Linking riparian vegetation spatial structure in Australian tropical savannas to ecosystem health indicators: semi-variogram analysis of high spatial resolution satellite imagery

Government agencies responsible for riparian environments are assessing the combined utility of field survey and remote sensing for mapping and monitoring indicators of riparian zone health. The objective of this work was to determine if the structural attributes of savanna riparian zones in northern Australia can be detected from commercially available remotely sensed image data. Two QuickBird images and coincident field data covering sections of the Daly River and the South Alligator River - Barramundie Creek in the Northern Territory were used. Semi-variograms were calculated to determine the characteristic spatial scales of riparian zone features, both vegetative and landform. Interpretation of semi-variograms showed that structural dimensions of riparian environments could be detected and estimated from the QuickBird image data. The results also show that selecting the correct spatial resolution and spectral bands is essential to maximize the accuracy of mapping spatial characteristics of savanna riparian features. The distribution of foliage projective cover of riparian vegetation affected spectral reflectance variations in individual spectral bands differently. Pan-sharpened image data enabled small-scale information extraction (< 6 m) on riparian zone structural parameters. The semi-variogram analysis results provide the basis for an inversion approach using high spatial resolution satellite image data to map indicators of savanna riparian zone health.

Combining spatially distributed predictions from neural networks

In this report we discuss the problem of combining spatially-distributed predictions from neural networks. An example of this problem is the prediction of a wind vector-field from remote-sensing data by combining bottom-up predictions (wind vector predictions on a pixel-by-pixel basis) with prior knowledge about wind-field configurations. This task can be achieved using the scaled-likelihood method, which has been used by Morgan and Bourlard (1995) and Smyth (1994), in the context of Hidden Markov modelling

Interactions between landcover pattern and geospatial processing methods:effects on landscape metrics and classification accuracy

Remote sensing data is routinely used in ecology to investigate the relationship between landscape pattern as characterised by land use and land cover maps, and ecological processes. Multiple factors related to the representation of geographic phenomenon have been shown to affect characterisation of landscape pattern resulting in spatial uncertainty. This study investigated the effect of the interaction between landscape spatial pattern and geospatial processing methods statistically; unlike most papers which consider the effect of each factor in isolation only. This is important since data used to calculate landscape metrics typically undergo a series of data abstraction processing tasks and are rarely performed in isolation. The geospatial processing methods tested were the aggregation method and the choice of pixel size used to aggregate data. These were compared to two components of landscape pattern, spatial heterogeneity and the proportion of landcover class area. The interactions and their effect on the final landcover map were described using landscape metrics to measure landscape pattern and classification accuracy (response variables). All landscape metrics and classification accuracy were shown to be affected by both landscape pattern and by processing methods. Large variability in the response of those variables and interactions between the explanatory variables were observed. However, even though interactions occurred, this only affected the magnitude of the difference in landscape metric values. Thus, provided that the same processing methods are used, landscapes should retain their ranking when their landscape metrics are compared. For example, highly fragmented landscapes will always have larger values for the landscape metric "number of patches" than less fragmented landscapes. But the magnitude of difference between the landscapes may change and therefore absolute values of landscape metrics may need to be interpreted with caution. The explanatory variables which had the largest effects were spatial heterogeneity and pixel size. These explanatory variables tended to result in large main effects and large interactions. The high variability in the response variables and the interaction of the explanatory variables indicate it would be difficult to make generalisations about the impact of processing on landscape pattern as only two processing methods were tested and it is likely that untested processing methods will potentially result in even greater spatial uncertainty. © 2013 Elsevier B.V.

Propuesta sostenible para mitigar los efectos climáticos adversos en una ciudad costera de Argentina

Los indicadores de sostenibilidad climática constituyen herramientas fundamentales para complementar las políticas de ordenamiento del territorio urbano y pueden beneficiar la calidad de vida sus habitantes. En el presente trabajo se diseñó un indicador climático urbano para la ciudad de Bahía Blanca considerando variables meteorológicas y análisis de la percepción social. El mismo permitió delimitar la ciudad en cuatro regiones bien diferenciadas entre sí. A partir de entonces, se realizó una propuesta sostenible para mitigar los efectos adversos del clima a partir de la aplicación del método DPSIR. Las mismas estuvieron destinadas a mejorar las condiciones de vida de la población. Los resultados permitieron considerar que una pronta implementación de la misma junto con una activa participación de los actores sociales y los tomadores de decisiones es necesaria para mejorar las condiciones actuales en la que se encuentra la ciudad. Con las medidas propuestas, la población local sabrá cómo actuar ante la ocurrencia de distintos eventos extremos, eventos de desconfort climático, etc. Al ser un método sencillo, la metodología aplicada en este estudio puede replicarse en otras ciudades del mundo con el objetivo de mejorar la calidad de vida de los habitantes.

Plant Migrations Impact on Potential Vegetation and Carbon Redistribution in Northern North America from Climate Change

Forests have a prominent role in carbon storage and sequestration. Anthropogenic forcing has the potential to accelerate climate change and alter the distribution of forests. How forests redistribute spatially and temporally in response to climate change can alter their carbon sequestration potential. The driving question for this research was: How does plant migration from climate change impact vegetation distribution and carbon sequestration potential over continental scales? Large-scale simulation of the equilibrium response of vegetation and carbon from future climate change has shown relatively modest net gains in sequestration potential, but studies of the transient response has been limited to the sub-continent or landscape scale. The transient response depends on fine scale processes such as competition, disturbance, landscape characteristics, dispersal, and other factors, which makes it computational prohibitive at large domain sizes. To address this, this research used an advanced mechanistic model (Ecosystem Demography Model, ED) that is individually based, but pseudo-spatial, that reduces computational intensity while maintaining the fine scale processes that drive the transient response. First, the model was validated against remote sensing data for current plant functional type distribution in northern North America with a current climatology, and then a future climatology was used to predict the potential equilibrium redistribution of vegetation and carbon from future climate change. Next, to enable transient calculations, a method was developed to simulate the spatially explicit process of dispersal in pseudo-spatial modeling frameworks. Finally, the new dispersal sub-model was implemented in the mechanistic ecosystem model, and a model experimental design was designed and completed to estimate the transient response of vegetation and carbon to climate change. The potential equilibrium forest response to future climate change was found to be large, with large gross changes in distribution of plant functional types and comparatively smaller changes in net carbon sequestration potential for the region. However, the transient response was found to be on the order of centuries, and to depend strongly on disturbance rates and dispersal distances. Future work should explore the impact of species-specific disturbance and dispersal rates, landscape fragmentation, and other processes that influence migration rates and have been simulated at the sub-continent scale, but now at continental scales, and explore a range of alternative future climate scenarios as they continue to be developed.

Metodologia de utilização de dados de sensoriamento remoto em zonas costeiras sob influência da indústria petrolífera

Oil spills in marine environments represent immediate environmental impacts of large magnitude. For that reason the Environmental Sensitivity to Oil Maps constitute a major instrument for planning actions of containment and cleanup. For both the Environmental Sensitivity Maps always need to be updated, to have an appropriate scale and to represent accurately the coastal areas. In this context, this thesis presents a methodology for collecting and processing remote sensing data for the purpose of updating the territorial basis of thematic maps of Environmental Sensitivity to Oil. To ensure greater applicability of the methodology, sensors with complementary characteristics, which provide their data at a low financial cost, were selected and tested. To test the methodology, an area located on the northern coast of the Northeast of Brazil was chosen. The results showed that the products of ASTER data and image hybrid sensor PALSAR + CCD and HRC + CCD, have a great potential to be used as a source of cartographic information on projects that seek to update the Environmental Sensitivity Maps of Oil

Typologies and spatialization of agricultural production systems in Rondônia, Brazil: linking land use, socioeconomics and territorial configuration.

The current Amazon landscape consists of heterogeneous mosaics formed by interactions between the original forest and productive activities. Recognizing and quantifying the characteristics of these landscapes is essential for understanding agricultural production chains, assessing the impact of policies, and in planning future actions. Our main objective was to construct the regionalization of agricultural production for Rondônia State (Brazilian Amazon) at the municipal level. We adopted a decision tree approach, using land use maps derived from remote sensing data (PRODES and TerraClass) combined with socioeconomic data. The decision trees allowed us to allocate municipalities to one of five agricultural production systems: (i) coexistence of livestock production and intensive agriculture; (ii) semi-intensive beef and milk production; (iii) semi-intensive beef production; (iv) intensive beef and milk production, and; (v) intensive beef production. These production systems are, respectively, linked to mechanized agriculture (i), traditional cattle farming with low management, with (ii) or without (iii) a significant presence of dairy farming, and to more intensive livestock farming with (iv) or without (v) a significant presence of dairy farming. The municipalities and associated production systems were then characterized using a wide variety of quantitative metrics grouped into four dimensions: (i) agricultural production; (ii) economics; (iii) territorial configuration, and; (iv) social characteristics. We found that production systems linked to mechanized agriculture predominate in the south of the state, while intensive farming is mainly found in the center of the state. Semi-intensive livestock farming is mainly located close to the southwest frontier and in the north of the state, where human occupation of the territory is not fully consolidated. This distributional pattern reflects the origins of the agricultural production system of Rondônia. Moreover, the characterization of the production systems provides insights into the pattern of occupation of the Amazon and the socioeconomic consequences of continuing agricultural expansion.

Proposta de modelagem de qualidade ambiental em áreas metropolitanas, por meio de dados de sensoriamento remoto

Tese (doutorado)—Universidade de Brasília, Instituto de Geociências, Pós-Graduação em Geociências Aplicadas, 2016.

FAULT MORPHOLOGY WITHIN THE SOUTHERN KENYAN PORTION OF THE EAST AFRICAN RIFT VALLEY

Faults form quickly, geologically speaking, with sharp, crisp step-like profiles. Logic dictates that erosion wears away this "sharpness" or angularity creating more rounded features. As erosion occurs, debris accumulates at the base of the scarp slope. The stable end point of this process is when the scarp slope approaches an ideal sigmoid shape. This theory of fault end process, in combination with a new method developed in this report for fault profile delineation, has the potential to enable observation and categorization of fault profiles over large, diverse swaths of fault formation-- in remote areas such as the Southern Kenyan Rift Valley. This up-to date method uses remote sensing data and the digitizer tool in Global Mapper to create shape files of fault segments. This method can provide further evidence to support the notion that sigmoidal- shaped profiles represent a natural endpoint of the erosional process of fault scarps. Over time, faults of many different ages would exist in this similar shape over a wide region. However, keeping in mind that other processes can be at work on scarps-- most notably drainage patterns, when anomalies in profiles are observed, reactivation in some form possibly has occurred.

Assessment of the Availability of Forest Biomass for Bioenergy Production in Southwest Portugal.

In 2014, Portugal was the seventh largest pellets producer in the World. Since the shortage of raw material is one of the major obstacles that the Portuguese sellets market faces, the need for a good assessment of biomass availability for energy purposes at both country and regional levels is reinforced. This work uses a Geographical Information System environment and remote sensing data to assess the availability and sustainability of forest biomass residues in a management unit with around 940 ha of maritime pine forest. The period considered goes from 2004 to 2015. The study area is located in Southwestern Portugal, close to a pellets factory; therefore the potential Contribution of the residual biomass generated in the management unit to the production of pellets is evaluated. An allometric function is used for the estimation of maritime pine above ground biomass. With this estimate, and considering several forest operations, the residual biomass available was assessed, according to stand composition and structure. This study shows that, when maritime pine forests are managed to produce wood, the amount of residues available for energy production is small (an average of 0.37 t ha -1  year -1 were generated in the study area between 2004 and 2015). As a contribution to the sustainability of the Portuguese pellets industries, new management models for maritime pine forests may be developed. The effect of the pinewood nematode on the availability of residual biomass can be clearly seen in this study. In the management unit considered, cuts were made to prevent dissemination of the disease. This contributes to a higher availability of forest residues in a specific period of time, but, in the medium term, they lead to a decrease in the amount of residues that can be used for energy purposes.

INTEGRACIÓN ESPACIAL Y ESPECTRAL DE IMÁGENES FOTOGRÁFICAS: EL CASO DE OROSI, PARAÍSO, CARTAGO – COSTA RICA

Los sensores remotos proveen imágenes que según sus características permiten determinar cambios en el uso de la tierra. Se han desarrollado sensores con alto potencial para llevar a cabo este tipo de trabajo, aunque en ocasiones es difícil tener todos los elementos para discriminar los objetos en una misma imagen, por ello recurrimos a transformaciones para la consecución de los objetivos. Este artículo constituye un subproducto del proyecto “Análisis de los cambios del uso de la tierra en el distrito de Orosi, utilizando datos teledetectados de los proyectos CENIGA1 (TERRA 97) y CARTA2 2003: período 1997-2003”. En el caso de Carta 2003 y Spot se presenta una coincidencia temporal pero no espacial ni espectral. El objetivo es ofrecer técnicas de transformación de imágenes fotográficas y multiespectrales del proyecto Carta 2003, así como una imagen de la plataforma del Spot. Las transformaciones de las imágenes permitieron cambiar la resolución espacial y espectral, las cuales variaban de 2 a 30 metros espacialmente y de 1 a 50 en su espectro. Para los objetivos de la investigación se seleccionaron 9 bandas a las cuales fue posible aplicarles las transformaciones. Se obtuvo resultante de 2 metros de resolución espacial y 9 bandas espectrales. Utilizando las resultantes se realizó la clasificación supervisada, con lo cual se obtuvo un mayor nivel de detalle en la delimitación de los diferentes usos presentes en el área de estudio. ABSTRACT Remote sensors supply images that, according to their characteristics, allow for determining changes in land use. Sensors have been developed with a high potential to carry out this type of work, although on occasion it is difficult to have all of the elements to distinguish the objects in the same image, and for that we resort to transformations to attain the objectives. This article constitutes a byproduct of the project: “Analysis of Land Use Changes in the District of Orosi, Using Remote Sensing Data of the Projects CENIGA (TERRA 97) and CARTA 2003: Period 1997-2003”. CARTA 2003 and Spot present temporary coincidence but not spatial or spectral. The objective is to offer techniques of transforming photographic images and multispectrals of the CARTA 2003 project, such as an image of the Spot platform. Transformation of the images allowed for changing the spatial and spectral resolution, which varied from 2 to 30 meters spatially and from 1 to 50 in their spectrum. For the objectives of the investigation, nine bands were selected to which it was possible to apply the transformations, and with them managed to obtain results of 2 meters of spatial resolution and 9 spectral bands. Utilizing the results, the supervised classification was realized, obtaining a greater level of detail in defining the different uses present in the area of study.

Hydrologic Dynamics of the Ground-Water-Dependent Sian Ka’an Wetlands, Mexico, Derived from InSAR and SAR Data

The 5,280 km2 Sian Ka’an Biosphere Reserve includes pristine wetlands fed by ground water from the karst aquifer of the Yucatan Peninsula, Mexico. The inflow through underground karst structures is hard to observe making it difficult to understand, quantify, and predict the wetland dynamics. Remotely sensed Synthetic Aperture Radar (SAR) amplitude and phase observations offer new opportunities to obtain information on hydrologic dynamics useful for wetland management. Backscatter amplitude of SAR data can be used to map flooding extent. Interferometric processing of the backscattered SAR phase data (InSAR) produces temporal phase-changes that can be related to relative water level changes in vegetated wetlands. We used 56 RADARSAT-1 SAR acquisitions to calculate 38 interferograms and 13 flooding maps with 24 day and 48 day time intervals covering July 2006 to March 2008. Flooding extent varied between 1,067 km2 and 2,588 km2 during the study period, and main water input was seen to take place in sloughs during October–December. We propose that main water input areas are associated with water-filled faults that transport ground water from the catchment to the wetlands. InSAR and Landsat data revealed local-scale water divides and surface water flow directions within the wetlands.