Article
Biodiversity Conservation
Yunfei Cao, Li Hua, Qi Tang, Lin Liu, Chongfa Cai
Summary: Soil water erosion has caused significant damage to agriculture and ecosystems globally. This study calculated the average monthly-scale soil erosion modulus from 2001 to 2019 in Northeast China using the revised universal soil loss equation (RUSLE) to evaluate soil erosion risk. The results showed a yearly average soil erosion modulus of 8.53 t center dot ha(- 1)center dot year(- 1) and a monthly average of 0.78 t center dot ha(-1)center dot month(-1). The months of April-July and October were identified as critical periods for erosion, with high erosion concentrated in southern Liaoning province and western Inner Mongolia. The topographic factor LS, rainfall erosivity (R), and cover management (C) were identified as important drivers of soil erosion.
ECOLOGICAL INDICATORS
(2023)
Article
Environmental Sciences
Mustafa Ali, Lingxuan Liu, Jing Zhang
Summary: This study estimated the environmental burden of eating away from home in the UK based on emission factors of food recipes, highlighting the impacts of Covid-19 lockdowns on eating out emissions in 2020. It is the first study focusing on regional food-based emissions from eating out in the United Kingdom.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Meteorology & Atmospheric Sciences
R. N. Singh, Sonam Sah, Bappa Das, Sunil Potekar, Amresh Chaudhary, H. Pathak
Summary: This study analyzed the spatio-temporal trends of rainfall in different meteorological sub-divisions of India over the last 119 years. Significant increasing trends in monsoon and annual rainfall were observed in most sub-divisions, while decreasing trends were found in some areas, particularly in winter rainfall. The Innovative trend analysis (ITA) method was more sensitive in detecting hidden trends missed out by traditional methods.
THEORETICAL AND APPLIED CLIMATOLOGY
(2021)
Article
Environmental Sciences
Caiqing Zhang, Zixuan Wang, Hongxia Luo
Summary: Improving carbon emission efficiency (CEE) is critical for RCEP members to promote carbon reduction. The study assesses the current state and trend of CEE in 15 RCEP countries using the SBM model and GML index, and investigates the influencing factors using the extended STIRPAT model and spatial Durbin model. The findings reveal variations in CEE among RCEP members and indicate the dominant role of technological progress. Factors like affluence and economic agglomeration inhibit CEE enhancement, while technology level and investment capacity facilitate it. These results are important for carbon-neutral planning and coordinated sustainable development.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Environmental Sciences
Shidong Liu, Jishang Xu, Lulu Qiao, Guangxue Li, Jinghao Shi, Dong Ding, Di Yu, Xue Yang, Yufeng Pan, Siyu Liu, Xiaoshuang Fu
Summary: In this study, the basic features and spatial-temporal variations of short-lived mesoscale eddies (MEs) in the western Pacific warm pool (WPWP) were analyzed for the first time. It was found that short-lived cyclonic and anticyclonic eddies (CEs/AEs) were widespread in two eddy belts in the tropical region. The development of these eddy belts was related to the variations in sea surface temperature, mixed layer depth, and surface chlorophyll-a concentration in the WPWP. This new insight contributes to our current understanding of ocean eddies and highlights the importance of studying the impacts of short-lived MEs in future research.
FRONTIERS IN MARINE SCIENCE
(2023)
Article
Meteorology & Atmospheric Sciences
Dnyaneshwar Arjun Madane, Abhishek M. Waghaye
Summary: In this study, the long-term rainfall trend in 20 districts of Punjab state from 1951 to 2021 was analyzed using the Mann-Kendall (MK) test and innovative trend analysis (ITA) method. The presence of serial correlation in the rainfall series was detected through autocorrelation test. MK or modified Mann-Kendall (MMK) test and Sen's slope test were employed to determine the direction and magnitude of the rainfall trend based on the autocorrelation test. ITA, compared with the traditional MK/MMK test, graphically revealed the presence of a trend. The study highlights the importance of efficient water resource planning due to the decreasing rainfall pattern and high irrigation requirement in Punjab state.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Environmental Sciences
Yaowen Luo, Jianguo Yan, Fei Li, Bo Li
Summary: The Martian surface temperature shows significant spatial aggregation, with thermal inertia and dust playing a major role in influencing temperature variations over time. Local surface temperature is likely affected by factors such as slope and wind, while the sheltering effects of mountains at basin edges contribute to spatial temperature differences.
Review
Environmental Sciences
Rebecca Talbot, Heejun Chang
Summary: Freshwater microplastics are influenced by anthropogenic factors such as urbanization, population density, and wastewater treatment plant effluent, as well as physical watershed characteristics like slope and elevation. Precipitation and stormwater runoff have positive correlations with microplastic concentrations, while water flow/discharge has negative correlations. Variations in study results may be attributed to differing scales or contributing area delineations, indicating a need for more rigorous and standardized spatial analytical methods.
ENVIRONMENTAL POLLUTION
(2022)
Article
Geography
Moses Asori, Ali Musah, Julius Odei, Anthony Kwame Morgan, Iddrisu Zurikanen
Summary: This study examined spatiotemporal hotspots and risk factors for malaria prevalence. The spatial cluster of malaria prevalence has increased over time. In the wet season, factors such as elevation, rainfall, vegetation index, and stream density were positively associated with malaria, while land surface temperature, distance from streams, and mean temperature were inversely related. In the dry season, factors such as elevation, vegetation index, rainfall, mean temperature, distance from streams, and land surface temperature were inversely related to malaria.
Article
Computer Science, Interdisciplinary Applications
Andrew Zammit-Mangion, Noel Cressie
Summary: FRK is an R software package for spatial/spatio-temporal modeling and prediction with large datasets, distinguishing itself by avoiding stationary and isotropic covariance and variogram models in favor of a spatial random effects (SRE) model. It offers the advantages of integrating multiple observations with different supports, obtaining precise predictions at millions of locations, and reliable quantification of uncertainty.
JOURNAL OF STATISTICAL SOFTWARE
(2021)
Article
Engineering, Environmental
Gongduan Fan, Shulei Bao, Yang Guo, Mingqian Xia, Mingcai Lin, Shujuan Cai, Weifang Ruan, Tingting Liao, Zhongsen Yan
Summary: The research revealed that disturbance plays a significant role in salt release from sediment, while microbial activity in sediment is crucial for maintaining salt content. Disturbing sediment and establishing plant belts can be used to slow down the salinization of freshwater reservoirs.
PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
(2022)
Article
Construction & Building Technology
Kairui You, Yanhui Yu, Weiguang Cai, Zhengxuan Liu
Summary: This study analyzed the changes in CO2 emissions and their driving factors in China's commercial and public building sector from a temporal and spatial perspective, providing insights for developing equitable and effective decarbonization strategies. The results showed that the sector has not yet reached its CO2 emissions peak in the temporal dimension, while the gravity center has moved southwestward in the spatial dimension. The study also reviewed decarbonization strategies and provided policy implications.
BUILDING AND ENVIRONMENT
(2023)
Article
Environmental Sciences
Alim Abbas, Qing He, Lili Jin, Jinglong Li, Akida Salam, Bo Lu, Yierpanjiang Yasheng
Summary: This study conducted a time series analysis on the variations of Land Surface Temperature (LST) in the Tarim Basin, China from 2001 to 2019, revealing significant differences in LST across different seasons and regions influenced by various factors. Factors such as temperature, elevation, and land-cover type were found to have a significant impact on LST, and El Nino and La Nina were identified as major influences on LST variations.
Article
Environmental Sciences
Shangbo Zhou, Tobias Schulze, Werner Brack, Thomas-Benjamin Seiler, Henner Hollert
Summary: This study investigated the spatial and temporal variations in the anti-androgen, receptor-mediated activity of surface water samples in the Holtemme River over a three-year period. The results showed that the anti-AR activity varied spatially, with the highest activity influenced by wastewater treatment plant effluents. On a temporal scale, no distinct trend was observed. The study also developed a novel risk assessment method based on bioanalytical equivalents and frequency of risk occurrence, which revealed that the highest risk was present at one site and considerably reduced at another site.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Xiaowei Ma, Xin Zhao, Lin Zhang, Yuanxiang Zhou, Huangxin Chen
Summary: The study reveals regional differences in atmospheric environmental efficiency in China, with the eastern region performing best and the central region performing worst, and these differences increase year by year. Technical progress is the dominant factor influencing atmospheric environmental efficiency, while economic development level and pollution control input also have significant impacts on atmospheric environmental efficiency.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Zoology
Fangyuan Yu, Yiwen Sun, Tiejun Wang, Andrew K. Skidmore, Changqing Ding, Xinping Ye
Summary: The study integrated ecological niche dynamics into the species distribution modeling of the Asian crested ibis in East Asia. The research found that the crested ibis retained similar ecological niches over time.
The current suitable habitat for crested ibis has decreased by 39.6% compared to historical range, with human activity having a greater impact than climate change on their distribution. Future potentially suitable habitat may shift northeastward and northwestward, possibly expanding by 18.7% compared to historical range.
INTEGRATIVE ZOOLOGY
(2022)
Article
Agronomy
Xu Ma, Tiejun Wang, Lei Lu, Huaguo Huang, Jiangli Ding, Fei Zhang
Summary: This study proposed a three-dimensional clumping index model based on area for measuring the leaf area index of crops, using digital cover photography data captured by digital cameras. Validation showed that the 3D model improved the prediction accuracy of LAI by 20.9% compared to the 1D model, addressing the underestimation issue and improving calculation accuracy in agriculture.
FIELD CROPS RESEARCH
(2022)
Article
Ecology
Inger K. de Jonge, Michiel P. Veldhuis, Anton Vrieling, Han Olff
Summary: Determining the drivers of aboveground net primary production (ANPP) is a crucial goal in ecosystem ecology. This study tested methods for estimating herbaceous productivity in savanna ecosystems, comparing different spectral greenness indices and their relationship to field-measured ANPP. The results showed that a satellite-based model including average NDVIs and its rate of change predicted herbaceous ANPP reasonably well, but the predictive accuracy was improved when using a camera trap-derived vegetation greenness index. The study also highlighted the importance of fine temporal resolution in capturing vegetation responses to rainfall events.
REMOTE SENSING IN ECOLOGY AND CONSERVATION
(2022)
Article
Environmental Sciences
Nasir Farsad Layegh, Roshanak Darvishzadeh, Andrew K. Skidmore, Claudio Persello, Nina Krueger
Summary: This study aims to develop a classification method by integrating graph-based semi-supervised learning (SSL) and an expert system (ES) to improve the accuracy of vegetation classification. The results show that this method has higher accuracy compared to other classification methods, and using all red-edge spectral band combinations yields the best results.
Article
Environmental Sciences
Yi-Wei Zhang, Tiejun Wang, Yanpei Guo, Andrew Skidmore, Zhenhua Zhang, Rong Tang, Shanshan Song, Zhiyao Tang
Summary: This study compares the performance of four non-parametric regression models in estimating plant community traits using UAV-based hyperspectral imaging. The results show that visible and near-infrared hyperspectral imaging can accurately estimate multiple plant community traits.
Review
Environmental Sciences
Katja Berger, Miriam Machwitz, Marlena Kycko, Shawn C. Kefauver, Shari Van Wittenberghe, Max Gerhards, Jochem Verrelst, Clement Atzberger, Christiaan van der Tol, Alexander Damm, Uwe Rascher, Ittai Herrmann, Veronica Sobejano Paz, Sven Fahrner, Roland Pieruschka, Egor Prikaziuk, Ma. Luisa Buchaillot, Andrej Halabuk, Marco Celesti, Gerbrand Koren, Esra Tunc Gormus, Micol Rossini, Michael Foerster, Bastian Siegmann, Asmaa Abdelbaki, Giulia Tagliabue, Tobias Hank, Roshanak Darvishzadeh, Helge Aasen, Monica Garcia, Isabel Pocas, Subhajit Bandopadhyay, Mauro Sulis, Enrico Tomelleri, Offer Rozenstein, Lachezar Filchev, Gheorghe Stancile, Martin Schlerf
Summary: This study provides an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Remote sensing technology can capture different plant responses under stress through specific light interaction processes. The analysis of research papers reveals the increasing usage of satellite and unmanned aerial vehicle data and a shift towards more advanced models. However, most studies still focus on proxies calculated from single-source sensor domains, and future research should explore simultaneous analysis of multiple stress responses, integration of multi-domain models and machine learning methods, and assimilation of estimated plant traits into integrated crop growth models.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Environmental Sciences
Anton Vrieling, Francesco Fava, Sonja Leitner, Lutz Merbold, Yan Cheng, Teopista Nakalema, Thomas Groen, Klaus Butterbach-Bahl
Summary: The use of night-time livestock enclosures, known as bomas, is common practice in African rangelands for protecting livestock from wildlife predation and theft. These enclosures have potential environmental impacts, such as emissions of nitrous oxide (a greenhouse gas) due to animal waste concentration. Recent advancements in satellite technology allow for accurate assessment of boma locations and numbers, as well as understanding their effects on the environment.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Ecology
Xin Zong, Tiejun Wang, Andrew K. Skidmore, Marco Heurich
Summary: This study demonstrates the use of three-dimensional cumulative viewshed in studying animal spatial behavior at a landscape level. The researchers utilized a combined terrestrial and airborne LiDAR technique to measure fine-scale habitat visibility in forested landscapes. The findings reveal the red deer's preference for intermediate habitat visibility and their adaptation of movement rate to fine-scale visibility. This research provides valuable insights into the influence of visibility on animal behavior and highlights the potential of LiDAR in animal ecology and behavior studies.
JOURNAL OF ANIMAL ECOLOGY
(2023)
Article
Biodiversity Conservation
Haili Yu, Tiejun Wang, Andrew Skidmore, Marco Heurich, Claus Baessler
Summary: This study used occurrence data from eight European countries to build species distribution models and predict the response of macrofungi to climate change. The results showed that considering climate change alone, 77% of macrofungal species will expand their distribution range and 57% of the area will have an increase in macrofungal species richness. However, when considering the combined climate and tree species distribution change, only 50% of the species are predicted to expand their distribution range and 49% of the area will experience an increase in macrofungal species richness.
DIVERSITY AND DISTRIBUTIONS
(2023)
Article
Multidisciplinary Sciences
Zijing Wu, Ce Zhang, Xiaowei Gu, Isla Duporge, Lacey F. Hughey, Jared A. Stabach, Andrew K. Skidmore, J. Grant C. Hopcraft, Stephen J. J. Lee, Peter M. Atkinson, Douglas J. McCauley, Richard Lamprey, Shadrack Ngene, Tiejun Wang
Summary: This study presents a deep learning pipeline that can automatically locate and count large herds of migratory ungulates in the Serengeti-Mara ecosystem using high-resolution satellite imagery. The results achieve accurate detection of nearly 500,000 individuals across thousands of square kilometers and multiple habitat types. This research demonstrates the capability of satellite remote sensing and machine learning techniques to automate the counting of large populations of terrestrial mammals and improve our understanding of animal behavior and ecology.
NATURE COMMUNICATIONS
(2023)
Article
Environmental Sciences
Yi Xu, Tiejun Wang, Andrew K. Skidmore, Tawanda W. Gara
Summary: This study proposes a novel approach to match individual trees between aerial photographs and airborne LiDAR data. By leveraging the maximum overlap of tree crowns in a local area, the correct and optimal offset vector is determined, and the mismatch in individual tree positions is rectified using this vector. Compared to a conventional method, the proposed approach significantly improves the accuracy of matching individual trees between aerial photographs and airborne LiDAR data.
Article
Geochemistry & Geophysics
Xu Ma, Jianli Ding, Tiejun Wang, Lei Lu, Hui Sun, Fei Zhang, Xiao Cheng, Ilyas Nurmemet
Summary: This study proposed a new method to estimate vegetation fractional vegetation cover (FVC) in arid areas using high-spatial-resolution (HSR) images. The method addressed the issue of estimating FVC from nadir-mode HSR images by modifying the radiation influence and developing a new pixel dichotomy coupled linear kernel-driven model. The results showed high consistency with true data and provided a useful algorithm for producing HSR FVCs in arid areas.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Forestry
Zhengnan Zhang, Tiejun Wang, Andrew K. Skidmore, Fuliang Cao, Guanghui She, Lin Cao
Summary: The diameter at breast height (DBH) is an important trait for studying plant ecology and biodiversity, as well as managing forests. Traditional ground-based approaches for measuring individual tree DBH over large areas are time-consuming and expensive. In this study, we propose an improved area-based approach using airborne LiDAR data to estimate plot-level DBH by utilizing the relationship between tree height and DBH. The results demonstrate the potential of using height-DBH relationships to improve the accuracy of estimating plot-level DBH from airborne LiDAR data.
Article
Environmental Sciences
Andrew K. Skidmore, Andjin Siegenthaler, Tiejun Wang, Roshanak Darvishzadeh, Xi Zhu, Anthony Chariton, G. Arjen de Groot
Summary: In this study, the relative abundance of soil microbiome in three terrestrial ecosystems across North America (savanna, boreal, and tundra) was mapped for the first time using airborne image spectroscopy and environmental DNA (eDNA) data. Linear Discriminate Analysis (LDA) scores were used to identify families with the greatest explanatory power in the community composition between the ecosystems. Spatial prediction of relative abundance of different bacteria taxa based on remote sensing was demonstrated, revealing patterns of soil microbiome biodiversity and ecosystem function within and across the three ecosystems.
SCIENCE OF REMOTE SENSING
(2022)
Article
Geography
Hunggul Y. S. H. Nugroho, Andrew Skidmore, Yousif A. Hussin
Summary: The decision of the Indonesian constitutional court to review forestry laws in 2013 marked a significant step forward in recognizing the rights of Indigenous people to forest. However, special measures are required to verify Indigenous status. This paper conducted a case study in a protected forest, evaluating the capacity of Indigenous communities to manage the forest and suggesting holistic approaches to ensure sustainable management for the benefit of the community and the environment.