 (3) ◽  
pp. 499-512 ◽  
Author(s):  
Magdalena Contreras-Pacheco ◽  
Ricardo Valenzuela ◽  
Tania Raymundo ◽  
Leticia Pacheco

2021 ◽  
Vol 490 ◽  
pp. 119127
Author(s):  
Tobias Fremout ◽  
Evert Thomas ◽  
Kelly Tatiana Bocanegra-González ◽  
Carolina Adriana Aguirre-Morales ◽  
Anjuly Tatiana Morillo-Paz ◽  
...  

2016 ◽  
Vol 77 (3) ◽  
pp. 542-552 ◽  
Author(s):  
J. Mertens ◽  
J. Germer ◽  
J. A. Siqueira Filho ◽  
J. Sauerborn

Abstract Spondias tuberosa Arr., a fructiferous tree endemic to the northeast Brazilian tropical dry forest called Caatinga, accounts for numerous benefits for its ecosystem as well as for the dwellers of the Caatinga. The tree serves as feed for pollinators and dispersers as well as fodder for domestic ruminants, and is a source of additional income for local smallholders and their families. Despite its vantages, it is facing several man-made and natural threats, and it is suspected that S. tuberosa could become extinct. Literature review suggests that S. tuberosa suffers a reduced regeneration leading to population decrease. At this juncture S. tuberosa cannot be considered threatened according to the International Union for Conservation of Nature Red List Categories and Criteria, as it has not yet been assessed and hampered generative regeneration is not considered in the IUCN assessment. The combination of threats, however, may have already caused an extinction debt for S. tuberosa. Due to the observed decline in tree density, a thorough assessment of the S. tuberosa population is recommended, as well as a threat assessment throughout the entire Caatinga.


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