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Landsat-8: Science and product vision for terrestrial global change research
- Remote Sens. Environ. 2014
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Forrest Disturbance Mapping Using Dense . . .
- REMOTE SENS
, 2016
"... Spatio-temporal information on process-based forest loss is essential for a wide range of applications. Despite remote sensing being the only feasible means of monitoring forest change at regional or greater scales, there is no retrospectively available remote sensor that meets the demand of monito ..."
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Spatio-temporal information on process-based forest loss is essential for a wide range of applications. Despite remote sensing being the only feasible means of monitoring forest change at regional or greater scales, there is no retrospectively available remote sensor that meets the demand of monitoring forests with the required spatial detail and guaranteed high temporal frequency. As an alternative, we employed the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to produce a dense synthetic time series by fusing Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) nadir Bidirectional Reflectance Distribution Function (BRDF) adjusted reflectance. Forest loss was detected by applying a multi-temporal disturbance detection approach implementing a Disturbance Index-based detection strategy. The detection thresholds were permutated with random numbers for the normal distribution in order to generate a multi-dimensional threshold confidence area. As a result, a more robust parameterization and a spatially more coherent detection could be achieved. (i) The original Landsat time series; (ii) synthetic time series; and a (iii) combined hybrid approach were used to identify the timing and extent of disturbances. The identified clearings in the Landsat detection were verified using an annual woodland clearing dataset from Queensland’s Statewide Landcover and Trees Study. Disturbances
Keywords: Grizzly bear
"... Philips, & Losos, 1998), and can alter the life histories of wildlife (Bengtsson, Nilsson, Franc, & Menozzi, 2000). On-going manage-ment of forests for resource extraction, largely for timber harvest the primary agent of disturbance (Andison, 1998; Johnson, Miyanishi, & Bridge, 2001; ..."
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Philips, & Losos, 1998), and can alter the life histories of wildlife (Bengtsson, Nilsson, Franc, & Menozzi, 2000). On-going manage-ment of forests for resource extraction, largely for timber harvest the primary agent of disturbance (Andison, 1998; Johnson, Miyanishi, & Bridge, 2001; Tande, 1979). Changes in disturbances impact wildlife: black bears select for regenerating forest stands over mature conifer forests (Brodeur, Ouellet, Courtois, & Fortin, 2008). However, elk avoid areas following disturbance, despite an increase in herbaceous biomass, due to the threat of wolf predation (Hebblewhite, Munro, & Merrill, 2009). Other predators may avoid disturbed areas seasonally. For example, in winter, areas of forest harvest are avoided by the Canadian lynx due to the lack of cover to
Remote Sensing of Environment
"... hat allows collection of a 2–2017) Landsat Science s ahead in support of pri-tification of new science ..."
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hat allows collection of a 2–2017) Landsat Science s ahead in support of pri-tification of new science
www.mdpi.com/journal/remotesensing Article Overcoming Limitations with Landsat Imagery for Mapping of Peat Swamp Forests in Sundaland
, 2012
"... Abstract: Landsat can be used to map tropical forest cover at 15–60 m resolution, which is helpful for detecting small but important perturbations in increasingly fragmented forests. However, among the remaining Landsat satellites, Landsat-5 no longer has global coverage and, since 2003, a mechanica ..."
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Abstract: Landsat can be used to map tropical forest cover at 15–60 m resolution, which is helpful for detecting small but important perturbations in increasingly fragmented forests. However, among the remaining Landsat satellites, Landsat-5 no longer has global coverage and, since 2003, a mechanical fault in the Scan-Line Corrector (SLC-Off) of the Landsat-7 satellite resulted in a 22–25 % data loss in each image. Such issues challenge the use of Landsat for wall-to-wall mapping of tropical forests, and encourage the use of alternative, spatially coarser imagery such as MODIS. Here, we describe and test an alternative method of post-classification compositing of Landsat images for mapping over 20.5 million hectares of peat swamp forest in the biodiversity hotspot of Sundaland. In order to reduce missing data to levels comparable to those prior to the SLC-Off error, we found that, for a combination of Landsat-5 images and SLC-off Landsat-7 images used to create a 2005 composite, 86 % of the 58 scenes required one or two images, while 14 % required three or more images. For a 2010 composite made using only SLC-Off Landsat-7 images, 64 % of
Article A Framework for Defining Spatially Explicit Earth Observation Requirements for a Global Agricultural Monitoring Initiative (GEOGLAM)
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