“Sensors operating in the visible and mid-infrared portions of the electromagnetic spectrum measure the fraction of the incoming solar radiation reflected at the surface. If the sensors are mounted ...”
We describe a method of identifying and counting whales using very high resolution satellite imagery through the example of southern right whales breeding in part of the Golfo Nuevo, Península Valdés in Argentina. Southern right whales have been extensively hunted over the last 300 years and although numbers have recovered from near extinction in the early 20thcentury, current populations are fragmented and are estimated at only a small fraction of pre-hunting total. Recent extreme right whale calf mortality events at Península Valdés, which constitutes the largest single population, have raised fresh concern for the future of the species. The WorldView2 satellite has a maximum 50 cm resolution and a water penetrating coastal band in the far-blue part of the spectrum that allows it to see deeper into the water column. Using an image covering 113 km2, we identified 55 probable whales and 23 other features that are possibly whales, with a further 13 objects that are only detected by the coastal band. Comparison of a number of classification techniques, to automatically detect whale-like objects, showed that a simple thresholding technique of the panchromatic and coastal band delivered the best results. This is the first successful study using satellite imagery to count whales; a pragmatic, transferable method using this rapidly advancing technology that has major implications for future surveys of cetacean populations.
Landslides, like other natural hazards, such as avalanches, floods, and debris flows, may result in a lot of property damage and human casualties. The volume of landslide deposits is a key parameter for landslide studies and disaster relief.
This study presents a thorough approach, based on the application of multi-spectral remote sensing Landsat imagery, to determine human-induced forest cover change in Italy during the decade 2002–2011. A total of 785.6 ×1 04 ha of forestland was mapped using the main forest classes described within the CORINE land cover 2006 database (3.11 – broad-leaved forest; 3.12 – coniferous forest; 3.13 – mixed forest). The approach employs multi-temporal Landsat imagery to determine large-scale spatiotemporal variations in forest cover with a high degree of precision. The semi-automated procedure is based on Normalized Difference Vegetation Index (NDVI) pixel-oriented image differencing technique. The results were validated and rectified as a result of on-screen visual interpretation, whereby all the false-positive forest changes that were incorrectly mapped during the automatic procedure were identified and removed. The derived high-resolution data of forest cover change show that 317,535 ha (4.04% of the total forest area in Italy) were harvested during the period under review. The 125,272 individual clear-cut areas identified are mainly located within protected areas of the European Natura 2000 network. The outcome of this study is a publicly accessible database that can encourage further studies in the framework of international biodiversity and soil protection conventions (http://eusoils.jrc.ec.europa.eu/library/themes/erosion/italy/). The methodology can contribute to the monitoring of human-induced forest changes in support of the Kyoto Protocol.
Researchers with the British Antarctic Survey have developed a methodology to use unsupervised classification to remotely identify and count right whale populations near Golfo Nuevo, Península Valdés in Argentina using Very High Resolution (VHR)...
Remote sensing used to detect moisture status of pecan orchards grown in a desert environment (#Life #Science ▶ Remote sensing used to detect moisture status of pecan orchards grown in a desert environment http://t.co/loUmNFvQP1)...
Accurate information on urban building types plays a crucial role for urban development, planning, and management. In this paper, we apply Object-Based Image Analysis (OBIA) methods to extract buildings from Airborne ...
Remotely-sensed green-up, maturity, senescence and dormancy MODIS dates were extracted for areas previously identified as crops and were compared with simulated leaf area indices (LAI) temporal profiles generated ...
A new analysis shows how changes in the angle between the Sun and a satellite sensor interact to create the illusion of greening during the dry season. (why we need ppl who understand remote sensing+maths+ecology "@NASA_EO: illusions of greening.
Testing CATS in space: Laser technology to debut on space station EurekAlert (press release) This Earth remote sensing instrument is scheduled to launch to the space station in September 2014 as a demonstration project.
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