Global burned-land estimation in Latin America using MODIS composite data

This paper presents results of the AQL2004 project, which has been develope within the GOFC-GOLD Latin American network of remote sensing and forest fires (RedLatif). The project intended to obtain monthly burned-land maps of the entire region, from Mexico to Patagonia, using MODIS (moderate-resolution imaging spectroradiometer) reflectance data. The project has been organized in three different phases: acquisition and preprocessing of satellite data; discrimination of burned pixels; and validation of results. In the first phase, input data consisting of 32-day composites of MODIS 500-m reflectance data generated by the Global Land Cover Facility (GLCF) of the University of Maryland (College Park, Maryland, U.S.A.) were collected and processed. The discrimination of burned areas was addressed in two steps: searching for "burned core" pixels using postfire spectral indices and multitemporal change detection and mapping of burned scars using contextual techniques. The validation phase was based on visual analysis of Landsat and CBERS (China-Brazil Earth Resources Satellite) images. Validation of the burned-land category showed an agreement ranging from 30% to 60%, depending on the ecosystem and vegetation species present. The total burned area for the entire year was estimated to be 153 215 km2. The most affected countries in relation to their territory were Cuba, Colombia, Bolivia, and Venezuela. Burned areas were found in most land covers; herbaceous vegetation (savannas and grasslands) presented the highest proportions of burned area, while perennial forest had the lowest proportions. The importance of croplands in the total burned area should be taken with reserve, since this cover presented the highest commission errors. The importance of generating systematic products of burned land areas for different ecological processes is emphasized.

Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data

The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

What does global mean temperature tell us about local climate?

The subject of climate feedbacks focuses attention on global mean surface air temperature (GMST) as the key metric of climate change. But what does knowledge of past and future GMST tell us about the climate of specific regions? In the context of the ongoing UNFCCC process, this is an important question for policy-makers as well as for scientists. The answer depends on many factors, including the mechanisms causing changes, the timescale of the changes, and the variables and regions of interest. This paper provides a review and analysis of the relationship between changes in GMST and changes in local climate, first in observational records and then in a range of climate model simulations, which are used to interpret the observations. The focus is on decadal timescales, which are of particular interest in relation to recent and near-future anthropogenic climate change. It is shown that GMST primarily provides information about forced responses, but that understanding and quantifying internal variability is essential to projecting climate and climate impacts on regional-to-local scales. The relationship between local forced responses and GMST is often linear but may be nonlinear, and can be greatly complicated by competition between different forcing factors. Climate projections are limited not only by uncertainties in the signal of climate change but also by uncertainties in the characteristics of real-world internal variability. Finally, it is shown that the relationship between GMST and local climate provides a simple approach to climate change detection, and a useful guide to attribution studies.

A new screen face for public service broadcasting

The contemporary broadcasting industry is characterised by technological and social change, it is increasingly competitive, and the media industry is fragmenting. New services need not necessarily compete with existing free-to-air broadcasting but could act as further incentive for audiences to invest in new equipment. New equipment will be necessary in the future as set out under the Television Broadcasting Services (Digital Conversion) Act 2000 (Cth), before the planned switch-off of analogue broadcasts planned for this year but now likely to be 2013. By then, however, audiences might already have migrated to the online environment for television and radio content as well as other services. Those that produce and deliver programs via free-to-air broadcasting need to consider what audiences do with new media in order to engage them. This will be an ongoing process as technology and audience expectations continue to change. Against such a background, this article examines how Australia’s public broadcasters are responding to the new media environment. It will consider their interactive online programs and services with specific analysis of ABC’s new ‘iView’ and ‘ABC Fora’ which offer content on-demand. It will also examine SBS online initiatives. I wish to argue that the new media offer public broadcasters new prospects to provide forums and spaces for education, entertainment, public discussion and interaction online.

Human factors in cargo X-ray examination systems

The project investigated factors which may determine operator performance in X-ray screening of cargo, which is of similar importance to aviation security screening. A target detection paradigm showed significant difference in several measures of performance between baggage and postal contexts which provides evidence that these may constitute separate expertise domains.

The impact of emerging technology in sport broadcasting on the preconditions for interorganizational relationship (IOR) formation in professional football

Environmental factors such as emerging technology, globalization, economic reform and social change are creating a background in which sporting organizations must seek to quickly adapt to manage their ongoing activities and operations. Focusing on emerging technology in the area of sport broadcasting, this research examined six preconditions for interorganizational relationship (IOR) formation from the perspective of professional football clubs in Australia. Based upon theories derived from the IOR literature, these six preconditions for IOR formation were considered to determine if emerging broadcasting technologies impact on IOR formation between Australian Football League (AFL) and National Rugby League (NRL) clubs and broadcasters. Semistructured in-depth interviews with senior managers of 11 AFL, and 10 NRL clubs were undertaken and data analyzed, coded and emergent themes identified. Results indicate that professional club managers display most of these attributes that precipitate the preconditions for IOR formation, but although these preconditions exist, there is little willingness by the clubs to formulate IORs with sport broadcasters.

Integrating time-series hydroacoustics and video observations for detecting changes in benthic habitats

The ability to quantify change in marine benthic habitats must be considered a key goal of marine habitat mapping activities. Changes in distribution of distinct suites of benthic biological species may occur as a result of natural or human induced processes and these processes may operate at a range of temporal and spatial scales. It is important to understand natural small scale inter-annual patterns of change in order to separate these signals from potential patterns of longer term change. Work to describe these processes of change from an acoustic remote sensing stand point has thus far been limited due to the relatively recent availability of full coverage swath acoustic datasets and cost pressures associated with multiple surveys of the same area. This paper describes the use of landscape transition analysis as a means to differentiate seemingly random patterns of habitat change from systematic signals of habitat transition at a shallow (10–50 m depth) 18 km2 study area on the temperate Australian continental shelf between the years 2006 and 2007. Supervised classifications for each year were accomplished using independently collected high resolution (3 m cell-size) multibeam echosounder (MBES) and video-derived reference data. Of the 4 representative biotic classes considered, signals of directional systematic changes were observed to occur between a shallow kelp dominated class, a deep sessile invertebrate dominated class and a mixed class of kelp and sessile invertebrates. These signals of change are interpreted as inter-annual variation in the density and depth related extent of canopy forming kelp species at the site, a phenomenon reported in smaller scale temporal studies of the same species. The methods applied in this study provide a detailed analysis of the various components of the traditional change detection cross tabulation matrix allowing identification of the strongest signals of systematic habitat transitions across broad geographical regions. Identifying clear patterns of habitat change is an important first step in linking these patterns to the processes that drive them.

Passenger monitoring in moving bus video

In this paper, we present a novel person detection system for public transport buses tackling the problem of changing illumination conditions. Our approach integrates a stable SIFT (Scale Invariant Feature Transform) background seat modeling mechanism with a human shape model into a weighted Bayesian framework to detect passengers on-board buses. SIFT background modeling extracts local stable features on the pre-annotated background seat areas and tracks these features over time to build a global statistical background model for each seat. Since SIFT features are partially invariant to lighting, this background model can be used robustly to detect the seat occupancy status even under severe lighting changes. The human shape model further confirms the existence of a passenger when a seat is occupied. This constructs a robust passenger monitoring system which is resilient to illumination changes. We evaluate the performance of our proposed system on a number of challenging video datasets obtained from bus cameras and the experimental results show that it is superior to state-of-art people detection systems.

Corner inlet and Nooramunga habitat mapping project

Deakin University and the University of Tasmania were commissioned by Parks Victoria (PV) to create two updated habitat maps for areas within the Corner Inlet and Nooramunga Marine and Coastal Park and Ramsar area. The team obtained a ground-truth data set using in situ video and still photographs. This dataset was used to develop and assess predictive models of benthic marine habitat distributions incorporating data from both ALOS (Advanced Land Observation Satellite) imagery atmospherically corrected by CSIRO and LiDAR (Light Detection and Ranging) bathymetry. This report describes the results of the mapping effort as well as the methodology used to produce these habitat maps.

Overall accuracies of habitat classifications were good, returning overall accuracies >73 % and kappa values > 0.62 for both study localities. Habitats predicted with highest accuracies included Zosteraceae in Nooramunga (91 %), reef in Corner Inlet (80 %), and bare sediment (no-visible macrobiota/no-visible seagrass classes; both > 76 %). The majority of classification errors were due to the misclassification of areas of sparse seagrass as bare sediment. For the Corner Inlet study locality the no-visible macrobiota (10,698 ha), Posidonia (4,608 ha) and Zosteraceae (4,229 ha) habitat classes covered the most area. In Nooramunga no-visible seagrass (5,538 ha), Zosteraceae (4,060 ha) and wet saltmarsh (1,562 ha) habitat classes were most dominant.

In addition to the commissioned work preliminary change detection analyses were undertaken as part of this project. These analyses indicated shifts in habitat extents in both study localities since the late 1990s/2000. In particular, a post-classification analysis highlighted that there were considerable increases in seagrass habitat (primarily Zosteraceae) throughout the littoral zones and river/creek mouths of both study localities. Further, the numerous channel systems remained stable and were free of seagrass at both times. A substantial net loss of Posidonia in the Corner Inlet locality is likely but requires further investigation due to potential misclassifications between habitats in both the 1998 map (Roob et al. 1998) and the current mapping. While the unsupervised Independent Components Analysis (ICA) change detection technique indicated some changes in habitat extent and distribution, considerable areas of habitat change observed in the post-classification approach are questionable, and may reflect misclassifications rather than real change. A particular example of this is an apparent large decrease in Zosteraceae and increase in Posidonia being related to the classification of Posidonia beds as Zosteraceae in the 1998 mapping. Despite this, we believe that changes indicated by both the ICA and post-classification approaches have a high likelihood of being ‘actual’ change. A pattern of gains and losses of Zosteraceae in the region north of Stockyard channel is an example of this. Further analyses and refinements of approaches in change detection analyses such as would improve confidence in the location and extent of habitat changes over this time period.

This work has been successful in providing new baseline maps using a repeatable method meaning that any future changes in intertidal and shallow water marine habitats may be assessed in a consistent way with quantitative error assessments. In wider use, these maps should also allow improved conservation planning, advance fisheries and catchment management, and progress infrastructure planning to limit impacts on the Inlet environment.

Monitoring protected areas using remote sensing technology

Due to irrational use of natural resources, human society is facing unprecedented threats. Remote sensing is one of the essential tools to determine changes in various forms of biological diversity over time. There are many methods to determine changes in protected areas, using satellite images. In this paper after introducing different change detection methods and their advantages and disadvantages, a hybrid method is used to analyse changes in forests and protected areas in a national park. Two Landsat images of Golestan National Park in Iran (taken in 1998 and 2010) were used. This hybrid approach combines Change Vector Analysis (CVA) for flagging the occurrence of changes, followed by signature extension to assign labels to changedpixels. The main objective of this paper is to propose a method for discovering and assessing environmental threats to natural treasures.

A new perspective of storm bite on sandy beaches using unmanned aerial vehicles

Aerial imagery collected before and after major storm events is ideal for the assessment of coastal landscape change driven by individual high-magnitude events. Using traditional satellite sensors and manned aerial systems can be challenging due to issues related to cloud cover, mobilization expenses and resolution. Rapid advances in unmanned aerial vehicle (UAV) technology allow for the cost-effective collection of aerial imagery and topography at centimetre resolution suitable for assessing change in coastal ecosystems. In this study we demonstrate the utility of UAV-based photogrammetry to quantify storm-driven sediment dynamics on a sandy beach on the open-coast shoreline of Victoria, Australia. UAV-based aerial photography was collected before and after a major storm event. High-resolution (< 5 cm) aerial imagery and digital surface models were acquired and change-detection techniques were applied to quantify changes in the beachface. An average beach erosion of 12.24 m3/m with a maximum of 28.05 m3/m was observed, and the volume of sand cut from the beachface and retreat of the foredune are clearly illustrated. Following the storm event, erosion was estimated at 7259.94 ± 503.69 m3 along 550 m of beach. By combining the aerial imagery and derived topographic datasets we demonstrate the advantage of UAV-based photogrammetry techniques for rapid high-resolution data collection in semi-remote locations. Its utility in setting unlimited virtual vantage points is also illustrated and the valuable perspective it provides for tracking landscape change discussed.

A new short and simple health-related quality of life measurement for paediatric rheumatic diseases: initial validation in juvenile idiopathic arthritis

Objective. To develop and validate a new short and simple measure of health-related quality of life (HRQL) in children with juvenile idiopathic arthritis (JIA).Methods. The Paediatric Rheumatology Quality of Life Scale (PRQL) is a 10-item questionnaire that explores HRQL in two domains: physical health (PhH) and psychosocial health (PsH). Validation of the parent proxy report and child self-report versions of the instrument was accomplished by evaluating 472 JIA patients and similar to 800 healthy children. Validation analyses included assessment of feasibility, face and content validity; construct and discriminative ability; internal structure and consistency; test-retest reliability; responsiveness to clinical change; and minimal clinically important difference.Results. The PRQL was found to be feasible and to possess both face and content validity. The PRQL score correlated in the predicted range with most of the other JIA outcome measures, thereby demonstrating good construct validity, and discriminated well between different levels of disease severity. Assessment of internal structure (factor analysis) revealed that the PhH and PsH subscales identify two unambiguously separated domains. The internal consistency (Cronbach's alpha) was 0.86. The intraclass correlation coefficient for test-retest reliability was 0.91. The PRQL revealed fair responsiveness, with a standardized response mean of 0.67 in improved patients. Overall, the PRQL appeared to be more able to capture physical HRQL than psychosocial HRQL.Conclusion. The PRQL was found to possess good measurement properties and is, therefore, a valid instrument for the assessment of HRQL in children with JIA. This tool is primarily proposed for use in standard clinical care.

Georeferenced road extraction and formulation of hypotheses for new road segments

The acquisition and update of Geographic Information System (GIS) data are typically carried out using aerial or satellite imagery. Since new roads are usually linked to georeferenced pre-existing road network, the extraction of pre-existing road segments may provide good hypotheses for the updating process. This paper addresses the problem of extracting georeferenced roads from images and formulating hypotheses for the presence of new road segments. Our approach proceeds in three steps. First, salient points are identified and measured along roads from a map or GIS database by an operator or an automatic tool. These salient points are then projected onto the image-space and errors inherent in this process are calculated. In the second step, the georeferenced roads are extracted from the image using a dynamic programming (DP) algorithm. The projected salient points and corresponding error estimates are used as input for this extraction process. Finally, the road center axes extracted in the previous step are analyzed to identify potential new segments attached to the extracted, pre-existing one. This analysis is performed using a combination of edge-based and correlation-based algorithms. In this paper we present our approach and early implementation results.

Proposta de atualização de cadastro urbano a partir de detecção de alterações em imagens QUICK BIRD tomadas em diferentes épocas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análise das pressões do uso e ocupação da terra sobre trecho da faixa de dutos Rio - Belo Horizonte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)