The catastrophic events caused by meteorological disasters are becoming more severe in the context of global warming. The disaster chains triggered by Tropical Cyclones induce the serious losses of population and economy. It is necessary to make the...
Large-scale crop mapping is essential for agricultural management. Phenological variation often exists in the same crop due to different climatic regions or practice management, resulting in current classification models requiring sufficient training...
The use of semantic representations to achieve place understanding has been widely studied using indoor information. This kind of data can then be used for navigation, localization, and place identification using mobile devices. Nevertheless, applyin...
Flooding periodicity is crucial for biomass production and ecosystem functions in wetland areas. Local monitoring networks may be enriched by spaceborne derived products with a temporal resolution of a few days. Unsupervised computer vision technique...
Because canola is a major oilseed crop, accurately determining its planting areas is crucial for ensuring food security and achieving UN 2030 sustainable development goals. However, when canola is extracted using remote-sensing data, winter wheat cau...
Disaster change mapping, which can provide accurate and timely changed information (e.g., damaged buildings, accessibility of road and the shelter sites) for decision makers to guide and support a plan for coordinating emergency rescue, is critical f...
Mobile eye tracking helps to investigate real-world settings, in which participants can move freely. This enhances the studies’ ecological validity but poses challenges for the analysis. Often, the 3D stimulus is reduced to a 2D image (reference view...
Limited by meteorological conditions, airspace, complex terrain and other factors, airborne millimeter-wave InSAR will inevitably face the situation of no control point layout when acquiring terrain data in the difficult mapping areas in Southwest Ch...
Cone-shaped volcanoes have important research significance and application value due to their typical cone shape and unique structural features. The existing methods for recognizing volcanoes are mainly morphological feature matching and machine lear...
The Google Earth Engine (GEE) has emerged as an essential cloud-based platform for land-cover classification as it provides massive amounts of multi-source satellite data and high-performance computation service. This paper proposed an automatic land...
Synthetic aperture radar (SAR) technology has become an important means of flood monitoring because of its large coverage, repeated observation, and all-weather and all-time working capabilities. The commonly used thresholding and change detection me...
Although plastic pollution is one of the most noteworthy environmental issues nowadays, there is still a knowledge gap in terms of monitoring the spatial distribution of plastics, which is needed to prevent its negative effects and to plan mitigation...
This study aimed to develop a rapid, 1 mm3 isotropic resolution, whole-brain MRI technique for automatic lesion segmentation and multi-parametric mapping without using contrast by continuously applying balanced steady-state free precession with inver...
Satellite data offer the opportunity for monitoring the temporal flooding dynamics of seasonal wetlands, a parameter that is essential for the ecosystem services these areas provide. This study introduces an unsupervised approach to estimate the exte...
The topographic map plays a very important role in economic construction. In the process of drawing topographic maps, different symbols represent different ground objects, but the symbols representing complex ground objects are often complicated and...
This study is oriented towards machine autonomous mapping and the need to improve the efficiency of map point symbol recognition and configuration. Therefore, an intelligent recognition method for point symbols was developed using the You Only Look O...
In recent years, hundreds of Earth observation satellites have been launched to collect massive amounts of remote sensing images. However, the considerable cost and time to process the significant amount of data have become the greatest obstacle betw...
Cold-water coral reefs are hotspots of biological diversity and play an important role as carbonate factories in the global carbon cycle. Reef-building corals can be found in cold oceanic waters around the world. Detailed knowledge on the spatial loc...
The German Aerospace Center’s (DLR) TIMELINE project (“Time Series Processing of Medium Resolution Earth Observation Data Assessing Long-Term Dynamics in our Natural Environment”) aims to develop an operational processing and data management environm...
Image registration is widely used in remote-sensing applications. The existing automatic image registration techniques fall into two categories: Intensity-based and feature-based; the latter (which extracts structures from both images) being more sui...
Wireless communication greatly contributes to the evolution of new technologies, such as the Internet of Things (IoT) and edge computing. The new generation networks, including 5G and 6G, provide several connectivity advantages for multiple applicati...
Massive landslides over large regions can be triggered by heavy rainfalls or major seismic events. Mapping regional landslides quickly is important for disaster mitigation. In recent years, deep learning methods have been successfully applied in many...
There is a great demand to develop new acoustic techniques to efficiently map the seabed and automate the interpretation of acoustic, sedimentological, and imaging data sets, eliminating subjectivity. Here, we evaluate the potential, limitations and...
Extracting facade maps from 3D point clouds is a fast and economical way to describe a building’s surface structure. Existing methods lack efficiency, robustness, and accuracy, and depend on many additional features such as point cloud reflecti...
Automatic modulation classification (AMC) plays a fundamental role in common communication systems. Existing clustering models typically handle fewer modulation types with lower classification accuracies and more computational resources. This paper p...
The high-definition map (HD-map) of road structures is crucial for the safe planning and control of autonomous vehicles. However, generating and updating such maps requires intensive manual work. Simultaneous localization and mapping (SLAM) is able t...
The global increase in wildfires due to climate change highlights the need for accurate wildfire mapping. This study performs a proof of concept on the usefulness of SuperDove imagery for wildfire mapping. To address this topic, we present an automat...
Impervious surface area (ISA) is a key factor for monitoring urban environment and land development. Automatic mapping of impervious surfaces has attracted growing attention in recent years. Spectral built-up indices are considered promising to map I...
Mapping potential landslides is crucial to mitigating and preventing landslide disasters and understanding mountain landscape evolution. However, the existing methods to map and demonstrate potential landslides in mountainous regions are challenging...
Rice is one of the most important staple foods in the world, feeding more than 50% of the global population. However, rice is also a significant emitter of greenhouse gases and plays a role in global climate change. As a result, quickly and accuratel...
The sea ice cover in the North evolves at a rapid rate. To adequately monitor this evolution, tools with high temporal and spatial resolution are needed. This paper presents IceMap250, an automatic sea ice extent mapping algorithm using MODIS reflect...
Reliable information about the spatial distribution of surface waters is critically important in various scientific disciplines. Synthetic Aperture Radar (SAR) is an effective way to detect floods and monitor water bodies over large areas. Sentinel-1...
Oceanic internal waves occur within stratified water along the boundary between water layers of different density and are generated when strong tidal currents flow over seabed topography. Their amplitude can exceed 50 m and they transport energy over...
Mapping the distribution and persistence of surface water in a timely fashion has broad value for tracking dynamic events like flooding, and for monitoring the effects of climate and human activities on natural resource values and biodiversity. Tradi...
Most 3D CityGML building models in street-view maps (e.g., Google, Baidu) lack texture information, which is generally used to reconstruct real-scene 3D models by photogrammetric techniques, such as unmanned aerial vehicle (UAV) mapping. However, due...
As a large-scale irrigation and water conservancy project in ancient times, karez are common in Central Asia and arid regions with a history of thousands of years. Turpan, which is located in the Xinjiang Uyghur Autonomous Region, has the most extens...
The academic community has witnessed a notable increase in paper publications, whereby the rapid pace at which modern society seeks information underscores the critical need for literature mapping. This study introduces an innovative automatic model...
Accurate apple orchard mapping plays a vital role in managing agricultural resources. However, national-scale apple orchard mapping faces challenges such as the “same spectrum with different objects” phenomenon between apple trees and oth...
The availability of freshwater is becoming a global concern. Because agricultural consumption has been increasing steadily, the mapping of irrigated areas is key for supporting the monitoring of land use and better management of available water resou...
Anthropogenic underwater noise impacts marine life across many taxa and life stages. Underwater noise mapping is an important tool in estimation and mitigation of this impact. The present study develops a framework for noise mapping of continuous und...
Mapping of exact tree positions can be regarded as a crucial task of field work associated with forest monitoring, especially on intensive research plots. We propose a two-stage density clustering approach for the automatic mapping of tree positions,...
29 October 2013
Tone mapping algorithms are used to adapt captured wide dynamic range (WDR) scenes to the limited dynamic range of available display devices. Although there are several tone mapping algorithms available, most of them require manual tuning of their re...
In this paper, we present and discuss the preliminary tools we devised for the automatic recognition of burnt areas and burn severity developed in the framework of the EU-funded SERV_FORFIRE project. The project is focused on the set up of operationa...
In the ongoing transition to renewable energy sources, power converters have become indispensable. Their prevalence is increasing, enabling efficient energy conversion, enhancing reliability and stability, and optimizing power extraction from renewab...
Terrestrial laser scanners, unmanned aerial LiDAR, and unmanned aerial photogrammetry are increasingly becoming the go-to methods for forest analysis and mapping. The three-dimensionality of the point clouds generated by these technologies is ideal f...
Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green...
Mobile Mapping is an efficient technology to acquire spatial data of the environment. The spatial data is fundamental for applications in crisis management, civil engineering or autonomous driving. The extrinsic calibration of the Mobile Mapping Syst...
The amount of Earth observation images available to the public has been the main source of information, helping governments and decision-makers tackling the current world’s most pressing global challenge. However, a number of highly skilled and...
Machine learning algorithms are effective in realizing the programming of robots that behave autonomously for various tasks. For example, reinforcement learning (RL) does not require supervision or data sets; the RL agent explores solutions by itself...
Detailed up-to-date ground reference data have become increasingly important in quantitative forest inventories. Field reference data are conventionally collected at the sample plot level by means of manual measurements, which are both labor-intensiv...
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