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.
期刊：
IEEE Transactions on Geoscience and Remote Sensing,2023年61:1-14 ISSN：0196-2892
作者机构：
[Xu, Baodong; Zhang, Zhewei; Wei, Haodong; Yang, Jingya; Cai, Zhiwen] Huazhong Agr Univ, Coll Resources & Environm, Macro Agr Res Inst, Wuhan 430070, Peoples R China.;[Wang, Cong] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat Hubei Prov, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Zhao, Jing; Li, Jing] Chinese Acad Sci, Jointly Sponsored Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.;[Zhao, Jing; Li, Jing] Beijing Normal Univ, Beijing 100101, Peoples R China.;[Qu, Yonghua] Beijing Normal Univ, Fac Geog Sci, Inst Remote Sensing Sci & Engn, State Key Lab Remote Sensing Sci,Beijing Key Lab, Beijing 100875, Peoples R China.
关键词：
Gaofen satellites;high spatiotemporal resolution;LAINet;leaf area index (LAI);time-series reconstruction
摘要：
High spatiotemporal resolution time series of leaf area index (LAI) are essential for monitoring crop dynamics and validating coarse-resolution LAI products. The optical satellite sensors at decametric resolution have historically suffered from a long revisit cycle and cloud contamination issues that hampered the acquisition of frequent and high-quality observations. The 16-m/four-day resolution of the new-generation Gaofen-1 (GF-1) and Gaofen-6 (GF-6) satellites provide an unprecedented opportunity to address these limitations. Here, we developed an effective strategy to generate daily 16-m LAI maps combining GF-1/6 data and ground LAINet measurements. All high-quality GF-1/6 observations were utilized first to derive smoothed time series of vegetation indices (VIs). Second, a random forest regression (RF-r) model was trained to link the VIs with corresponding field LAI measurements. The trained RF-r was finally employed to generate the LAI maps. Results demonstrated the reliability of the reconstructed daily VIs (relative error (RE) < 1%) and the derived LAI time series, which greatly benefited from GF-1/6 high-frequency observations. The direct comparison with field LAI measurements by LAI-2200/LI-3000 showed the good performance of retrieved LAI maps, with bias, root mean square error (RMSE), and $R^{\mathbf {2}}$ of 0.05, 0.59, and 0.75, respectively. The LAI time series well captured the spatiotemporal variation of crop growth. Furthermore, the continuous GF-1/6 LAI maps outperformed Sentinel-2 LAI estimates both in terms of temporal frequency and accuracy. Our study indicates the potential of GF-1/6 to generate continuous decametric-resolution LAI maps for fine-scale agricultural monitoring.
期刊：
Journal of Soil Science and Plant Nutrition,2023年23(4):6813-6826 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：
[Zheng, Wensheng; Xiong, Yajun; Wang, Xuzheng; Wang, Xiaofang; Zhou, Ying] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Zheng, Wensheng; Wang, Xiaofang] China Tourism Acad, Wuhan Branch, Wuhan 430079, Peoples R China.;[Zheng, Wensheng] Cent China Normal Univ, Hubei High qual Dev Inst, Wuhan 430079, Peoples R China.
通讯机构：
[Wensheng Zheng] C;College of Urban and Environment Science, Central China Normal University, Wuhan, China<&wdkj&>Wuhan Branch of China Tourism Academy, Wuhan, China<&wdkj&>Hubei High-quality Development Institute, Central China Normal University, Wuhan, China
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
作者：
Zheng, Jiangpeng;Huang, Zhou;Zhou, Xiao;Scheuer, Bronte;Wang, Han
期刊：
Sustainable Cities and Society,2023年99:104976 ISSN：2210-6707
通讯作者：
Huang, Z
作者机构：
[Huang, Zhou; Zheng, Jiangpeng; Huang, Z; Scheuer, Bronte] Peking Univ, Inst Remote Sensing & Geog Informat Syst, Sch Earth & Space Sci, Beijing 100871, Peoples R China.;[Huang, Zhou; Zheng, Jiangpeng; Scheuer, Bronte] Peking Univ, Beijing Key Lab Spatial Informat Integrat & Its Ap, Beijing 100871, Peoples R China.;[Zhou, Xiao] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.;[Wang, Han] Univ Hong Kong, Fac Architecture, Div Landscape Architecture, Future Urban & Sustainable Environm FUSE Lab, Hong Kong, Peoples R China.
通讯机构：
[Huang, Z ] P;Peking Univ, Inst Remote Sensing & Geog Informat Syst, Sch Earth & Space Sci, Beijing 100871, Peoples R China.
关键词：
CO2 emissions;Bus smart card;Spatiotemporal characteristics;Per person-kilometer;Emission reduction potential
摘要：
Human activities, primarily carbon dioxide emissions, have undeniably caused global warming. The transportation sector contributes about a quarter of global CO2 emissions. While replacing traditional buses with electric ones has reduced emissions, it is crucial to consider the indirect emissions resulting from electricity consumption. This study proposes a framework for modeling bus emissions using smart card data, integrating spatiotemporal distribution characteristics and emission reduction potentials. Our analysis reveals that routes spanning 10-30 km contribute to 81% of total bus emissions, with an average emission rate of 56.2 gCO2/per-km for residents traveling by bus. Bus emissions also exhibit cyclical variations during holidays, weekdays, and weekends, indicating spatial clustering and trends. Although the area within Beijing's 4th Ring Road constitutes only 13% of the total area within the 6th Ring Road, it generates almost half of the CO2 emissions. With urban expansion, total bus emissions increase gradually, but emission intensity decreases. This study emphasizes the potential for reducing emissions through improved public transportation operations. It recommends fully electrifying the bus fleet and employing low grid emission factors, which could reduce emissions by up to 71% compared to diesel options. Electrification of buses and optimizing power generation on the grid are essential priorities for emission reduction.
作者：
Wu, Tieniu;Cheng, Antai;Lin, Henry;Zhang, Hailin;Jie, Yi
期刊：
地球科学学刊,2023年34(5):1556-1566 ISSN：1674-487X
通讯作者：
Wu, TN
作者机构：
[Cheng, Antai; Wu, Tieniu; Jie, Yi; Zhang, Hailin] Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei Province, Peoples R China.;[Lin, Henry; Wu, Tieniu] Penn State Univ, Dept Ecosyst Sci & Management, University Pk, PA 16802 USA.;[Cheng, Antai; Wu, Tieniu; Jie, Yi; Zhang, Hailin] Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Wu, TN ] C;Cent China Normal Univ, Key Lab Geog Proc Anal & Simulat, Wuhan 430079, Hubei Province, Peoples R China.;Penn State Univ, Dept Ecosyst Sci & Management, University Pk, PA 16802 USA.;Cent China Normal Univ, Coll Urban & Environm Sci, Wuhan 430079, Peoples R China.
关键词：
MIS 9;climatic fluctuation;Paleosol;S3;Chinese Loess Plateau;environmental geology
摘要：
Marine Isotope Stages (MIS) 9 has been proposed as an analog for the present warm period. However, detailed studies of this geological time period are rare in loess-paleosol sequence. In the Chinese Loess Plateau (CLP), the corresponding stratum is the third paleosol layer (S3). Here, we report the terrestrial reconstruction of climatic fluctuations during MIS 9 by analyzing the paleo-climate indexes of S3 with high sampling density. Our results showed that: (1) During the period of MIS 9, the main climatic sub-cycle was 29 ka; (2) MIS 9 could be divided into five sections, MIS 9a, 9b, 9c, 9d, and 9e. Among them, MIS 9a, 9c, and 9e were warm stages, while MIS 9b and 9d were cool intervals; and 3) There were also three swift warm-wet events and one cool-dry event, which occurred around 332-331, 324-323, 311-310, and 331-329 ka BP, respectively. The overall trend of paleo-climate fluctuation correlated approximately with SPECMAP, LR04 stack and Iberian margin deep-sea cores. This study suggested that the paleosol records in the southern margin of the CLP have global significance and contain more detailed climatic signals than marine deposits.
期刊：
Pest Management Science,2023年79(7):2591-2602 ISSN：1526-498X
通讯作者：
Ran Meng<&wdkj&>Ran Meng Ran Meng Ran Meng
作者机构：
[Meng, Ran; Lv, Zhengang; Zhou, Longfei; Xu, Binyuan; Sun, Rui] Huazhong Agr Univ, Coll Resources & Environm, Wuhan, Peoples R China.;[Meng, Ran] HIT Inst Artificial Intelligence Co Ltd, Harbin, Peoples R China.;[Yang, Wanneng; Chen, Gengshen] Huazhong Agr Univ, Natl Ctr Plant Gene Res Wuhan, Natl Key Lab Crop Genet Improvement, Hubei Hongshan Lab, Wuhan, Peoples R China.;[Liang, Linlin] Chinese Acad Sci, Aerosp Informat Res Inst, Beijing, Peoples R China.;[Zhao, Feng] Cent China Normal Univ, Coll Urban & Environm Sci, Key Lab Geog Proc Anal & Simulat Hubei Prov, Wuhan, Peoples R China.
通讯机构：
[Ran Meng; Ran Meng Ran Meng Ran Meng] C;College of Resources and Environment, Huazhong Agricultural University, Wuhan, China<&wdkj&>HIT Institute for Artificial Intelligence Co. Ltd, Harbin, China
