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The detection of changes in synthetic aperture radar (SAR) images based on deep learning has been widely used in landslides detection, flood disaster monitoring, and other fields of change detection due to its high classification accuracy. However, the inherent speckle noise in SAR images restricts the performance of existing SAR image change detection algorithms by clustering analysis. Therefore, this paper proposes a novel method for SAR image change detection based on clustering fusion and deep neural networks. We first used hierarchical fuzzy c-means clustering (HFCM ) to process two different images to obtain HFCM classification results. Then a fusion strategy is designed to obtain the fused image from the two HFCM classified images as the pre-classification result. Furthermore, a lightweight deep neural network com posed of a decomposition convolution module and an auxiliary classification module was proposed; the former module could reduce network parameters by 28%, and the latter could reduce network parameters by 33.3%. To improve the recognition performance of the network, the classification layer was replaced by the regression layer at the outcome of the network. By comparing the experiments of different methods on five data sets, the performance of our proposed method is superior.

Aiming at the problem of rapid construction of a river three-dimensional 3D scene, this article integrates remote sensing, 3D modeling, and CityEngine technology to construct a 3D scene model reconstruction method of river water-land integration. The method includes intelligent extraction of underwater topography, refined modeling of hydraulic structures, and construction of a water-land integrated real scene model. Based on this method, the high-fidelity land-underwater seamless digital terrain and the water-land 3D real scene models can be formed. Through experiments, the feasibility and limitations of this method are verified. It can effectively extract the shallow underwater terrain of inland rivers, and the overall accuracy of the study area is less than 2 m. The performance of the seamless fusion 3D terrain is better than the public digital elevation model data set. In the inland basin of Class I to II water quality, it can meet the needs of intelligent perception of a river- and lake-integrated 3D scene model.

In this paper, an improved aerosol optical depth (AOD ) retrieval algorithm is proposed based on Sentinel-2 and AErosol RObotic NETwork (AERONET ) data. The surface reflectance for AOD retrieval was estimated from the image that had minimal aerosol contamination in a temporal window determined by AERONET data. Validation of the Sentinel-2 AOD retrievals was conducted against four Aerosol Robotic Network (AERONET ) sites located in Beijing. The results show that the Sentinel-2 AOD retrievals are highly consistent with the AERONET AOD measurements (R = 0.942), with 85.56% falling within the expected error. The mean absolute error and the root-mean-square error are 0.0688 and 0.0882, respectively. In addition, the AOD distribution map obtained by this algorithm well reflects the fine-spatial-resolution changes in AOD distribution. These results suggest that the improved high-resolution AOD retrieval algorithm is robust and has the potential advantage of retrieving high-resolution AOD over urban areas.

Intertidal zones serve as a critical transition between land and ocean and are periodically inundated by tides. They are extremely important to coastal communities as it provides diverse habitats and buffers against marine hazards. However, the reduced river sediment together with sea level rise and coastal reclamation have caused the widespread loss of intertidal areas. Reliable, high-resolution, and up-to-date intertidal topography maps are key information for coastal vulnerability assessment and restoration. Existing approaches to intertidal topography construction involve significant ground surveys, with limited spatial coverage, accuracy, and efficiency, thus, restricting their potential to generalize globally. To address these issues, we propose a pixel-based approach to construct intertidal topography from dense Sentinel-2 satellite time-series and limited ground truth surveys, named as Tide2Topo. Tide2Topo differs conceptually from the widely used waterline method since it considers tidal inundation frequency as a topographic indicator rather than instantaneous waterlines. Therefore, Tide2Topo does not involve manual selection of images at different tide levels. The relationship between intertidal inundation frequency and elevation is calibrated using linear and polynomial models based on a few transect measurements instead of tidal height, preventing errors introduced by inaccurate tidal data. The proposed Tide2Topo was applied and validated in the UK and China over several complicated estuaries and bays with extensive muddy flats or sandy beaches. The results demonstrated that the topography derived from intertidal inundation frequency compared to LiDAR or UAV photogrammetric observations has a root mean square error ranging from 16 to 38 cm. The large errors were found in the tidal channel areas where the inundation frequency calculation was prone to uncertainty. Dense Sentinel-2 time-series observations ensure finer sampling of the tidal cycle, thereby not only eliminating errors caused by spatial interpolation but also maintaining the accuracy of elevation estimations at pixel level. Tide2Topo is a robust, portable and rapid method well suitable for large-scale intertidal topography construction. Future work could use Sentinel-1 SAR as an alternative data source for Tide2Topo, realizing seasonal or annual monitoring of intertidal geomorphological changes.

The purpose of this article is to explore forest height estimation strategies using topographic data (DEM) combined with TanDEM-X while comparing the effect of volume scattering complex coherence selection on forest height estimation in the traditional random volume over ground (RVoG) three-stage algorithm. In this study, four experimental strategies were designed for comparison based on TanDEM-X polarized interferometric synthetic aperture radar (PolInSAR) data, TanDEM-DEM, and 42 field-measured data. Our results show that in the RVoG model, (1) a reference ground phase to select the volume scattering complex coherence provides greater accuracy in determining forest height, (2) forest height estimation can be achieved by directly using DEM as ground phase information without relying on model solving and obtaining a more accurate forest height than TanDEM-X alone, and (3) the highest estimation accuracy is obtained by using DEM as coherence information among all schemes. Although the difference in forest height estimation results is not significant in this study, it still proves that the forest height estimation strategy of high-precision DEM combined with short-wavelength PolInSAR can not only improve the forest height estimation accuracy but also simplify the solving process of the RVoG model, which is an important reference for global forest parameter estimation and ecosystem detection based on spaceborne PolInSAR.

Analyses of Doppler radar data and environmental parameters for 300 tornado cases are used to propose an alternative framework for tornado intensity prediction during pretornadic stages of ongoing storms, conditional on tornadogenesis. This framework is founded on the robust relationship (R² = 0.69) between pretornadic mesocyclone width and the EF rating of the subsequent tornado. In contrast, the linear relationship between pretornadic mesocyclone intensity and EF scale is much weaker (R² = 0.29). Environmental information for each case was additionally used to explore relationships between environmental parameters and tornado intensity. Such relationships depend in part on how the tornado-intensity categories are distributed [i.e., nonsignificant (EF0–1) versus significant (EF2–5), or weak (EF0–1) versus strong (EF2–3) versus violent (EF4–5)]. Low-level shear parameters discriminate the environments of significant tornadoes from nonsignificant tornadoes, but not the environments of violent tornadoes from strong tornadoes. The converse is true for thermodynamic parameters. Operational implementation of this framework for thepurposes of impact-based warnings will require real-time, automated quantification of mesocyclone width in addition to intensity and other attributes. The information gained from the pretornadic analysis demonstrated in this study would allow an operational forecaster to be aware of—and communicate—information about potential tornado intensity in warning text to the public before a tornado develops to better protect life and property. Currently, these relationships are being utilized in machine learning models for binary prediction of non-significant versus significant tornado intensity where skill is being demonstrated.

At present, the use of digital technologies is becoming increasingly relevant in all fields of anthropogenic activity. In agriculture, an important area of digitalization is precision farming. In this case, the method of analyzing remote sensing data in geoinformation systems is of great importance; it enables identifying various parameters of agricultural crops (indices of vegetation, moisture availability, etc.) at processing. Therefore, it is important to develop a computer technology for manipulating the mentioned information and creating digital maps and models of the territory based on it. This requires high-quality work at the available satellite imagery materials. The author considers the course of determining the vegetation cover water indices in the ENVI software package using satellite images of the Landsat 7–9 survey systems. Based on the results of the calculation, digital 2D maps of the object under study were compiled, a GIS project (database) was developed, and a 3D elevation model was created. The obtained materials are intended for the analysis of natural and anthropogenic features, as well as for assessing the moisture content of the study object’s territory vegetation cover.

The possibility of studying morphometric parameters of the Earth’s topographic surface using the ArcMap and digital elevation model SRTM3 with a resolution of 90 m to determine neotectonic structures, as well as associated ore clusters and deposits was considered using the method offered by V. P. Filosofov. The authors describe the technology of creating base and vertex surfaces for thalwegs and watersheds of different orders, with the subsequent subtraction of the former from the latter within one order to determine the amount of erosion cut (relief energy). As the object of the study, the Dnieper-Donets aulacogen was chosen, starting west of Kharkov and stretching to the Caspian Sea, wide from Rostov-on-Don to Millerovo. It was noted that the higher the potential relief energy is, the more powerful surface processes will be manifested in the form of active destruction of previously buried (hidden) geological structures with valuable components, which are later to be distributed throughout the territory. This study is proposed to be used to predict and search for latent mineralization; it enables identifying the root source of demolition, rational arranging geological work, and thereby reduces their cost.

With the advent of zenith camera, it became possible to improve the accuracy (up to 0,1″) and efficiency (no more than an hour) of measuring the plumb line deviation components at the point where the device is located in real-time mode. This enables measuring the components of the mentioned deviation at 4–12 or more points, depending on the season, during one observational night. Zenith camera is field-based, relocatable and can quantify the required components with any given discreteness, the process is fully automated. This makes the possibility of using the well-known method of astronomical leveling in a new way to define the height differences of the quasi-geoid. With a mistake in computing the deviation of a plumb line of 0,2″, the error in determining the elevation of the quasi-geoid heights is less than 1 mm at a kilometer distance between the points. This indicator is comparable with miscalculating of existing levels. In this case, there is no need for direct visibility between measurement points, computations can be performed between unrelated spots, and the distances between them can be kilometers or dozens of them. The authors present reviews of works on the use of zenith camera in creating quasi-geoid height models, develop the theory of astronomical leveling, consider its errors, and compare it with other leveling methods.

Thorough study of the equipment is essential before any measurements are made. Relative tidal gravimeters are complex technical devices; they enable measuring gravity time variations with high accuracy (1 μGal). The main source of systematic errors is their instrumental drift. Value and nonlinearity of the drift for each unit is individual. There are plenty of considering methods; they depend on material and technical opportunities. The simplest and less resource-consuming algorithm is to take the drift into account using the piecewise linear approximation technique. This research deals with assessing the accuracy of accounting the instrumental drift of the gPhoneX#117 (Micro-g LaCoste, USA) tidal gravimeter using the specified means. For this purpose, the drift was obtained through approximation by polynomials of the first and second degree was estimated in comparison with the results of reference (absolute) observations. It is concluded that the method of piecewise linear approximation can only be used for rejecting poor quality measurements. It is recommended to identify, control and accounting the instrumental drift by comparing measurements with the data of regular absolute monitoring.

The features of automating the processing of spatial data using geographic information systems are discussed. The main directions of automation at spatial data processing, including the use of artificial intelligence technologies, are identified. Possible technical approaches to that in geoinformation systems are identified and described. The software implementation of the listed techniques involving open source software is considered, using the example of a typical sequence of actions at working with spatial information

At processing geodetic networks, it is necessary to transform the coordinates of points from one system to another. Two methods are most common

The author makes a summary for a series of geomorphometric, geological, and biological field studies by a complex team of the 68th Russian Antarctic Expedition performed at two areas of the Larsemann Hills oasis (Ingrid Christensen Coast, Princess Elizabeth Land, East Antarctica) in February 2023. The areas (a rocky island and a cape) are located to the south of the Stornes Peninsula, at the western border of the oasis with the Polararboken Glacier, on the Wilcock Bay coast. At the time of filed studies, both the areas were white spots on large scale topographic and geological maps, unexplored, and without any names given before. Guided by traditions of land explorers as well as considering the mapping practice of new territories, the 68th Russian Antarctic Expedition complex team assigned seven toponyms to the areas and their particular elements.

The optimal path between two vertices in a graph depends on the optimization objective, which is often defined as a weighted sum of multiple criteria. When integrating two criteria, their relative importance is expressed with a balance factor α. We present a new approach for inferring α from trajectories. The core of our approach is a compression algorithm that requires a graph G representing a transportation network, two edge costs modeling routing criteria, and a path P in G representing the trajectory. It yields a minimum subsequence S of the sequence of vertices of P and a balance factor α, such that the path P can be fully reconstructed from S, G, its edge costs, and α. By minimizing the size of S over α, we learn the balance factor that corresponds best to the user's routing preferences. In an evaluation with crowd-sourced cycling trajectories, we weigh the usage of official signposted cycle routes against other routes. More than 50% of the trajectories can be segmented into five optimal sub-paths or less. Almost 40% of the trajectories indicate that the cyclist is willing to take a detour of 50% over the geodesic shortest path to use an official cycle path.

The surface network is an application of the Morse-Smale complex to digital terrain models connecting ridges and thalwegs of the terrain in a planar, undirected graph. Although it provides a topological structure embedding critical elements of the terrain, its application to morphological analysis and hydrology remains limited mainly because the drainage network is the most relevant structure for analysis and it cannot be derived from the surface network. The drainage network is a directed, hierarchical graph formed by streams. Ridges of the surface network are not equivalent to drainage divides, which are not contained in the drainage network, and there is no direct association between thalwegs and streams. Therefore, this paper proposes to extend the surface network into a new structure that also embeds the drainage network. This is done by (1) revising the definition of ridges so that they include drainage divides and (2) assigning a flow direction to each thalweg, taking into account spurious depressions to avoid flow interruption. We show that this extended surface network can be used to compute the flow accumulation and different hydrographic features such as drainage basins and the Strahler order. The drainage network extracted from the extended surface network is compared to drainage networks computed with the traditional D8 approach in three case studies. Differences remain minor and are mainly due to the elevation inaccuracy in flat or slightly convex areas. Hence, the extended surface network provides a richer data structure allowing the use of a common topological data structure in both terrain analysis and hydrology.

We introduce a representative dissimilar path (RDP) query, a novel type of path query in road networks. The k representative paths (RPs) between a source and a destination locations have k smallest costs for a feature (e.g., length, number of road intersections, or straightness). Given x features and k, an RDP query returns a set of paths for a source-destination pair such that the path set includes at least one of the k RPs for every feature, and the path set's similarity score is minimized. We formulate a novel measure to quantify the similarity of a set of paths. Considering different road features and incorporating the novel similarity measure in the computation of RDPs allow us to accommodate the human movement dynamics between two locations in an effective way. Finding the RDPs is a computational challenge because an RDP query requires computing the RPs for multiple features and then finding the RDPs from an exponential number of path combinations. We develop an efficient solution to answer RDP queries. The underlying ideas behind the efficiency of our algorithms are the refinement of the search space, finding the RPs for multiple features with a single search, and exploiting both the lower and upper bounds of the path set's similarity score while identifying the RDPs. We show the efficacy of the RDP query and the efficiency of our solution to answer the RDP query in extensive experiments using real datasets.

The concept of scale is inherent to, and consequential for, the modeling of geographical processes. However, scale also causes huge problems because the results of many types of spatial analysis appear to be dependent on the scale of the units for which data are reported (measurement scale). Consequently, when the same spatial models are calibrated at different scales of aggregations, the results are often vastly different (the well-known Modifiable Areal Unit Problem or MAUP). With the advent of local models and the fundamental difference in their scale of application compared to global models, this issue is further exacerbated in unexpected ways. For example, a global model and local model calibrated using data measured at the same aggregation scale can also result in different and sometimes contradictory inferences (the classic Simpson's Paradox). Here we provide a geographical perspective on why and how contrasting inferences might result from the calibration of a local and global model using the same data. Further, we examine the viability of such an occurrence using a synthetic experiment and two empirical examples. Finally, we discuss how such a perspective might inform the analyst’s conundrum: when the respective inferences run counter to one another, do we believe the local or global model results?

Mapping the extent of spatial objects from point samples is a fundamental process in geographical analysis. Computational geometry methods are commonly used, and one method that has been proposed is the alpha-shape as it is insensitive to both bias and errors that are common in crowdsourced geographic data and big geographic data more generally. However, many spatial objects are uncertain in nature, with vague boundaries that are not well represented by the current use of discrete alpha-shapes. Fuzzy alpha-shapes are presented as a highly generic and adaptable methodology that can produce maps of spatial objects that recognise the vague and uncertain nature of many geographies. A series of virtual geography experiments demonstrate that fuzzy alpha-shapes avoid the need for binary thresholds, create a model that better represents the uncertain boundaries of some spatial objects, while also retaining the robustness to errors and bias that motivated the original use of alpha-shapes for mapping spatial objects.

O presente trabalho apresenta um projeto cartográfico que tem o foco em posicionar o nome da via em relação à feição pontual tratada como símbolo de automóvel para mapa de sistema de navegação e guia de rota em automóvel. Além disso, este trabalho apresenta uma avaliação desses mapas junto a um grupo de 20 motoristas, 10 homens e 10 mulheres, para compreender alguns elementos de usabilidade e de estética do mapa: tempo de leitura, erro e acerto, satisfação geral, aprendabilidade e memorabilidade, adjetivos de estética, carga mental de trabalho e relevância da tarefa. Os resultados permitiram comparar os achados neste trabalho que investiga o posicionamento do nome da via em mapa dinâmico referenciado egocentricamente com a recomendação da literatura a respeito de posicionar a toponímia em relação à feição pontual para mapas estáticos referenciados não egocentricamente, especificamente para apoiar a realização da manobra à direita. Os achados mostram que a posição superior direita é a mais apropriada para mapas tanto estáticos quanto dinâmicos, mas que demais prioridades de posicionamentos recomendados para mapas estáticos referenciados não egocentricamente não podem ser estendidos para mapas dinâmicos referenciados egocentricamente no que diz respeito à rotulação do nome da via onde o motorista se encontra. Para o caso dos mapas dinâmicos para sistemas de navegação, a segunda prioridade dependerá do arranjo dos símbolos cartográficos, mas deverá ser evitada a posição superior esquerda para informar manobra à direita.