Wetlands across Canada have been, and continue to be, lost or altered under the influence of both anthropogenic natural activities. The ability assess rate change wetland habitats related spatial pattern dynamics is importance for effective meaningful management protection, particularly current context climate change. availability cloud-based geospatial platforms has allowed production maps at scales previously unfeasible due technical limitations, yet assessment changes wetlands level class...

A vast portion of Newfoundland and Labrador (NL) is covered by wetland areas. Notably, it the only province in Atlantic Canada that does not have a inventory system. Wetlands are important areas research because they play pivotal role ecological conservation impact human activities province. Therefore, classifying types monitoring their changes crucial tasks recommended for In this study, wetlands five pilot sites, distributed across NL, were classified using integration aerial imagery,...

Wetlands are important natural resources due to their numerous ecological services. Consequently, identifying locations and extents is imperative. The stability, repeatability, cost-effectiveness, multi-scale coverage, proper spatial resolution imagery of satellites provide a valuable opportunity for use in various large-scale applications, such as provincial wetland mapping. To do so, it required (1) process classify big geo data (i.e. large amount satellite datasets) time-...

Newfoundland and Labrador (NL) is the only province in Atlantic Canada that does not have a wetland inventory system. As consequence, both classifying monitoring areas are necessary for conservation human services province. In this study, wetlands 5 pilot sites, distributed across NL, were classified using multi-source multi-temporal optical remote sensing images. The procedures involved application of an object-based method to segment classify To areas, different machine learning algorithms...

Recently, there has been a significant increase in efforts to better inventory and manage important ecosystems across Canada using advanced remote sensing techniques. In this study, we improved the method results of our first-generation Canadian wetland map at 10-m resolution. Iin order classification accuracy, main contributions new study are adding more training data process Random Forest (RF) models on Google Earth Engine (GEE) platform within boundaries ecozones rather than provinces. A...

Development of the Canadian Wetland Inventory Map (CWIM) has thus far proceeded over two generations, reporting extent and location bog, fen, swamp, marsh, water wetlands across country with increasing accuracy. Each generation this training inventory improved previous results by including additional reference wetland data focusing on processing at scale ecozone, which represent ecologically distinct regions Canada. The first second generations attained relatively highly accurate an average...

Despite the fact that vast portions of Newfoundland and Labrador (NL) are covered by wetlands, currently there is no provincial inventory wetlands in province. In this study, we analyzed multi-temporal synthetic aperture radar (SAR) data for wetland classification at 4 pilot sites across NL. Object-based image analysis (OBIA) using a segmentation method based on optical (RapidEye study), well-adjusted to SAR images, was first compared pixel-based classification. Next, multi-date object-based...

Wetlands are among the most important, yet in danger ecosystems and play a vital role for well-being of humans as well flora fauna. Over past few years, state-of-the-art deep learning (DL) tools have gained attention wetland classification within remote sensing community. However, DL methods could complex structure their efficiency greatly depends on availability large number training data. Inspired by methods, with less complexity, Deep Forest (DF) classifier is an advanced tree-based tool...

Wetlands are important ecosystems that linked to climate change mitigation. As 25% of global wetlands located in Canada, accurate and up-to-date wetland classification is high importance, nationally internationally. The advent deep learning techniques has revolutionized the current use machine algorithms classify complex environments, specifically remote sensing. In this paper, we explore potential possible limitations be overcome regarding ensemble for discusses limitation various solo...

Due to the advent of powerful parallel processing tools, including modern Graphics Processing Units (GPU), new deep learning algorithms, such as Convolutional Neural Networks (CNNs), have significantly altered state-of-the-art algorithms in satellite classification complex environments. Recent studies demonstrated that generic feature maps extracted from CNNs are incredibly effective wetland classification. The main drawback very is described structurally complex, causing need for extensive...

Smoke derived from burning a natural mixture of plant species stimulates the germination seed wide range plants. It is not known, however, whether smoke individual equally effective in promoting germination. The gemination Themeda triandra following exposure to smoke, generated by individually leaf material 27 different common montane grasslands Drakensberg, reported. Gemination T. was promoted response all tested. Rook afkomstig van die brand 'n mengsel natuurlike plant-spesies stimuleer...

This article presents a rigorous, high-precision model for geometric orthorectification of declassified intelligence satellite photography (DISP) imagery the generation seamless, full-coverage mosaic Greenland ice sheet. integrates bundle adjustment method and orbital parameters, solving interior orientation (including lens distortion) exterior parameters simultaneously. In addition, techniques adaptive filtering, bright-strip removal, radiometric balancing, postprocessing are discussed. Two...

The grassland vegetation on the coast of north-eastern Pondoland was analysed after sampling 113 quadrats in Mkambati Game Reserve. Data were summarised using TWINSPAN and DECORANA multivariate procedures. Several communities subcommunities are recognized described relation to measured abiotic variables. A primary gradient from shore inland is evident, corresponding with changes altitude, soil conductivity, organic matter texture. Time since last fire influences invasion shrubland species.

The Conne River watershed is dominated by wetlands that provide valuable ecosystem services, including contributing to the survivability and propagation of Atlantic salmon, an important subsistence species has shown a dramatic decline over past 30 years. To better understand improve management watershed, in turn, wetland inventory area developed using advanced remote sensing methods field-collected data, object-based image analysis Sentinel-1, Sentinel-2, digital elevation model Earth...

Estimates of root standing crop were made at approximately 3-month intervals from two grassland communities each with three treatments. Roots extracted to a depth 0.5 m using corer and then separated the soil by wet sieving flotation. Peak crops 4487 g m− 2 4737 for respectively, in autumn or early winter, high relative previously published figures. Lowest recorded summer. Treatment effects masked variation data. These yields gave rise root/shoot ratios, which decreased aging sward grazing...

Article Vertical Zonation of Epiphytic Algae Associated with Avicennia marina (Forssk.) Vierh. Pneumatophores at Beachwood Mangroves Nature Reserve, Durban, South Africa was published on January 1, 1996 in the journal Botanica Marina (volume 39, issue 1-6).