Umbrella pine above ground biomass estimation with very high spatial resolution satellite images

Above ground biomass is frequently estimated with forest inventory data and an extrapolation method for the per unit area evaluations. This procedure is labour demanding and costly. In this study above ground biomass functions, whose independent variable is crown horizontal projection, were developed. Multi-resolution segmentation method and object-oriented classification, based on very high spatial resolution satellite images, were used to obtain the area of tree crown horizontal projection for umbrella pine (Pinus pinea L.). A set of inventory plots were measured and with existing allometric functions for this species above ground biomass per tree and per plot were calculated. The two data sets were used to fit linear functions both for individual plot and their cumulative values. The results show a good performance of the models. Errors smaller than 10% are obtained for stand areas greater than 1.4 ha. These functions have the advantages of estimating above ground biomass for all the area under study or surveillance, not requiring forest inventory; allow monitoring in short time periods; and are easily implemented in a geographical information system environment.

Above ground biomass estimation in Mediterranean multiple use systems with high spatial resolution satellite images

Forest biomass has been having an increasing importance in the world economy and in the evaluation of the forests development and monitoring. It was identified as a global strategic reserve, due to its applications in bioenergy, bioproduct development and issues related to reducing greenhouse gas emissions. The estimation of above ground biomass is frequently done with allometric functions per species with plot inventory data. An adequate sampling design and intensity for an error threshold is required. The estimation per unit area is done using an extrapolation method. This procedure is labour demanding and costly. The mail goal of this study is the development of allometric functions for the estimation of above ground biomass with ground cover as independent variable, for forest areas of holm aok (Quercus rotundifolia), cork oak (Quercus suber) and umbrella pine (Pinus pinea) in multiple use systems. Ground cover per species was derived from crown horizontal projection obtained by processing high resolution satellite images, orthorectified, geometrically and atmospheric corrected, with multi-resolution segmentation method and object oriented classification. Forest inventory data were used to estimate plot above ground biomass with published allometric functions at tree level. The developed functions were fitted for monospecies stands and for multispecies stands of Quercus rotundifolia and Quercus suber, and Quercus suber and Pinus pinea. The stand composition was considered adding dummy variables to distinguish monospecies from multispecies stands. The models showed a good performance. Noteworthy is that the dummy variables, reflecting the differences between species, originated improvements in the models. Significant differences were found for above ground biomass estimation with the functions with and without the dummy variables. An error threshold of 10% corresponds to stand areas of about 40 ha. This method enables the overall area evaluation, not requiring extrapolation procedures, for the three species, which occur frequently in multispecies stands.

Use of Coarse-resolution models of species' distributions to guide local conservation inferences

Distribution models are used increasingly for species conservation assessments over extensive areas, but the spatial resolution of the modeled data and, consequently, of the predictions generated directly from these models are usually too coarse for local conservation applications. Comprehensive distribution data at finer spatial resolution, however, require a level of sampling that is impractical for most species and regions. Models can be downscaled to predict distribution at finer resolutions, but this increases uncertainty because the predictive ability of models is not necessarily consistent beyond their original scale. We analyzed the performance of downscaled, previously published models of environmental favorability (a generalized linear modeling technique) for a restricted endemic insectivore, the Iberian desman (Galemys pyrenaicus), and a more widespread carnivore, the Eurasian otter ( Lutra lutra), in the Iberian Peninsula. The models, built from presence–absence data at 10 × 10 km resolution, were extrapolated to a resolution 100 times finer (1 × 1 km). We compared downscaled predictions of environmental quality for the two species with published data on local observations and on important conservation sites proposed by experts. Predictions were significantly related to observed presence or absence of species and to expert selection of sampling sites and important conservation sites. Our results suggest the potential usefulness of downscaled projections of environmental quality as a proxy for expensive and time-consuming field studies when the field studies are not feasible. This method may be valid for other similar species if coarse-resolution distribution data are available to define high-quality areas at a scale that is practical for the application of concrete conservation measures

Otter (Lutra lutra) distribution modeling at two resolution scales suited to conservation planning in the Iberian Peninsula

We used the results of the Spanish Otter Survey of 1994–1996, a Geographic Information System and stepwise multiple logistic regression to model otter presence/absence data in the continental Spanish UTM 10 10-km squares. Geographic situation, indicators of human activity such as highways and major urban centers, and environmental variables related with productivity, water availability, altitude, and environmental energy were included in a logistic model that correctly classified about 73% of otter presences and absences. We extrapolated the model to the adjacent territory of Portugal, and increased the model’s spatial resolution by extrapolating it to 1 1-km squares in the whole Iberian Peninsula. The model turned out to be rather flexible, predicting, for instance, the species to be very restricted to the courses of rivers in some areas, and more widespread in others. This allowed us to determine areas where otter populations may be more vulnerable to habitat changes or harmful human interventions. # 2003 Elsevier Ltd. All rights reserved.

Favourable areas for expansion and reintroduction of Iberian lynx accounting for distribution trends and genetic diversity of the European rabbit

Although on a local scale Iberian lynx distribution is determined by the availability of prey rabbits, recent modelling analyses have uncovered broad-scale disagreements between these two species’ distribution trends. These analyses showed also that the lynx had become restricted to only a fraction of the rabbit’s genetic diversity, and that this could be jeopardising its survival in the face of environmental hazards and uncertainty. In the present paper, a follow-up was carried out through the building of lynx and rabbit distribution models based on the most recent Spanish mammal atlas. Environmental favourability values for lynx and rabbit were positively correlated within the lynx’s current distribution area, but they were negatively correlated within the total Spanish area where lynx used to occur in the 1980’s. Environmental favourability for rabbits was significantly higher where lynx maintains reproductive populations than where it recently disappeared, indicating that rabbit favourability plays an important role and can be a good predictor of lynx persistence. The lynx and rabbit models were extrapolated to predict favourable areas for both species in Spain as well as in Portugal, on the original scale of the distribution data (10x10 km) and on a 100 times finer spatial resolution (1x1 km). The lynx and rabbit models were also combined through fuzzy logic to forecast the potential for lynx occurrence incorporating information on favourable areas for its main prey. Several areas are proposed as favourable for lynx expansion or re-introduction,

Above ground biomass functions with vegetation indices for multiple use systems of two evergreen oaks

Remote sensing is a promising approach for above ground biomass estimation, as forest parameters can be obtained indirectly. The analysis in space and time is quite straight forward due to the flexibility of the method to determine forest crown parameters with remote sensing. It can be used to evaluate and monitoring for example the development of a forest area in time and the impact of disturbances, such as silvicultural practices or deforestation. The vegetation indices, which condense data in a quantitative numeric manner, have been used to estimate several forest parameters, such as the volume, basal area and above ground biomass. The objective of this study was the development of allometric functions to estimate above ground biomass using vegetation indices as independent variables. The vegetation indices used were the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Simple Ratio (SR) and Soil-Adjusted Vegetation Index (SAVI). QuickBird satellite data, with 0.70 m of spatial resolution, was orthorectified, geometrically and atmospheric corrected, and the digital number were converted to top of atmosphere reflectance (ToA). Forest inventory data and published allometric functions at tree level were used to estimate above ground biomass per plot. Linear functions were fitted for the monospecies and multispecies stands of two evergreen oaks (Quercus suber and Quercus rotundifolia) in multiple use systems, montados. The allometric above ground biomass functions were fitted considering the mean and the median of each vegetation index per grid as independent variable. Species composition as a dummy variable was also considered as an independent variable. The linear functions with better performance are those with mean NDVI or mean SR as independent variable. Noteworthy is that the two better functions for monospecies cork oak stands have median NDVI or median SR as independent variable. When species composition dummy variables are included in the function (with stepwise regression) the best model has median NDVI as independent variable. The vegetation indices with the worse model performance were EVI and SAVI.

EFEITOS DE CENÁRIOS DE USO DO SOLO NA VAZÃO E PRODUÇÃO DE SEDIMENTOS NA BACIA DO RIO COBRES, PORTUGAL

Introdução Caracterização da área de estudo Materiais e métodos O modelo SWAT Dados de chuva, vazão e produção de sedimentos Tipos de solos e determinação dos parâmetros do SWAT Análises Estatísticas Cenários de Uso do Solo Resultados e discussões Estimativa da Vazão Estimativa da produção de sedimentos Modelagem Hidrossedimentológica em Diferentes Cenários Conclusões Referências bibliográficas RESUMO – A erosão dos solos é um dos mais graves problemas ambientais em todo o mundo, principalmente em regiões semiáridas que sofrem com a variabilidade espaço-temporal da precipitação. Este artigo analisou os processos hidrossedimentológicos na Bacia do Rio Cobres, localizada na porção semiárida de Portugal, utilizando o modelo SWAT. Neste estudo foram utilizados dados diários de precipitação, temperatura, umidade do ar, vazão e produção de sedimentos, para o período de 1960 a 2000, mapas digitais de elevação do terreno com resolução espacial de 90 m, uso e ocupação do solo e tipos de solo da bacia. Os resultados demonstraram a eficácia do modelo na calibração da vazão, com Coeficiente de Determinação (R²) = 0,81 e Coeficiente de Nash-Sutcliffe (NS) = 0,63, e também para produção de sedimentos com R² = 0,62 e NS = 0,47. O Cenário 3 (Mata) apresentou o maior decréscimo na vazão média, em relação aos Cenários 1 (Real) e 2 (Pastagem). Conclui-se que o modelo SWAT acoplado ao SIG é uma ferramenta poderosa na análise espaço-temporal do comportamento dos processos hidrossedimentológicos. Palavas-chave: SIG, modelo hidrossedimentológico, erosão ABSTRACT – Effects of Scenarios of Land Use on Runoff and Sediment Yield for Cobres River Basin, Portugal. Soil erosion is a major environmental problem worldwide, mainly in semiarid regions that suffer with rainfall spatial and temporal variability. Thus, this paper analysed the runoff-erosion process at the Cobres River Basin, located in semiarid portion of Portugal, using the SWAT model. In this paper, rainfall, temperature and humidity data from 1960 to 2000, and digital maps of land cover, terrain digital elevation model with spatial resolution of 90 m, soil types were used. The results showed the effectiveness of the model for the runoff calibration, with R² = 0.81 and NS = 0.63, and also for sediment yield with R² = 0.62 and NS = 0.47. Scenario 1 (Forest) had the highest decrease in average streamflow, in relation to the Scenarios 1 (Real) and 2 (Pasture) scenarios. It is concluded that the SWAT model coupled to GIS is a powerful tool in the analysis of temporal and spatial behaviour of runoff-erosion processes.