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Remote Sensing, Volume 11, Issue 1

January-1 2019 - 102 articles

Cover Story: Mineral dust is a key player in the Earth’s climate system. However, climate and weather prediction models still have difficulty predicting the amount and distribution of mineral dust in the atmosphere. One reason for this is the limited understanding of the spatiotemporal activity of dust sources. Here, an approach is presented to determine the location of potential dust sources in a study area in the central Sahara. For this, high-resolution optical data of the Sentinel-2 satellite together with HydroSHEDS flow accumulation data is used to create a sediment supply map, which is then implemented in a dust emission model. A comparison of the simulated dust flux to the observed dust source activation frequency reveals the extent to which the model benefits from having more accurate information on the distribution of dust sources. View this paper.
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Articles (102)

  • Review
  • Open Access
25 Citations
6,075 Views
34 Pages

4 January 2019

The Precipitation Radar (PR), the first space-borne precipitation radar onboard the Tropical Rainfall Measuring Mission (TRMM) satellite, could observe three-dimensional precipitation in global tropical regions and acquire continuous rainfall informa...

  • Article
  • Open Access
31 Citations
5,114 Views
15 Pages

4 January 2019

This article presents safe ship control optimization design for navigator advisory system. Optimal safe ship control is presented as multistage decision-making in a fuzzy environment and as multistep decision-making in a game environment. The navigat...

  • Article
  • Open Access
17 Citations
4,542 Views
16 Pages

4 January 2019

The hydrological regime in arid and semi-arid regions is quite sensitive to climate and land cover changes (LCC). The Three-North region (TNR) in China experiences diverse climate conditions, from arid to humid zones. In this region, substantial LCC...

  • Article
  • Open Access
98 Citations
10,773 Views
22 Pages

Semantic Segmentation on Remotely Sensed Images Using an Enhanced Global Convolutional Network with Channel Attention and Domain Specific Transfer Learning

  • Teerapong Panboonyuen,
  • Kulsawasd Jitkajornwanich,
  • Siam Lawawirojwong,
  • Panu Srestasathiern and
  • Peerapon Vateekul

4 January 2019

In the remote sensing domain, it is crucial to complete semantic segmentation on the raster images, e.g., river, building, forest, etc., on raster images. A deep convolutional encoder–decoder (DCED) network is the state-of-the-art semantic segm...

  • Article
  • Open Access
40 Citations
7,951 Views
19 Pages

4 January 2019

Detailed vertical forest structure information can be remotely sensed by combining technologies of unmanned aerial systems (UAS) and digital aerial photogrammetry (DAP). A key limitation in the application of DAP methods, however, is the inability to...

  • Article
  • Open Access
15 Citations
6,533 Views
24 Pages

3 January 2019

Up-to-date 3D city models are needed for many applications. Very-high-resolution (VHR) images with rich geometric and spectral information and a high update rate are increasingly applied for the purpose of updating 3D models. Shadow detection is the...

  • Article
  • Open Access
19 Citations
6,890 Views
24 Pages

Indoor Topological Localization Using a Visual Landmark Sequence

  • Jiasong Zhu,
  • Qing Li,
  • Rui Cao,
  • Ke Sun,
  • Tao Liu,
  • Jonathan M. Garibaldi,
  • Qingquan Li,
  • Bozhi Liu and
  • Guoping Qiu

3 January 2019

This paper presents a novel indoor topological localization method based on mobile phone videos. Conventional methods suffer from indoor dynamic environmental changes and scene ambiguity. The proposed Visual Landmark Sequence-based Indoor Localizatio...

  • Technical Note
  • Open Access
72 Citations
10,778 Views
13 Pages

Detection of Glacier Calving Margins with Convolutional Neural Networks: A Case Study

  • Yara Mohajerani,
  • Michael Wood,
  • Isabella Velicogna and
  • Eric Rignot

3 January 2019

The continuous and precise mapping of glacier calving fronts is essential for monitoring and understanding rapid glacier changes in Antarctica and Greenland, which have the potential for significant sea level rise within the current century. This eff...

  • Article
  • Open Access
8 Citations
4,197 Views
18 Pages

3 January 2019

A full-polarized facet based scattering model (FPFSM) for investigating the electromagnetic (EM) scattering by two-dimensional electrically large sea surfaces with high efficiency at high microwave bands is proposed. For this method, the scattering f...

  • Article
  • Open Access
21 Citations
4,977 Views
21 Pages

3 January 2019

Deep learning methods, especially convolutional neural networks (CNNs), have shown remarkable ability for remote sensing scene classification. However, the traditional training process of standard CNNs only takes the point-wise penalization of the tr...

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Remote Sens. - ISSN 2072-4292Creative Common CC BY license