作者机构：
华中师范大学地理过程分析与模拟湖北省重点实验室,武汉430079;华中师范大学城市与环境科学学院,武汉430079;格拉斯哥大学社会与政治科学学院,英国格拉斯哥G128QQ;[敖荣军; 高喆] Hubei Provincial Key Laboratory for Geographical Process Analysis & Simulation, Central China Normal University, Wuhan, 430079, China, College of Urban & Environmental Sciences, Central China Normal University, Wuhan, 430079, China;[李昱霄] School of Social and Political Sciences, University of Glasgow, Glasgow, G128QQ, United Kingdom
通讯机构：
[Ao, R.] H;Hubei Provincial Key Laboratory for Geographical Process Analysis & Simulation, China
作者机构：
[Li, Xiaojing] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Chen, Jing] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.
通讯机构：
[Chen, J ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.
关键词：
spatial spillovers;related variety;unrelated variety;regional economic resilience;the middle reaches of the Yangtze River urban agglomeration
摘要：
A growing body of literature has studied the empirical relationship between industrial diversity and economic resilience since the 2008 Great Recession. However, many existing studies are based on a nonspatial perspective, and little is known about the local or global spatial spillover effect of industrial diversity on economic resilience. This paper employs Bayesian spatial econometric methods to investigate the roles of related variety and unrelated variety on economic resilience in the middle reaches of the Yangtze River urban agglomeration, China and explores the possible local or global spatial spillover effect in the diversity-resilience relationship. The empirical results from the spatial Durbin error model estimation show that: (1) regions with high levels of related variety are economically resilient to the external shock in the postcrisis era, whereas unrelated variety has no significant direct effect on recovery resilience; (2) both related and unrelated variety have local spatial spillovers with respect to the one-year resilience of 2008-2009, but these spillovers are negligible in longer study periods. These results confirm the role of industrial relatedness and immediate neighbors in promoting regions' short-run capabilities of recovery from external economic shocks.
期刊：
Frontiers in Environmental Science,2023年11:1202661 ISSN：2296-665X
通讯作者：
Cui, J.
作者机构：
[Jing, Ying] School of Business, NingboTech University, Ningbo, China;[Cui, Jiaxing] College of Urban and Environmental Sciences, Central China Normal University, Wuhan, China;[Ma, Ding] School of Architecture and Urban Planning, Shenzhen University, Shenzhen, China;[Chen, Yiyun] School of Resource and Environmental Sciences, Wuhan University, Wuhan, China
通讯机构：
[Cui, J.] C;College of Urban and Environmental Sciences, China
关键词：
geographic big data;geographical information science (GIScience);spatial analysis;spatial planning and design;sustainable development
摘要：
Since the introduction of geo-big data, we could observe how its role in social development and humanenvironment interaction has grown through the years. Multiple examples of geo-big data applications can be found in leisure space optimization, traffic prediction, agricultural planning, air quality monitoring, livelihood improvement, social justice, forest management, interregional development, green space accessibility, and environmental diagnosis. This extensive use of geo-big data facilitates spatial information sharing, and spatial data mining and can be applied to geographic assessment, prediction, analysis, and planning. The geo-big data era provides a new opportunity for the transformation of spatial planning and sustainable decision-making through revealing spatial regularity based on geo-big data (see, for instance, [1,2]).The goal of this collection is to introduce academic outputs which adopt geospatial big data to facilitate intelligent urban governance. In the rapid process of urbanization, geo-big data serves as a crucial factor of technology innovation which covers all the aspects of urban systems (i.e., fundamental infrastructures, traffic networks, architectures, energy systems, etc.). Based on smart spatial analytical platforms and geospatial artificial intelligence technologies, geospatial big data can be used to empower urban governance in an intelligent and smart mode serving as an engine to monitor, assess, diagnose, and ultimately tackle urban proble...
作者机构：
[Zhao, Yutao; Meng, Ran; Lv, Zhengang; Zhou, Longfei; Zeng, Linglin; Huang, Zehua; Xu, Binyuan] Huazhong Agr Univ, Coll Resources & Environm, Wuhan 430070, Peoples R China.;[Yan, Jianbing; Chen, Gengshen] Huazhong Agr Univ, Natl Key Lab Crop Genet Improvement, Wuhan 430070, Peoples R China.;[Zhao, Feng] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Yan, Jianbing] Hubei Hongshan Lab, Wuhan 430070, Peoples R China.;[Meng, Ran] HIT Artificial Intelligence Res Inst Co Ltd, Harbin 150000, Peoples R China.
通讯机构：
[Ran Meng] C;College of Resources and Environment, Huazhong Agricultural University, Wuhan, China<&wdkj&>HIT Artificial Intelligence Research Institute Co., Ltd, Harbin, China
摘要：
Southern corn leaf blight (SCLB) seriously threatens corn production. The timely and accurate monitoring of SCLB conditions (e.g., detection during the asymptomatic stage and severity classification during the symptomatic stage) is valuable for precision agriculture, because the application of pesticides depends on disease conditions. Compared with time-consuming and laborious field surveys, spectroscopy is a promising tool for plant disease monitoring. The unique advantages of combining multiple spectral enhancement features for monitoring rice and wheat diseases have been recognized. However, physiological and biochemical differences between maize leaves and rice and wheat leaves, along with the specific spectral response of SCLB, are likely to affect the performance of combining multiple spectral enhancement features. In addition, similar previous studies have not combined spectral slope features, i.e., first-order spectral derivatives (FSDs), with spectral bands (SBs) and spectral indices (SIs) and wavelet features (WFs) to improve plant disease detection. Thus, the performance of a method that combines FSDs, WFs, SBs, and SIs for SCLB asymptomatic detection, symptomatic detection, and symptomatic severity classification should be evaluated further. Here, the utility of combining SBs, SIs, WFs, and FSDs was quantified and evaluated in the asymptomatic detection, symptomatic detection, and symptomatic severity classification of SCLB. Various forms of spectral enhancement features that were sensitive to SCLB infection from the asymptomatic stage to the severe stage were first identified and combined using the RELIEF-F and sequential floating forward selection algorithms on the basis of two independent inoculation experiments. Finally, SCLB asymptomatic detection, symptomatic detection, and symptomatic severity classification models were developed and evaluated using the support vector machine algorithm. Results showed that combining FSDs with SBs, SIs, and WFs achieved the best performance in SCLB spectroscopic monitoring. (1) SCLB asymptomatic detection and symptomatic detection were moderately improved, i.e., overall accuracy (OA) and macro F1 (MF1) improved by similar to 1% to 2%. The OA of SCLB asymptomatic detection was 87.1% with an MF1 of 0.87, and that of symptomatic detection was 93.1% with an MF1 of 0.93. (2) SCLB symptomatic severity classification was significantly improved, i.e., OA and MF1 improved by similar to 7%. The OA of severity classification was 81.8% with am MF1 of 0.82. This study demonstrated that the complementary relationships among SBs, SIs, WFs, and FSDs could effectively improve SCLB spectroscopic monitoring. The proposed method provides a novel tool for large-scale SCLB spectroscopic monitoring. It has broad implications for assisting management decisions (i.e., when and where to apply pesticides and how much to apply) in precision agriculture.
摘要：
Cadmium (Cd) contamination poses a considerable threat to human health through grain enrichment and limits biological nitrogen fixation (BNF) in paddy fields. Biochar has shown great potential for agricultural soil remediation because it inactivates Cd, but uncertainties remain as to how biochar amendments affect BNF and grain N use efficiency in paddies. To elucidate these issues, we investigated the effects of biochar amendment on the structure and function of diazotrophic bacterial communities in different rice growth stages in Cd-contaminated paddy fields, and evaluated the contribution of BNF to grain N use efficiency under biochar amendment. The results showed that biochar amendment significantly increased the abundance of diazotrophic bacteria in the tillering and jointing stages. Furthermore, the community structure of soil diazotrophic bacteria markedly changed with biochar amendment, with a significant reduction in the abundances of Euryarchaeota, Desulfobacterales (Proteobacteria), and Sphingomonadales (Bacteroidetes) in the tillering stage. Changes in the soil carbon/nitrogen (C/N) ratio was the main factor driving diazotrophic microbial community characteristics caused by the release of available C from biochar at the tillering stage, rather than the Cd. Moreover, biochar amendment increased the efficiency of BNF (especially for autotrophic N2 fixation) in the vegetative phase of rice growth. Notably, biochar amendment significantly decreased BNF efficiency during the filling stage and reduced grain N use efficiency. The limited available nutrients in biochar and the toxicity of polycyclic aromatics and phenols in biochar-derived dissolved organic matter were responsible for the varied impacts of biochar on BNF in different rice growth stages. For the first time, we report that biochar amendment in paddy soils reduces Cd toxicity but also inhibits BNF and thereby decreases N use efficiency. Therefore, before applying biochar to inactivate Cd in paddy fields, there should be a trade-off between agricultural production and ecological safety to achieve sustainable agriculture.
作者机构：
[Fu, Yongshuo H.; Xiao, Yi] Beijing Normal Univ, Coll Water Sci, Beijing 100875, Peoples R China.;[Hao, Fanghua; Guo, Yahui; Chen, Jiahao; Nie, Xingyu; Li, Xiran; Xu, Yue; Guo, Shihui] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Fu, YH ] B;Beijing Normal Univ, Coll Water Sci, Beijing 100875, Peoples R China.
关键词：
High spatial resolution;Optical Satellite;Inland waters;Chlorophyll-a;Suspended sediment;Unmanned aerial vehicle (UAV)
摘要：
In recent decades, phytoplankton proliferation and sediment input to rivers (especially urban rivers) have become more dramatic under the compound pressure of climate change and human activities. Given the generally narrow width of rivers and current high spatial resolution satellites, which are limited by band settings, bandwidth, and the signal-to-noise ratio, UAVs with their exceptional spatiotemporal resolution can be used as a useful tool for river environmental monitoring and inversion uncertainty assessment. In this study, UAV-based hyperspectral (X20P) and multispectral (P4M) images, along with Sentinel-2 MultiSpectral Instrument (MSI), Landsat-8 Operational Land Imager (OLI) and Landsat-9 OLI2 data, were used to assess the uncertainty in retrieving chlorophyll-a (Chla) and suspended sediment (SS) concentrations in rivers. Chla and SS models based on UAV and satellite data were constructed using stepwise multiple regression and typical Chla and SS retrieval algorithms, respectively, and the performance of the models was the focus of our research. The results demonstrated that in the Chla concentration inversion, each sensor performed as follows: X20P > P4M > Landsat9 OLI2 > Sentinel-2 MSI > Landsat8 OLI, and the performance in the SS concentration inversion was as follows: X20P > Sentinel-2 MSI > P4M > Landsat9 OLI2 > Landsat8 OLI. In addition, the uncertainty of high spatial resolution satellite retrievals was analyzed with the assistance of the UAV-based model. Results showed that narrow bandwidths and finely tuned band settings are more essential for the Chla inversion. The typical Chla retrieval algorithm, NDCI, is only effective in certain bands (band 1 from 684 to 724 nm and band 2 from 660 to 680 nm). It is also noted that Landsat8 and Landsat9 lack some key band settings (e.g., the red-edge band of 700-710 nm), severely limiting practical application in relation to Chla. However, specific variances in different sensor bands have a relatively small impact on SS inversion, for example, the correlation between SS and the R/B (a typical SS retrieval algorithm) constructed by each sensor ranged from 0.68 to 0.77. Chla monitoring, on the other hand, necessitates a higher spatial resolution than SS monitoring. The accuracy decreased markedly when UAV images were resampled to 10 m and 30 m spatial resolution. However, it is not as crucial for the SS inversion, images with the original spatial resolution (RMSE<30cm = 6.28 mg/L) were resampled to 10 m resolution (RMSE10m = 5.85 mg/L) and 30 m resolution (RMSE30m = 4.08 mg/L) while using P4M for SS inversion, and the accuracy increased. Our results demonstrated and highlighted various options for future monitoring of Chla and SS, while exploiting the synergy between UAVs and satellites to achieve more precise observations at greater spatial and temporal scales, which will benefit aquatic environment management and protection.
摘要：
A high-quality remote sensing interpretation dataset has become crucial for driving an intelligent model, i.e., deep learning (DL), to produce land-use/land-cover (LULC) products. The existing remote sensing datasets face the following issues: the current studies (1) lack object-oriented fine-grained information; (2) they cannot meet national standards; (3) they lack field surveys for labeling samples; and (4) they cannot serve for geographic engineering application directly. To address these gaps, the national-standards- and DL-oriented raster and vector benchmark dataset (RVBD) is the first to be established to map LULC for conducting soil water erosion assessment (SWEA). RVBD has the following significant innovation and contributions: (1) it is the first second-level object- and DL-oriented dataset with raster and vector data for LULC mapping; (2) its classification system conforms to the national industry standards of the Ministry of Water Resources of the People's Republic of China; (3) it has high-quality LULC interpretation accuracy assisted by field surveys rather than indoor visual interpretation; and (4) it could be applied to serve for SWEA. Our dataset is constructed as follows: (1) spatio-temporal-spectrum information is utilized to perform automatic vectorization and label LULC attributes conforming to the national standards; and (2) several remarkable DL networks (DenseNet161, HorNet, EfficientNetB7, Vision Transformer, and Swin Transformer) are chosen as the baselines to train our dataset, and five evaluation metrics are chosen to perform quantitative evaluation. Experimental results verify the reliability and effectiveness of RVBD. Each chosen network achieves a minimum overall accuracy of 0.81 and a minimum Kappa of 0.80, and Vision Transformer achieves the best classification performance with overall accuracy of 0.87 and Kappa of 0.86. It indicates that RVBD is a significant benchmark, which could lay a foundation for intelligent interpretation of relevant geographic research about SWEA in the Yangtze River Basin and promote artificial intelligence technology to enrich geographical theories and methods.
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.
作者机构：
[Jie Yan; Chaohui Zheng] School of Architecture and Urban Planning, Hunan City University, Yiyang, People’s Republic of China;College of Urban and Environmental Science, Central China Normal University, Wuhan, People’s Republic of China;[Hui Tang] School of Architecture and Urban Planning, Hunan City University, Yiyang, People’s Republic of China<&wdkj&>College of Urban and Environmental Science, Central China Normal University, Wuhan, People’s Republic of China
通讯机构：
[Jie Yan] S;School of Architecture and Urban Planning, Hunan City University, Yiyang, People’s Republic of China
关键词：
coupling coordination degree;Healthy;supply and demand matching;the central urban area of Yiyang;urban park green space
期刊：
Journal of Soil Science and Plant Nutrition,2023年:1-14 ISSN：0718-9508
通讯作者：
Yi, Jun;Zhang, HL
作者机构：
[Zhang, HL; Li, Shenglong; Nan, Xin; Liu, Muxing; Yi, Jun; Yi, J; Fei, Yuanhang; Xu, Tianxiang; Nie, Hanjiang; Hu, Kang; Ren, Qian; Zhang, Hailin] Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.;[Liu, Xiaoli] Chinese Acad Sci, Inst Soil Sci, Nanjing 210008, Peoples R China.
通讯机构：
[Yi, J; Zhang, HL ] C;Cent China Normal Univ, Hubei Prov Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Peoples R China.
关键词：
Soil Moisture;Rainfall;Land use Types;Soil Properties;Soil Water Storage
摘要：
Purpose Studying the response of soil moisture (theta) to rainfall is highly significant for comprehending water transport and balance. Nevertheless, the response of theta to rainfall in pristine forest land and farmland after forest reclamation in the Chinese red soil region is rarely compared.Methods In this study, the theta dynamics and the response characteristics of theta to rainfall in upland field (UF), paddy field (PF), and forest land (FL) were revealed, with continuous and high-frequency theta monitoring data at 5, 10, 20, 40, and 70 cm depths, respectively.Results The results showed that the average theta in PF (0.418 cm(3) cm(-3)) was much higher than that in UF (0.317 cm(3) cm(-3)) and FL (0.291 cm(3) cm(-3)). Meanwhile, the longest lag time (16.8 h) and largest required rainfall amount (16.4 mm) for triggering theta response (RRSR) were observed in FL as compared with UF (11.3 h, 10.2 mm) and PF (12.6 h, 8.7 mm). The maximum increment of theta was significantly positively correlated with the rainfall amount (P < 0.01). The RRSR exhibited significant negative correlations with root density, saturated hydraulic conductivities, and the soil pores content with a diameter > 0.1 mm (P < 0.01). Furthermore, the cumulative increment of soil water storage in FL (190.1 mm) was larger than that in UF (160.6 mm) and PF (143.8 mm).Conclusions The land use conversion from FL to UF and PF reduced the rainfall infiltration capacity and may increase runoff potential.
作者机构：
[Tian, Lingling; Han, Tingting; Tian, LL; Wang, Hafo; Luo, Jing; Gan, Yilin] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;[Tian, Lingling; Han, Tingting; Tian, LL; Wang, Hafo; Luo, Jing; Gan, Yilin] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Liu, Jianwei] Hubei Tiandiyun Geomat Technol Grp, Wuhan 430010, Peoples R China.
通讯机构：
[Tian, LL ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan 430079, Peoples R China.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
value realization of ecological products;capital circulation theory;path research;Zhengjiabang village
摘要：
Transforming ecological products into sources of economic value can help mitigate the tension between environmental conservation and economic growth. Using the capital cycle theory and the unique qualities of eco-friendly items, this study utilizes a case study approach, focusing on Zhengjiabang Village located in Changyang, Hubei Province. Meanwhile, we build a value realization chain of ecological products by combining the practical process of the village. On this basis, we reveal the roles of each subject and object in the evolutionary process, from ecological resources to ecological products. We also identify the key issues of eco-industrial expansion and spatial evolution. Taking the industrialization of ecological capital as the key, we add a step of value feedback to create a cycle of ecological product value realization and strengthen the sustainability of capital and industry. Ultimately, we aim to promote the transformation of ecological environmental advantages into economic advantages, and provide a new concept able to promote the construction of endogenous mechanisms for realizing the value of ecological products in rural areas.
