Remote Sensing in Decision Support for Management of Protected Lands

2011 ◽  
pp. 493-494
Keyword(s):  
Remote Sensing ◽  
Decision Support

scholarly journals An Efficient Decision Support System for Flood Inundation Management Using Intermittent Remote-Sensing Data

2021 ◽  
Vol 13 (14) ◽  
pp. 2818
Author(s):  
Hai Sun ◽  
Xiaoyi Dai ◽  
Wenchi Shou ◽  
Jun Wang ◽  
Xuejing Ruan
Keyword(s):  
Remote Sensing ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Water Body ◽  
Remote Sensing Data ◽  
Flood Inundation ◽  
Remote Sensing Images ◽  
Sensing Data ◽  
Tracking Model

Timely acquisition of spatial flood distribution is an essential basis for flood-disaster monitoring and management. Remote-sensing data have been widely used in water-body surveys. However, due to the cloudy weather and complex geomorphic environment, the inability to receive remote-sensing images throughout the day has resulted in some data being missing and unable to provide dynamic and continuous flood inundation process data. To fully and effectively use remote-sensing data, we developed a new decision support system for integrated flood inundation management based on limited and intermittent remote-sensing data. Firstly, we established a new multi-scale water-extraction convolutional neural network named DEU-Net to extract water from remote-sensing images automatically. A specific datasets training method was created for typical region types to separate the water body from the confusing surface features more accurately. Secondly, we built a waterfront contour active tracking model to implicitly describe the flood movement interface. In this way, the flooding process was converted into the numerical solution of the partial differential equation of the boundary function. Space upwind difference format and the time Euler difference format were used to perform the numerical solution. Finally, we established seven indicators that considered regional characteristics and flood-inundation attributes to evaluate flood-disaster losses. The cloud model using the entropy weight method was introduced to account for uncertainties in various parameters. In the end, a decision support system realizing the flood losses risk visualization was developed by using the ArcGIS application programming interface (API). To verify the effectiveness of the model constructed in this paper, we conducted numerical experiments on the model's performance through comparative experiments based on a laboratory scale and actual scale, respectively. The results were as follows: (1) The DEU-Net method had a better capability to accurately extract various water bodies, such as urban water bodies, open-air ponds, plateau lakes etc., than the other comparison methods. (2) The simulation results of the active tracking model had good temporal and spatial consistency with the image extraction results and actual statistical data compared with the synthetic observation data. (3) The application results showed that the system has high computational efficiency and noticeable visualization effects. The research results may provide a scientific basis for the emergency-response decision-making of flood disasters, especially in data-sparse regions.

Significant Advances in Applied Geography from Combining Curiosity-Driven and Client-Driven Research Methodologies

2012 ◽  
pp. 1-20
Author(s):  
Barry Wellar
Keyword(s):  
Remote Sensing ◽  
Decision Support ◽  
Operational Research ◽  
Support Systems ◽  
Geographic Information ◽  
Optimization Techniques ◽  
Research Methodologies ◽  
Effect Analysis ◽  
Security Index ◽  
Professional Practitioners

The central thesis of the 2005 Anderson Lecture is that significant achievements in applied geography occur when the principles and practices of curiosity-driven and client-driven research are combined in the statement of problem, the idealized and operational research design, and the procedures of evaluating results. A companion thesis extends the Anderson Lectures by Jack Dangermond, Brian Berry, and Tom Wilbanks by positing that the best of applied geography incorporates a commutative perspective when establishing the parameters of an inquiry. That is, using pairwise combinations for illustration, research study parameters such as epistemology-praxis, conceptual-empirical, spatial-aspatial, theory-hypothesis, method-technique, cause-effect, analysis-synthesis, and structure-function are necessary elements in applied research that validates geography as a science-based, societally-relevant discipline, and geographers as professional practitioners. The examples of remote sensing, optimization techniques, decision support systems, geographic information systems, and the Walking Security Index project are used to illustrate how significant advances in applied geography result from combining curiosity-driven and client-driven research methodologies.

scholarly journals A novel decision support system for the interpretation of remote sensing big data

2017 ◽  
Vol 11 (1) ◽  
pp. 31-45 ◽  
Author(s):  
Wadii Boulila ◽  
Imed Riadh Farah ◽  
Amir Hussain
Keyword(s):  
Remote Sensing ◽  
Big Data ◽  
Decision Support ◽  
Decision Support System ◽  
Support System
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