ABSTRACT Urban physical environments are the physical settings and built environments in neighbourhoods and cities which provide places for human activities. Evidence suggests that there are substantial associations between urban physical environments and various health outcomes, e.g. people’s physical activities might be influenced by surrounding physical environments, thereby affecting their health behaviours; more exposure to urban physical environments may benefit human mental health. Street view imagery enables us to capture the landscape at eye-level, making it a promising data source for observing and analysing the realistic dynamics of urban physical environments. Compared with traditional in-person assessments and field observations, street view imagery-based data collection is relatively time-effective and cost-effective. Researchers from epidemiology, psychology, and geography have used street view imagery to quantify the built environment and understand its impacts on public health. To summarize current research trends, this paper systematically reviews the use of street view images for sensing urban environments in public health studies. Specifically, we describe the characteristics of street view imagery and review the methodology for image processing and semantic understanding. We then summarize the challenges that remain for quantifying urban environments in terms of data and methodology. Several future research directions that would benefit public health research and practices are recommended in urban environment research.
Viktoriia Lovynska, Oliver Wiche, Hermann Heilmeier
et al.
Soil pollution is a global threat that seriously affects biodiversity in (agro)ecosystems and may compromise water and food quality. Therefore, the ability of tree species (<i>Populus tremula</i>, <i>Salix caprea,</i> and <i>Betula pendula)</i> to accumulate and phytoextract specific toxic heavy metals from soil was investigated. The study was conducted in and near relict mining areas of Freiberg (Germany) and sampling sites selected according to their spatial location relative to potential sources of metal(loid)s. The concentrations of geogenic (P, Fe, Mn, Ca) and pollutant (Pb, Cd, Zn, As) elements in soil and the present trees were measured using ICP-MS. The highest total soil concentrations of As (8978 µg g<sup>−1</sup>) were found within the Davidschaft mining area, and for soil Pb, both in the Davidschaft vicinity (328 µg g<sup>−1</sup>) and mining area (302 µg g<sup>−1</sup>). Unexpectedly, the highest soil Zn (0.64 mg g<sup>−1</sup>) and Cd (3.5 mg g<sup>−1</sup>) concentrations were found in Freiberg city Forest. The lowest soil concentrations of pollutants (As, Cd, Pb, and Zn) were recorded for Seifersdorf. Total soil P was highest in Colmnitz, but Ca, Mn, and Fe concentrations were very similar across all sites. The available concentration of all measured toxic elements in the soil generally decreased in the order Davidschaft > Davidschaft vicinity, Colmnitz > Seifersdorf = Freiberg city forest. All studied tree species had higher concentrations of the essential elements in leaves than in branches. Generally, higher values of bioaccumulation coefficients (especially for Cd) were found for <i>Salix caprea</i> compared with <i>Populus tremula</i> and <i>Betula pendula</i>.
Cropland non-agriculturalization (CNA) monitoring is a typical change detection (CD) problem based on remote sensing imagery, aimed at tracking cropland outflow changes, which holds significant importance for cropland protection and food security. Recently, numerous advanced CD methods have been proposed to address the CNA problem. However, applying these methods to cross-regional or large-scale CNA detection presents several challenges: (1) Radiance-feature differences of croplands across regions i.e., crop type and phenology differences arising from variations in planting structures and seasonality; (2) Change-pattern differences of croplands across regions, i.e., differences in predominant change types resulting from distinct regional economic development characteristics. These cross-regional differences, when coupled together, result in insufficient adaptability of CD methods across regions. To address these issues, a Cross-Region Cropland Change Detection (CR-CLCD) framework with Multi-View Domain Adaptation (MVDA) is proposed. Specifically, Pattern Distribution Contrastive (PDC) sub-module achieves feature alignment from the semantic view by imposing contrastive constraints across inter-domain categories. Radiative Discrepancy Adversarial (RDA) sub-module, performs inter-domain global and local feature confusion by identifying regions of local uncertainty and applying enhanced adversarial training. MVDA is a flexible, plug-and-play domain adaptation module that can be seamlessly integrated with any existing change detection backbone network (e.g., CNN, Transformer), enabling rapid generalization to new data under unsupervised conditions. The experimental results demonstrate that the proposed CR-CLCD method achieves the best or second-best accuracy compared to other domain adaptation methods across different baselines.
Accurate extraction of landslide information is crucial for timely disaster emergency response, yet this process faces significant challenges due to the interference of bare land and vegetation cover as well as the variability in landslide scales. Furthermore, the scarcity of comprehensive landslide datasets has hindered the in-depth exploration of deep learning techniques in this domain. Addressing these issues, this study introduces a novel framework for landslide extraction that leverages the characteristics of context association. In the encoding phase, a two-branch multiscale context feature extraction module (TMCFM) is established, which captures the contextual relationships across different scales through an attention mechanism while concurrently extracting context information within the same scale. To refine the interplay between features at different levels, self-attention is utilized, allowing for the effective fusion of context information at both ends of the same scale through feature fusion exploiting static and dynamic context feature modules (FSDC). Building upon this, this study develops a deeply supervised classifier (DSC) that enhances the network’s discriminative capabilities in the prediction phase via six auxiliary branches. Additionally, this study contributes a new aerial image dataset for landslide extraction created through meticulous visual interpretation. The proposed method is thoroughly compared with 17 contemporary deep learning methods, demonstrating an increase in the intersection-over-union (IoU) metric of 0.92%-16.94% over these methods. The robustness and superiority of the proposed approach are further validated through various discussions and analyses.
Study region: The Dajing and Xiaojing karst underground river system is the longest underground river in Guizhou Province, Southwest of China，located around the Five-hundred-meter Aperture Spherical radio Telescope (FAST). Study focus: The water quality of underground rivers around the FAST being affected by multiple anthropogenic activities. The underground river system is an extremely non-homogeneous and anisotropic media with complex hydrodynamic and hydrochemical responses. Multi-tools (hydrochemistry, water isotope, sulfur isotope and statistical methods) were applied to accurate identification and quantification of the proportions, spatiotemporal evolution and mechanisms of karst aquifer impacted by different anthropogenic activities. New hydrological insights for the region: The synchronous variations of δ18O, δD, d-excess and δ34SO42- in the effluent and the underground rivers suggested that the underground rivers are influenced by anthropogenic activities. The relationships of ionic ratios revealed that agricultural activities, effluent from the sewage treatment plant, and water-rock interactions control the hydro-chemical characteristics of the underground river system with a distinct spatiotemporal differentiation. The response time for the water quality of Dajing and Xiaojing underground river to anthropogenic impacts were 24 and 27 days, respectively. Spatially, the PCA-ACPS-MLR and MixSIAR indicated that more impacts of anthropogenic activities on Xiaojing underground river than Dajing underground river system. A quantification of spatiotemporal response differentiation provides new insights into the precise identification and prevention of pollution in karst underground rivers.
Roghayeh Ghasempour, Kiyoumars Roushangar, V. S. Ozgur Kirca
et al.
Beside in situ observations, satellite-based products can provide an ideal data source for spatiotemporal monitoring of drought. In this study, the spatiotemporal pattern of drought was investigated for the northwest part of Iran using ground- and satellite-based datasets. First, the Standardized Precipitation Index series were calculated via precipitation data of 29 sites located in the selected area and the CPC Merged Analysis of Precipitation satellite. The Maximal Overlap Discrete Wavelet Transform (MODWT) was used for obtaining the temporal features of time series, and further decomposition was performed using Ensemble Empirical Mode Decomposition (EEMD) to have more stationary time series. Then, multiscale zoning was done based on subseries energy values via two clustering methods, namely the self-organizing map and K-means. The results showed that the MODWT–EEMD–K-means method successfully identified homogenous drought areas. On the other hand, correlation between the satellite sensor data (i.e. the Normalized Difference Vegetation Index, the Vegetation Condition Index, the Vegetation Healthy Index, and the Temperature Condition Index) was evaluated. The possible links between central stations of clusters and satellite-based indices were assessed via the wavelet coherence method. The results revealed that all applied satellite-based indices had significant statistical correlations with the ground-based drought index within a certain period. HIGHLIGHTS
Discussing the spatiotemporal variations of drought using in situ observations and satellite-based datasets.;
Applying the hybrid MODWT–EEMD–K-means method for catching similar zones.;
Discussing the possible links between the SPIs of the central stations of clusters and satellite-based drought indices via the wavelet coherence (WTC) method.;
Evaluating drought conditions using the satellite-derived NDVI and LST products.;
River, lake, and water-supply engineering (General), Physical geography
Karl J. Romanowicz, Byron C. Crump, George W. Kling
Soil anoxia is common in the annually thawed surface (‘active’) layer of permafrost soils, particularly when soils are saturated, and supports anaerobic microbial metabolism and methane (CH<sub>4</sub>) production. Rainfall contributes to soil saturation, but can also introduce oxygen, causing soil oxidation and altering anoxic conditions. We simulated a rainfall event in soil mesocosms from two dominant tundra types, tussock tundra and wet sedge tundra, to test the impacts of rainfall-induced soil oxidation on microbial communities and their metabolic capacity for anaerobic CH<sub>4</sub> production and aerobic respiration following soil oxidation. In both types, rainfall increased total soil O<sub>2</sub> concentration, but in tussock tundra there was a 2.5-fold greater increase in soil O<sub>2</sub> compared to wet sedge tundra due to differences in soil drainage. Metagenomic and metatranscriptomic analyses found divergent microbial responses to rainfall between tundra types. Active microbial taxa in the tussock tundra community, including bacteria and fungi, responded to rainfall with a decline in gene expression for anaerobic metabolism and a concurrent increase in gene expression for cellular growth. In contrast, the wet sedge tundra community showed no significant changes in microbial gene expression from anaerobic metabolism, fermentation, or methanogenesis following rainfall, despite an initial increase in soil O<sub>2</sub> concentration. These results suggest that rainfall induces soil oxidation and enhances aerobic microbial respiration in tussock tundra communities but may not accumulate or remain in wet sedge tundra soils long enough to induce a community-wide shift from anaerobic metabolism. Thus, rainfall may serve only to maintain saturated soil conditions that promote CH<sub>4</sub> production in low-lying wet sedge tundra soils across the Arctic.
Study region: Hong Kong, China. Study focus: This paper aims to develop a flood analysis model to integrate the effects of multiple flooding triggers (i.e. rainfall, high sea levels and wave overtopping) during powerful tropical cyclones and investigate coastal flood hazards in an urban area at the street scale. The process of wave overtopping is properly estimated and integrated in a dual-drainage model in a maneuverable way as an inflow discharge hydrograph. The inundation during Typhoon Mangkhut, 2018, in Tseung Kwan O town center, a coastal community of Hong Kong, is taken as a case study. New hydrological insights for the region: The inundation scenario in Tseung Kwan O town center during Tyhpoon Mangkhut is reproduced and comparison between different drainage conditions demonstrates the key role of drainage facilities in the mitigation of flooding induced by wave overtopping, although the varying sea level boundary could partly reduce the drainage efficiency. In addition, possible flood scenarios and pedestrian stability in flowing water upon the unfavorable combination of storm surge and astronomical tide, as well as the effectiveness of a 1.1 m wave wall are evaluated. The overtopping discharge, flooding severity and dangerous zones for pedestrian can be markedly reduced by the wave wall.
Nutchanart Sriwongsitanon, Thienchart Suwawong, Sansarith Thianpopirug
et al.
Study region: Annual and monthly ET values from seven global remote sensing products (ALEXI, CMRSET, ETMonitor, GLEAM V3.3b, MOD16A2, SEBS V3 and SSEBop) were validated for 172 sub-basins in Thailand. Study focus: This study describes a generalised validation procedure that uses rainfall (P), streamflow (Q) and storage change data (from the Gravity Recovery and Climate Experiment - TWSCGRACE) and land use information. For each sub-basin, bulk ET was computed using the water balance framework and compared to estimates by ET products. Inverse water balance computations were applied to infer the storage change estimates from each product (ΔS = P – Q - ETRS), which were compared to TWSCGRACE to assess their monthly scale performances. New hydrological insights for the region under study: All products performed very well on the annual basis (mean NSE > 0.96) and satisfactorily on the monthly scale (mean NSE > 0.65). Land use classifications from the Land Development Department were used to examine the ability of four candidates (CMRSET, MOD16A2, GLEAM V3.3b and ETMonitor) to provide ET estimates with correspondence to physical land use conditions. By also considering product resolutions and data accessibility, MOD16A2 was consensually shown to be the most promising product to be used for water resources management in Thailand. In addition to local applications, the outcomes emanate the potential for utilisation on the global scale which should be further investigated.
Este artigo busca analisar as implicações sócioterritoriais resultantes dos processos de expropriação das comunidades locais do megaprojecto de mineração da Vale no distrito de Nacala-a-Velha. A perspectiva teórico-metodológica, adoptada consistiu na abordagem qualitativa, com carácter descritivo e exploratório. Para a análise do objecto de pesquisa, o estudo privilegiou as pesquisas bibliográfica e documental. Foram aplicadas as técnicas de observação directa e entrevista semi-estruturada aos representantes das duas comunidades reassentadas pela Vale no distrito de Nacala-a-Velha. Os resultados obtidos permitiram-nos compreender que os programas de reassentamento da Vale no distrito de Nacala-a-Velha inserem-se no contexto da emergência das apropriações transnacionais de terras ou landgrabbing, que prevêem a concessão de vastas porções de terra para investidores estrangeiros, e, por conseguinte, a expropriação das comunidades locais para regiões longínquas, inférteis, desprovidas de acesso a bens naturais como: a água potável, insumos agrícolas, escolas, hospitais e outras infra-estruturas aumentando assim, a insegurança alimentar.
Chek Lap Kok (Hong Kong Airport) 21.00 01.12.19, a short video by Stephen Connolly which documents a walk to Hong Kong Airport from the Expo centre on the airport island, by means of slow travel, under makeshift conditions, and without carbon expenditure. The video offers a brief exploration of the materialities and grounded infrastructures of aviation at a moment of pandemic-led change and invites us to look anew at the familiar and banal physical geography of the airport and how we move within it, drawing on Lefebvre’s Production of Space and theories of ‘Spatial Cinema’.
Urban green parks perform a remarkable role for the physical, social and psychological wellbeing of the urban public by providing space for relaxation and recreation, directly influencing public health through mitigation of the urban heat impact, noise reduction and moderation of air and water pollution. An indicator-based approach on analytical hierarchical processing was used to identify and assess the driving forces for the utilization of urban green parks and their accessibility. Eight indicators: location, topography and geography, facility and services, safety and security, social and culture, ecology, demography, and weather and climate (further divided into 50 factors) were used in the study. Data were collected through a questionnaire survey in which 887 regular park users participated. A standardized study design was implemented to study and assess four urban green parks in the Colombo metropolitan district, Sri Lanka. The study identified park facilities and services as well as safety and security measures maintained by the park as the key factors of appeal, while location, ecology, topography and geography, including weather and climate, had a lower relative influence when selecting a park for recreation. Social, cultural and demographic factors appeared to be of the least interest. The study recommends park managers to assess their parks using this model to enhance the characteristics found to be the most important. It further suggests developing models also for other park types by considering which factors would have the highest relative influence in providing a better service for the regular park user.
Study region: The annually flooded Barotse Floodplain in the upper Zambezi River Basin in the Western Province of Zambia, Southern Africa.
Study focus: Discharge variability plays a significant role in inundation extent and thus it controls habitat conditions of river channels and the linked wetlands. The linkage between discharge and inundation extent in the Barotse Floodplain allowed us to analyse the trends in extent overtime using optical satellite imagery MODIS. The Desert Flood Index, a surface water extraction algorithm, was used to generate time series of inundation extent. For validation of the inundation extent we used a flood mask extracted from a supervised classification land cover map using Landsat imagery. The land cover map was validated using the error matrix method with ground truthed data. The estimated inundation extent time series enabled us to test the inundation correlation with discharge and water level using Pearson r correlation, a parametric statistical test. Based on the established correlation we used the Mann–Kendall, a non-parametric test, to analyse trends in the inundation extent and discharge and water level time series from which we made inferences on the direction of the historical trend in inundation extent.
New hydrological insights for the region: The results revealed that there is observable inter-annual variability in inundation extent in the Barotse Floodplain with prominent differences demonstrated in both the flood ascending/peak and receding period. For the period 2003–2013 the results indicated a rising trend in inundation extent with a Mann–Kendall Z statistic of 1.71 and increase in magnitude of 33.1 km2 at significance level alpha of 0.05. Strong correlations between inundation extent and water level and between inundation extent and discharge with correlation coefficients of determination of 0.86 and 0.89 respectively were observed. For the period 2000–2011 water level time series showed a rising trend with the Mann–Kendall Z statistic of 2.97 and increase in magnitude of 0.1 m at significance level alpha of 0.05. Overall, during the period 1952–2004 discharge in the floodplain showed a declining trend with Mann–Kendall Z statistics of −2.88 and −3.38 at the inlet and outlet of the floodplain respectively. By correlation inference, the overall inundation extent trend in the floodplain was in a downward movement. Rainfall and discharge variability, high evapotranspiration and the changes in the land cover-use in the catchment of the floodplain are largely the factors affecting the observed variability and trends in inundation extent in the floodplain. The presented remote sensing based approach significantly reduces the need for the expensive and time limiting traditional physical field based wetland inundation mapping methods that form a limitation for achieving progress in wetland monitoring especially in open and sparsely gauged floodplains such as the Barotse.
Krzysztof Hryniewicz, Kazutaka Amano, Robert G. Jenkins
et al.
We present a systematic study of thyasirid bivalves from Cretaceous to Oligocene seep carbonates worldwide. Eleven species of thyasirid bivalves are identified belonging to three genera: Conchocele, Maorithyas, and Thyasira. Two species are new: Maorithyas humptulipsensis sp. nov. from middle Eocene seep carbonates in the Humptulips Formation, Washington State, USA, and Conchocele kiritachiensis sp. nov. from the late Eocene seep deposit at Kiritachi, Hokkaido, Japan. Two new combinations are provided: Conchocele townsendi (White, 1890) from Maastrichtian strata of the James Ross Basin, Antarctica, and Maorithyas folgeri (Wagner and Schilling, 1923) from Oligocene rocks from California, USA. Three species are left in open nomenclature. We show that thyasirids have Mesozoic origins and appear at seeps before appearing in “normal” marine environments. These data are interpreted as a record of seep origination of thyasirids, and their subsequent dispersal to non-seep environments. We discuss the age of origination of thyasirids in the context of the origin of the modern deep sea fauna and conclude that thyasirids could have deep sea origins. This hypothesis is supported by the observed lack of influence of the Cretaceous and Paleogene Oceanic Anoxic Events on the main evolutionary lineages of the thyasirids, as seen in several other members of the deep sea fauna.