bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of DINCAE to Reconstruct the Gaps in Chlorophyll-a Satellite Observations in the South China Sea and West Philippine Sea
Authors: Han Zhaohui , He Yijun , Liu Guoqiang , Perrie William
Published: February 2020

The Data Interpolating Empirical Orthogonal Functions (DINEOF) method has demonstrated usability and accuracy for filling spatial gaps in remote sensing datasets. In this study, we conducted the reconstruction of the chlorophyll-a concentration (Chl-a) data using a convolutional neural networks model called Data-Interpolating Convolutional Auto-Encoder (DINCAE), and we compared its performance with that of DINEOF. Furthermore, the cloud-free sea surface temperature (SST) was used as a phytoplankton dynamics predictor for the Chl-a reconstruction. Finally, four reconstruction schemes were implemented: DINCAE (Chl-a only), DINCAE (Chl-a and SST), DINEOF (Chl-a only), and DINEOF (Chl-a and SST), denoted rec1, rec2, rec3, and rec4 respectively. To quantitatively evaluate the accuracy of these reconstruction schemes, both the cross-validation and in situ data were used. The study domain was chosen to be the Northern South China Sea (SCS) and West Philippine Sea (WPS), bounded by 115–125°E and 16–24°N to test the model performance for the reconstruction of Chl-a under different Chl-a controlling mechanisms. The in situ validation showed that rec1 performs best among the four reconstruction schemes, and that adding SST into the Chl-a reconstruction cannot improve the reconstruction results. However, for cross validation, adding SST can slightly improve spatial distributions of the root mean square error (RMSE) between the reconstructed data and the original data, especially over the SCS continental shelf. Furthermore, the potential of DINCAE prediction is confirmed in this paper; thus, the trained DINCAE model can be re-applied to reconstruct other missing data, and more importantly, it can also be re-trained using the reconstructed data, thereby further improving reconstruction results. Another consideration is efficiency; with similar reconstruction conditions, DINCAE is 5–10 times faster than DINEOF.
Parsing Synthetic Aperture Radar Measurements of Snow in Complex Terrain: Scaling Behaviour and Sensitivity to Snow Wetness and Landcover
Authors: Manickam Surendar , Barros Ana
Published: February 2020

This study investigates the spatial signatures of seasonal snow in Synthetic Aperture Radar (SAR) observations at different spatial scales and for different physiographic regions. Sentinel-1 C-band (SAR) backscattering coefficients (BSC) were analyzed in the Swiss Alps (SA), in high elevation forest and grasslands in Grand Mesa (GM), Colorado, and in North Dakota (ND) croplands. GM BSC exhibit 10 dB sensitivity to wetness at small scales (~100 m) over homogeneous grassland. Sensitivity decreases to 5 dB in the presence of trees, and it is demonstrated that VH BSC sensitivity enables wet snow mapping below the tree-line. Area-variance scaling relationships show minima at ~100 m and 150–250 m, respectively, in barren and grasslands in SA and GM, increasing up to 1 km and longer in GM forests and ND agricultural fields. The spatial organization of BSC (as described by 1D-directional BSC wavelength spectra) exhibits multi-scaling behavior in the 100–1000 m range with a break at (180–360 m) that is also present in UAVSAR L-band measurements in GM. Spectral slopes in GM forested areas steepen during accumulation and flatten in the melting season with mirror behavior for grasslands reflecting changes in scattering mechanisms with snow depth and wetness, and vegetation mass and structure. Overall, this study reveals persistent patterns of SAR scattering variability spatially organized by land-cover, topography and regional winds with large inter-annual variability tied to precipitation. This dynamic scaling behavior emerges as an integral physical expression of snowpack variability that can be used to model sub-km scales and for downscaling applications.
An Automated Method for Surface Ice/Snow Mapping Based on Objects and Pixels from Landsat Imagery in a Mountainous Region
Authors: Wang Xuecheng , Gao Xing , Zhang Xiaoyan , Wang Wei , Yang Fei
Published: February 2020

Surface ice/snow is a vital resource and is sensitive to climate change in many parts of the world. The accurate and timely measurement of the spatial distribution of ice/snow is critical for managing water resources. Object-oriented and pixel-oriented methods often have some limitations due to the image segmentation scale, the determination of the optimal threshold and background heterogeneity. Therefore, this study proposes a method for automatically extracting large-scale surface ice/snow from Landsat series images, which takes advantage of the combination of image segmentation, the watershed algorithm and a series of ice/snow indices. We tested our novel method in three different regions in the Karakoram Mountains, and the experimental results show that the produced ice/snow map obtained a user’s accuracy greater than 90%, a producer’s accuracy greater than 97%, an overall accuracy greater than 98% and a kappa coefficient greater than 0.93. Comparing the extraction results under segmentation scales of 10, 15, 20 and 25, the user’s accuracy and producer’s accuracy from the proposed method are very similar, which indicates that the proposed method is more reliable and stable for extracting ice/snow objects than the object-oriented method. Due to the different reflectivity values in the near-infrared band in the snow and water categories, the normalized difference forest snow index (NDFSI) is suitable for Landsat TM and ETM+ images. This study can serve as a reliable, scientific reference for rapidly and accurately extracting ice/snow objects.
Analysis of the Spatiotemporal Change in Land Surface Temperature for a Long-Term Sequence in Africa (2003–2017)
Authors: NourEldeen Nusseiba , Mao Kebiao , Yuan Zijin , Shen Xinyi , Xu Tongren , Qin Zhihao
Published: February 2020

It is very important to understand the temporal and spatial variations of land surface temperature (LST) in Africa to determine the effects of temperature on agricultural production. Although thermal infrared remote sensing technology can quickly obtain surface temperature information, it is greatly affected by clouds and rainfall. To obtain a complete and continuous dataset on the spatiotemporal variations in LST in Africa, a reconstruction model based on the moderate resolution imaging spectroradiometer (MODIS) LST time series and ground station data was built to refactor the LST dataset (2003–2017). The first step in the reconstruction model is to filter low-quality LST pixels contaminated by clouds and then fill the pixels using observation data from ground weather stations. Then, the missing pixels are interpolated using the inverse distance weighting (IDW) method. The evaluation shows that the accuracy between reconstructed LST and ground station data is high (root mean square er–ror (RMSE) = 0.84 °C, mean absolute error (MAE) = 0.75 °C and correlation coefficient (R) = 0.91). The spatiotemporal analysis of the LST indicates that the change in the annual average LST from 2003–2017 was weak and the warming trend in Africa was remarkably uneven. Geographically, “the warming is more pronounced in the north and the west than in the south and the east”. The most significant warming occurred near the equatorial region in South Africa (slope > 0.05, R > 0.61, p < 0.05) and the central (slope = 0.08, R = 0.89, p < 0.05) regions, and a nonsignificant decreasing trend occurred in Botswana. Additionally, the mid-north region (north of Chad, north of Niger and south of Algeria) became colder (slope > −0.07, R = 0.9, p < 0.05), with a nonsignificant trend. Seasonally, significant warming was more pronounced in winter, mostly in the west, especially in Mauritania (slope > 0.09, R > 0.9, p < 0.5). The response of the different types of surface to the surface temperature has shown variability at different times, which provides important information to understand the effects of temperature changes on crop yields, which is critical for the planning of agricultural farming systems in Africa.
Monitoring of Coral Reefs Using Artificial Intelligence: A Feasible and Cost-Effective Approach
Authors: González-Rivero Manuel , Beijbom Oscar , Rodriguez-Ramirez Alberto , Bryant Dominic E. P. , Ganase Anjani , Gonzalez-Marrero Yeray , Herrera-Reveles Ana , Kennedy Emma V. , Kim Catherine J. S. , Lopez-Marcano Sebastian , Markey Kathryn , Neal Benjamin P. , Osborne Kate , Reyes-Nivia Catalina , Sampayo Eugenia M. , Stolberg Kristin , Taylor Abbie , Vercelloni Julie , Wyatt Mathew , Hoegh-Guldberg Ove
Published: February 2020

Ecosystem monitoring is central to effective management, where rapid reporting is essential to provide timely advice. While digital imagery has greatly improved the speed of underwater data collection for monitoring benthic communities, image analysis remains a bottleneck in reporting observations. In recent years, a rapid evolution of artificial intelligence in image recognition has been evident in its broad applications in modern society, offering new opportunities for increasing the capabilities of coral reef monitoring. Here, we evaluated the performance of Deep Learning Convolutional Neural Networks for automated image analysis, using a global coral reef monitoring dataset. The study demonstrates the advantages of automated image analysis for coral reef monitoring in terms of error and repeatability of benthic abundance estimations, as well as cost and benefit. We found unbiased and high agreement between expert and automated observations (97%). Repeated surveys and comparisons against existing monitoring programs also show that automated estimation of benthic composition is equally robust in detecting change and ensuring the continuity of existing monitoring data. Using this automated approach, data analysis and reporting can be accelerated by at least 200x and at a fraction of the cost (1%). Combining commonly used underwater imagery in monitoring with automated image annotation can dramatically improve how we measure and monitor coral reefs worldwide, particularly in terms of allocating limited resources, rapid reporting and data integration within and across management areas.
Application of Beamforming Technology in Ionospheric Oblique Backscatter Sounding with a Miniaturized L-Array
Authors: Liu Tongxin , Yang Guobin , Zhao Zhengyu , Jiang Chunhua , Hu Yaogai
Published: February 2020

In this paper, a new dedicated multi-channel ionospheric oblique backscatter sounder is described. A miniaturized L-shaped antenna array was employed for the receiving of the oblique backscatter echoes in the present system. Firstly, two typical adaptive beamforming algorithms were introduced to improve the anti-jamming ability. Then, simulations were carried out to verify the beamforming performance in azimuth and elevation simultaneously. Furthermore, the experimental results by the present sounding system were used to test the performance of the adaptive beamformers. Results show that the radio frequency interference and the interference of the vertical echoes can be effectively suppressed by the adaptive beamformers. In particular, the use value of the beamforming in the receiving of the ionospheric oblique backscatter sounding is described in detail through the analysis of the signal sequences in several typical frequencies. And after the constant false-alarm rate processing, the oblique backscatter ionograms processed by the adaptive beamforers have clearer and continuous leading edge compared with the original ionograms. As a result, the adaptive beamformers of great significance to improve the detection ability of the ionospheric oblique backscatter sounding.
Spatio-Temporal Sub-Pixel Land Cover Mapping of Remote Sensing Imagery Using Spatial Distribution Information From Same-Class Pixels
Authors: Li Xiaodong , Chen Rui , Foody Giles M. , Wang Lihui , Yang Xiaohong , Du Yun , Ling Feng
Published: February 2020

The generation of land cover maps with both fine spatial and temporal resolution would aid the monitoring of change on the Earth’s surface. Spatio-temporal sub-pixel land cover mapping (STSPM) uses a few fine spatial resolution (FR) maps and a time series of coarse spatial resolution (CR) remote sensing images as input to generate FR land cover maps with a temporal frequency of the CR data set. Traditional STSPM selects spatially adjacent FR pixels within a local window as neighborhoods to model the land cover spatial dependence, which can be a source of error and uncertainty in the maps generated by the analysis. This paper proposes a new STSPM using FR remote sensing images that pre- and/or post-date the CR image as ancillary data to enhance the quality of the FR map outputs. Spectrally similar pixels within the locality of a target FR pixel in the ancillary data are likely to represent the same land cover class and hence such same-class pixels can provide spatial information to aid the analysis. Experimental results showed that the proposed STSPM predicted land cover maps more accurately than two comparative state-of-the-art STSPM algorithms.
Extracting Impervious Surface from Aerial Imagery Using Semi-Automatic Sampling and Spectral Stability
Authors: Zhang Hua , Gorelick Steven M. , Zimba Paul V.
Published: February 2020

The quantification of impervious surface through remote sensing provides critical information for urban planning and environmental management. The acquisition of quality reference data and the selection of effective predictor variables are two factors that contribute to the low accuracies of impervious surface in urban remote sensing. A hybrid method was developed to improve the extraction of impervious surface from high-resolution aerial imagery. This method integrates ancillary datasets from OpenStreetMap, National Wetland Inventory, and National Cropland Data to generate training and validation samples in a semi-automatic manner, significantly reducing the effort of visual interpretation and manual labeling. Satellite-derived surface reflectance stability is incorporated to improve the separation of impervious surface from other land cover classes. This method was applied to 1-m National Agriculture Imagery Program (NAIP) imagery of three sites with different levels of land development and data availability. Results indicate improved extractions of impervious surface with user’s accuracies ranging from 69% to 90% and producer’s accuracies from 88% to 95%. The results were compared to the 30-m percent impervious surface data of the National Land Cover Database, demonstrating the potential of this method to validate and complement satellite-derived medium-resolution datasets of urban land cover and land use.
The Prevalence and Severity of External Auditory Exostosis in Young to Quadragenarian-Aged Warm-Water Surfers: A Preliminary Study
Authors: Simas Vini , Hing Wayne , Furness James , Walsh Joe , Climstein Mike
Published: February 2020

External auditory exostosis (EAE) has previously only been shown to occur in cold water surfers. We assessed young surfers living and surfing in Queensland, Australia, for EAE in water temp ranges from 20.6 °C (69.1 °F, Winter) to 28.2 °C (82.8 °F, Summer). All participants underwent a bilateral otoscopic examination to assess the presence and severity of EAE. A total of 23 surfers participated with a mean age of 35.4 years (8.3 years) and a mean surfing experience of 20.0 years (9.9 years). Nearly two-thirds of participants (n = 14, 60.9%) had regular otological symptoms, most commonly water trapping (n = 13, 56.5%), pain (n = 8, 34.8%), and hearing loss (n = 6, 26.1%). Only 8.7% (n = 2) of all surfers reported regular use of protective equipment (e.g., earplugs) on a regular basis. The overall prevalence of exostosis was 69.6% (n = 16), and the majority (n = 12, 80.0%) demonstrated bilateral lesions of a mild grade (<33% obstruction of the external auditory canal). This is the first study assessing EAE in young surfers exposed to only warm waters (above 20.6 °C). The prevalence of EAE in this study highlights that EAE is not restricted to cold water conditions, as previously believed. Warm water surfing enthusiasts should be screened on a regular basis by their general medical practitioner and utilize prevention strategies such as earplugs to minimize exposure to EAE development.
Gender Parity within the Gender—Sustainability Paradigm: A Case Study on Management Structures of the Romanian Academia
Authors: Drumea Cristina , Băcanu Bogdan , Anton Carmen Elena , Litra Adriana Veronica , Busuioceanu Steliana , Doroș Alexandra
Published: February 2020

Our study proposes a Romanian national perspective of the gender–sustainability paradigm in higher education under the Sustainable Development Goal 5 (SDG5) approach. The starting point is the interlinkage of the two concepts, gender parity and sustainability, depicted on a fundamental societal domain. Data collection was completed following a census approach, resulting in staffing data on 47 Romanian state-owned universities. Data collected envisaged the tenure teaching staff, divided into two gender groups; the count was focused on executive roles and collective managerial elected bodies for the 2015–2019 mandate. The gender situation was analyzed quantitatively by the number of teaching staff, their gender structure, and their representation in the executive functions and collective decision-making bodies. We calculated gender indexes and used statistical correlation coefficients to explain the relations between the different categories of personnel and their influence on establishing the management structures. The results of the gender configuration analysis were further associated with the latest national meta-ranking of Romanian universities. Our findings show that Romanian universities demonstrate sustainability under SDG5 through their institutional capacity to use either feminine majorities or a statistically detected pro-female voting propensity in order to construct optimally gendered management structures through vote only.
Co-Combustion of Waste Tires and Plastic-Rubber Wastes with Biomass Technical and Environmental Analysis
Authors: Carmo-Calado Luís , Hermoso-Orzáez Manuel Jesús , Mota-Panizio Roberta , Guilherme-Garcia Bruno , Brito Paulo
Published: February 2020

The present work studies the possibility of energy recovery by thermal conversion of combustible residual materials, namely tires and rubber-plastic, plastic waste from outdoor luminaires. The waste has great potential for energy recovery (HHV: 38.6 MJ/kg for tires and 31.6 MJ/kg for plastic). Considering the thermal conversion difficulties of these residues, four co-combustion tests with mixtures of tires/plastics + pelletized Miscanthus, and an additional test with 100% Miscanthus were performed. The temperature was increased to the maximum allowed by the equipment, about 500 °C. The water temperature at the boiler outlet and the water flow were controlled (60 °C and 11 L/min). Different mixtures of residues (0–60% tires/plastics) were tested and compared in terms of power and gaseous emissions. Results indicate that energy production increased with the increase of tire residue in the mixture, reaching a maximum of 157 kW for 40% of miscanthus and 60% of tires. However, the automatic feeding difficulties of the boiler also increased, requiring constant operator intervention. As for plastic and rubber waste, fuel consumption generally decreased with increasing percentages of these materials in the blend, with temperatures ranging from 383 °C to 411 °C. Power also decreased by including such wastes (66–100 kW) due to feeding difficulties and cinder-fusing problems related to ash melting. From the study, it can be concluded that co-combustion is a suitable technology for the recovery of waste tires, but operational problems arise with high levels of residues in the mixture. Increasing pollutant emissions and the need for pre-treatments are other limiting factors. In this sense, the thermal gasification process was tested with the same residues and the same percentages of mixtures used in the co-combustion tests. The gasification tests were performed in a downdraft reactor at temperatures above 800 °C. Each test started with 100% acacia chip for reference (like the previous miscanthus), and then with mixtures of 0–60% of tires and blends of plastics and rubbers. Results obtained for the two residues demonstrated the viability of the technology, however, with mixtures higher than 40% it was very difficult to develop a process under stable conditions. The optimum condition for producing a synthesis gas with a substantial heating value occurred with mixtures of 20% of polymeric wastes, which resulted in gases with a calorific value of 3.64 MJ/Nm3 for tires and 3.09 MJ/Nm3 for plastics and rubbers.
Biocapacity—Premise of Sustainable Development in the European Space
Authors: Gogonea Rodica-Manuela , Ghita Simona Ioana , Saseanu Andreea Simona
Published: February 2020

The contemporary lifestyle, based on unsustainable consumption patterns, leads to an orientation of the society towards the development and application of sustainable development strategies and policies. The comparative analysis of the ecological footprint and biocapacity allows one to study the interaction between human activities and environment, through the biocapacity reserve or deficit. In this context, this article carries out a complex analysis of the biocapacity reserve/deficit, as a latent variable that quantifies sustainability, viewed through a selection of determinants, from which three main components have been extracted: A component of education and social exclusion, a component of economic development, innovation, and environment, and a demographic component. These were transformed—through a multiple linear regression model—into exogenous variables with high explanatory power over the variation of the biocapacity reserve/deficit and constituted the tools in identifying behavioral patterns of the European countries and a set of measures leading to the sustainability of the ecological reserve.
Nurse Practitioners’ Work Values and Their Conflict Management Approaches in a Stressful Workplace: A Taiwan Study
Authors: Jing Lei , Ma Zhenzhong , Ma Zhijuan , Chen Baomin , Cheng Shuya
Published: February 2020

Globalization has created an urgent need to understand management practices in different cultures. This study examines Confucianism-based work values of nurse practitioners in Taiwan and explores their impact on conflict management approaches in order to help health practitioners maintain sustainable work relationships and improve organizational effectiveness in an increasingly stressful workplace. Based on the data from 259 nurse practitioners in Taiwan, this study shows that nurse practitioners in Taiwan consider holistic rewards, self-fulfillment and personal growth, challenge and responsibility, autonomy, and meaningfulness as important work values. Hierarchical regression results further indicate that nurse practitioners with strong group-centered needs, such as needs for holistic rewards, preferred collaborative methods to manage conflicts in the workplace, and individuals with strong self-centered needs, such as needs for personal growth and self-fulfillment and needs for autonomy, preferred competitive methods to manage conflicts. Interestingly, this study also finds that self-centered needs such as needs for self-fulfillment and personal growth, and needs for challenge and responsibility are also related to collaborative approaches. Managerial implications are then discussed for conflict management training for nurse practitioners under stressful work conditions.
Alliance Network Diversity and Innovation Ambidexterity: The Differential Roles of Industrial Diversity, Geographical Diversity, and Functional Diversity
Authors: Zhang Guiyang , Tang Chaoying , Qi Yong
Published: February 2020

Innovation ambidexterity, namely, performing exploitative and exploratory innovation simultaneously, is important for high-tech firms to achieve sustainable success. This can be achieved by building an egocentric alliance network. Research into the influence of alliance network diversity on innovation ambidexterity is seeing more attention. However, the differences among multiple alliance network diversities are unclear. Grounded on a knowledge-based view, organizational learning theory, and transaction cost theory, this study investigates in-depth the roles of geographical diversity, industrial diversity, and functional diversity of the alliance network. The empirical analysis based on panel data, including alliance data from the SDC Joint & Venture database and patent data from the Derwent Innovation Index database of 106 top high-tech firms from electronic information and biopharmaceutical industries, suggests that industrial diversity enhances firm innovation ambidexterity, geographical diversity impedes firm innovation ambidexterity, and functional diversity shows an inverted U-shaped relationship with firm innovation ambidexterity. These results provide practical suggestions about alliance network diversity configuration and innovation ambidexterity construction for high-tech firms.
Evaluation of Sustainable Urban Development under Environmental Constraints: A Case Study of Jiangsu Province, China
Authors: Wang Yaqiong , Yuan Guanghui , Yan Ying , Zhang Xueliang
Published: February 2020

Sustainable development is a long-term solution for urban development and a guideline for urban development. Only by better coordination around the population, resources, and environment can the city achieve sustained and steady development. In order to evaluate the efficiency of sustainable urban development under environmental constraints, this paper takes 13 prefecture-level cities in Jiangsu Province as an example. To address the infeasibility problem in the Malmquist-Luenberger (M-L) index, a modified M-L index analysis method based on the new directional distance function (DDF) is adopted. Combined with the consideration of desirable and undesirable outputs, a linear programming model for sustainable urban development evaluation is constructed to provide a scientific decision-making basis for sustainable development of the city. The results show that the growth of sustainable urban development efficiency is not only related to desirable outputs but also affected by undesirable outputs. Technical change is the main driver of most sustainable urban development efficiency growth. However, efficiency changes also affect the sustainable development potential of cities to a certain extent. Through the modified M-L index analysis, we analyze the characteristics of different regions of Jiangsu Province, the changes in efficiency and the impact of technological innovation on sustainable urban development, and give policy recommendations to promote sustainable urban development.
Research on the Work Process of a Station for Preparing Forage
Authors: Marczuk Andrzej , Misztal Wojciech , Bulatov Sergey , Nechayev Vladimir , Savinykh Petr
Published: February 2020

Forage from grain plays a special role in animal nutrition because it constitutes feed with a high content of readily available carbohydrates. Unfortunately, the equipment used to prepare forage is often manufactured without the necessary justification and confirmation of the declared sizes and indicators of the work process. This forms the basis for our theoretical and experimental studies. Research has been carried out to provide justification of the design and operating parameters of the patented station for producing forage from cereal crops. This article describes the technology for preparing forage from grain and provides a detailed description of the station used and the principle of its operation. During the experiments, we studied the influence of the angle α of setting the grid-work (plate) and the distance S from the nozzle to the grid-work on the quality of forage. Qualitative, quantitative, and energy indicators have been evaluated using up-to-date measuring instruments and equipment. The method is described, and the studied factors and evaluation criteria for the preparation of forage from grain are indicated. The forage quality results are presented, as determined by the content of whole grains in it via the residue on a sieve with a sieve size of 3 mm when preparing it with a different combination of the studied factors. The analysis of the energy consumption results of the process of preparing forage from grain under various operating conditions of the plant is shown. As a result, the optimal location parameters of the passive grinder have been found, allowing to obtain high-quality forage with minimal power consumption of the electric motor. A grid-work should be used as a grinder. Its installation angle should be 30°, and the distance between the grid-work and the nozzle should be 205 mm. With this combination of parameters, the specific energy consumption is minimal and amounts to 41.5 W·h/L.
Community, Natural Resources, and Sustainability: Overview of an Interdisciplinary and International Literature
Authors: Qin Hua , Bass Martha , Ulrich-Schad Jessica D. , Matarrita-Cascante David , Sanders Christine , Bekee Barituka
Published: February 2020

The Special Issue Community, Natural Resources, and Sustainability seeks to engage in an interdisciplinary and international dialogue on the interrelationships of society, natural resources, and sustainability at the community level. In addition to introducing the twelve research articles published in this collection, we provide an overview of the existing literature on community and natural resource management, mainly through a review of previous reviews and a bibliometric analysis. While this literature is dominated by studies on various aspects of community-based natural resource management, the present Special Issue showcases multiple thematic areas of research that collectively contribute to a more complete understanding of the community-resources-sustainability linkages. Our review also pinpoints important gaps in existing meta-analyses and bibliometric analyses. Promising directions for future research are highlighted.
The Nexus between Poverty and the Environment: A Case Study of Lijiang, China
Authors: Gao Ping , Liu Shenghe , Qi Wei , Qi Honggang
Published: February 2020

Highlighting the nexus between poverty and environment is essential to promote poverty alleviation and sustainable development. This study analyzed spatial differences and environmental factors influencing poverty incidence and reduction using spatial statistical methods and GeoDetector tools. It focused on Lijiang in the Hengduan Mountains of western China as the case area. The results indicate a notable decline in poverty incidence in most Lijiang villages during 2014–2018 under China’s poverty alleviation strategy. However, there are distinct spatial differences for both poverty incidence and reduction. The main environmental factors affecting poverty incidence and reduction are available water storage and geological hazard risks. Socioeconomic factors such as administrative unit and distance to city center also play a key role. The anti-poverty policies in various administrative units have the most significant influence. However, existing policy formulation mainly considers elevation factor in mountainous areas. This study suggests that water resources and geological hazards should also be highly considered, and not only elevation. It is imperative to promote the construction of water conservancy facilities and improve the prevention and control of geological disasters. Moreover, targeted poverty alleviation should focus on, not only policy or socioeconomic factors, but also main environmental factors affecting poverty incidence and reduction.
A Flood Risk Management Program of Wadi Baysh Dam on the Downstream Area: An Integration of Hydrologic and Hydraulic Models, Jizan Region, KSA
Authors: Abu-Abdullah Mazen M. , Youssef Ahmed M. , Maerz Norbert H. , Abu-AlFadail Emad , Al-Harbi Hasan M. , Al-Saadi Nasser S.
Published: February 2020

For public safety, especially for people who dwell in the valley that is located downstream of a dam site, as well as the protection of economic and environmental resources, risk management programs are urgently required all over the world. Despite the high safety standards of dams because of improved engineering and excellent construction in recent times, a zero-risk guarantee is not possible, and accidents can happen, triggered by natural hazards, human actions, or just because the dam is aging. In addition to that is the impact of potential climate change, which may not have been taken into account in the original design. A flood risk management program, which is essential for protecting downstream dam areas, is required. Part of this program is to prepare an inundation map to simulate the impact of dam failure on the downstream areas. The Baysh dam has crucial importance both to protect the downstream areas against flooding, to provide drinking water to cities in the surrounding areas, and to use the excess water for irrigation of the agricultural areas located downstream of the dam. Recently, the Kingdom of Saudi Arabia (KSA) was affected by extraordinary rainstorm events causing many problems in many different areas. One of these events happened along the basin of the Baysh dam, which raised the alarm to the decision makers and to the public to take suitable action before dam failure occurs. The current study deals with a flood risk analysis of Wadi Baysh using an integration of hydrologic and hydraulic models. A detailed field investigation of the dam site and the downstream areas down to the Red Sea coast has been undertaken. Three scenarios were applied to check the dam and the reservoir functionality; the first scenario at 100- and 200-year return period rainfall events, the second scenario according to the Probable Maximum Precipitation (PMP), and the third scenario if the dam fails. Our findings indicated that the Baysh dam and reservoir at 100- and 200-year rainfall events are adequate, however, at the PMP the water will spill out from the spillway at ~8900 m3/s causing flooding to the downstream areas; thus, a well-designed channel along the downstream wadi portion up to the Red Sea coast is required. However, at dam failure, the inundation model indicated that a vast area of the section downstream of the dam will be utterly devastated, causing a significant loss of lives and destruction of urban areas and agricultural lands. Eventually, an effective warning system and flood hazard management system are imperative.
The Transition of Soundscapes in Tourist Destinations from the Perspective of Residents’ Perceptions: A Case Study of the Lugu Lake Scenic Spot, Southwestern China
Authors: Zuo Lin , Zhang Jie , Zhang Ronda J , Zhang Yingying , Hu Meng , Zhuang Min , Liu Wei
Published: February 2020

As an important part of regional synthesis, the local landscape is a crucial source of attractiveness for tourist destinations, in which soundscapes play a notable and special role. Many studies have investigated changes in the economic, cultural, and environmental aspects of tourist destinations under development, while little attention has been paid to how soundscapes change after tourism development. To this end, we chose the Lugu Lake Scenic Spot as a study area and explored the characteristics of soundscape changes by conducting a survey of residents in six villages at different stages of tourism development. The following conclusions were drawn: (1) Geophony did not obviously change under the influence of tourism. Biophony increasingly lost its influence, while anthrophony increased significantly, causing wide concern among residents. (2) The phenomenon of soundscape commercialization could be attributed to the impact of tourism maturation. Further, the representation of folk songs has undergone a great change. (3) In terms of spatial patterns, residents whose villages were in different states of tourism development had significantly different perceptions of soundscape transition. For example, the one village not undergoing tourism development was in its original soundscape phase. In the other villages, which were in the consolidation stage or the involvement stage, the sound environment had changed significantly, entering a tourism soundscape phase once there were tourism elements involved. Finally, we propose suggestions for enhancing the conservation of local soundscapes, with a focus on both building the tourism industry and enhancing the sustainable development of tourist destinations.
Can Design for the Environment be Worthwhile? Green Design for Manufacturers Brands When Confronted with Competition from Store Brands
Authors: Yang Xi , Xu Maozeng , Zhang Wanleng
Published: February 2020

To contribute to global sustainability, many manufacturers are starting to implement green product development and trying to provide environmentally friendly products. Although green products are environmentally beneficial to our society, the performance of green product development remains poor because of cannibalization from traditional alternatives at lower prices. This is particularly the case in the current unforgiving marketing reality in which many brand retailers, such as Wal-Mart, Tesco, and Carrefour, offer their own store brands as traditional alternatives. Although a large stream of research has studied the effects of competition on manufacturers’ green design, to the best of our knowledge, there is a dearth of research on the effects of competition from retailers’ store brands on manufacturers’ green design. To fill this gap, we present two models in which the manufacturer has an incentive to design for the environment, and the retailer has the flexibility to sell store brands (Model S), or it does not (Model N). Surprisingly, our analysis indicates that the presence of store brands may stimulate the manufacturer to release a new greener version of the national brand. Moreover, we find that although the presence of store brands is beneficial to the retailer and industry, it always hurts the manufacturer’s profitability. To incentivize the manufacturer to support Model S, we propose a two-part tariff contract.
Sustainable Emergency Management Based on Intelligent Information Processing
Authors: Luo Yu-Meng , Liu Wei , Yue Xiao-Guang , A. Rosen Marc
Published: February 2020

In this paper, we introduce how to identify, rank, evaluate, and respond to risks based on intelligent information processing, providing new ideas and research directions for sustainable emergency management. First, we discuss the contributions and deficiencies of the existing research that have informed the development and launch of this Special Issue and, second, we provide an overview of the three articles included. In addition, this article introduces this particular Special Issue, not only to complement the somewhat lacking body of related literature, but also to help contemporary companies deal with issues related to sustainable emergency management based on intelligent information processing.
Multi-Period Generation Expansion Planning for Sustainable Power Systems to Maximize the Utilization of Renewable Energy Sources
Authors: Li Qingtao , Wang Jianxue , Zhang Yao , Fan Yue , Bao Guojun , Wang Xuebin
Published: February 2020

The increasing penetration of renewable energy brings great challenges to the planning and operation of power systems. To deal with the fluctuation of renewable energy, the main focus of current research is on incorporating the detailed operation constraints into generation expansion planning (GEP) models. In most studies, the traditional objective function of GEP is to minimize the total cost (including the investment and operation cost). However, in power systems with high penetration of renewable energy, more attention has been paid to increasing the utilization of renewable energy and reducing the renewable energy curtailment. Different from the traditional objective function, this paper proposes a new objective function to maximize the accommodation of renewable energy during the planning horizon, taking into account short-term operation constraints and uncertainties from load and renewable energy sources. A power grid of one province in China is modified as a case study to verify the rationality and effectiveness of the proposed model. Numerical results show that the proposed GEP model could install more renewable power plants and improve the accommodation of renewable energy compared to the traditional GEP model.
Threatened Status Assessment of Multiple Grassland Ecosystems and Conservation Strategies in the Xilin River Basin, NE China
Authors: Meng Xia , Huang Huasheng , Guo Luo , Wang Dan , Han Rui , Zhou Kexin
Published: February 2020

The Red List of Ecosystems, proposed by the International Union for Conservation of Nature can determine the status of ecosystems for biodiversity conservation. In this study, we applied the Red List of Ecosystems Categories and Criteria 2.0 with its four major criteria (A, B, C, and D) to assess twelve dominant ecosystems in the Xilin River Basin, a representative grassland-dominating area in China. We employed Geographical Information Systems and remote sensing to process the obtained satellite products from the years 2000 to 2015, and generated indicators for biological processes and degradation of environment with boreal ecosystem productivity simulator. The results show that all twelve ecosystems in the Xilin River Basin confront varying threats: Artemisia frigida grassland and Festuca ovina grassland face the highest risk of collapse, sharing an endangered status; Filifolium sibiricum meadow grassland and Leymus chinensis grassland have a least concern status, while the remaining eight ecosystems display a vulnerable status. This study overcomes the limits of data deficiency by introducing the boreal ecosystem productivity simulator to simulate biological processes and the plant–environment interaction. It sheds light on further application of the Red List of Ecosystems, and bridges the research gap and promote local ecosystems conservation in China.
Assessing the Net Import Welfare Impacts of the Rising Global Price of Food in Italy
Authors: Aghabeygi Mona , Arfini Filippo
Published: February 2020

In Italy, as one of the developed countries, the agricultural sector is key in supplying food, food security and food safety. In this study, the amount and value of net imports for various foodstuffs in Italy was used. At first, compensatory price elasticities were calculated by using the Almost Ideal Demand System (AIDS) and the effect of increasing the global price of food on net import welfare was studied. The results show that the welfare index of compensatory changes calculated for the entire food groups is 126.46 billion USD. Meat and beverage groups have the most and the least compensatory changes, respectively.
Sensitivity Analysis of Passive Design Strategies for Residential Buildings in Cold Semi-Arid Climates
Authors: Mahar Waqas Ahmed , Verbeeck Griet , Reiter Sigrid , Attia Shady
Published: February 2020

Buildings are significant drivers of greenhouse gas emissions and energy consumption. Improving the thermal comfort of occupants in free-running buildings and avoiding active and fossil fuel-based systems is the main challenge in many cities worldwide. However, the impacts of passive design measures on thermal comfort in cold semi-arid regions are seldom studied. With the rapid urbanization and the widespread use of personalised heating and cooling systems, there is a need to inform building designers and city authorities about passive design measures that can achieve nearly optimal conditions. Therefore, in this study, a global sensitivity analysis of the impact of passive design parameters on adaptive comfort in cold semi-arid climates was conducted. A representative residential building was simulated and calibrated in Quetta, Pakistan, to identify key design parameters for optimal thermal comfort. The results list and rank a set of passive design recommendations that can be used widely in similar climates. The results show that among the investigated 21 design variables, the insulation type of roof is the most influential design variable. Overall, the sensitivity analysis yielded new quantitative and qualitative knowledge about the passive design of buildings with personalised heating systems, but the used sensitivity analysis has some limitations. Finally, this study provides evidence-based and informed design recommendations that can serve architects and homeowners to integrate passive design measures at the earliest conceptual design phases in cold semi-arid climates.
Impacts of Excise Taxation on Non-Alcoholic Beverage Consumption in Vietnam
Authors: Luong Linh , Vu Linh Hoang
Published: February 2020

Vietnam is faced with the issue of increasing overweight and obesity, particularly among children and adolescents in urban areas. As a result, the government of Vietnam recently introduced a proposal to impose a special consumption tax on sugar-sweetened beverages (SSB) in Vietnam, as the drinks are causing negative health consequences for Vietnamese people. This research is aimed at evaluating the impacts of a 10% special consumption tax on SSB in Vietnam using the Almost Ideal Demand System (AIDS) model. We found that a 10% SSB tax will reduce SSB consumption by 11.4%. Consumers will switch to substitutes, leading to an increase in the consumption of milk by 2.3%, beer by 2.5%, dried tea by 2.2%, and wine by 1.7%. However, in the short run, the tax could lead to a decrease in consumer welfare due to higher SSB prices. In addition to people from better-off households, people from the ethnic majority group, most of which live in urban areas with a large number of children, have a relatively high welfare reduction.
Farmers’ Perceptions of Tree Shelterbelts on Agricultural Land in Rural Kyrgyzstan
Authors: Ruppert Daniel , Welp Martin , Spies Michael , Thevs Niels
Published: February 2020

The reestablishment of agroforestry systems in Central Asia, combining crop production with protective tree shelterbelts, provides significant potential to improve farming systems. This includes increasing crop yields, additional income from timber, as well as reducing soil degradation and wind erosion. Thus, adopting shelterbelts as a form of pro-environmental behavior provides a number of socio-economic benefits, although some trade-offs need to be considered as well. This paper investigates factors that shape the perception of—and attitude towards—the establishment of tree shelterbelts by farmers in two case study regions in Kyrgyzstan. Applying a conceptual framework distinguishing between extrinsic and intrinsic factors, research methods included semi-structured interviews with farmers and local policy makers. The results show spatial differences in the perception of shelterbelts, both on the regional and on the village scale. In general, shelterbelts were negatively perceived by more than half of the farmers. The main concern raised by farmers was the shading of crops by shelterbelts, resulting in a decrease of yield. In addition, small field sizes and potential conflicts with neighbors were key concerns. Furthermore, rules set by local self-government bodies were inconsistent with the legislative framework, posing significant restrictions to the adoption of sustainable land use practices.