scholarly journals Spaceborne radar imagery – An under-utilized source of information for humanitarian relief

2020 ◽  
Vol 8 (1) ◽  
Author(s):  
Andreas Braun Braun
Keyword(s):  
Radar Data ◽  
Humanitarian Relief ◽  
Humanitarian Action ◽  
Radar Images ◽  
Radar Imagery ◽  
Multi Temporal ◽  
Radar Satellite ◽  
Spaceborne Radar ◽  
Source Of Information ◽  
Humanitarian Work

This practical paper gives an overview about the widely unused potential of radar satellite imagery to assist humanitarian action. It briefly introduces the basic differences between optical and radar images and demonstrates the practical use of the latter in different settings based on their information content and their potential for multi-temporal analyses. It gives recommendations on further reading and closes with suggestions on the practical integration of radar data into humanitarian work.

Navigation by Computer Processing of Marine Radar Images

1985 ◽  
Vol 38 (3) ◽  
pp. 375-383 ◽  
Author(s):  
G. L. Austin ◽  
A. Bellon ◽  
M. Riley ◽  
E. Ballantyne
Keyword(s):  
Radar Data ◽  
Computer Processing ◽  
Pattern Recognition Technique ◽  
Radar Images ◽  
Well Yield ◽  
Radar Imagery ◽  
On Line ◽  
Marine Radar ◽  
Recognition Technique ◽  
Better Than

The advantages of being able to process marine radar imagery in an on-line computer system have been illustrated by study of some navigational problems. The experiments suggest that accuracies of the order of 100 metres may be obtained in navigation in coastal regions using map overlays with marine radar data. A similar technique using different radar imagery of the same location suggests that the pattern-recognition technique may well yield a position-keeping ability of better than 10 metres.

scholarly journals Retrieval of digital elevation models from Sentinel-1 radar data – open applications, techniques, and limitations

2021 ◽  
Vol 13 (1) ◽  
pp. 532-569
Author(s):  
Andreas Braun
Keyword(s):  
Digital Elevation Models ◽  
Radar Data ◽  
Error Sources ◽  
New Era ◽  
Differential Interferometry ◽  
Digital Elevation ◽  
Radar Imagery ◽  
Solid Foundation ◽  
The Impact ◽  
Spaceborne Radar

Abstract With the launch of Sentinel-1 in 2014, a new era of openly accessible spaceborne radar imagery was begun, and its potential has been demonstrated throughout all fields of applications. However, while interferometric approaches to detect surface deformations are continuously being published, only a few studies address the derivation of digital elevation models (DEMs) from Sentinel-1 data. This is mainly because of the narrow orbital tube, which was primarily designed for subsidence measurements using differential interferometry. Nonetheless, the technical conditions are provided for successful applications involving DEM generation. These are outlined in the first part of this article with a focus on potential error sources and the impact of the most important constraints, namely, temporal and perpendicular baselines. The second part evaluates 21 studies on this topic, their aims, and how they dealt with error sources and the necessity of validation. These studies are then discussed based on the main challenges and potentials including how these can be tackled in the future to lay a solid foundation for scientific discourse.

scholarly journals Processing the results of space observation of the processed areas of Karaganda

2021 ◽  
Author(s):  
A. Alimzhanova ◽  
◽  
Kh. Kadylbekova ◽  
Keyword(s):  
Software Package ◽  
Radar Data ◽  
Dynamic Processes ◽  
Archival Data ◽  
Satellite Systems ◽  
Radar Images ◽  
Modern Methods ◽  
Radar Satellite

The article is devoted to the development of a method for tracking deformation in the underworked territories of Karaganda based on the data processed by radar images from the ENVISAT satellite. The article provides an overview of the use of modern radar satellite systems. The step-by-step search of archival data on the territory of Karaganda in the Eoli-sa program is described. The processing of radar images from the ENVISAT satellite for the period from 2003 to 2010 in the SARscape module of the ENVI software package is described in detail. Based on the processed data, graphs of dynamic processes were compiled. The analysis of the results of interferometric processing of radar data is performed. Traditional and modern methods of tracking the deformation of underworked territories are also analyzed.

scholarly journals COMBINATION OF SPECKLE DIVERGENCE AND NEIGHBORHOOD ANALYSIS TO CLASSIFY SETTLEMENT FROM TERASAR-X DATA

2012 ◽  
Vol 9 (1) ◽  
Author(s):  
Rokhis Komarudin ◽  
Agung Indrajit
Keyword(s):  
Specific Area ◽  
Temporal Analysis ◽  
Radar Data ◽  
Tropical Country ◽  
Neighborhood Analysis ◽  
Object Based ◽  
Radar Imagery ◽  
Multi Temporal ◽  
Sar Imagery ◽  
Spatial Indexes

Abstract.  The  objectives  of  this  research  were  to  develop  and  improve  methods  for determination  of  settlements  area  with  focus  on  synthetic  aperture  radar  (SAR)  data. Remote  sensing  settlement  classification  has  made  great  progress,  both  for  optical  and radar  data  as  well  for  their  fusion.  Yet,  in  radar  imagery,  settlement  classification  still contains  some  problems.  Several  studies  on  application  of  radar  imagery  have  been conducted  using  techniques  such  as  textural  analysis,  multi-temporal  analysis,  statistical model,  spatial  indexes,  and  object-based  classification.  Most  of  the  development  methods have several problems in the specific area especially in the tropical country. Several studies also  showed  that  settlement  classification  accuracies  were  just  below  60%.    This  was  not sufficient    enough  to  classify  settlement  areas  using  SAR  imagery.  Therefore,  in  this research, we proposed a new method i.e., the combination of the speckle divergence and the neighborhood  analysis.  The  proposed  method  was  applied  to  classify  settlement  area  in Cilacap  and  Padang  Districts  of  Indonesia.  The  results  showed  that  the  proposed  method produced a good accuracy i.e., 85.5% for Cilacap Districts and 78.1% for Padang Districts. 

The research study in the convergence of the results of processing radar images Sentinel-1A with field observations of agricultural sites

2019 ◽  
Vol 950 (8) ◽  
pp. 52-58
Author(s):  
D.V. Mozer ◽  
Е.L. Levin ◽  
A.K. Satbergenova
Keyword(s):  
Satellite Remote Sensing ◽  
Satellite Images ◽  
Research Study ◽  
High Accuracy ◽  
Agricultural Fields ◽  
Field Observations ◽  
Radar Images ◽  
The Earth ◽  
Radar Satellite ◽  
Modern Technologies

The manuscript discusses how to monitor the condition of seedlings on agricultural fields planted with winter wheat, fodder maize and areas of fir forest located in the Freudenstadt district of Baden-Wuerttemberg in Germany. To solve the range of agricultural problems , they often use modern technologies such as satellite remote sensing of the Earth. The paper displays the monitoring results of the Sentinel-1A radar satellites scenes, as well as visual spectrum imagery of field observations are presented when leaving directly to terrain segments. The processing deployed data chain, consisting of 11 Sentinel-1A scenes acquired in the timefrane from March to November 2018. Specifically, the SNAP Sentinel Toolboxes software was used to process the radar satellite images Sentinel-1А, the. Based on the the research outcomes the Committee of Agriculture of the Freudenstadt district is able to predict the yield amount with high accuracy due to good data convergence. According to the study, the following three important problems can be resolved by means of Sentinel-1A imagery

scholarly journals Earth Environmental Monitoring Using Multi-Temporal Synthetic Aperture Radar: A Critical Review of Selected Applications

2021 ◽  
Vol 13 (4) ◽  
pp. 604
Author(s):  
Donato Amitrano ◽  
Gerardo Di Martino ◽  
Raffaella Guida ◽  
Pasquale Iervolino ◽  
Antonio Iodice ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Synthetic Aperture Radar ◽  
Microwave Remote Sensing ◽  
Radar Data ◽  
Synthetic Aperture ◽  
Special Focus ◽  
Arid Environments ◽  
Synthetic Aperture Radar Data ◽  
Multi Temporal ◽  
Aperture Radar

Microwave remote sensing has widely demonstrated its potential in the continuous monitoring of our rapidly changing planet. This review provides an overview of state-of-the-art methodologies for multi-temporal synthetic aperture radar change detection and its applications to biosphere and hydrosphere monitoring, with special focus on topics like forestry, water resources management in semi-arid environments and floods. The analyzed literature is categorized on the base of the approach adopted and the data exploited and discussed in light of the downstream remote sensing market. The purpose is to highlight the main issues and limitations preventing the diffusion of synthetic aperture radar data in both industrial and multidisciplinary research contexts and the possible solutions for boosting their usage among end-users.

New technologies and new policies: the ICRC's evolving approach to working with separated families

2012 ◽  
Vol 94 (888) ◽  
pp. 1455-1479 ◽  
Author(s):  
Olivier Dubois ◽  
Katharine Marshall ◽  
Siobhan Sparkes McNamara
Keyword(s):  
New Technologies ◽  
Rapid Rise ◽  
Changing Environment ◽  
Humanitarian Action ◽  
The Past ◽  
New Policies ◽  
Humanitarian Work ◽  
Insight Into

AbstractThe field of humanitarian action is far from static, and the ICRC has worked over the years to evolve and respond to changing needs and changing circumstances. The past several decades have seen a proliferation of humanitarian actors, protracted, complex conflicts, and the rapid rise of new technologies that have significantly impacted how humanitarian work is done. The ICRC has been continually challenged to adapt in this changing environment, and its core work of supporting separated families – through restoration of family links and through support to the families of the missing – provides insight into ways that it has met this challenge and areas in which it may still seek to improve.

Fusion of rain radar images and wind forecasts in adeep learning model applied to rain nowcasting

2021 ◽  
Author(s):  
Anastase Charantonis ◽  
Vincent Bouget ◽  
Dominique Béréziat ◽  
Julien Brajard ◽  
Arthur Filoche
Keyword(s):  
Deep Learning ◽  
Optical Flow ◽  
Weather Forecast ◽  
Forecast Model ◽  
Radar Data ◽  
Learning Model ◽  
Rainfall Forecasting ◽  
Radar Images ◽  
Deep Learning Model ◽  
Rain Radar

<p>Short or mid-term rainfall forecasting is a major task with several environmental applications such as agricultural management or flood risks monitoring. Existing data-driven approaches, especially deep learning models, have shown significant skill at this task, using only rainfall radar images as inputs. In order to determine whether using other meteorological parameters such as wind would improve forecasts, we trained a deep learning model on a fusion of rainfall radar images and wind velocity produced by a weather forecast model. The network was compared to a similar architecture trained only on radar data, to a basic persistence model and to an approach based on optical flow. Our network outperforms by 8% the F1-score calculated for the optical flow on moderate and higher rain events for forecasts at a horizon time of 30 minutes. Furthermore, it outperforms by 7% the same architecture trained using only rainfall radar images. Merging rain and wind data has also proven to stabilize the training process and enabled significant improvement especially on the difficult-to-predict high precipitation rainfalls. These results can also be found in Bouget, V., Béréziat, D., Brajard, J., Charantonis, A., & Filoche, A. (2020). Fusion of rain radar images and wind forecasts in a deep learning model applied to rain nowcasting. arXiv preprint arXiv:2012.05015</p>

scholarly journals Compiling a new glacier inventory for southeastern Qinghai–Tibet Plateau from Landsat and PALSAR data

2016 ◽  
Vol 62 (233) ◽  
pp. 579-592 ◽  
Author(s):  
LINGHONG KE ◽  
XIAOLI DING ◽  
LEI ZHANG ◽  
JUN HU ◽  
C. K. SHUM ◽  
...  
Keyword(s):  
Shuttle Radar Topography Mission ◽  
Tibet Plateau ◽  
Landsat 8 ◽  
Glacier Change ◽  
Glacier Area ◽  
Glacier Inventory ◽  
Radar Images ◽  
Water Classification ◽  
Multi Temporal ◽  
Classification Information

ABSTRACTGlacier change has been recognized as an important climate variable due to its sensitive response to climate change. Although there are a large number of glaciers distributed over the southeastern Qinghai–Tibetan Plateau, the region is poorly represented in glacier databases due to seasonal snow cover and frequent cloud cover. Here, we present an improved glacier inventory for this region by combining Landsat observations acquired over 2011–13 (Landsat 8/OLI and Landsat TM/ETM+), coherence images from Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar images and the Shuttle Radar Topography Mission (SRTM) DEM. We present a semi-automated scheme for integrating observations from multi-temporal Landsat scenes to mitigate cloud obscuration. Further, the clean-ice observations, together with coherence information, slope constraints, vegetation cover and water classification information extracted from the Landsat scenes, are integrated to determine the debris-covered glacier area. After manual editing, we derive a new glacier inventory containing 6892 glaciers >0.02 km2, covering a total area of 6566 ± 197 km2. This new glacier inventory indicates gross overestimation in glacier area (over 30%) in previously published glacier inventories, and reveals various spatial characteristics of glaciers in the region. Our inventory can be used as a baseline dataset for future studies including glacier change assessment.

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