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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 , 16 (2) : 291-306 . |
| MLA | Wang, Qianfeng et al. "Global Climate Change Exacerbates Socioeconomic Drought Severity Across Vegetation Zones During 1901-2018" . | INTERNATIONAL JOURNAL OF DISASTER RISK SCIENCE 16 . 2 (2025) : 291-306 . |
| 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 , 16 (2) , 291-306 . |
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Extreme weather events are occurring more frequently and becoming increasingly unpredictable amid climate change. Low-temperature events (LTEs), in particular, exhibit dynamic variations across different regions and environments. Using a single threshold to define LTEs can be limiting, so this study considered nine distinct LTE types, characterized by varying consecutive day counts and percentile thresholds, to uncover their spatiotemporal patterns and dynamics. Furthermore, the correlation between LTEs and climate factors is assessed across distinct climatic regions in China. The results reveal that: the spatial distribution and overall dynamics of different LTEs are largely consistent, with higher frequency and longer duration observed in the Xinjiang region; the frequency and duration of various LTEs exhibit a declining trend across most regions, and minimum temperatures during LTEs demonstrate a decreasing trend in arid regions, juxtaposed with an increasing trend observed in cold zones. The threshold definition method using minimum temperatures below the 10th percentile for at least three consecutive days best characterizes LTEs in China. Additionally, LTEs show a strong correlation with longwave radiation. This study offers valuable quantitative insights for managing and responding to extreme weather events in the context of climate change.
Keyword ：
Climate change Climate change Climate factors Climate factors Longwave radiation Longwave radiation Low temperature events Low temperature events Minimum temperature Minimum temperature
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| GB/T 7714 | Chen, Huixia , Qiu, Han , Bento, Virgilio A. et al. Representing low temperature events and uncovering their dynamics in China between 1979 and 2018 amid climate change [J]. | CLIMATE DYNAMICS , 2025 , 63 (2) . |
| MLA | Chen, Huixia et al. "Representing low temperature events and uncovering their dynamics in China between 1979 and 2018 amid climate change" . | CLIMATE DYNAMICS 63 . 2 (2025) . |
| APA | Chen, Huixia , Qiu, Han , Bento, Virgilio A. , Wang, Qianfeng . Representing low temperature events and uncovering their dynamics in China between 1979 and 2018 amid climate change . | CLIMATE DYNAMICS , 2025 , 63 (2) . |
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Dust aerosols significantly impact climate, human health, and ecosystems, but how land cover changes (LCC) influence dust concentrations remains unclear. Here, we applied the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to assess the effects of LCC on dust aerosol concentrations from 2000 to 2020 in northern China. Based on land cover data derived from multi-source satellite remote sensing data, we conducted two simulation scenarios: one incorporating actual annual LCC and another assuming static land cover since 2000. Results revealed that approximately 293,300 km2 of land underwent conversion over the past 20 years. LCC generally resulted in an average annual reduction of 5.70 mu g kg-1 (micrograms per kilogram of dry air) in dust aerosol concentrations. The most significant reduction occurred in winter, averaging 8.90 mu g kg-1, followed by spring (8.06 mu g kg-1), autumn (5.27 mu g kg-1), and summer (1.06 mu g kg-1). Converting bare land to forestland was most effective in reducing dust concentrations, followed by conversions to grassland and built-up areas. Conversely, conversions to bare land increased dust aerosol concentrations, especially when forestland or cultivated land was transformed into bare land. These results emphasize the importance of targeted land use strategies to mitigate the adverse environmental and health effects of dust aerosols.
Keyword ：
Air pollution Air pollution Dust concentrations Dust concentrations Dust emissions Dust emissions Land use change Land use change WRF-Chem WRF-Chem
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| GB/T 7714 | Liu, Xian , Min, Ruiqi , Zhang, Haopeng et al. Land cover changes reduce dust aerosol concentrations in Northern China (2000-2020) [J]. | ENVIRONMENTAL RESEARCH , 2025 , 268 . |
| MLA | Liu, Xian et al. "Land cover changes reduce dust aerosol concentrations in Northern China (2000-2020)" . | ENVIRONMENTAL RESEARCH 268 (2025) . |
| APA | Liu, Xian , Min, Ruiqi , Zhang, Haopeng , Wang, Qianfeng , Song, Hongquan . Land cover changes reduce dust aerosol concentrations in Northern China (2000-2020) . | ENVIRONMENTAL RESEARCH , 2025 , 268 . |
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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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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 crises. Amid the different environmental predictors, soil moisture (SM) is an important agricultural drought indicator. However, current operational microwave SM products have generally low spatial resolution, challenging the effective characterization of SM spatial heterogeneity. In this study, empowered by the hourly land surface temperature (LST) observations from geostationary operational environmental satellites (GOES), we first spatially-downscale SM using machine learning (ML) algorithms. Then, by designing three sets of experiment respectively using downscaled SM, coarse-resolution SM, and precipitation observation, we assess the comparative performance of downscaled SM among its counterparts in estimating crop yield variability, based on three mainstream ML 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 out performs coarse-resolution SM and precipitation products, with the average R-2 between the crop yield estimates and the yield records being 0.814, 0.809, and 0.805, respectively. In addition, we find that among the five algorithms, the nonlinear ML algorithms exceed the linear algorithms in crop yield estimation, with the average R-2 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.
Keyword ：
Data models Data models Land surface temperature Land surface temperature Land surface temperature (LST) Land surface temperature (LST) Machine learning algorithms Machine learning algorithms machine learning (ML) machine learning (ML) Predictive models Predictive models Soil moisture Soil moisture soil moisture (SM) downscaling soil moisture (SM) 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, Ruiwen , Xin, Qinchuan , Qiu, Jianxiu et al. High Spatial Resolution Soil Moisture Improves Crop Yield Estimation [J]. | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2024 , 17 : 19067-19077 . |
| MLA | Mai, Ruiwen et al. "High Spatial Resolution Soil Moisture Improves Crop Yield Estimation" . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 17 (2024) : 19067-19077 . |
| APA | Mai, Ruiwen , Xin, Qinchuan , Qiu, Jianxiu , Wang, Qianfeng , Zhu, Peng . High Spatial Resolution Soil Moisture Improves Crop Yield Estimation . | IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING , 2024 , 17 , 19067-19077 . |
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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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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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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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As global climate change intensifies and population growth continues, water scarcity has emerged as a critical constraint to sustainable agricultural development. Conservation management, an effective water-saving technique, plays a crucial role in enhancing soil water content (SWC) and promoting sustainable agriculture. This study utilizes CiteSpace to perform a bibliometric analysis of research literature on the effects of conservation management on SWC, encompassing publications indexed in the Web of Science database from 1992 to 2024. By systematically examining 599 papers, we analyzed key research institutions, authors' collaborative contributions, keyword co-occurrences, and shifts in research hotspots related to conservation management and its impact on SWC. The results reveal that significant topics in this field include "conservation agriculture", "water use efficiency", and "conservation tillage". China (225, 38%) and the United States (129, 22%) lead in publication volume, whereas European countries and institutions show a higher degree of collaboration. The research focus has transitioned from examining the impacts and mechanisms of conservation tillage on crop yield and soil physical and chemical properties to long-term monitoring, water use efficiency, and mitigation. Furthermore, keyword co-occurrence and temporal analysis highlight a growing emphasis on soil quality and greenhouse gas emissions. In the future, it remains imperative to enhance the implementation of automated monitoring systems, secure long-term continuous monitoring data, promote conservation agriculture technology, and bolster the early warning network for extreme climate events. These measures are crucial for preserving soil nutrient levels and ensuring the sustainable development of agriculture.
Keyword ：
network analysis network analysis publication analysis publication analysis soil moisture soil moisture sustainable agriculture sustainable agriculture
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| GB/T 7714 | Du, Can , Wu, Yuexi , Ma, Limei et al. Bibliometric Analysis of Research on the Effects of Conservation Management on Soil Water Content Using CiteSpace [J]. | WATER , 2024 , 16 (23) . |
| MLA | Du, Can et al. "Bibliometric Analysis of Research on the Effects of Conservation Management on Soil Water Content Using CiteSpace" . | WATER 16 . 23 (2024) . |
| APA | Du, Can , Wu, Yuexi , Ma, Limei , Lei, Dong , Yuan, Yin , Ren, Xiaohua et al. Bibliometric Analysis of Research on the Effects of Conservation Management on Soil Water Content Using CiteSpace . | WATER , 2024 , 16 (23) . |
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