ABSTRACT Semantic segmentation of remote sensing images is an important but unsolved problem in the remote sensing society. Advanced image semantic segmentation models, such as DeepLabv3+, have achieved astonishing performance for semantically labeling very high resolution (VHR) remote sensing images. However, it is difficult for these models to capture the precise outlines of ground objects and explore

ABSTRACT This article describes the conception and implementation of a web platform which uses special charts and maps for climate monitoring and analysis. At first it gives an overview of related web applications and their advantages and limitations. This is followed by a basic introduction of current technologies and methods for working with climate data, geospatial web services and visualization

ABSTRACT The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, Brazil, Russia, and the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., India, Russia, and Brazil. In response

ABSTRACT The Russian Far East is a region between China and the Russian Arctic with a diverse climatological, geophysical, oceanic, and economical characteristic. The southern region is located in the Far East monsoon sector, while the northern parts are affected by the Arctic Ocean and cold air masses penetrating far to the south. Growing economic activities and traffic connected to the China Belt

ABSTRACT Globe-based Digital Earth (DE) is a promising system that uses 3D models of the Earth for integration, organization, processing, and visualization of vast multiscale geospatial datasets. The growing size and scale of geospatial datasets present significant obstacles to interactive viewing and meaningful visualizations of these DE systems. To address these challenges, we present a novel web-based

Soil moisture (SM) plays a crucial role in the dynamics of coupled atmosphere, water, energy, and carbon cycles. In this study, the spatiotemporal distribution and variations of SM in the Mongolian Plateau were investigated for the period of 1982–2018 based on four gridded SM datasets. Taking the observed SM from 33 monitoring stations as a reference, the reliability of these four gridded products

The old city centers of many major cities represent a great challenge from a constructive point of view since the foundations of the buildings consist of an aggregation of previous constructions. This endorses thorough monitoring activities during any underground construction. The capabilities of the persistent scatterer interferometry (PSI) can be exploited to cope with these monitoring needs. However

Forest disturbances have been altering the ecological properties of ecosystems; meanwhile, disturbance events of varying sizes create different structures and functions for a forest landscape. Therefore, size and frequency are important attributes of disturbances, and their relationship should be studied. We present a hierarchical method through the modeling of the overall trend of the size–frequency

Many factors are involved in urban heat island development, such as lack of green spaces, improper choice of building materials, densification, and other human activities. The aim of this research was to quantify the effects of land-use/land-cover (LU/LC) changes on urban land surface temperature (LST) during a 25-year period (1993–2018) for the semiarid Shiraz City in southern Iran using Landsat data

Separating the individual effects of climate variability and human activities on streamflow is more important than just knowing their combined effects. In this paper, using a scenario-based hydrological simulation approach, the streamflow changes caused by climate variability and two different types of human activities (i.e. land-use change and large reservoirs operations) as well as the contribution

Long-term and large-scale lake statistics are meaningful for the study of environment change, but many of the existing methods are labour-intensive and time-consuming. To overcome this problem, a novel method for long-term and large-scale lake extraction by shape-factors- and machine-learning-based water body classification is proposed. An experiment was conducted to extract the lakes in the Yangtze

NDVI (Normalized difference vegetation index) is a critical variable for monitoring climate change, studying ecological balance, and exploring the pattern of regional phenology. Traditional neural network models only consider image features in time series prediction, while historical data and its changes play an important role in time series forecasting. For this study, we proposed convolutional neural

Searching for a property is inherently a multicriteria spatial decision. The decision is primarily based on three high-level criteria composed of household needs, building facilities, and location characteristics. Location choice is driven by diverse characteristics; including but not limited to environmental factors, access, services, and the socioeconomic status of a neighbourhood. This article aims

ABSTRACT This paper presents a framework containing ten components to deliver a data management process for the storage and management of data used for Marine Spatial Planning (MSP) in Ireland. The work includes a data process flow and a recommended solution architecture. The architecture includes a central data catalogue and a spatial storage system. The components of the process are presented to

Remote sensing satellites are playing very important roles in diverse earth observation fields. However, long revisit period, high cost and dense cloud cover have been the main limitations of satellite remote sensing for a long time. This paper introduces the novel volunteered passenger aircraft remote sensing (VPARS) concept, which can partly overcome these problems. By obtaining aerial imaging data

We present systematic analyses of the temporal dynamics of the growth of Kumasi, the fastest growing city in Ghana using 20-year Landsat time-series data from 2000 to 2020 (with 1986 Landsat image as a baseline). Two classification algorithms – random forest (RF) and support vector machines (SVM) – were used to produce binary (built-up / non-built up) maps for all years within the temporal span. We

The process of modern photogrammetry converts images and/or LiDAR data into usable 2D/3D/4D products. The photogrammetric industry offers engineering-grade hardware and software components for various applications. While some components of the data processing pipeline work already automatically, there is still substantial manual involvement required in order to obtain reliable and high-quality results

ABSTRACT Big Earth Data—big data associated with Earth sciences—can potentially revolutionize research on climate change, sustainable development, and other issues of global concern. For example, analyzing massive amounts of satellite imagery of polar environments, which are sensitive to the effects of climate change, provides insights into global climate trends. This study proposes a method to use

ABSTRACT Assessment of vegetation biochemical and biophysical variables is useful when developing indicators for biodiversity monitoring and climate change studies. Here, we compared a radiative transfer model (RTM) inversion by merit function and five machine learning algorithms trained on an RTM simulated dataset predicting the three plant traits leaf chlorophyll content (LCC), canopy chlorophyll

VIIRS 375 m active fire data (VNP14IMG), the highest spatial resolution available cost-free fire product, were assessed for representing fire in typical degraded tropical peatlands in Indonesia. The results of applying the Tropical Peatland Combustion Algorithm to Landsat-8 (ToPeCAl-L8) daytime imagery were utilised as the fire references. To permit the comparison of non-simultaneous VNP14IMG and ToPeCAl-L8

Most ground filtering algorithms are primarily designed for airborne LiDAR point cloud processing and their successful use in identifying ground points from photogrammetric point clouds remains questionable. We compared six ground filtering algorithms implemented in Metashape, ArcGIS, CloudCompare, LAStools, and PDAL. We used UAV photogrammetry-based (acquired under leaf-off conditions) and airborne

This paper proposes a novel data indexing scheme, the distributed access pattern R-tree (DAPR-tree), for spatial data retrieval in a distributed computing environment. As compared to traditional distributed indexing schemes, the DAPR-tree introduces the data access patterns during the indexing utilization stage so that a more balanced indexing structure can be provided for spatial applications (e.g

Brazilian farming influences directly the worldwide economy. Thus, fast and reliable information on areas sown with the main crops is essential for planning logistics and public or private commodity market policies. Recent farming practices have embraced remote sensing to provide fast and reliable information on commodity dynamics. Medium-to-low resolution free orbital images, such as those from Landsat

Virtual Landslide Disaster environments are important for multilevel simulation, analysis and decision-making about Landslide Disasters. However, in the existing related studies, complex disaster scene objects and relationships are not deeply analyzed, and the scene contents are fixed, which is not conducive to meeting multilevel visualization task requirements for diverse users. To resolve the above

Quantifying the kinematic evolution patterns of dune migration plays a major role in resisting the sand-dust disasters and evaluating the desertification process. With the increment of optical observations, measuring the dune migration with dense spatial and temporal density has become possible. In this study, with the open-accessible Landsat-8 (L8)/Sentinel-2 (S2) imagery and global terrain datasets

Registration of TLS data is an important prerequisite to overcome the limitations of occlusion. Most existing registration methods rely on stems to determine the transformation parameters. However, the complexity of the registration problem increases dramatically as the number of stems grows. It is tricky to reduce the stems and determine the valid ones that can provide reliable registration transformation

Spot elevations published on historical U.S. Geological Survey topographic maps were established as needed to enhance information imparted by the quadrangle’s contours. In addition to other features, labels were routinely placed on mountain summits. While some elevations were established through field survey triangulation, many were computed during photogrammetric stereo-compilation. Today, Global

The polyhedral discrete global grid system (DGGS) is a multi-resolution discrete earth reference model supporting the fusion and processing of multi-source geospatial information. The orientation of the polyhedron relative to the earth is one of its key design choices, used when constructing the grid system, as the efficiency of indexing will decrease if local areas of interest extend over multiple

ABSTRACT The Belt and Road (B&R) region, a vital area with historical, economic, cultural and political significance, has undergone rapid urbanization in the past several decades, especially in the form of urban expansion. In this study, 20 megacities in the B&R region were selected to explore different spatiotemporal patterns of urban expansion. Object-oriented support vector machines (SVM), annual

ABSTRACT Question Answering (QA), the process of computing valid answers to questions formulated in natural language, has recently gained attention in both industry and academia. Translating this idea to the realm of geographic information systems (GIS) may open new opportunities for data scientists. In theory, analysts may simply ask spatial questions to exploit diverse geographic information resources

The zircon U-Pb chronology database provides a good opportunity to obtain important zircon growth peak periods in the Earth's history so as to study the origin and evolution of the crust. It should be noted that research preference affects the objectivity of zircon sampling, leading to hot data in the database and age statistics. To evaluate the influence of hot data on statistical results, the W and

ABSTRACT The advancements of sensing technologies, including remote sensing, in situ sensing, social sensing, and health sensing, have tremendously improved our capability to observe and record natural and social phenomena, such as natural disasters, presidential elections, and infectious diseases. The observations have provided an unprecedented opportunity to better understand and respond to the spatiotemporal

ABSTRACT Many augmented reality (AR) systems are developed for entertainment, but AR and particularly mobile AR potentially have more application possibilities in other fields. For example, in civil engineering or city planning, AR could be used in combination with CityGML building models to enhance some typical workflows in planning, execution and operation processes. A concrete example is the geo-referenced

Maps based on virtual reality (VR) are evolving and are being increasingly used in the field of geography. However, the advantages of VR based on the map use processes of users over desktop-based environments (DEs) are not fully understood. In this study, an experiment was conducted in which 120 participants performed map use tasks using maps and globes in VR and DE. The participants’ eye movements

Land surface temperature (LST) retrieval from thermal infrared (TIR) remote sensing image requires atmospheric and land surface emissivity (LSE) data that are sometimes unattainable. To overcome this problem, a hybrid algorithm is developed to retrieve LST without atmospheric correction and LSE data input, by combining the split-window (SW) and temperature–emissivity separation (TES) algorithms. The

A salient scene is an area within an image that contains visual elements that stand out from surrounding areas. They are important for distinguishing landmarks in first-person-view (FPV) applications and determining spatial relations in images. The relative spatial relation between salient scenes acts as a visual guide that is easily accepted and understood by users in FPV applications. However, current

This study reports an inventory of marsh dieback events from spatial and temporal perspectives in the North Inlet-Winyah Bay (NIWB) estuary, South Carolina (SC). Past studies in the Gulf/Atlantic coast states have reported acute marsh dieback events in which marsh rapidly browned and thinned, leaving stubble of dead stems or mudflat with damaged ecosystem services. Reported marsh dieback in SC, however

Despite the increasingly prominent role of social media in disaster events, studies analyzing its use in rescue operations remain scanty. Hurricane Harvey hit Texas with unprecedented rainfall and flooding in 2017 and was marked by widespread use of social media for rescue requests. We conducted a survey of 195 Twitter users in Houston and surrounding communities who had requested for rescue during

ABSTRACT Reference data for large-scale land cover map are commonly acquired by visual interpretation of remotely sensed data. To assure consistency, multiple images are used, interpreters are trained, sites are interpreted by several individuals, or the procedure includes a review. But little is known about important factors influencing the quality of visually interpreted data. We assessed the effect

The objective of this research is to propose and confirm a new machine learning approach of Best-First tree (BFtree), AdaBoost (AB), MultiBoosting (MB), and Bagging (Bag) ensembles for potential groundwater mapping and assessing role of influencing factors. The Yasuj-Dena area (Iran) is selected as a case study. For this regard, a Yasuj-Dena database was established with 362 springs locations and 12

During map generalization, the collapse of geometry, which is also called geometric dimension reduction, is a basic generalization operation. When the map scale decreases, rivers with long, shallow polygonal shapes, usually require their dual-line representation to be collapsed to a single line. This study presents a new algorithm called superpixel river collapse (SURC) to convert dual-line rivers

As one of the main components of Grassland Fire Danger Index, grassland curing degree provides crucial information for determining grassland fire danger. Accurate estimates of grassland curing are critical for determining grassland fire risk. This research focuses on the use of Landsat 8 to estimate grassland curing. Results demonstrate that Landsat 8 observations can be used to estimate curing percentages

Airborne laser scanning (ALS) has recently been identified as a potential tool in topographic mapping for archaeological prospection. However, most existing applications in this field refers to manned ALS systems, for which the high operation and maintenance costs limits its application in small-scale archaeological investigation. In this paper, we conducted an exploratory study on the application

Land surface temperature (LST) is a key parameter in land surface system. The National Aeronautics and Space Administration (NASA) recently released new Moderate Resolution Imaging Spectroradiometer (MODIS) LST products (MOD21 and MYD21). Here, we conducted a detailed comparison between the MYD11 and MYD21 LST data in mainland China. The LSTs of MYD21 were approximately 1°C higher than those of MYD11

Flood visualization is an effective and intuitive tool for representing flood information from abstract spatiotemporal data. With the growing demand for flood disaster visualizations and mitigation, augmented flood visualizations that support decision makers’ perspectives are needed, which can be enhanced by emerging augmented reality (AR) and 3D printing technologies. This paper proposes an innovative

In landmark-based way-finding, determining the most salient landmark from several candidates at decision points is challenging. To overcome this problem, current approaches usually rely on a linear model to measure the salience of landmarks. However, linear models are not always able to establish an accurate quantitative relationship between the attributes of a landmark and its perceived salience.

ABSTRACT Unmanned aerial vehicles (UAV) based remote sensing is an emerging and important data source. Recently, the use of UAVs for remote sensing applications has been rapidly growing owing to their greater availability and the miniaturization of sensors. UAVs are surpassing satellites and aircraft in remote sensing data supply for many local requirements. In comparison with satellite remote sensing

Dynamic visualization of multidimensional hydrometeorological data is vital for decision-makers to catch situational awareness and command an emergency response in natural disasters. Nevertheless, few software tools can comprehensively visualize hydrometeorological data in different scales, dimensions, and time. In this paper, an interactive 4D spatio-temporal visualization system based on a virtual

Full-waveform decomposition is crucial for obtaining accurate satellite-ground distance, the accuracy of which is severely affected by noises. However, the traditional filters all depend on filtering parameters. This paper presents a new and adaptive method for denoising based on empirical mode decomposition (EMD) and Hurst analysis (EMD-Hurst). The noisy full-waveforms are first decomposed into their

(2019). List of reviewers for International Journal of Digital Earth. International Journal of Digital Earth: Vol. 12, No. 12, pp. (i)-(ii).

ABSTRACT With the rapid development of digital earth, smart city, and digital twin technology, the demands of three-dimensional model data’s application is getting higher and higher. These data tend to be multi-objectification, multi-type, multi-scale, complex spatial relationship, and large amount, which brings great challenges to the efficient organization of them. This paper mainly studies the organization

(2019). The 11th International Symposium on Digital Earth, Florence DECLARATION by the International Society for Digital Earth. International Journal of Digital Earth: Vol. 12, No. 12, pp. 1465-1466.

ABSTRACT Identifying land forms and land cover classes are important tasks in image interpretation. Sometimes, a phenomenon called terrain reversal effect (TRE) causes an inverted perception of 3D forms. When this inversion occurs, valleys appear as ridges and vice versa. While the TRE can severely impair the ability to identify 3D land forms, ‘correcting’ for the TRE in imagery can introduce new problems

Traditional data collection methods such as remote sensing and field surveying often fail to offer timely information during or immediately following disaster events. Social sensing enables all citizens to become part of a large sensor network, which is low cost, more comprehensive, and always broadcasting situational awareness information. However, data collected with social sensing is often massive

ABSTRACT The automatic definition of the ground from 3D point clouds has been a common process for the last two decades, with many different approaches and applications that can be found in a vast literature. This paper presents a comparison of three different methodological concepts for ground classification, in order to establish the advantages and drawbacks of each method. First, a heuristic method

(2019). Remote sensing of land use/cover changes in South and Southeast Asian Countries. International Journal of Digital Earth: Vol. 12, Remote Sensing of Land Use/Cover Changes in South and Southeast Asian Countries, pp. 1099-1102.

ABSTRACT The overarching goal of this study was to perform a comprehensive meta-analysis of irrigated agricultural Crop Water Productivity (CWP) of the world’s three leading crops: wheat, corn, and rice based on three decades of remote sensing and non-remote sensing-based studies. Overall, CWP data from 148 crop growing study sites (60 wheat, 43 corn, and 45 rice) spread across the world were gathered

Location-aware big data from social media have been widely used to quantitatively characterize natural disasters and disaster-induced losses. It is not clear how human activities collectively respond to a disaster. In this study, we examined the collective human activities in response to Typhoon Hato at multi spatial scales using aggregated location request data. We proposed a Multilevel Abrupt Changes

The foundation of modern Digital Earth frameworks is the Discrete Global Grid System (DGGS). To standardize the DGGS model, the Open Geospatial Consortium (OGC) recently created the DGGS Abstract Specification, which also aims to increase usability and interoperability between DGGSs. To support these demands and aid future research, open implementations are necessary. However, several OGC conformant

Coastal settlements face many hazards from climate change. Consequently, there has been extensive focus on developing and implementing adaptation. However, these efforts have prodominantly centred on larger cities. Coastal towns and small cities (urban areas between 1000 and 100,000 people) have received little attention, despite experiencing a number of barriers to adaptation. The absence of information