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学者姓名：王前锋
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This study evaluates the comparative performance of spatiotemporal fusion and time-series fitting methods for constructing high-spatiotemporal-resolution remote sensing time-series data. Due to in-class similarity of fusion methods and fitting methods, we employ the Fit-FC (Fitting, spatial Filtering, and residual Compensation) model as a representative fusion method and the linear harmonic fitting model as a representative fitting method. Both Fit-FC and the linear harmonic fitting are widely used for high-spatiotemporal-resolution time-series data construction, and we modify the original Fit-FC model to enable automatic time-series fusion. To ensure data representativeness, we use 3 years (2019-2021) of Harmonized Landsat and Sentinel-2 surface reflectance datasets and Terra MCD43A4 products. Eight experimental regions are selected worldwide to guarantee generalization of the comparative performance between fusion and fitting methods, covering diverse land-use types (cropland, developed land, forest, and grassland) and varying climatological conditions. Time-series of NDVI and surface reflectance are analyzed under both actual observations and simulated data-missing scenarios. The constructed time-series data reveals that (1) the modified Fit-FC and linear harmonic fitting model achieve excellent performance in constructing high-resolution time-series images; (2) the fusion method outperforms the fitting method in constructing time-series of NDVI and surface reflectance images in cropland-, forest-, and grassland-dominated regions; (3) both methods achieve comparable performance in developed-dominated regions; (4) the fusion method is more robust to missing data, and better captures abrupt phenological transitions under conditions of continuous missing data; (5) the fitting method is computationally more efficient, making it suitable for large-scale time-series image reconstruction. This study provides valuable insights for selecting optimal strategies to generate high-resolution time-series images across diverse application scenarios and lays a foundation for extensions to other vegetation indices or land surface variables.
Keyword ：
harmonic fitting harmonic fitting remote sensing data remote sensing data Spatiotemporal fusion Spatiotemporal fusion time series construction time series construction
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| GB/T 7714 | Tang, Jia , Bento, Virgilio A. , Hao, Dalei et al. Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations [J]. | GISCIENCE & REMOTE SENSING , 2025 , 62 (1) . |
| MLA | Tang, Jia et al. "Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations" . | GISCIENCE & REMOTE SENSING 62 . 1 (2025) . |
| APA | Tang, Jia , Bento, Virgilio A. , Hao, Dalei , Zeng, Yelu , Guo, Pengcheng , Chen, Yu et al. Assessing methods in fusion and fitting for time series construction in remote sensing-based earth observations . | GISCIENCE & REMOTE SENSING , 2025 , 62 (1) . |
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Drought is one of the most complicated natural hazards and is among those that pose the greatest socioeconomic risks. How long-term climate change on a large scale affects different types of drought has not been well understood. This study aimed to enhance comprehension of this critical issue by integrating the run theory for drought identification, Mann-Kendall trend analysis, and partial correlation attribution methods to analyze global drought dynamics in 1901-2018. Methodological innovations include: (1) a standardized drought severity metric enabling cross-typology comparisons; and (2) quantitative separation of precipitation and temperature impacts. Key findings reveal that socioeconomic drought severity exceeded meteorological, agricultural, and hydrological droughts by 350.48%, 47.80%, and 14.40%, respectively. Temporal analysis of Standardized Precipitation Evapotranspiration Index (SPEI) trends demonstrated intensification gradients: SPEI24 (- 0.09 slope/100 yr) > SPEI01 (- 0.088/100 yr) > SPEI06 (- 0.087/100 yr) > SPEI12 (- 0.086/100 yr). Climate drivers exhibited distinct patterns, with precipitation showing stronger partial correlations across all drought types (meteorological: 0.78; agricultural: 0.76; hydrological: 0.60; socioeconomic: 0.39) compared to temperature (meteorological: - 0.45; agricultural: - 0.38; hydrological: - 0.27; socioeconomic: - 0.18). These results quantitatively establish a hierarchical climate response gradient among drought types. The framework advances drought typology theory through three original contributions: (1) systematic quantification of cross-typology drought severity disparities; (2) precipitation-temperature influence partitioning across drought types; and (3) identification of socioeconomic drought as the most climate-decoupled yet fastest-intensifying type. This study refined drought typological theories and provides a methodological foundation for climate-resilient drought management planning.
Keyword ：
Climate change Climate change Drought severity Drought severity Global scale Global scale Multi-type drought Multi-type drought Various vegetation zones Various vegetation zones
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| GB/T 7714 | Wang, Qianfeng , Yang, Xiaofan , Qu, Yanping et al. Global Climate Change Exacerbates Socioeconomic Drought Severity Across Vegetation Zones During 1901-2018 [J]. | INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE , 2025 . |
| MLA | Wang, Qianfeng et al. "Global Climate Change Exacerbates Socioeconomic Drought Severity Across Vegetation Zones During 1901-2018" . | INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE (2025) . |
| APA | Wang, Qianfeng , Yang, Xiaofan , Qu, Yanping , Qiu, Han , Wu, Yiping , Qi, Junyu et al. Global Climate Change Exacerbates Socioeconomic Drought Severity Across Vegetation Zones During 1901-2018 . | INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE , 2025 . |
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Land use and land cover change (LUCC) can alter surface properties, such as albedo, roughness, and vegetation coverage, directly affecting dust emissions and aerosol concentrations, leading to variations in direct radiative forcing (DRF) of dust aerosols and consequently impacting the climate. This study utilized the Weather Research and Forecasting model with Chemistry (WRF-Chem) to quantify the impact of LUCC in northern China from 2000 to 2020 on dust aerosol DRF. Results indicated that LUCC's influence on shortwave radiative forcing of dust was significantly greater than its influence on longwave radiative forcing and exhibited obvious seasonal variations. Overall, LUCC can cause net direct radiative forcing to increase by 5.3 W m−2 at the surface and decrease by 7.8 W m−2 in the atmosphere. Different types of LUCC transformation showed distinct impacts on dust aerosol DRF, with the conversion from sparse vegetation to barren land had the most significant effect on net radiative intensity, resulting in a decrease of 8.1 W m−2 at the surface, an increase of 12.2 W m−2 in the atmosphere, and an increase of 4.1 W m−2 at the top of the atmosphere. Conversely, the conversion from barren land to sparse vegetation led to surface cooling and atmospheric warming. These findings are of great significance for enhancing our knowledge of the effects of LUCC on the radiative balance of dust aerosols. © 2024 Elsevier Ltd
Keyword ：
China China Climate Climate Direct radiative forcing Direct radiative forcing Dust aerosol Dust aerosol LUCC LUCC WRF-Chem WRF-Chem
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| GB/T 7714 | Wang, W. , Song, H. , Min, R. et al. LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China [J]. | Journal of Environmental Management , 2024 , 368 . |
| MLA | Wang, W. et al. "LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China" . | Journal of Environmental Management 368 (2024) . |
| APA | Wang, W. , Song, H. , Min, R. , Wang, Q. , Qi, M. . LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China . | Journal of Environmental Management , 2024 , 368 . |
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The global food supply system is under increasing pressure due to population growth and more extreme climate events. Developing forecast models for accurate prediction of crop yields is helpful for early warning of food crise. Amid the different environmental predictors, soil moisture (SM) information is an important agricultural drought indictor, but the operational microwave SM products have generally low spatial resolution, challenging the effective characterization of the spatial heterogeneity in SM. In this study, empowered by the ability of hourly land surface temperature (LST) from Geostationary Operational Environmental Satellites (GOES) to inform moisture status, we firstly downscaled SM data using machine learning algorithms. Then, by designing three sets of experiment configurations using either downscaled SM, coarse-resolution SM, or precipitation observation, we assess the performance of downscaled SM in estimating crop yields variability using three mainstream machine learning algorithms and two traditional regression algorithms. Our research shows that downscaled SM based on high temporal resolution GOES-LST demonstrates outstanding performance in characterizing the spatial variation of SM. With respect to yield estimation, downscaled high-resolution SM outperformed coarse-resolution SM and precipitation products, with the average R2 between the estimated crop yields and the yield records being 0.814, 0.809, and 0.805, respectively. In addition, we find that among the five algorithms, the non-linear machine learning algorithms exceed the linear algorithms, with the average R2 being 0.827 and 0.783, respectively. Our research demonstrates the great potential of infusing different satellite information to improve the monitoring of crop growing status and yield prediction. Authors
Keyword ：
Data models Data models land surface temperature land surface temperature Land surface temperature Land surface temperature machine learning machine learning Machine learning algorithms Machine learning algorithms Predictive models Predictive models Soil moisture Soil moisture Soil moisture downscaling Soil moisture downscaling Spatial resolution Spatial resolution Switched mode power supplies Switched mode power supplies yield estimation yield estimation
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| GB/T 7714 | Mai, R. , Xin, Q. , Qiu, J. et al. High spatial resolution soil moisture improves crop yield estimation in the midwestern United States [J]. | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 2024 , 17 : 1-12 . |
| MLA | Mai, R. et al. "High spatial resolution soil moisture improves crop yield estimation in the midwestern United States" . | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 17 (2024) : 1-12 . |
| APA | Mai, R. , Xin, Q. , Qiu, J. , Wang, Q. , Zhu, P. . High spatial resolution soil moisture improves crop yield estimation in the midwestern United States . | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing , 2024 , 17 , 1-12 . |
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Land use and land cover change (LUCC) can alter surface properties, such as albedo, roughness, and vegetation coverage, directly affecting dust emissions and aerosol concentrations, leading to variations in direct radiative forcing (DRF) of dust aerosols and consequently impacting the climate. This study utilized the Weather Research and Forecasting model with Chemistry (WRF-Chem) to quantify the impact of LUCC in northern China from 2000 to 2020 on dust aerosol DRF. Results indicated that LUCC's influence on shortwave radiative forcing of dust was significantly greater than its influence on longwave radiative forcing and exhibited obvious seasonal variations. Overall, LUCC can cause net direct radiative forcing to increase by 5.3 W m- 2 at the surface and decrease by 7.8 W m- 2 in the atmosphere. Different types of LUCC transformation showed distinct impacts on dust aerosol DRF, with the conversion from sparse vegetation to barren land had the most significant effect on net radiative intensity, resulting in a decrease of 8.1 W m- 2 at the surface, an increase of 12.2 W m- 2 in the atmosphere, and an increase of 4.1 W m- 2 at the top of the atmosphere. Conversely, the conversion from barren land to sparse vegetation led to surface cooling and atmospheric warming. These findings are of great significance for enhancing our knowledge of the effects of LUCC on the radiative balance of dust aerosols.
Keyword ：
China China Climate Climate Direct radiative forcing Direct radiative forcing Dust aerosol Dust aerosol LUCC LUCC WRF-Chem WRF-Chem
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| GB/T 7714 | Wang, Weijiao , Song, Hongquan , Min, Ruiqi et al. LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China [J]. | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 368 . |
| MLA | Wang, Weijiao et al. "LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China" . | JOURNAL OF ENVIRONMENTAL MANAGEMENT 368 (2024) . |
| APA | Wang, Weijiao , Song, Hongquan , Min, Ruiqi , Wang, Qianfeng , Qi, Minghui . LUCC-induced dust aerosol change increase surface and reduce atmospheric direct radiative forcing in Northern China . | JOURNAL OF ENVIRONMENTAL MANAGEMENT , 2024 , 368 . |
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Study region: Hanjiang River Basin, China Study focus: Under the joint influences of human activities and climate change, droughts frequently occur in the Hanjiang River Basin (HRB). Quantifying the driving forces contribution on hydrological drought is crucial to enhance the early warning ability. This study employed the standardized streamflow index (SSI) to assess hydrological drought. The Soil and Water Assessment Tool (SWAT) model was utilized to reconstruct natural streamflow based on hydrological and meteorological data. By comparing the variations of drought characteristics in simulated and observed scenarios, the impacts of human activities and climate change to hydrological drought were quantified. New hydrological insights for the study region: The SWAT model is capable of effectively simulating the natural streamflow conditions of the HRB with NSE>0.7, R2>0.8, logNSE>0.7 and |PBIAS|< 20 %. Hydrological drought has intensified as a prolonged duration and greater severity affected by human activities and climate change. During the whole impact period (1968-2022), the duration and severity increased by 66.22 % and 81.16 % compared to baseline period (1956-1967). The year 1991 is detected as the mutation point. From 1968-1990 climate change has been the main factor in exacerbating hydrological drought. Since 1991, the influence of human activities has gradually exceeded the influence of climate change. These findings provide valuable insights for watershed integrated water resources management and water security.
Keyword ：
Attribution analysis Attribution analysis Hydrological drought Hydrological drought SWAT model SWAT model The Hanjiang River The Hanjiang River
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| GB/T 7714 | Li, Cheng , Qu, Yanping , Jiang, Tianliang et al. Attribution analysis of hydrological drought after the impoundment of the Danjiangkou reservoir in the Hanjiang River Basin [J]. | JOURNAL OF HYDROLOGY-REGIONAL STUDIES , 2024 , 56 . |
| MLA | Li, Cheng et al. "Attribution analysis of hydrological drought after the impoundment of the Danjiangkou reservoir in the Hanjiang River Basin" . | JOURNAL OF HYDROLOGY-REGIONAL STUDIES 56 (2024) . |
| APA | Li, Cheng , Qu, Yanping , Jiang, Tianliang , Jiang, Furen , Wang, Qianfeng , Zhang, Xuejun et al. Attribution analysis of hydrological drought after the impoundment of the Danjiangkou reservoir in the Hanjiang River Basin . | JOURNAL OF HYDROLOGY-REGIONAL STUDIES , 2024 , 56 . |
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植被物候直接影响其生物量，调控生态系统碳循环过程。目前，气候变化(尤其干旱)对中国中高纬度植被物候的影响依然不清楚。因此，文章基于GIMMS NDVI3g数据集，提取中国30°N以北地区中多种植被类型生长季的开始日期(Start of the Season, SOS)与结束日期(End of the Season, EOS)两物候参数。然后结合野外观测数据，验证提取物候参数结果可靠性，并结合饱和水汽压差(Vapor Pressure Deficit, VPD)与改进后的标准化降水蒸散指数(Standardized Precipitation Evapotranspiration Index, SPEI)探究植被物候对干旱的响应特征规律。结果表明：(1)不同地区的植被物候变化呈现明显的差异性，单季植被与双季植被第1个生长季的SOS集中在每年的第30～180天，而双季植被第2个生长季的SOS集中在每年的第200～220天。单季植被与双季植被第1个生长季的EOS主要集中在每年的第180～300天，双季植被第2个生长季的EOS主要集中在每年的第260～300天。(2)森林季前VPD的上升导致植被的SOS提前及EOS延迟；草地季前VPD上升导致植被的SOS滞后以及EOS提前。(3)研究区内大部分地区的SPEI与植被的SOS、EOS均呈正相关，即干旱促使该地区植被的SOS、EOS提前。
Keyword ：
标准化降水蒸散发指数 标准化降水蒸散发指数 植物生长季开始日期 植物生长季开始日期 植物生长季结束日期 植物生长季结束日期 植被物候 植被物候 饱和水汽压差 饱和水汽压差
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| GB/T 7714 | 王前锋 , 陆锦阔 , 张容容 . 中国中高纬地区植被物候对干旱的响应特征研究 [J]. | 华南师范大学学报(自然科学版) , 2024 , 56 (03) : 70-79 . |
| MLA | 王前锋 et al. "中国中高纬地区植被物候对干旱的响应特征研究" . | 华南师范大学学报(自然科学版) 56 . 03 (2024) : 70-79 . |
| APA | 王前锋 , 陆锦阔 , 张容容 . 中国中高纬地区植被物候对干旱的响应特征研究 . | 华南师范大学学报(自然科学版) , 2024 , 56 (03) , 70-79 . |
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Potential toxic metal (PTM) is hazardous to human health, but the mechanism of spatial heterogeneity of PTM at a macro-scale remains unclear. This study conducts a meta-analysis on the data of PTM concentrations in the soil of 164 major cities in China from 2006 to 2021. It utilizes spatial analysis methods and geodetector to investigate the spatial distribution characteristics of PTMs. The geographic information systems (GIS) and geodetector were used to investigate the spatial distribution characteristics of PTMs, assess the influence of natural factors (NFs) and anthropogenic factors (AFs) on the spatial heterogeneity of PTMs in urban soils, and identified the potential pollution areas of PTMs. The results indicated that the pollution levels of PTMs in urban soils varied significantly across China, with higher pollution levels in the south than in the north. Cd and Hg were the most severely contaminated elements. The geodetector analysis showed that temperature and precipitation in NFs and land use type in AFs were considered as the main influencing factors, and that both AF and NF together led to the PTM variation. All these factors showed a mutually enhancing pattern which has important implications for urban soil management. PTM high-risk areas were identified to provide early warning of pollution risk under the condition of climate change.
Keyword ：
Geodetector Geodetector High-risk areas High-risk areas Influencing factors Influencing factors Potential toxic metal Potential toxic metal Urban soil Urban soil
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| GB/T 7714 | Zeng, Yue , Liu, Xinyu , Li, Yunqin et al. Analysis of driving factors for potential toxic metals in major urban soils of China: a geodetetor-based quantitative study [J]. | ENVIRONMENTAL GEOCHEMISTRY AND HEALTH , 2024 , 46 (10) . |
| MLA | Zeng, Yue et al. "Analysis of driving factors for potential toxic metals in major urban soils of China: a geodetetor-based quantitative study" . | ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 46 . 10 (2024) . |
| APA | Zeng, Yue , Liu, Xinyu , Li, Yunqin , Jin, Zhifan , Shui, Wei , Wang, Qianfeng . Analysis of driving factors for potential toxic metals in major urban soils of China: a geodetetor-based quantitative study . | ENVIRONMENTAL GEOCHEMISTRY AND HEALTH , 2024 , 46 (10) . |
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The Yellow River basin of China has experienced significant land use and land cover change (LUCC) due to excessive exploitation of nature resources, ecological degradation, and rapid urbanization, which plays an important role in the regional climate. It is crucial to explore the climate patterns of the basin under different future development scenarios to mitigate climate issues and achieve "carbon peaking and carbon neutrality goals ". Here we utilized land use and land cover (LULC) data and projections of future climate under two shared socioeconomic path - representative concentration path (SSP245 and SSP585) scenarios. Using the Weather Research and Forecasting (WRF) model, we simulated four future spatial variation patterns of temperature and precipitation in the basin. Results indicated that under the SSP245 and SSP585 scenarios, the temperature is projected to increase by 0.18 degrees C and 0.46 degrees C, respectively, while precipitation is expected to rise by 32.21 mm and 134.24 mm, respectively. The impact of LUCC was found to be relatively minor and mainly concentrated in the middle reaches of the basin. It resulted in a slight increase in temperature in both scenarios and an increase in precipitation in SSP245, but a decrease in precipitation in SSP585. Changes in farmland and urban area exhibited a certain warming effect in both scenarios, with urban areas having a greater influence, leading to a temperature increase by 0.25 degrees C and 0.28 degrees C, respectively. Forest, grassland, and bare areas had a lesser impact on temperature and showed different trends under two scenarios. Regarding precipitation, forests and urban areas had a greater influence in both SSP245 and SSP585 scenarios. This study identified the significant role of LUCC under different development scenarios in shaping future temperature and precipitation changes, providing valuable insights for effectively addressing climate issues in the Yellow River basin. It also highlights the need for clear policy recommendations and identifies institutions or agencies responsible for implementing such recommendations.
Keyword ：
Climate change Climate change Land use and land cover Land use and land cover SSP-RCPs SSP-RCPs WRF WRF Yellow River basin Yellow River basin
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| GB/T 7714 | Ru, Xutong , Qiao, Longxin , Zhang, Haopeng et al. Effects of land use and land cover change under shared socioeconomic pathways on future climate in the Yellow River basin, China [J]. | URBAN CLIMATE , 2024 , 55 . |
| MLA | Ru, Xutong et al. "Effects of land use and land cover change under shared socioeconomic pathways on future climate in the Yellow River basin, China" . | URBAN CLIMATE 55 (2024) . |
| APA | Ru, Xutong , Qiao, Longxin , Zhang, Haopeng , Bai, Tianqi , Min, Ruiqi , Wang, Yaobin et al. Effects of land use and land cover change under shared socioeconomic pathways on future climate in the Yellow River basin, China . | URBAN CLIMATE , 2024 , 55 . |
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Previous studies have primarily focused on the influence of temperature and precipitation on phenology. It is unclear if the easily ignored climate factors with drivers of vegetation growth can effect on vegetation phenology. In this research, we conducted an analysis of the start (SOS) and end (EOS) of the growing seasons in the northern region of China above 30 degrees N from 1982 to 2014, focusing on two-season vegetation phenology. We examined the response of vegetation phenology of different vegetation types to preseason climatic factors, including relative humidity (RH), shortwave radiation (SR), maximum temperature (Tmax), and minimum temperature (Tmin). Our findings reveal that the optimal preseason influencing vegetation phenology length fell within the range of 0-60 days in most areas. Specifically, SOS exhibited a significant negative correlation with Tmax and Tmin in 44.15% and 42.25% of the areas, respectively, while EOS displayed a significant negative correlation with SR in 49.03% of the areas. Additionally, we identified that RH emerged as the dominant climatic factor influencing the phenology of savanna (SA), whereas temperature strongly controlled the SOS of deciduous needleleaf forest (DNF) and deciduous broadleaf forest (DBF). Meanwhile, the EOS of DNF was primarily influenced by Tmax. In conclusion, this study provides valuable insights into how various vegetation types adapt to climate change, offering a scientific basis for implementing effective vegetation adaptation measures.
Keyword ：
Climate change Climate change Phenology Phenology Preseason Preseason Vegetation Vegetation
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| GB/T 7714 | Wang, Qianfeng , Chen, Huixia , Xu, Feng et al. Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes [J]. | SCIENTIFIC REPORTS , 2024 , 14 (1) . |
| MLA | Wang, Qianfeng et al. "Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes" . | SCIENTIFIC REPORTS 14 . 1 (2024) . |
| APA | Wang, Qianfeng , Chen, Huixia , Xu, Feng , Bento, Virgilio A. , Zhang, Rongrong , Wu, Xiaoping et al. Understanding vegetation phenology responses to easily ignored climate factors in china's mid-high latitudes . | SCIENTIFIC REPORTS , 2024 , 14 (1) . |
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