Florencia Sangermano - Profile on Academia.edu (original) (raw)

Papers by Florencia Sangermano

Forest baseline and deforestation map of the Dominican Republic through the analysis of time series of MODIS data

Data in brief, 2015

Deforestation is one of the major threats to habitats in the Dominican Republic. In this work we ... more Deforestation is one of the major threats to habitats in the Dominican Republic. In this work we present a forest baseline for the year 2000 and a deforestation map for the year 2011. Maps were derived from Moderate Resolution Imaging Radiometer (MODIS) products at 250 m resolution. The vegetation continuous fields product (MOD44B) for the year 2000 was used to produce the forest baseline, while the vegetation indices product (MOD13Q1) was used to detect change between 2000 and 2011. Major findings based on the data presented here are reported in the manuscript "Habitat suitability and protection status of four species of amphibians in the Dominican Republic" (Sangermano et al., Appl. Geogr.,) [7].63, 2015, 55-65.

International Journal of Remote Sensing - INT J REMOTE SENS, 2011

Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico pr... more Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico presents a number of significant challenges for the fine-scale land-cover information required of land-change science. Subtle variation in mature forest types across the regional ecocline is compounded by vegetation transitions following agricultural land uses. Such complex mapping environments require innovation in multispectral classification methodologies. This research presents an application of a step-wise maximum likelihood/In-Process Classification Assessment (IPCA) procedure. This hybrid supervised and unsupervised classification methodology allows for exploration of underlying characteristics of Landsat Thematic Mapper (TM) imagery in tropical environments. Once spectrally separable classes have been identified, field data then determine the ecological definition of vegetation types with special attention paid to areas of unknown or mixed classes. A post-field assessment re-classification using the Dempster–Shafer method reduced the original 25 spectral classes to 14 ecologically distinctive classes, providing the fine-tuned land-cover distinctions that are required for both environmental and socioeconomic research questions. The overall map accuracy was 87% with an average per-class accuracy of 86%. Per-class accuracy ranged from as low as 45% for pasture grass to a high of 100% for tall-stature evergreen upland forest, low and medium-stature semi-deciduous upland forest and deciduous forest.

Medical and …, Jan 1, 2011

The present work evaluates the use of species distribution model (SDM) algorithms to classify hig... more The present work evaluates the use of species distribution model (SDM) algorithms to classify high densities of small container-breeding Aedes mosquitoes (Diptera: Culicidae) on a fine scale in the Bermuda Islands. Weekly ovitrap data collected by the Department of Health, Bermuda for the years 2006 and 2007 were used for the models. The models evaluated included the algorithms Bioclim, Domain, GARP (genetic algorithm for rule-set prediction), logistic regression and MaxEnt (maximum entropy). Models were evaluated according to performance and robustness. The area under the receiver operating characteristic curve was used to evaluate each model's performance, and robustness was assessed according to the spatial correlation between classification risks for the two datasets. Relative to the other algorithms, logistic regression was the best and MaxEnt the second best model for classifying high-risk areas. We describe the importance of covariables for these two models and discuss the utility of SDMs in vector control efforts and the potential for the development of scripts that automate the task of creating risk assessment maps.

Landscape Ecology, Jan 1, 2012

Tropical deforestation is a major contributor to green house gas emissions in developing countrie... more Tropical deforestation is a major contributor to green house gas emissions in developing countries. Incentive mechanisms, such as reducing emissions from deforestation and forest degradation (REDD), are currently being considered as a possible emissions reduction and offset solution. Although REDD has expanded its scope to include co-benefits such as sustainable management of forests and biodiversity conservation (known as REDD?), current carbon-base methodologies do not specifically target projects for the parallel protection of these co-benefits. This study demonstrates the incorporation of both carbon and biodiversity benefits within REDD? in the Bolivian Amazon, through the analysis of land cover change and future change scenario modeling to the year 2050. Current protected areas within the Bolivian Amazon were evaluated for REDD? project potential by identifying concordant patterns of carbon content, species biodiversity and deforestation vulnerability. Biodiversity-based versus carbon-based protection schemes were evaluated and protected areas were prioritized using irreplaceability-vulnerability plots.

RE-DEFINING SPECIES RANGE POLYGONS USING A GIS

geogra.uah.es

A significant resource in the analysis of biodiversity for conservation planning is the archive o... more A significant resource in the analysis of biodiversity for conservation planning is the archive of species range polygons developed on the basis of expert knowledge. However, these polygons are known to contain omissions (because of knowledge gaps) and imprecision ...

International Journal of …, Jan 1, 2012

The archives of species range polygons developed under comprehensive assessments of the conservat... more The archives of species range polygons developed under comprehensive assessments of the conservation status of species, such as the IUCN's Global Assessments, are a significant resource in the analysis of biodiversity for conservation planning. Species range polygons obtained from these studies are known to exhibit omissions (because of knowledge gaps) and imprecision in their boundaries. In this work, we present a method to refine those species range polygons in order to create more realistic representations of species geographic ranges. Using range polygons of four species of mammals in South America and environmental variables at a 1 km resolution, combined with a set of GIS algorithms, a procedure was developed to map the confidence that sub-polygon elements belong to a logical species range. The confidence map is then used as a weight for a Mahalanobis typicality empirical modelling procedure to generate a map of species-weighted typicalities that is then thresholded to generate the refined species range map. Methods for variable selection and quality assessment of the refined range are also included in the procedure. Analysis using independent validation data shows the power of this methodology to redefine species ranges in a more biophysically reasonable way. The quality of the final-range map depends on the habitat suitability threshold used to define the species range. The report of quality assessment produced is useful for identifying not only the threshold that produces the highest match to the original expert range but also for flagging those ranges with higher discrepancies, facilitating the identification of ranges that need further revision.

… Journal of Remote …, Jan 1, 2011

Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico pr... more Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico presents a number of significant challenges for the fine-scale land-cover information required of land-change science. Subtle variation in mature forest types across the regional ecocline is compounded by vegetation transitions following agricultural landuses. Such complex mapping environments require innovation in multispectral classification methodologies. This research presents an application of a step-wise maximum likelihood/ in-Process Classification Assessment (IPCA) procedure. This hybrid supervised and unsupervised classification methodology allows for exploration of underlying characteristics of Landsat Thematic Mapper imagery in tropical environments. Once spectrally-separable classes have been identified, field data then determine the ecological definition of vegetation types with special attention paid to areas of unknown or mixed classes. A post-field assessment re-classification using the Dempster-Shafer method reduced the original 25 spectral classes to 14 ecologically-distinctive classes, providing the fine-tuned land-cover distinctions that are required for both environmental and socioeconomic research questions. The overall map accuracy was 87% with an average per-class accuracy of 86%. Per-class accuracy (omission errors) ranged from as low as 45% for pasture grass to a high of 100% for tall-stature evergreen upland forest (selva alta perennifolia), for semi-deciduous medium-stature forests (selva baja and mediana subcaducifolia) and deciduous forest (selva caducifolia).

Linking GIS and ecology–the use of Mahalanobis typicalities to model species distribution

Memorias XI Conferencia …, Jan 1, 2007

Transactions in GIS, Jan 1, 2010

Land use change models are increasingly being used to evaluate the effect of land change on clima... more Land use change models are increasingly being used to evaluate the effect of land change on climate and biodiversity and to generate scenarios of deforestation. Although many methods are available to model land transition potentials, they are usually not user-friendly and require the specification of many parameters, making the task difficult for decision makers not familiar with the tools, as well as making the process difficult to interpret. In this article we propose a simple method for modeling transition potentials. SimWeight is an instance-based learning algorithm based on the logic of the K-Nearest Neighbor algorithm. The method identifies the relevance of each driver variable and predicts the transition potential of locations given known instances of change. A case study was used to demonstrate and validate the method. Comparison of results with the Multi-Layer Perceptron neural network (MLP) suggests that SimWeight performs similarly in its capacity to predict transition potentials, without the need for complex parameters. Another advantage of SimWeight is that it is amenable to parallelization for deployment on a cloud computing platform.

… Journal of Remote …, Jan 1, 2009

A procedure is introduced for the analysis of seasonal trends in time series of Earth observation... more A procedure is introduced for the analysis of seasonal trends in time series of Earth observation imagery. Called Seasonal Trend Analysis (STA), the procedure is based on an initial stage of harmonic analysis of each year in the series to extract the annual and semi-annual harmonics. Trends in the parameters of these harmonics over years are then analysed using a robust median-slope procedure. Finally, images of these trends are used to create colour composites highlighting the amplitudes and phases of seasonality trends. The technique specifically rejects high-frequency sub-annual noise and is robust to short-term interannual variability up to a period of 29% of the length of the series. It is, thus, a very effective procedure for focusing on the general nature of longer-term trends in seasonality.

ecological …, Jan 1, 2008

This paper presents a novel methodology for multi-scale and multi-type spatial data integration i... more This paper presents a novel methodology for multi-scale and multi-type spatial data integration in support of insect pest risk/vulnerability assessment in the contiguous United States. Probability of gypsy moth (Lymantria dispar L.) establishment is used as a case study. A neural network facilitates the integration of variables representing dynamic anthropogenic interaction and ecological characteristics. Neural network model (back-propagation network [BPN]) results are compared to logistic regression and multi-criteria evaluation via weighted linear combination, using the receiver operating characteristic area under the curve (AUC) and a simple threshold assessment. The BPN provided the most accurate infestation-forecast predictions producing an AUC of 0.93, followed by multi-criteria evaluation (AUC = 0.92) and logistic regression (AUC = 0.86) when independently validating using post model infestation data. Results suggest that BPN can provide valuable insight into factors contributing to introduction for invasive species whose propagation and establishment requirements are not fully understood. The integration of anthropogenic and ecological variables allowed production of an accurate risk model and provided insight into the impact of human activities.

Ecological …, Jan 1, 2007

The southern Yucata´n contains the largest expanse of seasonal tropical forests remaining in Mexi... more The southern Yucata´n contains the largest expanse of seasonal tropical forests remaining in Mexico, forming an ecocline between the drier north of the peninsula and the humid Pete´n, Guatemala. The Calakmul Biosphere Reserve resides in the center of this region as part of the Mesoamerican Biological Corridor. The reserve's functions are examined in regard to land changes throughout the region, generated over the last 40 years by increasing settlement and the expansion and intensification of agriculture. These changes are documented from 1987/1988 to 2000, and their implications regarding the capacity of the reserve to protect the ecocline, forest habitats, and butterfly diversity are addressed. The results indicate that the current landscape matrix serves the biotic diversity of the reserve, with several looming caveats involving the loss of humid forests and the interruption of biota flow across the ecocline, and the amount and proximity of older forest patches beyond the reserve. The highly dynamic land cover changes underway in this economic frontier warrant an adaptive management approach that monitors the major changes underway in mature forest types, while the paucity of systematic ecological and environment-development studies is rectified in order to inform policy and practice.

Forest baseline and deforestation map of the Dominican Republic through the analysis of time series of MODIS data

Data in brief, 2015

Deforestation is one of the major threats to habitats in the Dominican Republic. In this work we ... more Deforestation is one of the major threats to habitats in the Dominican Republic. In this work we present a forest baseline for the year 2000 and a deforestation map for the year 2011. Maps were derived from Moderate Resolution Imaging Radiometer (MODIS) products at 250 m resolution. The vegetation continuous fields product (MOD44B) for the year 2000 was used to produce the forest baseline, while the vegetation indices product (MOD13Q1) was used to detect change between 2000 and 2011. Major findings based on the data presented here are reported in the manuscript "Habitat suitability and protection status of four species of amphibians in the Dominican Republic" (Sangermano et al., Appl. Geogr.,) [7].63, 2015, 55-65.

International Journal of Remote Sensing - INT J REMOTE SENS, 2011

Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico pr... more Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico presents a number of significant challenges for the fine-scale land-cover information required of land-change science. Subtle variation in mature forest types across the regional ecocline is compounded by vegetation transitions following agricultural land uses. Such complex mapping environments require innovation in multispectral classification methodologies. This research presents an application of a step-wise maximum likelihood/In-Process Classification Assessment (IPCA) procedure. This hybrid supervised and unsupervised classification methodology allows for exploration of underlying characteristics of Landsat Thematic Mapper (TM) imagery in tropical environments. Once spectrally separable classes have been identified, field data then determine the ecological definition of vegetation types with special attention paid to areas of unknown or mixed classes. A post-field assessment re-classification using the Dempster–Shafer method reduced the original 25 spectral classes to 14 ecologically distinctive classes, providing the fine-tuned land-cover distinctions that are required for both environmental and socioeconomic research questions. The overall map accuracy was 87% with an average per-class accuracy of 86%. Per-class accuracy ranged from as low as 45% for pasture grass to a high of 100% for tall-stature evergreen upland forest, low and medium-stature semi-deciduous upland forest and deciduous forest.

Medical and …, Jan 1, 2011

The present work evaluates the use of species distribution model (SDM) algorithms to classify hig... more The present work evaluates the use of species distribution model (SDM) algorithms to classify high densities of small container-breeding Aedes mosquitoes (Diptera: Culicidae) on a fine scale in the Bermuda Islands. Weekly ovitrap data collected by the Department of Health, Bermuda for the years 2006 and 2007 were used for the models. The models evaluated included the algorithms Bioclim, Domain, GARP (genetic algorithm for rule-set prediction), logistic regression and MaxEnt (maximum entropy). Models were evaluated according to performance and robustness. The area under the receiver operating characteristic curve was used to evaluate each model's performance, and robustness was assessed according to the spatial correlation between classification risks for the two datasets. Relative to the other algorithms, logistic regression was the best and MaxEnt the second best model for classifying high-risk areas. We describe the importance of covariables for these two models and discuss the utility of SDMs in vector control efforts and the potential for the development of scripts that automate the task of creating risk assessment maps.

Landscape Ecology, Jan 1, 2012

Tropical deforestation is a major contributor to green house gas emissions in developing countrie... more Tropical deforestation is a major contributor to green house gas emissions in developing countries. Incentive mechanisms, such as reducing emissions from deforestation and forest degradation (REDD), are currently being considered as a possible emissions reduction and offset solution. Although REDD has expanded its scope to include co-benefits such as sustainable management of forests and biodiversity conservation (known as REDD?), current carbon-base methodologies do not specifically target projects for the parallel protection of these co-benefits. This study demonstrates the incorporation of both carbon and biodiversity benefits within REDD? in the Bolivian Amazon, through the analysis of land cover change and future change scenario modeling to the year 2050. Current protected areas within the Bolivian Amazon were evaluated for REDD? project potential by identifying concordant patterns of carbon content, species biodiversity and deforestation vulnerability. Biodiversity-based versus carbon-based protection schemes were evaluated and protected areas were prioritized using irreplaceability-vulnerability plots.

RE-DEFINING SPECIES RANGE POLYGONS USING A GIS

geogra.uah.es

A significant resource in the analysis of biodiversity for conservation planning is the archive o... more A significant resource in the analysis of biodiversity for conservation planning is the archive of species range polygons developed on the basis of expert knowledge. However, these polygons are known to contain omissions (because of knowledge gaps) and imprecision ...

International Journal of …, Jan 1, 2012

The archives of species range polygons developed under comprehensive assessments of the conservat... more The archives of species range polygons developed under comprehensive assessments of the conservation status of species, such as the IUCN's Global Assessments, are a significant resource in the analysis of biodiversity for conservation planning. Species range polygons obtained from these studies are known to exhibit omissions (because of knowledge gaps) and imprecision in their boundaries. In this work, we present a method to refine those species range polygons in order to create more realistic representations of species geographic ranges. Using range polygons of four species of mammals in South America and environmental variables at a 1 km resolution, combined with a set of GIS algorithms, a procedure was developed to map the confidence that sub-polygon elements belong to a logical species range. The confidence map is then used as a weight for a Mahalanobis typicality empirical modelling procedure to generate a map of species-weighted typicalities that is then thresholded to generate the refined species range map. Methods for variable selection and quality assessment of the refined range are also included in the procedure. Analysis using independent validation data shows the power of this methodology to redefine species ranges in a more biophysically reasonable way. The quality of the final-range map depends on the habitat suitability threshold used to define the species range. The report of quality assessment produced is useful for identifying not only the threshold that produces the highest match to the original expert range but also for flagging those ranges with higher discrepancies, facilitating the identification of ranges that need further revision.

… Journal of Remote …, Jan 1, 2011

Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico pr... more Analysis of land-cover change in the seasonal tropical forests of the Southern Yucatán, Mexico presents a number of significant challenges for the fine-scale land-cover information required of land-change science. Subtle variation in mature forest types across the regional ecocline is compounded by vegetation transitions following agricultural landuses. Such complex mapping environments require innovation in multispectral classification methodologies. This research presents an application of a step-wise maximum likelihood/ in-Process Classification Assessment (IPCA) procedure. This hybrid supervised and unsupervised classification methodology allows for exploration of underlying characteristics of Landsat Thematic Mapper imagery in tropical environments. Once spectrally-separable classes have been identified, field data then determine the ecological definition of vegetation types with special attention paid to areas of unknown or mixed classes. A post-field assessment re-classification using the Dempster-Shafer method reduced the original 25 spectral classes to 14 ecologically-distinctive classes, providing the fine-tuned land-cover distinctions that are required for both environmental and socioeconomic research questions. The overall map accuracy was 87% with an average per-class accuracy of 86%. Per-class accuracy (omission errors) ranged from as low as 45% for pasture grass to a high of 100% for tall-stature evergreen upland forest (selva alta perennifolia), for semi-deciduous medium-stature forests (selva baja and mediana subcaducifolia) and deciduous forest (selva caducifolia).

Linking GIS and ecology–the use of Mahalanobis typicalities to model species distribution

Memorias XI Conferencia …, Jan 1, 2007

Transactions in GIS, Jan 1, 2010

Land use change models are increasingly being used to evaluate the effect of land change on clima... more Land use change models are increasingly being used to evaluate the effect of land change on climate and biodiversity and to generate scenarios of deforestation. Although many methods are available to model land transition potentials, they are usually not user-friendly and require the specification of many parameters, making the task difficult for decision makers not familiar with the tools, as well as making the process difficult to interpret. In this article we propose a simple method for modeling transition potentials. SimWeight is an instance-based learning algorithm based on the logic of the K-Nearest Neighbor algorithm. The method identifies the relevance of each driver variable and predicts the transition potential of locations given known instances of change. A case study was used to demonstrate and validate the method. Comparison of results with the Multi-Layer Perceptron neural network (MLP) suggests that SimWeight performs similarly in its capacity to predict transition potentials, without the need for complex parameters. Another advantage of SimWeight is that it is amenable to parallelization for deployment on a cloud computing platform.

… Journal of Remote …, Jan 1, 2009

A procedure is introduced for the analysis of seasonal trends in time series of Earth observation... more A procedure is introduced for the analysis of seasonal trends in time series of Earth observation imagery. Called Seasonal Trend Analysis (STA), the procedure is based on an initial stage of harmonic analysis of each year in the series to extract the annual and semi-annual harmonics. Trends in the parameters of these harmonics over years are then analysed using a robust median-slope procedure. Finally, images of these trends are used to create colour composites highlighting the amplitudes and phases of seasonality trends. The technique specifically rejects high-frequency sub-annual noise and is robust to short-term interannual variability up to a period of 29% of the length of the series. It is, thus, a very effective procedure for focusing on the general nature of longer-term trends in seasonality.

ecological …, Jan 1, 2008

This paper presents a novel methodology for multi-scale and multi-type spatial data integration i... more This paper presents a novel methodology for multi-scale and multi-type spatial data integration in support of insect pest risk/vulnerability assessment in the contiguous United States. Probability of gypsy moth (Lymantria dispar L.) establishment is used as a case study. A neural network facilitates the integration of variables representing dynamic anthropogenic interaction and ecological characteristics. Neural network model (back-propagation network [BPN]) results are compared to logistic regression and multi-criteria evaluation via weighted linear combination, using the receiver operating characteristic area under the curve (AUC) and a simple threshold assessment. The BPN provided the most accurate infestation-forecast predictions producing an AUC of 0.93, followed by multi-criteria evaluation (AUC = 0.92) and logistic regression (AUC = 0.86) when independently validating using post model infestation data. Results suggest that BPN can provide valuable insight into factors contributing to introduction for invasive species whose propagation and establishment requirements are not fully understood. The integration of anthropogenic and ecological variables allowed production of an accurate risk model and provided insight into the impact of human activities.

Ecological …, Jan 1, 2007

The southern Yucata´n contains the largest expanse of seasonal tropical forests remaining in Mexi... more The southern Yucata´n contains the largest expanse of seasonal tropical forests remaining in Mexico, forming an ecocline between the drier north of the peninsula and the humid Pete´n, Guatemala. The Calakmul Biosphere Reserve resides in the center of this region as part of the Mesoamerican Biological Corridor. The reserve's functions are examined in regard to land changes throughout the region, generated over the last 40 years by increasing settlement and the expansion and intensification of agriculture. These changes are documented from 1987/1988 to 2000, and their implications regarding the capacity of the reserve to protect the ecocline, forest habitats, and butterfly diversity are addressed. The results indicate that the current landscape matrix serves the biotic diversity of the reserve, with several looming caveats involving the loss of humid forests and the interruption of biota flow across the ecocline, and the amount and proximity of older forest patches beyond the reserve. The highly dynamic land cover changes underway in this economic frontier warrant an adaptive management approach that monitors the major changes underway in mature forest types, while the paucity of systematic ecological and environment-development studies is rectified in order to inform policy and practice.