A5037551062- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Land Use and Ecosystem Services
- Flood Risk Assessment and Management
- Remote-Sensing Image Classification
- Peatlands and Wetlands Ecology
- Soil erosion and sediment transport
- Automated Road and Building Extraction
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Soil Geostatistics and Mapping
- Soil Moisture and Remote Sensing
- Oil Spill Detection and Mitigation
- Advanced Image Fusion Techniques
- Coral and Marine Ecosystems Studies
- Remote Sensing and Land Use
- Oceanographic and Atmospheric Processes
- Meteorological Phenomena and Simulations
- Marine and coastal ecosystems
- Atmospheric aerosols and clouds
- Coastal wetland ecosystem dynamics
- Image and Signal Denoising Methods
- Wind and Air Flow Studies
- Soil and Unsaturated Flow
- Hydrology and Watershed Management Studies
- Water Quality Monitoring Technologies
Nordion (Canada)
2024
ORCID
2020-2021
Community Sector Council Newfoundland and Labrador
2020
Centre For Cold Ocean Resources Engineering
2017-2019
Memorial University of Newfoundland
2016-2019
Although wetlands provide valuable services to humans and the environment cover a large portion of Canada, there is currently no Canada-wide wetland inventory based on specifications defined by Canadian Wetland Classification System (CWCS). The most practical approach for creating Inventory (CWI) develop remote sensing method feasible areas with potential be updated within certain time intervals monitor dynamic landscapes. Thus, this study aimed create first using Landsat-8 imagery...
Wildfires are major natural disasters negatively affecting human safety, ecosystems, and wildlife. Timely accurate estimation of wildfire burn areas is particularly important for post-fire management decision making. In this regard, Remote Sensing (RS) images great resources due to their wide coverage, high spatial temporal resolution, low cost. study, Australian affected by were estimated using Sentinel-2 imagery Moderate Resolution Imaging Spectroradiometer (MODIS) products within the...
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,...
The ability of the Canadian agriculture sector to make better decisions and manage its operations more competitively in long term is only as good information available inform decision-making. At all levels Government, a reliable flow between scientists, practitioners, policy-makers, commodity groups critical for developing supporting agricultural policies programs. Given vastness complexity Canada’s regions, space-based remote sensing one most approaches get detailed describing evolving...
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-...
Iran is among the driest countries in world, where many natural hazards, such as floods, frequently occur. This study introduces a straightforward flood hazard assessment approach using remote sensing datasets and Geographic Information Systems (GIS) environment an area located western part of Iran. Multiple GIS datasets, including Digital Elevation Model (DEM), slope, rainfall, distance from main rivers, Topographic Wetness Index (TWI), Land Use/Land Cover (LULC) maps, soil type map,...
MODIS land surface temperature (LST) product (MOD11A1) has been widely used in analysing spatiotemporal trends of LST. However, its applicability is limited, partially due to coarse spatial resolution (i.e., 1 km). In this study, an Adaptive random forest regression (ARFR) method was developed for LST downscaling at national scale. This study also provided a framework shift from single-time image sets extensive time-series MOD11A1 images operational approach 19-years trend analysis over...
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...
Wetlands provide many benefits, such as water storage, flood control, transformation and retention of chemicals, habitat for species plants animals. The ongoing degradation wetlands in the Great Lakes basin has been caused by a number factors, including climate change, urbanization, agriculture. Mapping monitoring across large spatial temporal scales have proved challenging; however, recent advancements accessibility processing efficiency remotely sensed imagery facilitated these...
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...
Change detection using Remote Sensing (RS) techniques is valuable in numerous applications, including environmental management and hazard monitoring. Synthetic Aperture Radar (SAR) images have proven to be even more effective this regard because of their all-weather, day night acquisition capabilities. In study, a polarimetric index based on the ratio span (total power) values was introduced, which neighbourhood information considered. The role central pixel its adjusted weight parameter....
In this study, wetland trends in Alberta were investigated the past four decades using Landsat satellite imagery to produce updated information about changes and prevent further degradation of these valuable natural resources. All processing steps analyses conducted Google Earth Engine (GEE) 16 maps from 1984 2020. A comprehensive change analysis showed (1) approximately 18% province was subjected change; (2) terms classes, there a decreasing trend for Shallow Water Swamp classes an...
Wetlands are among the most valuable natural resources, being highly beneficial to both environment and humans. Therefore, it is very important map monitor wetlands. Although various remote sensing datasets, including optical, synthetic aperture radar (SAR), light detection ranging (LiDAR) imagery, have been widely applied classify wetlands, still required discuss advantages/limitations of each these datasets suggest best methodology for wetland mapping. Thus, Terra Nova National Park,...
The first Canadian wetland inventory (CWI) map, which was based on Landsat data, produced in 2019 using the Google Earth Engine (GEE) big data processing platform. proposed GEE-based method to create preliminary CWI map proved be a cost, time, and computationally efficient approach. Although initial effort produce valuable with 71% overall accuracy (OA), there were several inevitable limitations (e.g., low-quality samples for training validation of map). Therefore, it important...