Summary

With the growth of satellite and airborne-based platforms, remote sensing is gaining increasing attention in recent decades. Every day, sensors acquire data with different modalities and several resolutions. Leveraging on their complementary properties is a key scientific challenge, usually called remote sensing data fusion. Data fusion can be performed at three different processing levels: 1) pixel-based or raw level; 2) object-based or feature level; 3) decision level. Fusion at pixel level is often called image fusion. It means fusion at the lowest processing level referring to the merging of digital numbers or measured physical quantities. It uses co-registered raster data acquired by different sources. The co-registration step is of crucial importance because misregistration usually causes evident artifacts. Fusion at feature level requires the extraction of objects recognized in several sources of data. This is the goal of this entry collection, which will focus both on methodological and practical aspects of remote sensing data fusion.

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Entries
Topic Review
Uncrewed Aerial Vehicles in Bridge Inspection
Uncrewed Aerial Vehicles (UAV) constitute a rapidly evolving technology field that is becoming more accessible and capable of supplementing, expanding, and even replacing some traditionally manual bridge inspections. Given the classification of the bridge inspection types as initial, routine, in-depth, damage, special, and fracture critical members, specific UAV mission requirements can be developed, and their suitability for UAV application examined.
  • 915
  • 06 Apr 2022
Topic Review
Deep Learning-Based Change Detection
Change detection based on remote sensing images plays an important role in the field of remote sensing analysis, and it has been widely used in many areas, such as resources monitoring, urban planning, disaster assessment, etc. With the improved spatial resolution of remote sensing images, many deep learning methods have been proposed for aerial and satellite image change detection. Depending on the granularity of the detection unit, these methods can be roughly classified into two main categories : scene-level methods (SLCDs) and region-level methods (RLCDs). These two categories are not necessarily independent of each other, and sometimes, the same change detection process may be present in different methods simultaneously.
  • 1.4K
  • 01 Apr 2022
Topic Review
The Evaluation Role of the Ground-Penetrating Radar
Ground-Penetrating Radar (GPR) is a popular non-destructive technique for evaluating RC bridge elements as it can identify major subsurface defects within a short span of time.
  • 1.2K
  • 01 Apr 2022
Topic Review
Wireless Technologies for Social Distancing in COVID-19 Pandemic
So-called “social distance” refers to measures that work to prevent disease spread through minimizing human physical contact frequency and intensity, including the closure of public spaces (e.g., schools and offices), avoiding large crowds, and maintaining a safe distance between individuals. Because it reduces the likelihood that an infected person would transmit the illness to a healthy individual, social distance reduces the disease’s progression and impact. During the early stages of a pandemic, social distancing techniques can play a crucial role in decreasing the infection rate and delaying the disease’s peak. Consequently, the load on healthcare systems is reduced, and death rates are reduced. The concept of social distancing may not be as easy as physical distancing, given the rising complexity of viruses and the fast expansion of social interaction and globalization. It encompasses numerous non-pharmaceutical activities or efforts designed to reduce the spread of infectious diseases, including monitoring, detection, and alerting people. Different technologies can assist in maintaining a safe distance (e.g., 1.5 m) between persons in the adopted scenarios. There are a number of wireless and similar technologies that can be used to monitor people and public locations in real-time.
  • 1.1K
  • 25 Mar 2022
Topic Review
Remote Sensing Methods for Flood Prediction
Floods are a major cause of loss of lives, destruction of infrastructure, and massive damage to a country’s economy. Floods, being natural disasters, cannot be prevented completely; therefore, precautionary measures must be taken by the government, concerned organizations such as the United Nations Office for Disaster Risk Reduction and Office for the coordination of Human Affairs, and the community to control its disastrous effects. Floods are uncertain depending on several climatic and environmental factors, and therefore are difficult to predict. A classification framework is presented which classifies the remote sensing technologies being used for flood prediction into three types, which are: multispectral, radar, and light detection and ranging (LIDAR). 
  • 2.3K
  • 21 Mar 2022
Topic Review
Hyperspectral Remote Sensing
Hyperspectral imaging is an incorporation of the modern imaging system and traditional spectroscopy technology. Unmanned aerial vehicle (UAV) hyperspectral imaging techniques have recently emerged as a valuable tool in agricultural remote sensing, with tremendous promise for many application such as weed detection and species separation
  • 8.7K
  • 21 Mar 2022
Topic Review
Remote Sensing of Urban Vegetation
Green space is increasingly recognized as an important component of the urban environment yet inventorying urban vegetation is a costly and time-consuming process. Various types of remote sensing can be used in the automated mapping of urban vegetation. 
  • 1.0K
  • 21 Mar 2022
Topic Review
Radar Signal Intrapulse Modulation Recognition Based on DGDNet
Accurate recognition of radar modulation mode helps to better estimate radar echo parameters, thereby occupying an advantageous position in the radar electronic warfare (EW). The pure radar signal representation (PSR) is disentangled from the noise signal representation (NSR) through a feature disentangler and used to learn a radar signal modulation recognizer under low-SNR environments. Signal noise mutual information loss is proposed to enlarge the gap between the PSR and the NSR.
  • 805
  • 16 Mar 2022
Topic Review
Bidirectional Reflection Distribution Function
The bidirectional reflection distribution function (BRDF) is among the most effective means to study the phenomenon of light–object interaction. It can precisely describe the characteristics of spatial reflection of the target surface, and has been applied to aerial remote sensing, imaging technology, materials analysis, and computer rendering technology. 
  • 1.3K
  • 15 Mar 2022
Topic Review
Detection of the Seasonally Activated Rural Areas
Tourist activity is the main cause of seasonal activation of rural areas. The largest seasonal fluctuations were registered in mountain areas and spa resorts. For mountain areas, the highest seasonality is in the winter months (peak—January/February), and lowest is in the summer season. The seasonal character of spa centers indicates the similar trend, generally less pronounced (peak—January), however, with higher seasonality during the summer. 
  • 871
  • 07 Mar 2022
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