摘要：
The global shipping industry faces increasingly complex safety challenges due to the rapid growth of international maritime trade. This study develops a novel framework that combines spatial density analysis and machine learning (i.e., extreme gradient boosting model) to investigate the evolutionary patterns of global maritime accidents during 2001-2020 from both spatial and temporal dimensions, and then identifies key environmental risk factors affecting maritime safety. The results show that the number of global maritime accidents exhibits fluctuations between 2001 and 2019, with a significant decrease observed in 2020. Furthermore, the distribution of global maritime accidents shows significant spatial variation over different time periods. Denmark's sea areas have high accident rates between 2001 and 2005, while concentrated accidents are observed in the seas around the United Kingdom, Denmark, and China between 2006 and 2010. From 2011 to 2015, Europe's accident-prone areas increase, but fewer accidents are reported along China's east coast. The Strait of Malacca is also an accident-prone area from 2016 to 2020. In addition, wave height, sea surface temperature, wind speed, water depth, and precipitation are identified as key environmental risk factors affecting maritime safety. These findings can inform strategies and mitigation plans to improve navigational safety in the global shipping industry.
摘要：
Semantic change detection (SCD) holds a critical place in remote sensing image interpretation, as it aims to locate changing regions and identify their associated land cover classes. Presently, post-classification techniques stand as the predominant strategy for SCD due to their simplicity and efficacy. However, these methods often overlook the intricate relationships between alterations in land cover. In this paper, we argue that comprehending the interplay of changes within land cover maps holds the key to enhancing SCD's performance. With this insight, a Temporal-Transform Module (TTM) is designed to capture change relationships across temporal dimensions. TTM selectively aggregates features across all temporal images, enhancing the unique features of each temporal image at distinct pixels. Moreover, we build a Temporal-Transform Network (TTNet) for SCD, comprising two semantic segmentation branches and a binary change detection branch. TTM is embedded into the decoder of each semantic segmentation branch, thus enabling TTNet to obtain better land cover classification results. Experimental results on the SECOND dataset show that TTNet achieves enhanced performance when compared to other benchmark methods in the SCD task. In particular, TTNet elevates mIoU accuracy by a minimum of 1.5% in the SCD task and 3.1% in the semantic segmentation task.
通讯机构：
[Yi, J.] H;Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, China
关键词：
nitrogen balance;nitrogen leaching;nitrogen uptake;nitrogen use efficiency;paddy yield
摘要：
Nitrogen loss from paddy fields contributes to most of the nitrogen pollution load in the Ningxia Yellow River irrigation area, threatening the water quality of the Yellow River. Consequently, optimizing the nitrogen management practices in this area is essential, which can maintain paddy grain productivity and reduce nitrogen loss simultaneously. Five treatments with different nitrogen application rates and nitrogen fertilizer types were set in this study, including conventional urea application with zero nitrogen application rate (CK, 0 kg hm(-2)), nitrogen expert-based fertilization application strategy (NE, 210 kg hm(-2)), optimized nitrogen fertilizer application strategy recommended by local government (OPT, 240 kg hm(-2)), and farmer's experience-based nitrogen fertilizer application strategy (FP, 300 kg hm(-2)), and controlled-release urea application (CRU, 180 kg hm(-2)). The data from one growth season field experiment in 2021 revealed the dynamics of nitrogen concentration, paddy yield and its nitrogen uptake characteristic, and nitrogen balance in the paddy field under different nitrogen application practices. Most nitrogen leaching was observed during the seedling and tillering stages in the form of nitrate nitrogen (NO3-N). Compared with the FP, the CRU and OPT significantly reduced the nitrogen concentrations of total nitrogen (TN), ammonium nitrogen (NH4+-N), and NO3-N in the surface and soil water and reduced the nitrogen leaching at 100 cm soil depth. Meanwhile, the paddy grain yield in CRU (7737 kg hm(-2)) and OPT (7379 kg hm(-2)) was not significantly decreased compared with FP (7918 kg hm(-2)), even though the nitrogen uptake by grain and straw was higher in FP (135 kg hm(-2)) than in other treatments (52.10 similar to 126.40 kg hm(-2)). However, the grain yield in NE (6972 kg hm(-2)) was decreased compared with the FP. The differences in grain yield among these treatments were mainly attributed to the ear number and grain number changes. Also, the highest nitrogen use efficiency (40.14%), apparent nitrogen efficiency (19.53 kg kg(-1)), and nitrogen partial productivity (43.98 kg kg(-1)) were identified in CRU than in other treatments. Considering increased grain yield and reducing nitrogen loss in the paddy field simultaneously, the treatments of CRU (i.e., 180 kg hm(-2) nitrogen application rate with controlled-release urea) and OPT (i.e., 240 kg hm(-2) nitrogen application rate with conventional urea) were recommended for nitrogen fertilizer application in the study area.
作者机构：
[Zhu, Yuanyuan; Ao, Rongjun; Shen, Xue; Zhou, Xiaoqi; Chen, Jing; Aihemaitijiang, Yierfanjiang] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Hubei, Peoples R China.;[Zhu, Yuanyuan; Ao, Rongjun; Shen, Xue; Zhou, Xiaoqi; Chen, Jing; Aihemaitijiang, Yierfanjiang] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
通讯机构：
[Ao, RJ ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Hubei, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan, Hubei, Peoples R China.
摘要：
This study introduces the principle of resilience into the study of human settlements. In this study, a comprehensive evaluation model of urban human settlements' resilience based on the provincial region of China was constructed using the Driver-Pressure-State-Impact-Response framework. The spatio-temporal evolution characteristics of urban human settlements' resilience was explored. The influencing factors were analysed by geographical detectors, and the driving mechanism was constructed. Results show that the following. (1) The resilience level of human settlements in China continued to increase, and the resilience level of each province and city changed significantly. The overall clustering effect showed a tendency to fluctuate and weaken. The distribution of cold spot areas became less and less, and the hot spots were moving from northeast China to southeast China. (2) Significant differences existed in the intensity of the impact of different indicators on the resilience system. The value of the impact factor showed an overall upward trend, and the number of key impact factors increased. (3) Improving the ability of scientific and technological innovation, accelerating the transformation and upgrading of the regional economy, increasing the training of talents and making financial inclination in scientific and technological development and industrial pollution control were all important ways for developing and maintaining the resilience of urban human settlements. This study not only introduces a new evaluation of urban human settlements from the perspective of resilience but also explores key impact indices and driving mechanisms, which provides new ideas for studying urban human settlements.
摘要：
With ongoing climate change, aridity is increasing worldwide, affecting biodiversity and ecosystem function in drylands. However, how the depth-profile microbial community structure and metabolic limitations change along aridity gradients are still poorly explored. Here, 16S rRNA and ITS amplicon sequencing and ecoenzymatic stoichiometry analysis were used to investigate both bacterial and fungal diversities and resource limitations in 1 m depth profiles across a wide aridity gradient (0.51-0.78) in a semiarid region. Results showed a sharp decrease in microbial diversity with soil depth, accompanied by an increase in microbial phosphorus (P) vs. N (nitrogen) limitation and a decrease in microbial carbon (C) vs. nutrient limitation. Aridity led to a strong shift in microbial community composition, but aridity has a threshold effect on microbial resource limitation through impacts on soil pH and C/P or N/P. When the aridity threshold (1-precipitation/evapotranspiration) exceeds 0.65, relationship between aridity and microbial resource demand was decoupled; but at aridity threshold = 0.65, microbial relative C limitation and C-acquiring enzyme activity dropped. These results suggest that aridity might have a stronger influence on microbial community composition, than on diversity, shaped by inherent soil biotic factors (i.e., MBC:MBP or MBN:MBP). These findings suggest that soil microbial diversity or enzymatic stoichiometry may be not necessary to mirror changes in water availability in the drylands, while aridity would be well explained by microbial community composition.
作者机构：
[Ma, Li; Ni, Yongxin; Wang, Jianwei; Lv, Xizhi; Zhang, Qiufen] Yellow River Inst Hydraul Res, Henan Key Lab Yellow Basin Ecol Protect & Restorat, Zhengzhou 450003, Peoples R China.;[Zhang, Xin; Qin, TL; Qin, Tianling] China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China.;[Ni, Yongxin] Hohai Univ, Coll Hydrol & Water Recourses, Nanjing 210098, Peoples R China.;[Nie, Hanjiang] Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Nie, Hanjiang] Cent China Normal Univ, Sch Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Qin, TL ] C;China Inst Water Resources & Hydropower Res, State Key Lab Simulat & Regulat Water Cycle River, Beijing 100038, Peoples R China.
关键词：
distributed hydrological model;water and land resources;evapotranspiration;runoff coefficient;Sihe River Basin
摘要：
Conflicts between humans and land use in the process of using water and conflicts between humans and water resources in the process of using land have led to an imbalance between natural ecosystems and socio-economic systems. It is difficult to understand the impact of the processes of water production and consumption on land patches and their ecological effects. A grid-type, basin-distributed hydrological model was established in this study, which was based on land-use units and coupled with groundwater modules to simulate the water production and consumption processes in different units. By combining land use and net primary productivity, the runoff coefficient and the water use efficiency (NPP/ET) of different land units were used as indicators to characterize the interaction between water and land resources. The results showed that the average runoff coefficients of cultivated land, forest land and grassland were 0.7, 0.5 and 0.9, respectively. Moreover, the average runoff coefficients of hills, plains and basins were 0.7, 0.7 and 0.8, respectively. The NPP produced by the average unit, evapotranspiration, in cultivated land, forest land and grassland was 7 (gC/(m(2).a))/mm, 0.7 (gC/(m(2).a))/mm and 0.2 (gC/(m(2).a))/mm, respectively. These results provide quantitative scientific and technological support in favor of the comprehensive ecological management of river basins.
期刊：
Environmental Science and Pollution Research,2023年30(42):96329-96349 ISSN：0944-1344
通讯作者：
Yu, J
作者机构：
[Li, Yimin; Nie, Yan; Yin, Chen; Zhou, Yong; Yu, Lei] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.;[Li, Yimin; Qin, Hong; Nie, Yan; Yin, Chen; Zhou, Yong; Yu, Lei] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Yu, J; Yu, Jing] Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan 430062, Peoples R China.
通讯机构：
[Yu, J ] H;Hubei Univ, Hubei Key Lab Reg Dev & Environm Response, Wuhan 430062, Peoples R China.
关键词：
Arable land multifunction;Functional trade-offs;Root mean square deviation method;Ecological compensation;The West Mountain Regions of Hubei Province
摘要：
Drainage network pattern recognition is a significant task with wide applications in geographic information mining, map cartography, water resources management, and urban planning. Accurate identification of spatial patterns in river networks can help us understand geographic phenomena, optimize map cartographic quality, assess water resource potential, and provide a scientific basis for urban development planning. However, river network pattern recognition still faces challenges due to the complexity and diversity of river networks. To address this issue, this study proposes a river network pattern recognition method based on graph convolutional networks (GCNs), aiming to achieve accurate classification of different river network patterns. We utilize binary trees to construct a hierarchical tree structure based on river reaches and progressively determine the tree hierarchy by identifying the upstream and downstream relationships among river reaches. Based on this representation, input features for the graph convolutional model are extracted from both spatial and geometric perspectives. The effectiveness of the proposed method is validated through classification experiments on four types of vector river network data (dendritic, fan-shaped, trellis, and fan-shaped). The experimental results demonstrate that the proposed method can effectively classify vector river networks, providing strong support for research and applications in related fields.
期刊：
Critical Reviews in Environmental Science and Technology,2023年53(20):1795-1816 ISSN：1064-3389
通讯作者：
Linchuan Fang
作者机构：
[He, Haoran; Fang, Linchuan; Chao, Herong; Zeng, Yi; Chen, Li; Zhang, Zhiqin] Northwest A&F Univ, Coll Nat Resources & Environm, Yangling, Peoples R China.;[He, Haoran; Duan, Chengjiao; Fang, Linchuan; Chao, Herong; Zeng, Yi; Chen, Li; Zhang, Zhiqin] Inst Soil & Water Conservat CAS & MWR, State Key Lab soil Eros & Dryland Farming Loess Pl, Yangling, Peoples R China.;[Wang, Fayuan] Qingdao Univ Sci & Technol, Coll Environm & Safety Engn, Qingdao, Peoples R China.;[Hu, Weifang] Guangdong Acad Agr Sci, Inst Agr Resources & Environm, Guangzhou, Peoples R China.;[Liu, Ji] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan, Peoples R China.
通讯机构：
[Linchuan Fang] C;College of Natural Resources and Environment, Northwest A&F University, Yangling, China<&wdkj&>State Key Laboratory of soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation CAS and MWR, Yangling, China
关键词：
Arbuscular mycorrhizal fungi;bioaccumulation;crop growth;Jörg Rinklebe and Lena Q. Ma;meta-analysis;physiological activities;potentially toxic elements
摘要：
Soil pollution from potentially toxic elements (PTEs) is a serious environmental issue worldwide that affects agricultural safety and human health. Arbuscular mycorrhizal fungi (AMF), as ecosystem engineers, can alleviate PTE toxicity in crop plants. However, the comprehensive effects of AMF on crop performance in PTE-contaminated soils have not yet been recognized globally. Here, a meta-analysis of 153 studies with 3213 individual observations was conducted to evaluate the effects of AMF on the growth and PTE accumulation of five staple crops (wheat, rice, maize, soybean, and sorghum) in contaminated soils. Our results demonstrated that AMF had strong positive effects on the shoot and root biomass. This is because AMF can effectively alleviate oxidative damage induced by PTEs by stimulating photosynthesis, promoting nutrition, and activating non-enzymatic and enzymatic defense systems in crop plants. AMF also decreased shoot PTE accumulation by 23.6% and increased root PTE accumulation by 0.8%, demonstrating that AMF effectively inhibited the PTE transfer and uptake by crop shoot. Meanwhile, AMF-mediated effects on shoot PTE accumulation were weaker in soils with pH > 7.5. Overall, this global survey has essential implications on the ability of AMF to enhance crop performance in PTE-contaminated soils and provides insights into the guidelines for safe agricultural production worldwide.
摘要：
Fractional vegetation cover (FVC) has a significant role in indicating changes in ecosystems and is useful for simulating growth processes and modeling land surfaces. The fine-resolution FVC products represent detailed vegetation cover information within fine grids. However, the long revisit cycle of satellites with fine-resolution sensors and cloud contamination has resulted in poor spatial and temporal continuity. In this study, we propose to derive a spatially and temporally continuous FVC dataset by comparing multiple methods, including the data-fusion method (STARFM), curve-fitting reconstruction (S-G filtering), and deep learning prediction (Bi-LSTM). By combining Landsat and Sentinel-2 data, the integrated FVC was used to construct the initial input of fine-resolution FVC with gaps. The results showed that the FVC of gaps were estimated and time-series FVC was reconstructed. The Bi-LSTM method was the most effective and achieved the highest accuracy (R-2 = 0.857), followed by the data-fusion method (R-2 = 0.709) and curve-fitting method (R-2 = 0.705), and the optimal time step was 3. The inclusion of relevant variables in the Bi-LSTM model, including LAI, albedo, and FAPAR derived from coarse-resolution products, further reduced the RMSE from 5.022 to 2.797. By applying the optimized Bi-LSTM model to Hubei Province, a time series 30 m FVC dataset was generated, characterized by a spatial and temporal continuity. In terms of the major vegetation types in Hubei (e.g., evergreen and deciduous forests, grass, and cropland), the seasonal trends as well as the spatial details were captured by the reconstructed 30 m FVC. It was concluded that the proposed method was applicable to reconstruct the time-series FVC over a large spatial scale, and the produced fine-resolution dataset can support the data needed by many Earth system science studies.
期刊：
Science of The Total Environment,2023年892:164735 ISSN：0048-9697
通讯作者：
Li, J
作者机构：
[Liu, Qinhuo; Gu, Chenpeng; Dong, Yadong; Zhao, Jing; Li, Jing; Liu, Chang; Mumtaz, Faisal] Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.;[Liu, Qinhuo; Gu, Chenpeng; Dong, Yadong; Zhao, Jing; Li, Jing; Liu, Chang; Mumtaz, Faisal] Univ Chinese Acad Sci, Beijing 100049, Peoples R China.;[Gao, Jixi] Minist Ecol & Environm Peoples Republ China, Satellite Applicat Ctr Ecol & Environm, Beijing 100094, Peoples R China.;[Wang, Cong] Cent China Normal Univ, Sch Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.
通讯机构：
[Li, J ] C;Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
关键词：
Leaf area index;Eurasian Steppe (EAS);ENSO;Vegetation change
摘要：
As the most influential atmospheric oscillation on Earth, the El Niño/Southern Oscillation (ENSO) can significantly change the surface climate of the tropics and subtropics and affect the high latitudes of northern hemisphere areas through atmospheric teleconnection. The North Atlantic Oscillation (NAO) is the dominant pattern of low-frequency variability in the Northern Hemisphere. As the dominant oscillations in the Northern Hemisphere, the ENSO and NAO have been affecting the giant grassland belt in the world, the Eurasian Steppe (EAS), in recent decades. In this study, the spatio-temporal anomaly patterns of grassland growth in the EAS and their correlations with the ENSO and NAO were investigated using four long-term leaf area index (LAI) and one normalized difference vegetation index (NDVI) remote sensing products from 1982 to 2018. The driving forces of meteorological factors under the ENSO and NAO were analyzed. The results showed that grassland in the EAS has been turning green over the past 36years. Warm ENSO events or positive NAO events accompanied by increased temperature and slightly more precipitation promoted grassland growth, and cold ENSO events or negative NAO events with cooling effects over the whole EAS and uneven precipitation decreased deteriorated the EAS grassland. During the combination of warm ENSO and positive NAO events, a more severe warming effect caused more significant grassland greening. Moreover, the co-occurrence of positive NAO with cold ENSO or warm ENSO with negative NAO kept the characteristic of the decreased temperature and rainfall in cold ENSO or negative NAO events, and deteriorate the grassland more severely.
摘要：
Predicting drought severity is essential for drought management and early warning systems. Although numerous physical model-based and data-driven methods have been put forward for drought prediction, their abilities are largely constrained by data requirements and modeling complexity. There remains a challenging task to efficiently predict categorial drought, especially for the U.S. Drought Monitor (USDM). Aiming at this issue, multiple Markov chains for USDM-based categorial drought prediction are successfully proposed and evaluated in this paper. In particular, this study concentrated on how the Markov order, step size, and training set length affected prediction accuracy (PA). According to experiments from 2000 to 2021, it was found that the 1-step and first-order Markov models had the best accuracy in predicting droughts up to 4 weeks ahead. The PA steadily dropped with increasing step size, and the average accuracy at monthly scale was 88%. In terms of seasonal variability, summer (July-August) had the lowest PA while winter had the highest (January-February). In comparison with the western region, the PA in the eastern United States is 25% higher. Moreover, the length of the training set had an obvious impact on the PA of the model. The PA in 1-step prediction was 87% and 78% under 20-and 5-yr training sets, respectively. The results of the study showed that Markov models predicted categorical drought with high accuracy in the short term and showed different performances on time and space scales. Proper use of Markov models would help disaster managers and policy makers to put mitigation policies and measures into practice.
摘要：
As a driving force for regional development, innovation holds an increasing position in regional competitiveness, and a reasonable and coordinated innovation network structure can promote high-quality regional development. Utilizing the modified gravity model and social network analysis method, an innovation network composed of 27 cities in the Yangtze River Delta urban agglomeration from 2010 to 2021 was studied. The following conclusions were founded: (1) The innovation development level in the Yangtze River Delta urban agglomeration was constantly improving, and the innovation development level generally showed a spatial pattern of high in the southeast and low in the northwest. (2) The intensity and density of innovation network correlations in urban agglomerations were increasing, and the centrality of network nodes had an obvious hierarchical characteristic. The innovation network had a significant core-periphery spatial structure, with core cities that had higher centrality, such as Shanghai, Nanjing, and Hangzhou, playing the role of "intermediaries" and "bridges", while cities with lower centrality, such as Anhui and cities in northern Jiangsu, generally played the role of "periphery actors" in the network. (3) The spatial correlation network of innovation of the Yangtze River Delta urban agglomeration could be divided into four blocks, namely, main benefit, broker, two-way spillover, and net spillover, and the spillover effect among them had obvious gradient characteristics of hierarchy.
期刊：
European Journal of Agronomy,2023年151 ISSN：1161-0301
通讯作者：
Xu, BD;Hu, Q
作者机构：
[Xu, Baodong; Xu, BD; Zhou, Wei; Cai, Zhiwen] Huazhong Agr Univ, Macro Agr Res Inst, Coll Resources & Environm, Wuhan 430070, Peoples R China.;[Hu, Jie; Zhang, Xinyu; Wei, Haodong; Chen, Yunping] Huazhong Agr Univ, Coll Plant Sci & Technol, Wuhan 430070, Peoples R China.;[Yang, Jingya] Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, State Key Lab Efficient Utilizat Arid & Semiarid A, Beijing 100081, Peoples R China.;[Hu, Q; Hu, Qiong] Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Xiong, Hang] Huazhong Agr Univ, Coll Econ & Management, Wuhan 430070, Peoples R China.
通讯机构：
[Hu, Q ] C;[Xu, BD ] H;Huazhong Agr Univ, Macro Agr Res Inst, Coll Resources & Environm, Wuhan 430070, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.
关键词：
Plastic -mulched citrus index;Spectral separability;Intra-annual and interannual analysis;Spatio-temporal variation;Multi -source remote sensing data
摘要：
The technology of canopy plastic mulching has been widely used in citrus orchards for protecting fruit trees from cold damage. Understanding the spatio-temporal dynamics of plastic-mulched citrus (PMC) is of great importance for precision management of citrus orchards. However, monitoring the long-term and large-area PMC dynamics is challenging because the PMC is typically distributed in cloudy and rainy areas with rapid spatial variability, leading to the limited availability of high-quality remotely sensed data. Moreover, it is difficult to collect sufficient field samples in rugged mountainous regions for extracting PMC. To address these limitations, we proposed a new plastic-mulched citrus index (PMCI) based on spectral separability analysis of PMC and other land cover types. The images from Landsat-5/7/8, Sentinel-2, and Gaofen-1 satellites were employed to extract the intra-annual PMC distribution from 2019 to 2020 and interannual PMC distribution from 2008 to 2020 in Yangshuo county, Guangxi Zhuang Autonomous Region, China. Results showed that the PMCI outperformed other widely used indices in PMC extraction with overall accuracy (OA) increased by 0.09-0.3. Besides, the PMCI exhibited good performances in extracting PMC over different observation dates with OA ranging 0.92-0.98 and 0.91-0.98 in the intra-annual and annual PMC maps, respectively. According to the derived PMC time series maps, PMC displayed significant intra-annual spatial variations in the start date and length of plastic mulching period, whereas the interannual variation of PMC revealed long-term technology adoption patterns in the study area. Furthermore, we found that temperature mainly affected intra-annual PMC variability, and that agricultural policy, market factor, neighborhood effect and variety replacement can explain the interannual PMC variability. These results indicate that the developed PMCI can effectively identify PMC over different agricultural regions and observation dates, and the resultant spatio-temporal dynamic PMC maps based on multi-source satellite data provide an important basis for the promotion of PMC at larger scales and the sustainable development of the citrus industry.
作者机构：
[Zhu, Wenchao; Wu, Hao; Jiang, Zhimeng; Cen, Luyu] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Zhu, Wenchao; Wu, Hao; Jiang, Zhimeng; Cen, Luyu] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.
通讯机构：
[Zhimeng Jiang] C;College of Urban and Environmental Sciences, Central China Normal University, Wuhan, China<&wdkj&>Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Central China Normal University, Wuhan, China
关键词：
land use spatial pattern;resource environment carrying capacity;land use change;spatial optimization;high-quality land development;Zhengzhou city
摘要：
High-intensity land use and resource overloaded-induced regional land use spatial pattern (LUSP) are essential and challenging for high-quality development. The empirical studies have shown that a scientific land uses spatial layout, and the supporting system should be based on a historical perspective and require better considering the double influence between the current characteristics and future dynamics. This study proposes a comprehensive framework that integrates the resource environment carrying capacity (RECC) and land use change (LUC) to investigate strategies for optimizing the spatial pattern of land use for high-quality development. China's Zhengzhou city was the subject of a case study whose datasets include remote sensing, spatial monitoring, statistics, and open sources. Three significant results emerged from the analysis: (1) The RECC has significant spatial differentiation but does not follow a specific spatial law, and regions with relatively perfect ecosystems may not necessarily have better RECC. (2) From 2020 to 2030, the construction land and farmland will fluctuate wildly, with the former increasing by 346.21 km(2) and the latter decreasing by 295.98 km(2). (3) The study area is divided into five zones, including resource conservation, ecological carrying, living core, suitable construction, and grain supply zones, and each one has its LUSP optimization orientation. This uneven distribution of RECC reflects functional defects in the development and utilization of LUSP. In addition, the increase in construction land and the sharp decline of farmland pose potential threats to the sustainable development of the study area. Hence, these two elements cannot be ignored in the future high-quality development process. The findings indicate that the LUSP optimization based on dual dimensions of RECC and LUC is more realistic than a single-dimension solution, exhibiting the LUSP optimization's effectiveness and applicability.
作者机构：
[Fan, Junfu; Zuo, Jiwei; Shi, Zongwen; Chen, Jiahao; Zhang, Mengzhen] Shandong Univ Technol, Sch Civil Engn & Geomat, Zibo 255000, Peoples R China.;[Fan, Junfu; Zhang, Mengzhen] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China.;[Chen, Jiahao] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Ji, Min] Shandong Univ Sci & Technol, Coll Geodesy & Geomat, Qingdao 266510, Peoples R China.
通讯机构：
[Chen, JH ] S;Shandong Univ Technol, Sch Civil Engn & Geomat, Zibo 255000, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
building change detection;deep learning;high-resolution;multispectral;multisource spectral data
摘要：
Building change detection is an important task in the remote sensing field, and the powerful feature extraction ability of the deep neural network model shows strong advantages in this task. However, the datasets used for this study are mostly three-band high-resolution remote sensing images from a single data source, and few spectral features limit the development of building change detection from multisource remote sensing images. To investigate the influence of spectral and texture features on the effect of building change detection based on deep learning, a multisource building change detection dataset (MS-HS BCD dataset) is produced in this paper using GF-1 high-resolution remote sensing images and Sentinel-2B multispectral remote sensing images. According to the different resolutions of each Sentinel-2B band, eight different multisource spectral data combinations are designed, and six advanced network models are selected for the experiments. After adding multisource spectral and texture feature data, the results show that the detection effects of the six networks improve to different degrees. Taking the MSF-Net network as an example, the F1-score and IOU improved by 0.67% and 1.09%, respectively, compared with high-resolution images, and by 7.57% and 6.21% compared with multispectral images.
通讯机构：
[Yonglong Lu] S;State Key Laboratory of Marine Environmental Science and Key Laboratory of the Ministry of Education for Coastal Wetland Ecosystems, College of the Environment and Ecology, Xiamen University, Fujian 361102, China<&wdkj&>State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
关键词：
Energy Modeling;Energy management;Energy policy;Energy resources
摘要：
The flourishing logistics in both developed and emerging economies leads to huge greenhouse gas (GHG) emissions; however, the emission fluxes are poorly constrained. Here, we constructed a spatial network of logistic GHG emissions based on multisource big data at continental scale. GHG emissions related to logistics transportation reached 112.14Mt CO(2)-equivalents (CO(2)e), with seven major urban agglomerations contributing 63% of the total emissions. Regions with short transport distances and well-developed road infrastructure had relatively high emission efficiency. Underlying value flow of the commodities is accompanied by logistics carbon flow along the supply chain. The main driving factors affecting GHG emissions are driving speed and gross domestic product. It may mitigate GHG emissions by 27.50-1162.75 Mt CO(2)e in 15 years if a variety of energy combinations or the appropriate driving speed (65-70km/h) is adopted. The estimations are of great significance to make integrated management policies for the global logistics sector.
摘要：
This study utilized Trichoderma and activated sludge to construct combined activated sludge (TAS). The metagenomic approach was employed to examine the shifts in microbial community structure and function of TAS under amoxicillin stress and investigate the mechanism underlying the reduction of β-lactam antibiotic resistance genes (β-ARGs). The findings demonstrated that the elevated aundance of glpa, glpd, ugpq, glpq, and glpb were primarily responsible for the reduction in total phosphorus (TP) removal by TAS. The increased abundance of Proteobacteria and Verrucomicrobia led to enhanced expression of ugpb, phnd, and phne, thereby improving the TP removal of TAS. Furthermore, antibiotic inactivation has gradually become the primary antibiotic resistance mechanism in TAS. Specifically, an increase in the abundance of OXA-309 in TAS will decrease the probability of amoxicillin accumulation in TAS. A decrease in β-ARGs diversity confirmed this. This study presents a novel approach to reducing antibiotic and ARG accumulation in sludge.
