The subdivision of the Earth's terrestrial surface into different biomes, ecozones, bio-climatic realms or other large ecological land units is an essential reference for global biogeographical and ecological studies. Various classification schemes exist. These differ significantly in terms of the considered criteria for classification and the underlying methodology of class assignments. Evident divergences

Anticipating when and where changes in species' demographic rates will lead to range shifts in response to changing climate remains a major challenge. Despite evidence of increasing mortality in dry forests across the globe in response to drought and warming temperatures, the overall impacts on the distribution of dry forests are largely unknown because we lack comparable large-scale data on tree recruitment

Large levels of working from home (WfH) were induced by social distancing and viral control measures undertaken to mitigate the Covid-19 pandemic. Representing an unpredicted change in the way large amounts of people undertake their day to day work, it is expected that the legacy of this event, in terms of significant alterations to work and commuting patterns will have wide-ranging and long-lasting

The accuracy of phase unwrapping in multi-temporal interferometric synthetic aperture radar (MT-InSAR) technology affect closely on the accuracy of ground deformation monitoring. In the urban area, urban infrastructures such as high-rise buildings present additional challenges to phase unwrapping due to the sudden elevation changes. The failure rate of phase unwrapping is often much higher in such

Environmental studies based on analyses of fluvio-aeolian successions with paleosols in central Poland, forming the central part of the European Sand Belt, are presented. Paleogeographic reconstruction was based on high-resolution analyses of four sites using sedimentological and paleopedological methods as well as forty-four optically stimulated luminescence and fourteen radiocarbon dating measurements

Initiation of autumnal leaf senescence is crucial for plant overwintering and ecosystem dynamics. Previous studies have focused on the advanced stages of autumnal leaf senescence and reported that climatic warming delayed senescence, despite the fundamental differences among the stages of senescence. However, the timing of onset of leaf coloration (DLCO), the earliest visual sign of senescence, has

Historical changes in sea level caused shifting coastlines that affected the distribution and evolution of marine and terrestrial biota. At the onset of the Last Glacial Maximum (LGM) 26 ka, sea levels were >130 m lower than at present, resulting in seaward-shifted coastlines and shallow shelf seas, with emerging land bridges leading to the isolation of marine biota and the connection of land-bridge

In recent years, near-surface ozone (O3) pollution has been increasing, seriously endangering both the ecological environment and human health. Accurately monitoring spatially continuous surface O3 is still difficult with only remote sensing observations. In this paper, to address this issue, we propose a method for estimating surface O3 by fusing multi-source data, including in-situ observations,

Urban Geography studies forms, social fabrics, and economic structures of cities from a geographic perspective. Catalysed by the increasingly abundant spatial big data, Urban Geography seeks new models and research paradigms to explain urban phenomena and address urban issues. Recent years have witnessed significant advances in spatially-explicit geospatial artificial intelligence (GeoAI), which integrates

Inter-tree competition can be assessed using relatively simple indices derived from tree diameters, heights and locations, but they have often been found to be deficient for predicting tree growth. To better understand these linkages, we measure dimensions of Scots pine and Norway spruce crowns, which are assumed to be affected by competition pressure. We extract these features from terrestrial laser

Given the prominence of 3D sensors in recent years, 3D point cloud scene data are worthy to be further investigated. Point cloud scene understanding is a challenging task because of its characteristics of large-scale and discrete. In this study, we propose a network called LEARD-Net, focuses on semantic segmentation for the large-scale point cloud scene data with color information. The proposed network

The stable and reliable supply of electric power is strongly related to the normal social production. In recent years, power transmission lines inspection based on remote sensing methods has made great progress, especially using the UAV-borne LiDAR system. The extraction and identification of power transmission lines (i.e., conductors) from 3D point clouds are the basis of LiDAR data-based power grid

The rapid expansion of CubeSat constellations could revolutionize the way inland and nearshore coastal waters are monitored from space. This potential stems from the ability of CubeSats to provide daily imagery with global coverage at meter-scale spatial resolution. In this study, we explore the unique opportunity to improve the retrieval of bathymetry offered by CubeSats, specifically those of the

Ocean temperature is a vital physical variable of the oceans. Accurately predicting the long lead dynamics of the three-dimensional ocean temperature (3D-OT) can help us identify in advance potential extreme events (e.g., droughts and floods) that may be caused by the changes of the 3D-OT, which however remains a challenge. To achieve this goal, a deep learning (DL) model was proposed to make predictions

Cycling benefits both the individual and society in terms of public health promotion, traffic congestion relief and vehicle emissions reduction. To better understand cycling behaviors, we analyze non-linear relationships and interaction effects between the built environment and cycling distance. Few studies explore the interaction effects on cycling distance in which road network patterns interact

Dispersal and environmental gradients shape marine microbial communities, yet the relative importance of these factors across taxa with distinct sizes and dispersal capacity in different ocean layers is unknown. Here, we report a comparative analysis of surface and deep ocean microbial beta diversity and examine how these patterns are tied to oceanic distance and environmental gradients.

Geographically and temporally weighted regression (GTWR) models have been widely used to explore spatiotemporal nonstationarity where all the regression coefficients are assumed to be varying over both space and time. In reality, however, constant, only temporally varying, and only spatially varying coefficients might also be possible depending on the underlying effects of the explanatory variables

In this article, we explore rights of nature (RoN) as an emerging rights-based environmental governance that intends to reframe nature from property to an entity with a right to exist unharmed. Its proponents claim this is a paradigm shift that reworks the imbalanced human–nature hierarchy. We interrogate this claim using data collected from more than 60 U.S. communities where RoN ordinances have been

Shared micromobility services have undergone rapid growth in cities throughout the world, including expansions in bike sharing and e-scooter sharing services. Shared micromobility provides a potential complement to public transit by accommodating first and last-mile trips. I analyze detailed data on shared, dockless bikes and e-scooters from Seattle, Washington. I find micromobility vehicles cluster

Fostering environmentally friendly transport solutions for visitors lies at the core of the strategies aimed at implementing sustainable tourism destinations. In this sense, this study aims to identify the determinants of green mobility choices taken by young adults during their holidays. It is based on a survey proposed to Italian and Spanish University students. The study demonstrates the intrinsic

ABSTRACT Airborne LiDAR has become an essential data source for large-scale, high-resolution modeling of forest aboveground biomass and carbon stocks, enabling predictions with much higher resolution and accuracy than can be achieved using optical imagery alone. Ground noise filtering – that is, excluding returns from LiDAR point clouds based on simple height thresholds – is a common practice meant

Despite its success, deep learning in land cover mapping requires a massive amount of pixel-wise labeled images. It typically assumes that the training and test scenes are similar in data distribution. The performance of models trained on any particular dataset could degrade significantly on a new dataset due to the domain shift or domain gap across datasets, resulting in new training data requiring

Deep learning has been extensively applied in hyperspectral image (HSI) classification for its excellent representation ability. However, the existing training scheme generally adds a supervised classifier to the last layer of the network, so it is difficult to acquire full-scale fine-grained details and coarse-grained semantic information. Moreover, the robust performance of deep learning is commonly

Pine wilt disease (PWD) poses a serious threat to the worldwide pine forest resources. Unmanned aerial vehicle (UAV) remote sensing has been widely used for PWD control, due to its flexibility and efficiency. Although pixel-level detection can obtain fine detection boundaries, there have been few related works in complex scenes because of the difficulty of setting a preset category system and the poor

This paper aims to assess the potential of Ocean Land Colour Instrument (OLCI) for the retrieval of chlorophyll-a (chl-a) over southern coastal waters of Vietnam. For that purpose, four chlorophyll-a ocean color (OC) algorithms (OC4ME and three new OC version 7 OC4, OC5, OC6) were applied based on water-leaving reflectance obtained from two atmospheric correction processors (C2RCC and DSF). To overcome

The aim was to evaluate fire activity for the entire Amazon and Amazon regions within each country/department from 2003 to 2020, assessing the potential contributions of drought and deforestation and contrasting 2020 with the previous years.

While it is now well accepted that human activities are having pronounced effects on natural ecosystems, regional variation in the rate and magnitude of various human impacts is unclear. Moreover, the effects of land use change on natural aquatic communities have only relatively recently begun to be explored. Our goal was to understand how and where assemblages of a central food web component of freshwater

Compared with gradual climate change, extreme climatic events have more direct and dramatic impacts on vegetation growth. However, the influence of climate extremes on important phenological periods, such as the end of the growing season (EOS), remains unclear. Here, we investigate the temporal trends of EOS across different biomes and quantify the response of EOS to multiple climate extreme indices

This article advances a new approach using hierarchical cluster analysis (HCA) for identifying and delineating spatial agglomerations and applies it to venture-backed startups. HCA identifies nested clusters at varying aggregation levels. We describe two methods for selecting a particular aggregation level and the associated agglomerations. The ‘elbow method’ relies entirely on geographic information

Semantic segmentation of 3D mobile laser scanning point clouds is the foundational task for scene understanding in several fields. Most existing segmentation methods tend to simply stack the common point attributes, such as the coordinates and intensity, but ignore their heterogeneous. This paper presents IDA-Net, an intensity-distribution aware network that mines the uniqueness and discrepancy of

Tree pests have major impacts in both natural and agricultural systems. Despite their ecological and economic importance, it is likely that pests go unreported in many regions. Using a global dataset of tree pests and multiple metrics of pest diversity standardized for host availability, we describe the biogeography of under-reporting and reveal potential for future pest invasions.

Deep learning based change detection has brought a significant improvement in the accuracy and efficiency when compared with conventional machine learning methods. However, the issues of the lack of differential information and the diversity of the scale features of artificial objects are crucial barriers to the application of building change detection algorithms. A novel deep learning based approach

Usually, continuous effective optical observation data collected from a single-sensor within one year is not available, most studies conducted rice mapping in Northeast China using optical remote sensing images collected from multi-years and multi-sensors. Meanwhile, the accuracies of mapping results are limited by the employed traditional machine learning algorithms, which cannot fully exploit the

The assessment of forest abiotic damages such as snow breakage is important to ensure compensation to forest owners. Currently, information on the extent of snow breakage is gathered through time-consuming and potentially biased field surveys. In such situations where field surveys are still common practice, unmanned aerial vehicles (UAVs) are increasingly being used to provide a more cost-efficient

Extensive human activities and climate change in recent decades have triggered severe eutrophication problems in the coastal oceans in the Greater Bay Area (GBA) of China. However, a comprehensive characterization of the spatial and temporal patterns of chlorophyll-a (Chl-a, a major indicator of phytoplankton biomass) in this region is not available. Our study attempts to fill this gap by using long-term

Geomorphological mapping became one of the important aspects of landforms depiction, which has been developed from classical field-based to remotely sensed-based observations with or without ground-truthing over the last few decades. The availability of such data is essential for land-use planning as well as for decision-makers. To that end, we have created a simplified SRTM-based map for Saudi Arabia

The main solution for large-scale point clouds registration is to first obtain a set of matched 3D keypoint pairs and then accomplish the point cloud registration task based on these matched keypoint pairs. However, at present, many methods study the feature descriptors in the point clouds registration task, but few methods discuss the 3D keypoints detection issues. The commonly used 3D keypoints detection

From an epidemiological perspective, previous research on COVID-19 has generally been based on classical statistical analyses. As a result, spatial information is often not used effectively. This paper uses image-based neural networks to explore the relationship between urban spatial risk and the distribution of infected populations, and the design of urban facilities. To achieve this objective, we

ABSTRACT This study examines the use of the Multi-Spectral Instrument (MSI) in Sentinel-2 satellite in combination with regression-based random forest models to estimate bathymetry along the extended southwestern Florida nearshore region. In this study, we focused on the development of a framework leading to a generalized Satellite-Derived Bathymetry (SDB) model applicable to an extensive and diversified

ABSTRACT Remote sensing has evolved as an alternative to traditional techniques in the spatio-temporal monitoring of the Antarctic ecosystem, especially with the rapid expansion of the use of Unmanned Aerial Vehicles (UAVs), providing a centimeter-scale spatial resolution. In this study, the potential of a high-spatial resolution multispectral sensor embedded in a UAV is compared to medium resolution

ABSTRACT In the research of automatic interpretation of remote sensing images, semantic segmentation based on deep convolutional neural networks has been rapidly developed and applied, and the feature segmentation accuracy and network model generalization ability have been gradually improved. However, most of the network designs are mainly oriented to the three visible RGB bands of remote sensing images

ABSTRACT Building detection from very high resolution (VHR) optical remote sensing images, which is an essential but challenging task in remote sensing, has attracted increased attention in recent years. However, despite the many methods that have been developed, an in-depth review of the recent literature on building extraction from VHR optical images is still lacking. In this article, we present

ABSTRACT Abstract: Rangelands have a dynamic response to climate change, fire, and other anthropogenic disturbances. The Rangeland Condition, Monitoring, Assessment, and Projection (RCMAP) product aims to capture this response by quantifying the percent cover of eight rangeland components, associated error, and trends across the western United States using Landsat from 1985 to 2020. The current generation

This research sets an example of how large-scale walkability indices can be transformed into microscale walkability indices through a systematic evaluation of the different local components of the built environment. A Geographic Information System (GIS)-based qualitative scoring system of 15 micro-variables is developed to assess the walkability performances of the urban streets. Furthermore, the proposed

The article is based on a multidisciplinary research project that aimed to study mobility challenges that refugees in Tucson, Arizona experience after their resettlement. Using qualitative and quantitative data collected from interviews and survey data, we argue that mobility shapes the ways refugees foster social connections, attain employment and access educational opportunities. Accordingly, barriers

Buildings are the predominant objects that characterize the urban structure. For many cities, local governments establish building databases for administration as well as urban planning and monitoring. However, newly constructed buildings are often only included with a considerable time delay in the official digital cadastral maps due to processes in the acquisition of data, so-called undocumented

Tropical forests are important sources of securing basic human needs (livelihoods) for both the deprived and well-endowed but are also critical for reducing metric tonnes of carbon (tC) emitted from deforestation and land degradation. However, inequalities of human population and land-use land-cover change (LULCC) are existential threats to sustainable tropical forest reserve management and their aboveground

Converting an image to a set of superpixels is a useful preprocessing step in many computer vision applications; it reduces the dimensionality of the data and removes noise. The most popular superpixels algorithm is the Simple Linear Iterative Clustering (SLIC). To use original SLIC with non-imagery data (for example, rasters of discrete probability distributions, time-series, or matrices describing

Do any of the known synergies existing between either geography and art or mathematics and art bridge all three of these disciplines? The geo-humanities and the math-humanities literatures describe only these two individual synergies. A new quantitative geography methodology exploits a sophisticated mathematical concept to analyze remotely sensed satellite images, which, when extended to artistic paintings

In the United States, the Federal Emergency Management Agency (FEMA) delineates 100-year flood zones to define risks, regulate flood insurance premiums, and inform flood management. Evidence indicates that FEMA flood maps are incomplete, calling much of our current knowledge of U.S. flood hazard inequities into question. We use a state-of-the-art flood hazard model and census tract-level dasymetrically

Historically, urban developers, politicians, and public water utilities have invented Los Angeles as a semitropical oasis in a dry climate. During the California drought of 2011 through 2016, however, the city’s residential gardens became a new frontier of water conservation policy. Water agencies started to subsidize the replacement of lushly irrigated lawns with California Friendly® landscapes, thereby

The recruitment and deployment of migrant fishers in distant waters (DW) fisheries has emerged as a significant site for the production of unfree labor relations. We trace the recruitment and deployment geographies of migrant fishers from the Philippines to the vessel, conceptualizing the time-spaces of the journey as a significant site for producing unfree labor. We argue that labor brokerage not

This article considers haptic—the sense of touch in all its forms—as an assemblage of performative and situated knowledge, multisensory experiences, digital and material relationalities, and everyday practices, that is shaping and shaped by domestic atmospheres and affects. It brings research topics on haptic geographies and geographies of home into the digital context to investigate how routinized

This study envisages to investigate the hurdles in widespread usage of Electric-Vehicles(EVs) on a global scale by using cross-country panel data. This paper empirically studies the impact of wide range of parameters like policies & incentives, national commitments, socioeconomic factors, charger infrastructure, fuel price and renewables on cross-country EV demand by using two-way Fixed Effect Model

ABSTRACT Landslides are major geological hazards and frequently occur in mountainous areas with steep slopes, often causing significant loss. Interferometric Synthetic Aperture Radar (InSAR) has been widely used in landslide measurement over the last three decades. However, InSAR only can measure one-dimensional displacements (i.e. those in the radar’s line of sight (LOS) direction), resulting in the

Laser point cloud provides a high-precision data source for the 3D model reconstruction of existing trees. However, due to the complexity of tree structure and the data missing of point cloud, it is difficult to reconstruct complete, detailed and accurate 3D tree models from discrete points, especially the points are incomplete due to single-view scanning. To this end, a new point cloud driven method

Butterflies represent a model in biology and a flagship group for invertebrate conservation. We provide four new resources for the Western Palaearctic butterflies: (1) an updated checklist comprising 552 species; (2) a curated dataset of 32,126 mitochondrial cytochrome c oxidase subunit I (COI) sequences for 532 species, including a de novo reference library for the Maghreb (Morocco, northern Algeria

We examine the fertility impact of a family-based regularization policy granting temporary legal status to unauthorized immigrants based on their offspring’s citizenship. The policy, enacted through a 2011 Royal Decree in Spain, allows for unauthorized parents of eligible nationalities to become temporary legal residents if they have a Spanish minor. Using data from the Spanish Labor Force Survey (2007–2016)