\u27It was all connected\u27: Understanding and addressing early school-leaving among learners of English as a second language

The goal of this research project, therefore, was to develop an understanding of the educational experiences of ESL youth so as to identify the facilitators and inhibitors of early school-leaving. Participants shared their recognition of the value of education. They also spoke of the ways in which negative interactions with teachers and peers, inflexible school practices and policies, financial responsibilities, lack of time, and perception of low levels of English-language proficiency negatively affected their educational experiences. Among the factors facilitating a positive educational experience were teachers who went out of their way to provide the youth with extra assistance and to integrate them into the school; peers who provided academic, linguistic, and social support; and limited or no financial responsibility. To the extent that the participants\u27 felt that their needs were met and they were integrated in the social and academic world of the school, they were facilitated in accessing the available educational opportunities

Modeling the distribution of a wide-ranging invasive species using the sampling efforts of expert and citizen scientists

1- Results for the models calibrated with <i>Weigted Pts</i> pseudo-absences for the paper 'Modelling the distribution of a wide-ranging invasive species using the sampling efforts of expert and citizen scientists'.<div>2- Final figure of the probability of distribution of rabbits in black and white.</div><div>3- Final figure of the probability of distribution of rabbits in ASC format.<br></div

Remote detection of invasive alien species

The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail

The comparison index: A tool for assessing the accuracy of image segmentation

Segmentation algorithms applied to remote sensing data provide valuable information about the size, distribution and context of landscape objects at a range of scales. However, there is a need for well-defined and robust validation tools to assessing the reliability of segmentation results. Such tools are required to assess whether image segments are based on ‘real’ objects, such as field boundaries, or on artefacts of the image segmentation algorithm. These tools can be used to improve the reliability of any land-use/land-cover classifications or landscape analyses that is based on the image segments.\ud \ud The validation algorithm developed in this paper aims to: (a) localize and quantify segmentation inaccuracies; and (b) allow the assessment of segmentation results on the whole. The first aim is achieved using object metrics that enable the quantification of topological and geometric object differences. The second aim is achieved by combining these object metrics into a ‘Comparison Index’, which allows a relative comparison of different segmentation results. The approach demonstrates how the Comparison Index CI can be used to guide trial-and-error techniques, enabling the identification of a segmentation scale H that is close to optimal. Once this scale has been identified a more detailed examination of the CI–H- diagrams can be used to identify precisely what H value and associated parameter settings will yield the most accurate image segmentation results.\ud \ud The procedure is applied to segmented Landsat scenes in an agricultural area in Saxony-Anhalt, Germany. The segmentations were generated using the ‘Fractal Net Evolution Approach’, which is implemented in the eCognition software

Supporting Mangrove Monitoring in Australia: A Role for TERN/AusCover.

Over the past few years, significant changes in mangroves have occurred across large areas of Australia, with these including extensive mangrove dieback (along much of the northern coastline) and cyclone damage (e.g., on the east coast). Such changes need to be detected as and when they occur and the recovery from such events monitored over extended periods. This paper therefore focuses on the formulation, development and implementation of a monitoring system, with key elements being routine detection of mangrove change (e.g., extent, health, species) using dense time-series of optical satellite data available within the Australian Geoscience Data Cube (AGDC) and C- and L-band SAR observations (in conjunction with global forest and mangrove monitoring systems), the collation of all publicly available field, drone and aircraft observations through TERN/AusCover and the collection of new datasets under common protocols, and the planning and facilitation of airborne and satellite missions to generate key high resolution baseline datasets against which to quantify change. For effective delivery and operation, whole of community involvement is essential through avenues such as the AMSN and the Australian Earth Observation Community Coordination Group (AEOCCG). All datasets and products also need to be made publically available to inform policy and enable coordinated scientific research

Addressing mangrove protection in Australia:The contribution of earth observation technologies

Significant changes in mangrove ecosystems have occurred across large areas of Australia over the last decade, with these including extensive mangrove dieback (along much of the northern coastline) and cyclone damage. Such changes need to be detected and quantified when they occur, and the recovery from such events monitored over extended periods to ascertain effectiveness of adaptive management strategies. This paper presents the conceptual basis for development and implementation of a monitoring system, with key elements being routine detection of mangrove change (e.g., extent, health, species) using dense time-series of optical satellite data available within the Australian Geoscience Data Cube (AGDC), the collation of all publicly available field, drone and aircraft observations through Australia's Terrestrial Ecosystem Research Network (TERN), and the acquisition of new datasets under common protocols. Datasets and products need to be open access to inform policy and enable coordinated scientific research