Blending remote sensing data products to estimate photochemical production of hydrogen peroxide and superoxide in the surface ocean

2014 ◽  
Vol 16 (4) ◽  
pp. 792-806 ◽  
Author(s):  
Leanne C. Powers ◽  
William L. Miller
Keyword(s):  
Remote Sensing ◽  
Hydrogen Peroxide ◽  
Remote Sensing Data ◽  
Production Rates ◽  
Sensing Data ◽  
Surface Ocean ◽  
Photochemical Production ◽  
Production Of Hydrogen ◽  
Data Products ◽  
Global Surface

A novel combination of remote sensing products is used to estimate photochemical production rates of hydrogen peroxide and superoxide in the global surface ocean.

Detecting drought effects on tree mortality in forests of Franconia (Germany)

2020 ◽  
Author(s):  
Johannes Heisig ◽  
Cyrus Samimi
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Remote Sensing Data ◽  
Water Levels ◽  
Landsat 8 ◽  
Sensing Data ◽  
Dead Trees ◽  
Spatial Coverage ◽  
Data Products ◽  
Dead Vegetation

<p>Central European forests face challenges with climate changing much faster than they can adapt. Extremely hot and dry summers like in 2018 deprive forests of soil moisture, leaving them with low ground water levels. While individuals with deep and well-established root systems survive, young individuals and shallow-rooted species perish.</p><p>In southern Germany, die-off of single trees or small groups got noticeable recently. Such effects of harsher conditions rarely occur over large areas, but more in a spotted, irregular manner. This makes the phenomenon difficult to detect and to estimate its extent. The share of trees lately deteriorated may be larger than expected and represent a considerable portion of forests. Therefore, we see the great need for monitoring. Remote sensing data is suitable to examine inaccessible areas at a large scale. To quantify mortality of individual trees among a majority of vital ones, sensor platforms and respective data have to fulfill certain criteria regarding spatial, temporal and spectral resolution. Dead trees can be distinguished from others due to discoloration and defoliation. This change in appearance affects the spectral response, even in pixels larger than the tree’s extent.</p><p>This study aims at recommending a suitable spatial scale for space-borne multispectral imagery products to achieve this task. We evaluate commercial and free remote sensing data products and their ability to estimate fractional cover of dead vegetation. Satellite data employed in this study comes from Landsat 8 (30 m), Sentinel-2 (10 m), RapidEye (6.5 m) and PlanetScope (3 m). Classification performance is tested against high-resolution multispectral aerial imagery (17 cm) acquired with a Micasense RedEdge-M camera.</p><p>High-resolution Micasense images are capable of detecting single dead trees, even after downgrading the resolution from 17 cm to 3 m. For all data products tested, fraction of dead trees per pixel did not differ significantly among land cover types (dead vegetation, vital vegetation, pavement, open soil). This indicates that individual dead trees may not be detectable in vital forest stands. The finding even seems to be valid for a resolution of 3 m (PlanetScope), which is identical to the downgraded Micasense data. In the near future the detection of this phenomenon might profit from technical developments towards even higher spatial detail of space-borne sensors. Alternatively, high resolution images from aerial campaigns, manned or unmanned, could bridge this gap when flight time and spatial coverage are increased significantly and facilitating policies are in place.</p>

scholarly journals Software Technologies for Generation and Distribution of Basic Earth Remote Sensing Data Products

2015 ◽  
Vol 3 ◽  
pp. 23-32
Author(s):  
A.I. Vasilyev ◽  
◽  
A.P. Korshunov ◽  
N.A. Olshevskiy ◽  
A.S. Stremov ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Earth Remote Sensing ◽  
Sensing Data ◽  
Data Products

The Role of Remote Sensing in Earthquake Science and Engineering: Opportunities and Challenges

2008 ◽  
Vol 24 (2) ◽  
pp. 471-492 ◽  
Author(s):  
Ellen M. Rathje ◽  
Beverley J. Adams
Keyword(s):  
Remote Sensing ◽  
Significant Role ◽  
Remote Sensing Data ◽  
Science And Engineering ◽  
Comprehensive Review ◽  
Sensing Data ◽  
Future Developments ◽  
Data Products ◽  
Earthquake Science

Earthquake science and engineering are experience-driven fields in which lessons are learned after each significant earthquake. Remote sensing represents a suite of technologies that can play a significant role in documenting the effects of earthquakes and lead to important developments in our understanding of earthquakes. This paper describes current remote sensing technologies and the experience to date in using them in earthquake studies. The most promising activities that may benefit from remote sensing data products are identified, as well as the challenges that may impede the widespread use of remote sensing in earthquake studies. A comprehensive review of the use of remote sensing to document the effects of the 2003 Bam, Iran earthquake is presented, and recommendations for future developments in remote sensing in the context of earthquake science and engineering are provided.

scholarly journals Multi-Source Remote Sensing Data Product Analysis: Investigating Anthropogenic and Naturogenic Impacts on Mangroves in Southeast Asia

2020 ◽  
Vol 12 (17) ◽  
pp. 2720
Author(s):  
Anjar Dimara Sakti ◽  
Adam Irwansyah Fauzi ◽  
Felia Niwan Wilwatikta ◽  
Yoki Sepwanto Rajagukguk ◽  
Sonny Adhitya Sudhana ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Vegetation Index ◽  
Anthropogenic Impacts ◽  
Remote Sensing Data ◽  
Tree Cover ◽  
Product Analysis ◽  
Sensing Data ◽  
Data Products ◽  
The Impact

This study investigated the drivers of degradation in Southeast Asian mangroves through multi-source remote sensing data products. The degradation drivers that affect approximately half of this area are unidentified; therefore, naturogenic and anthropogenic impacts on these mangroves were studied. Various global land cover (GLC) products were harmonized and examined to identify major anthropogenic changes affecting mangrove habitats. To investigate the naturogenic factors, the impact of the water balance was evaluated using the Normalized Difference Vegetation Index (NDVI), and evapotranspiration and precipitation data. Vegetation indices’ response in deforested mangrove regions depends significantly on the type of drivers. A trend analysis and break point detection of percentage of tree cover (PTC), percentage of non-tree vegetation (PNTV), and percentage of non-vegetation (PNV) datasets can aid in measuring, estimating, and tracing the drivers of change. The assimilation of GLC products suggests that agriculture and fisheries are the predominant drivers of mangrove degradation. The relationship between water balance and degradation shows that naturogenic drivers have a wider impact than anthropogenic drivers, and degradation in particular regions is likely to be a result of the accumulation of various drivers. In large-scale studies, remote sensing data products could be integrated as a remarkably powerful instrument in assisting evidence-based policy making.

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