Bicycle-metro integration is an efficient method of solving the “last mile” issue around metro stations. Built environment is believed to have a significant effect on cycling behavior. However, transfer cycling around metro stations, as a specific type of cycling behavior, has often been overlooked in transport research. In addition, static contextual units such as circular or street-network buffers

Object-based image analysis (OBIA) has been widely used for classifying high-spatial-resolution images, and the selection of scale parameter(s) is inevitable in previous OBIA tasks. However, selecting appropriate scale(s) for an application inherently depends on the objective of the application, which cannot be robustly solved at the segmentation stage. In this study, a novel framework without any

High-altitude environments are among the most sensitive to climate change, where impacts are amplified. To clarify alpine pasture dynamics in three typical mountains (i.e., Altay, Tianshan, and Kunlun) in central Asia, the change trends in the long-term summer peak Normalized Difference Vegetation Index (NDVI) were examined by applying three satellite sources: Landsat ETM+/OLI (1999–2020), Global Inventory

ABSTRACT MODIS sensors are widely used in a broad range of environmental studies, many of which involve joint analysis of multiple MODIS spectral bands acquired at disparate spatial resolutions. To extract land surface information from multi-resolution MODIS spectral bands, existing studies often downscale lower resolution (LR) bands to match the higher resolution (HR) bands based on simple interpolation

Remote sensing image change detection is an essential aspect of remote sensing technology application. Existing change detection algorithms based on deep learning do not distinguish between changed and unchanged areas explicitly, resulting in serious loss of edge detail information during detection. Therefore, a new attentional change detection network based on Siamese U-shaped structure (SUACDNet)

Remote sensing images have been applied to many aspects in Earth observation work. However, tons of optical remote sensing images are abandoned due to the information loss caused by the clouds and damage of sensing instruments. Recently, many deep learning methods have been proposed to reconstruct the missing information of remote sensing images but they will be non-effective when it comes to the condition

The speeds at which transactions are completed in global financial markets are accelerating and, in the process, connecting financial centers around the globe like never before. Algorithmic trading at high frequency is a form of automated trading in which machines, rather than humans, make the decision to buy or sell in spatiotemporal sequences. Insofar as they have agency of their own, their actions

AbstractThis article questions retailers’ role as buyers driving production. Exploring a network involving Indian suppliers of UK retailers’ cotton garments, limitations preventing coercive buyer power from controlling production practices are identified. Overall, the dominant system of large-scale fragmented supplier networks connecting raw materials to final products accommodates commercially viable

Hyperspectral lidar (HSL) is a novel remote sensing technology that provides spectral information in addition to spatial features. This unprecedented data source leads to new possibilities for monitoring leaf biochemistry. Inversion of physically based radiative transfer models (RTMs) is a popular method for deriving leaf physiological traits due to its robustness and generalization capability. However

Poyang Lake, the largest freshwater lake in China, is featured with high-frequency fluctuations and unique seasonal changes in water level and inundation areas, which plays a substantial part in regulating the runoff of the Yangtze River and maintaining the ecological balance of the region. Frequent observations enable more effectively reflecting the water budgets and related driving force of Poyang

Wetlands serve many important ecosystem services, yet the United States lacks up-to-date, high-resolution wetland inventories. New, automated techniques for developing wetland segmentation maps from high-resolution aerial imagery can improve our understanding of the location and amount of wetlands. We assembled training and testing data sets (patch sizes of 28 × 28 m2 and 56 × 56 m2) of high-resolution

The difficulty in predicting responses to press perturbation is largely due to the tangled nature of indirect interactions in natural ecological networks. Although previous theories have paved the way for evaluating net interaction effects by incorporating direct and indirect effects related to press perturbation, there are still critical knowledge gaps regarding the relationships between net interaction

Plants and their associated microbes influence nutrient cycling in terrestrial ecosystems, yet we have a limited understanding of how soil acidity mediates the process. Here, we investigate whether reported differences in nitrogen (N) cycling between forests dominated by arbuscular mycorrhizal (AM) trees and ectomycorrhizal (ECM) trees are related to changes in soil acid–base chemistry induced by mycorrhizal

Building change detection (BCD) plays a crucial role in urban planning and development and has received extensive attention. However, existing deep learning-based change detection methods suffer from limited accuracy, mainly due to the information loss and inadequate capability in feature extraction. To overcome these shortcomings, we propose a novel deeply supervised attention-guided network (DSA-Net)

Photogrammetry is one of the most reliable techniques to generate high-resolution topographic data and it is key to territorial mapping and change detection analysis of landforms in hydro-geomorphological high-risk areas. Specifically, the Structure from Motion (SfM) is an emerging topographic survey technique that addresses the problem of determining the 3D position of image descriptors to estimate

AbstractIncreasing returns to scale is the basis for many powerful results in economics and economic geography. But the limitations of assumptions about returns to scale in economic growth theories are often ignored when applied to geography. This leads to an unintentional bias favoring scale and mistaken conclusions about geography, scale and growth. Alternatively, this bias is used as a convenient

The geographical literature on urban policymaking has made a considerable contribution to enabling understandings of the relational processes involved in assembling local policies. Reviewing this literature’s journey from its origins in political science to its recent embrace of poststructuralism, this article argues that the debates and discussions involved have arrived at a point of core epistemological

This article examines self-defense as an inherently spatial phenomenon that evidences an assumed right to the individual self and the creation and occupation of space. I argue that self-defense and its claims to space are conceptually and historically denied to Black diasporic populations, as gratuitous violence and the assumption of Black aspatiality void Black claims to self and space. I draw on

Various studies show that bikeshare systems have positive implications for people's health, social cohesion, urban livability, and urban congestion, although many suggest bikeshare systems are not achieving equity goals, particularly regarding low-income people and women. To date, most of these studies come from cities in the Global North, the majority with well-managed governance structures and less

Spatiotemporal variations of forest canopy gaps are essential indicators for both forest dynamic monitoring by capturing their size and location variations and forest ecosystem management for tree seedling regeneration through altering the radiation regime within and under forest canopies. To differentiate the effects of forest canopy gaps on forest three-dimensional (3-D) structure and direct incoming

High spatial resolution hyperspectral images (HR-HSIs) have shown considerable potential in urban green infrastructure monitoring. A prevalent scheme to overcome spatial resolution limitations in HSIs is by fusing low-resolution hyperspectral images (LR-HSIs) and high-resolution multispectral images (HR-MSIs). Existing methods considering the spectral dictionary or spatial dictionary can only reflect

Building height is a pivotal factor in studying urban form and understanding the impacts of the vertical characteristics of urban areas on the environment. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) employ photon-counting LiDAR to collect Earth’s surface elevation data globally. However, method at ground and building photon classification and subsequently building height extraction from

ABSTRACT Poplars are one of the most widespread fast-growing tree species used for forest plantations. Owing to their distinct features (fast growth and short rotation) and the dependency on the timber price market, poplar plantations are characterized by large inter-annual fluctuations in their extent and distribution. Therefore, monitoring poplar plantations requires a frequent update of information

ABSTRACT InSAR processing is vastly used for land deformation monitoring from the space. Machine learning methods are known as strong tools for data modeling as well as predicting. In this study, we are going to model and predict the future behavior of land subsidence by InSAR processing and leveraging deep learning methods over the lands in the vicinity of Lake Urmia (located in the northwest of Iran)

Color cast of the UAV imagery is inevitable due to the temperature and illuminance changes during the UAV flight. Since color is an important feature in crop monitoring, color cast often produces misleading inference in estimation of crop stress, nutrient, and productivity. Therefore, color calibration is a necessary step to remove the negative effects of color variation for UAV based crop monitoring

Mainstream architectures of convolutional neural networks (CNNs) for image recognition follow the protocol of shrinking input data size to extract semantic information. However, poor overall accuracy (OA) may be achieved when dealing with small input size and low-resolution images with classic CNNs. This paper proposes a novel, deep CNN architecture called DRSNet for small patch size Landsat 8 remote

Misclassification of features is a major source of uncertainty in OpenStreetMap (OSM). This study is an automated data-enrichment study whose primary goal is predicting road classes based on multi-classifier systems (MCSs). In this regard, fourteen parameters (thirteen centrality parameters and length) that were assumed to have the highest impact on the classes of the features were calculated for the

Large-scale quantification of ecosystem stability in multiple dimensions is crucial to understanding underlying ecological processes and informing ecological management decision-making. However, historically this field has been limited to spatiotemporal scales based on the use of discrete ground-based measurements. The objective of this study was to quantify ecosystem stability in multiple dimensions

Detection of craters is important not only for planetary research but also for engineering applications. Although the existing crater detection approaches (CDAs) based on terrain analysis consider the topographic information of craters, they do not take into account the spatial structural information of real craters. In this article, we propose an automatic crater detection approach by training random

Created in 1957, the well-known English children’s book character Paddington Bear is the product of a dizzying number of displacements. Author Michael Bond (1926–2017) was inspired to make Paddington an undocumented migrant by World War II and Cold War mass evacuations in Europe, but he transposed Paddington’s origins to the troped space of “Darkest Africa” only to relocate them to “Darkest Peru.”

This article contributes to contemporary debates within the financialization and assetization literatures by examining the sale of tax credits in U.S. property markets over the last twenty years. Whereas the vast majority of research on financial assets focuses on the income-generating aspects of property, this article considers a more holistic approach to assets. Through detailed empirical analysis

Moso bamboo (Phyllostachys edulis) tends to invade any surrounding forest areas due to its aggressive characteristics (fast growth and clonal reproduction), where it changes the species composition and canopy structure of the forests, and has negative effects on forest diversity and ecosystem functions. Unmanned aerial system (UAS)-based remote sensing has the capacity to provide high-resolution, continuous

Assessing the inclination angles (IAs) of tree branches is essential to evaluate their rainfall interception ability. However, depicting the IA distribution within a forest canopy is still a challenge. This study developed the WoodSKE method to extract skeletons from discrete point clouds of tree branches collected by terrestrial laser scanners (TLSs) for assessing their IAs. A TLS point cloud of tree

The quality and integrity of available dam data are critical for broad efforts to produce fine-scale assessments of their basin cycle, water quality, and other environmental and ecological effects. This study proposes a dam identification method in broad areas, object identification based on remote sensing images, and geographical analysis. First, we extracted dam candidate regions from broad surface

Large-scale mapping activities can benefit from the vastly increasing availability of earth observation (EO) data, especially when combined with volunteered geographical information (VGI) using machine learning (ML). High-resolution maps of inland surface water bodies are important for water supply and natural disaster mitigation as well as for monitoring, managing, and preserving landscapes and ecosystems

A wide variety of methods exist nowadays to address the important problem of estimating crop yields from available remote sensing and climate data. Among the different approaches, machine learning (ML) techniques are being increasingly adopted, since they allow exploiting all the information on crop progress and environmental conditions and their relations with crop yield, achieving reliable and accurate

Plant potassium accumulation (PKA) plays an important role in evaluating the production capacity of crops. Remote sensing from unmanned aerial vehicles (UAVs) is increasingly used in precision agriculture, but relatively little is known about its use for determining the potassium (K) nutritional status of rice (Oryza sativa L.). This study compares the performance of different sets of spectral and

Airborne measurements of sun-induced chlorophyll fluorescence (SIF) are a promising tool for monitoring plant functioning on different scales. However, currently operational airborne imaging spectrometers for SIF measurements still have limited spatial resolution and pointing accuracy. This is challenging in terms of the practical use of SIF maps for crop breeding and plant phenotyping. We developed

Journal of Economic Geography 2021, https://doi:10.1093/jeg/lbab028

Journal of Economic Geography, 2021, lbab025, https://doi.org/10.1093/jeg/lbab025

Traditional change detection (CD) algorithms cannot meet the requirements of today’s high resolution remote sensing images (HR). Recently, deep learning-based CD has become a popular research topic. However, there are not many annotated samples for training deep learning (DL) models. Patch-based algorithm has become an important research direction in CD in response to the lack of training datasets

There is a growing acceptance of and interest in transit accessibility-based developments as a means to address urban challenges, such as automobile dependency, air pollution, urban sprawl, and congestion. Additionally, prompting car drivers to switch to public transit requires the construction of attractive and accessible public transit systems. Accordingly, it is necessary to measure railway network

We calibrated the integrated water vapor (IWV) data retrieved from near-infrared (NIR) channels of the Ocean and Land Color Instrument (OLCI) onboard the Sentinel-3A satellite using in-situ GPS-sensed IWV observations. Unlike conventional water vapor retrieval methodologies relying upon radiative transfer code, this method utilized a regression equation to empirically estimate GPS IWV from two NIR

The relationships between the built environment (BE) and car dependence have been thoroughly evaluated, with a primary focus on the residential BE; however, the effects of the BE at workplaces have remained largely unexplored. Little is known about the potential nonlinear effects of the BE at both locations. Using data from a household travel survey in Changchun, China, we aimed to reveal the nonlinear

Free-floating bike-sharing systems have rapidly gained popularity as a viable short-distance transportation mode. As users play a significant role in the movement of the bikes in such a system, the basis for evaluating bike usage is to predict the gap between the locking and unlocking behaviour in a specified grid, which is defined as the inflow and outflow gap. The Spatial-Temporal grid size, including

ABSTRACT Air pollution is a significant urban issue, with practical applications for pollution control, urban environmental management planning, and urban construction. However, owing to the complexity and differences in spatiotemporal changes for various types of pollution, it is challenging to establish a framework that can capture the spatiotemporal correlations of different types of air pollution

ABSTRACT Wind and soil confrontation under specific atmospheric conditions leads to the horrendous phenomenon of dust storms, particularly in arid lands. The negative impact of storms on the health and life of living beings is evident, resulting in many losses in the economic, social, and environmental sectors. Dust storm detection is the most important topic in dust studies, where many algorithms

ABSTRACT The Forel–Ule index (FUI) is one of the indicators used to assess the trophic state of inland waters, which can be objectively determined based on satellite-retrieved corrected hue angles (α). However, the functions for α correction have been proposed based on a dataset from Dutch and the North Sea, which might be inadequate for the precise FUI-derived trophic state. This study proposed a

Tree cover, which has been widely studied using various remote sensing techniques, serves an essential indicator of forest productivity and habitat quality. Spatial heterogeneity in tree cover has received less attention despite links with critical phenomena such as biodiversity, tree re-expansion into formerly deforested areas, and degradation of existing forest landscapes. Few remote sensing studies

The effects of heat waves on traffic collisions require investigation to improve traffic safety during extreme heat events. A time-stratified case-crossover design was used to examine associations between heat waves and traffic collisions in Alabama between May and September from 2009 to 2018. We derived a heat wave index, defined as the daily mean temperature greater than the 95th percentile for two

We examine how China’s urban sprawl is systemically linked to policy sprawl that results from the contradictions inherent within policies but also their magnification by the specifics of policy development and circulation within China. We define the concept of policy sprawl by distinguishing it from policy creep and churn, making a distinct contribution to the extant literature on policy mobility.

Climate-induced displacement is attracting increasing media, state, and scholarly attention, albeit often in a way that situates migration as either an example of climate adaptation or a failure thereof. Whether depicted as success or failure, both framings can invisibilize the preexisting socioenvironmental processes that render climate-induced migrations necessary—or, conversely, that can inhibit

Journal of Economic Geography 2020, 21, 287–315; doi: 10.1093/jeg/lbaa035

Demand Responsive Transport (DRT) systems are often discussed to expand public transport in rural areas, where conventional buses are often used below capacity. DRT systems can particularly improve the mobility situation for less mobile people or other people who depend on public transport and ultimately prevent them from social exclusion. This paper examines whether people who show characteristics

Researchers usually conduct a questionnaire survey at bus stops to obtain data regarding the satisfaction of bus passengers with waiting times. The results are affected by many factors. Among them, the land use of the bus stops was proved to have an important impact on the survey results. The main contribution of this paper is the introduction of propensity score matching (PSM) into the evaluation

Former field systems (FFS) are the most widespread traces of ancient activities in present European landscapes and represent significant perturbations to ecosystems. Through its ability to penetrate forest canopies and detect microlandforms, Airborne Laser Scanning data reveal archaeological relics over large areas, from periods older than the first available Historical Topographic Maps. Mapping these

A long-standing question in ecology and biogeography is how the population of a species is distributed across space. The highest abundance has been hypothesized to be in the geographical centre or the niche centre, although mixed patterns from empirical studies have triggered a recent debate. Here, we propose a conceptual framework based on environmental suitability and dispersal to interpret the mixed

Whether marine species can respond to ocean warming by changing their depth remains controversial. Some evidence suggests that species can deepen to cope with warming climates, whereas other studies have found ecologically constrained depth distributions. Our study focuses on generalizing the depth response of species to warming and elucidating whether some species display a larger change in depth