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  • 1
    In: AGU Advances, American Geophysical Union (AGU), Vol. 4, No. 4 ( 2023-08)
    Abstract: Novel methods of teaching must be used in the cloud‐based Earth observation (EO) paradigm The Earth Engine Education community is a valuable example of teaching and learning in the new cloud‐based EO paradigm Cloud‐based EO science must prioritize teaching fundamentals, ethics, and engagement with the broader field
    Type of Medium: Online Resource
    ISSN: 2576-604X , 2576-604X
    Language: English
    Publisher: American Geophysical Union (AGU)
    Publication Date: 2023
    detail.hit.zdb_id: 3008306-0
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  • 2
    In: Remote Sensing of Environment, Elsevier BV, Vol. 268 ( 2022-01), p. 112741-
    Type of Medium: Online Resource
    ISSN: 0034-4257
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2022
    detail.hit.zdb_id: 1498713-2
    SSG: 11
    SSG: 14
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  • 3
    Online Resource
    Online Resource
    MDPI AG ; 2020
    In:  Remote Sensing Vol. 12, No. 4 ( 2020-02-20), p. 688-
    In: Remote Sensing, MDPI AG, Vol. 12, No. 4 ( 2020-02-20), p. 688-
    Abstract: Landsat 5 has produced imagery for decades that can now be viewed and manipulated in Google Earth Engine, but a general, automated way of producing a coherent time series from these images—particularly over cloudy areas in the distant past—is elusive. Here, we create a land use and land cover (LULC) time series for part of tropical Mato Grosso, Brazil, using the Bayesian Updating of Land Cover: Unsupervised (BULC-U) technique. The algorithm built backward in time from the GlobCover 2009 data set, a multi-category global LULC data set at 300 m resolution for the year 2009, combining it with Landsat time series imagery to create a land cover time series for the period 1986–2000. Despite the substantial LULC differences between the 1990s and 2009 in this area, much of the landscape remained the same: we asked whether we could harness those similarities and differences to recreate an accurate version of the earlier LULC. The GlobCover basis and the Landsat-5 images shared neither a common spatial resolution nor time frame, But BULC-U successfully combined the labels from the coarser classification with the spatial detail of Landsat. The result was an accurate fine-scale time series that quantified the expansion of deforestation in the study area, which more than doubled in size during this time. Earth Engine directly enabled the fusion of these different data sets held in its catalog: its flexible treatment of spatial resolution, rapid prototyping, and overall processing speed permitted the development and testing of this study. Many would-be users of remote sensing data are currently limited by the need to have highly specialized knowledge to create classifications of older data. The approach shown here presents fewer obstacles to participation and allows a wide audience to create their own time series of past decades. By leveraging both the varied data catalog and the processing speed of Earth Engine, this research can contribute to the rapid advances underway in multi-temporal image classification techniques. Given Earth Engine’s power and deep catalog, this research further opens up remote sensing to a rapidly growing community of researchers and managers who need to understand the long-term dynamics of terrestrial systems.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2020
    detail.hit.zdb_id: 2513863-7
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  • 4
    In: Ecology and Society, Resilience Alliance, Inc., Vol. 20, No. 4 ( 2015)
    Type of Medium: Online Resource
    ISSN: 1708-3087
    Language: English
    Publisher: Resilience Alliance, Inc.
    Publication Date: 2015
    detail.hit.zdb_id: 2647724-5
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  • 5
    Online Resource
    Online Resource
    Chelonian Conservation and Biology Journal ; 2011
    In:  Chelonian Conservation and Biology Vol. 10, No. 2 ( 2011-12), p. 259-265
    In: Chelonian Conservation and Biology, Chelonian Conservation and Biology Journal, Vol. 10, No. 2 ( 2011-12), p. 259-265
    Type of Medium: Online Resource
    ISSN: 1071-8443
    Language: English
    Publisher: Chelonian Conservation and Biology Journal
    Publication Date: 2011
    detail.hit.zdb_id: 2365033-3
    SSG: 12
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  • 6
    Online Resource
    Online Resource
    Elsevier BV ; 2013
    In:  Ecological Informatics Vol. 15 ( 2013-05), p. 14-21
    In: Ecological Informatics, Elsevier BV, Vol. 15 ( 2013-05), p. 14-21
    Type of Medium: Online Resource
    ISSN: 1574-9541
    Language: English
    Publisher: Elsevier BV
    Publication Date: 2013
    detail.hit.zdb_id: 2218079-5
    SSG: 12
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  • 7
    Online Resource
    Online Resource
    MDPI AG ; 2018
    In:  Remote Sensing Vol. 10, No. 9 ( 2018-09-12), p. 1455-
    In: Remote Sensing, MDPI AG, Vol. 10, No. 9 ( 2018-09-12), p. 1455-
    Abstract: Remote sensing is undergoing a fundamental paradigm shift, in which approaches interpreting one or two images are giving way to a wide array of data-rich applications. These include assessing global forest loss, tracking water resources across Earth’s surface, determining disturbance frequency across decades, and many more. These advances have been greatly facilitated by Google Earth Engine, which provides both image access and a platform for advanced analysis techniques. Within the realm of land-use/land-cover (LULC) classifications, Earth Engine provides the ability to create new classifications and to access major existing data sets that have already been created, particularly at global extents. By overlaying global LULC classifications—the 300-m GlobCover 2009 LULC data set for example—with sharper images like those from Landsat, one can see the promise and limits of these global data sets and platforms to fuse them. Despite the promise in a global classification covering all of the terrestrial surface, GlobCover 2009 may be too coarse for some applications. We asked whether the LULC labeling provided by GlobCover 2009 could be combined with the spatial granularity of the Landsat platform to produce a hybrid classification having the best features of both resources with high accuracy. Here we apply an improvement of the Bayesian Updating of Land Cover (BULC) algorithm that fused unsupervised Landsat classifications to GlobCover 2009, sharpening the result from a 300-m to a 30-m classification. Working with four clear categories in Mato Grosso, Brazil, we refined the resolution of the LULC classification by an order of magnitude while improving the overall accuracy from 69.1 to 97.5%. This “BULC-U” mode, because it uses unsupervised classifications as inputs, demands less region-specific knowledge from analysts and may be significantly easier for non-specialists to use. This technique can provide new information to land managers and others interested in highly accurate classifications at finer scales.
    Type of Medium: Online Resource
    ISSN: 2072-4292
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2513863-7
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  • 8
    Online Resource
    Online Resource
    MDPI AG ; 2018
    In:  Land Vol. 7, No. 4 ( 2018-11-15), p. 137-
    In: Land, MDPI AG, Vol. 7, No. 4 ( 2018-11-15), p. 137-
    Abstract: At present, 10.5% of Canada’s land base is under some form of formal protection. Recent developments indicate Canada aims to work towards a target of protecting 17% of its terrestrial and inland water area by 2020. Canada is uniquely positioned globally as one of the few nations that has the capacity to expand the area under its protection. In addition to its formally protected areas, Canada’s remote regions form de facto protected areas that are relatively free from development pressure. Opportunities for expansion of formally protected areas in Canada include official delineation and designation of de facto protected areas and the identification and protection of land to improve connectivity between protected areas (PAs). Furthermore, there are collaborative opportunities for expanding PA through commitments from industry and provincial and territorial land stewards. Other collaborative opportunities include the contributions of First Nations aligning with international examples of Indigenous Protected Areas, or the incorporation and cultivation of private protection programs with documented inclusion in official PA networks. A series of incremental additions from multiple actors may increase the likelihood for achieving area-based targets, and expands stakeholder engagement and representation in Canada’s PA system. Given a generational opportunity and high-level interest in expansion of protected areas in Canada and elsewhere, it is evident that as a diverse number of stakeholders and rights holders collaboratively map current and future land uses onto forest landscapes, science-based conservation targets and spatial prioritizations can inform this process.
    Type of Medium: Online Resource
    ISSN: 2073-445X
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2682955-1
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  • 9
    Online Resource
    Online Resource
    Canadian Science Publishing ; 2014
    In:  Environmental Reviews Vol. 22, No. 2 ( 2014-06), p. 135-160
    In: Environmental Reviews, Canadian Science Publishing, Vol. 22, No. 2 ( 2014-06), p. 135-160
    Abstract: Boreal forests maintain regionally important biodiversity and globally important ecosystem services, such as carbon storage and freshwater resources. Many boreal systems have limited anthropogenic disturbances and are preserved, in effect, to date largely by their harsh climates and remoteness. As of 2011, almost 10% of Canada is subject to some manner of formal protection, with 4.5% of this protected area found within the boreal zone. The management of existing parks and protected areas (PPAs) is shared amongst many federal, provincial, and territorial jurisdictions. Although there are currently low levels of anthropogenic development in some portions of the boreal zone (especially the north), if expansion of protected areas is of interest, there are challenges to traditional PPA networks that may be more prominent in the boreal zone than elsewhere: (1) the boreal zone is home to charismatic mammal species with area requirements much larger than typical PPAs; (2) the boreal zone is characterized by natural disturbance regimes that impact large areas; and (3) projected changes to climate for the boreal zone are among the greatest in the world, creating temporal considerations for conservation planning exercises. There is currently no PPA assessment specific to boreal Canada. To address this lack of an assessment, we developed a conservation gap analysis of the current PPA system with respect to a variety of environmental surrogates (ecozones, land cover, vegetation productivity, and landscape structure). The amount of formally protected land varied within each surrogate, with few commonly reported features meeting national or international conservation targets. Furthermore, few reserves met the areal requirements that have been previously recommended to protect large mammals or accommodate the disturbance regimes present. We also discuss considerations and implications of area-based versus value-based protection objectives. While recognizing that there are still scientific challenges around understanding and evaluating the effectiveness of PPAs, based upon our review and assessment, the following considerations should inform conservation options for the boreal zone: (1) representation of the distribution of natural features within the PPA network; (2) effective maintenance of habitat requirements and spatial resilience to both cyclical and directional changes in spatial patterns through large, connected reserves; and (3) implementation of sustainable forest management practices (where applicable) throughout the broader landscape, as traditional on-reserve protection is unlikely to be sufficient to meet conservation goals. The Canadian boreal is unique in possessing large tracts of inaccessible forested lands that are not subject to management interventions, thereby offering functions similar to protected lands. The question of how to more formally integrate these lands into the existing PPA network requires further consideration. Further, the important temporal role of landscape dynamics in designing an effective PPA needs to be further studied as well as development of a better understanding of design needs in the context of a changing climate.
    Type of Medium: Online Resource
    ISSN: 1181-8700 , 1208-6053
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2014
    detail.hit.zdb_id: 2027518-3
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  • 10
    In: Canadian Journal of Fisheries and Aquatic Sciences, Canadian Science Publishing, Vol. 77, No. 5 ( 2020-05), p. 869-881
    Abstract: Horizon scanning is a systematic approach increasingly used to explore emerging trends, issues, opportunities, and threats in conservation. We present the results from one such exercise aimed at identifying emerging issues that could have important scientific, social, technological, and managerial implications for the conservation of inland waters in Canada in the proximate future. We recognized six opportunities and nine challenges, for which we provide research implications and policy options, such that scientists, policy makers, and the Canadian society as a whole can prepare for a potential growth in each of the topic areas we identified. The issues spanned a broad range of topics, from recognizing the opportunities and challenges of community-enabled science and the need to consider the legal rights of nature, to the likely increase of pharmaceuticals in wastewater due to an aging population. These issues represent a first baseline that could help decision makers identify and prioritize efforts while simultaneously stimulate new research avenues. We hope our horizon scan will pave the way for similar exercises related to the conservation of biodiversity in Canada.
    Type of Medium: Online Resource
    ISSN: 0706-652X , 1205-7533
    Language: English
    Publisher: Canadian Science Publishing
    Publication Date: 2020
    detail.hit.zdb_id: 7966-2
    detail.hit.zdb_id: 1473089-3
    SSG: 21,3
    SSG: 12
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