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| 1 | Altered trends in carbon uptake in China’s terrestrial ecosystems under the enhanced summer monsoon and warming hiatus显示文摘The carbon budgets in terrestrial ecosystems in China are strongly coupled with climate changes.Over the past decade,China has experienced dramatic climate changes characterized by enhanced summer monsoon and decelerated warming.However,the changes in the trends of terrestrial net ecosystem production(NEP)in China under climate changes are not well documented.Here,we used three ecosystem models to simulate the spatiotemporal variations in China's NEP during 1982–2010 and quantify the contribution of the strengthened summer monsoon and warming hiatus to the NEP variations in four distinct climatic regions of the country.Our results revealed a decadal-scale shift in NEP from a downtrend of–5.95 Tg C/yr^2(reduced sink)during 1982–2000 to an uptrend of 14.22 Tg C/yr^2(enhanced sink)during 2000–10.This shift was essentially induced by the strengthened summer monsoon,which stimulated carbon uptake,and the warming hiatus,which lessened the decrease in the NEP trend.Compared to the contribution of 56.3%by the climate effect,atmospheric CO2 concentration and nitrogen deposition had relatively small contributions(8.6 and 11.3%,respectively)to the shift.In conclusion,within the context of the global-warming hiatus,the strengthening of the summer monsoon is a critical climate factor that enhances carbon uptake in China due to the asymmetric response of photosynthesis and respiration.Our study not only revealed the shift in ecosystem carbon sequestration in China in recent decades,but also provides some insight for understanding ecosystem carbon dynamics in other monsoonal areas. | Honglin He Shaoqiang Wang Li Zhang Junbang Wang Xiaoli Ren Lei Zhou Shilong Piao Hao Yan Weimin Ju Fengxue Gu Shiyong Yu Yuanhe Yang Miaomiao Wang Zhongen Niu Rcmg Ge Huimin Yan Mei Huang Guoyi Zhou Yongfei Bai Zongqiang Xie Zhiyao Tang Bingfang Wu Leiming Zhang Nianpeng He Qiufeng Wang Guirui Yu | 2019 | National Science Review2019，6，3： | 24 |
| 2 | Assessment of soil erosion and sediment delivery ratio using remote sensing and GIS:a case study of upstream Chaobaihe River catchment, north China显示文摘Soil erosion in catchment areas reduces soil productivity and causes a loss of reservoir capacity.Several parametric models have been developed to predict soil erosion at drainage basins,hill slopes and field levels.The well-known Universal Soil Loss Equation(USLE) represents a standardized approach.Miyun reservoir,which sits on Chaobaihe River,is the main surface source of drinking water for Beijing,the capital of China.Water and soil loss are the main reasons for sediment to enter a reservoir.Sediment yield is assessed using a version of the universal soil loss equation modified by Chinese researchers.All year 2001 and 2002 data for factors in the equation are obtained from remote sensing or collected to form an analysis database.These factors are computed and mapped using Geographic Information System tools.Based on the complex database,the modified model is developed.Through pixel-based computing the sediment yield per hydrological unit is calculated.The model does not consider sediment deposition occurring on hillslopes.Gross soil loss is often higher than the sum of those measured at catchment outlets.The sediment delivery ratio(SDR) per hydrological unit is also computed.This study analyzes the main contributions of sediment yields on sub-basins of the Chaobaihe River to the Miyun Reservoir,and discusses the possible reasons for the difference between SDRs in 2001 and 2002 at different outlets.The result shows that in the upper basin of the Miyun Reservoir,in 2001 the area of erosion that could be neglected was 8,202.76 km2,the area of low erosion 3,269.59 km2,the area of moderate erosion 3,400.97 km2,the area of high erosion 436.89 km2,the area of strong erosion 52.19 km2 and the area of severe erosion 3.13 km2.The highest soil loss was 70,353 t/km2.yr in Fengning County in 2001,followed by 64,418 t/km2.yr by Chicheng County in 2001.The SDR in 2002 was lower than that in 2001.The main reasons are the decreasing rainfall erosivity and total runoff. | Weifeng ZHOU Bingfang WU | 2008 | International Journal of Sediment Research2008，23，2： | 13 |
| 3 | Cloud services with big data provide a solution for monitoring and tracking sustainable development goals显示文摘To achieve the Sustainable Development Goals(SDGs),high-quality data are needed to inform the formulation of policies and investment decisions,to monitor progress towards the SDGs and to evaluate the impacts of policies.However,the data landscape is changing.With emerging big data and cloud-based services,there are new opportunities for data collection,influencing both official data collection processes and the operation of the programmes they monitor.This paper uses cases and examples to explore the potential of crowdsourcing and public earth observation(EO)data products for monitoring and tracking the SDGs.This paper suggests that cloud-based services that integrate crowdsourcing and public EO data products provide cost-effective solutions for monitoring and tracking the SDGs,particularly for low-income countries.The paper also discusses the challenges of using cloud services and big data for SDG monitoring.Validation and quality control of public EO data is very important;otherwise,the user will be unable to assess the quality of the data or use it with confidence. | Bingfang Wu Fuyou Tian Miao Zhang Hongwei Zeng Yuan Zeng | 2020 | Geography and Sustainability2020，1，1： | 9 |
| 4 | Remote sensing based monitoring of interannual variations in vegetation activity in China from 1982 to 2009显示文摘Terrestrial vegetation is one of the most important components of the Earth's land surface. Variations in terrestrial vegetation directly impact the Earth system's balance of material and energy. This paper describes detected variations in vegetation activity at a national scale for China based on nearly 30 years of remote sensing data derived from NOAA/AVHRR(1982–2006) and MODIS(2001–2009). Vegetation activity is analyzed for four regions covering agriculture, forests, grasslands, and China's Northwest region with sparse vegetation cover(including regions without vegetation). Relationships between variations in vegetation activity and climate change as well as agricultural production are also explored. The results show that vegetation activity has generally increased across large areas, especially during the most recent decade. The variations in vegetation activity have been driven primarily by human factors, especially in the southern forest region and the Northwest region with sparse vegetation cover. The results further show that the variations in vegetation activity have influenced agricultural production, but with a certain time lag. | LI Fei ZENG Yuan LI XiaoSong ZHAO QianJun WU BingFang | 2014 | Science China Earth Sciences2014，57，8： | 8 |
| 5 | Remote sensing-based global crop monitoring: experiences with China’s CropWatch system显示文摘Monitoring the production of main agricultural crops is important to predict and prepare for disruptions in food supply and fluctuations in global crop market prices.China’s global crop-monitoring system(CropWatch)uses remote sensing data combined with selected field data to determine key crop production indicators:crop acreage,yield and production,crop condition,cropping intensity,crop-planting proportion,total food availability,and the status and severity of droughts.Results are combined to analyze the balance between supply and demand for various food crops and if needed provide early warning about possible food shortages.CropWatch data processing is highly automated and the resulting products provide new kinds of inputs for food security assessments.This paper presents a comprehensive overview of CropWatch as a remote sensingbased system,describing its structure,components,and monitoring approaches.The paper also presents examples of monitoring results and discusses the strengths and limitations of the CropWatch approach,as well as a comparison with other global crop-monitoring systems. | Bingfang Wu Jihua Meng Qiangzi Li Nana Yan Xin Du Miao Zhang | 2014 | International Journal of Digital Earth2014，7，2： | 6 |
| 6 | A Synthesizing Land-cover Classification Method Based on Google Earth Engine: A Case Study in Nzhelele and Levhuvu Catchments, South Africa显示文摘This study designed an approach to derive land-cover in the South Africa with insufficient ground samples, and made a case demonstration in Nzhelele and Levhuvu catchments, South Africa. The method was developed based on an integration of Landsat 8, Sentinel-1, and Shuttle Radar Topography Mission(SRTM) Digital Elevation Model(DEM), and the Google Earth Engine(GEE) platform. Random forest classifier with 300 trees is employed as land-cover classification model. In order to overcome the defect of insufficient ground data, the stratified sampling method was used to generate the training and validation samples from the existing land-cover product. Likewise, in order to recognize different land-cover categories, the percentile and monthly median composites were employed to expand input metrics of random forest classifier. Results showed that the overall accuracy of the land-cover of Nzhelele and Levhuvu catchments, South Africa in 2017–2018 reached to 76.43%. Three important results can be drawn from our research. 1) The participation of Sentinel-1 data can slightly improve overall accuracy of land-cover while its contribution on land-cover classification varied with land types. 2) Under-fitting problem was observed in the training of non-dominant land-cover categories using the random sampling, the stratified sampling method is recommended to make sure the classification accuracy of non-dominant classes. 3) When related reflectance bands participated in the training process, individual Normalized Difference Vegetation index(NDVI), Enhanced Vegetation Index(EVI), Soil Adjusted Vegetation Index(SAVI), Normalized Difference Built-up Index(NDBI) have little effect on final land-cover classification result. | ZENG Hongwei WU Bingfang WANG Shuai MUSAKWA Walter TIAN Fuyou MASHIMBYE Zama Eric POONA Nitesh SYNDEY Mavengahama | 2020 | Chinese Geographical Science2020，30，3： | 4 |
| 7 | Generation of high spatial and temporal resolution NDVI and its application in crop biomass estimation显示文摘While data like HJ-1 CCD images have advantageous spatial characteristics for describing crop properties,the temporal resolution of the data is rather low,which can be easily made worse by cloud contamination.In contrast,although Moderate Resolution Imaging Spectroradiometer(MODIS)can only achieve a spatial resolution of 250 m in its normalised difference vegetation index(NDVI)product,it has a high temporal resolution,covering the Earth up to multiple times per day.To combine the high spatial resolution and high temporal resolution of different data sources,a new method(Spatial and Temporal Adaptive Vegetation index Fusion Model[STAVFM])for blending NDVI of different spatial and temporal resolutions to produce high spatialtemporal resolution NDVI datasets was developed based on Spatial and Temporal Adaptive Reflectance Fusion Model(STARFM).STAVFM defines a time window according to the temporal variation of crops,takes crop phenophase into consideration and improves the temporal weighting algorithm.The result showed that the new method can combine the temporal information of MODIS NDVI and spatial difference information of HJ-1 CCD NDVI to generate an NDVI dataset with both high spatial and high temporal resolution.An application of the generated NDVI dataset in crop biomass estimation was provided.An average absolute error of 17.2%was achieved.The estimated winter wheat biomass correlated well with observed biomass(R^(2) of 0.876).We conclude that the new dataset will improve the application of crop biomass estimation by describing the crop biomass accumulation in detail.There is potential to apply the approach in many other studies,including crop production estimation,crop growth monitoring and agricultural ecosystem carbon cycle research,which will contribute to the implementation of Digital Earth by describing land surface processes in detail. | Jihua Meng Xin Du Bingfang Wu | 2013 | International Journal of Digital Earth2013，6，3： | 4 |
| 8 | Land Cover Changes and Drivers in the Water Source Area of the Middle Route of the South-to-North Water Diversion Project in China from 2000 to 2015显示文摘The Middle Route of the South-to-North Water Diversion Project(MR-SNWDP)in China,with construction beginning in 2003,diverts water from Danjiangkou Reservoir to North China for residential,agriculture and industrial use.The water source area of the MR-SNWDP is the region that is most sensitive to and most affected by the construction of this water diversion project.In this study,we used Landsat Thematic Mapper(TM)and HJ-1 A/B images from 2000 to 2015 by an object-based approach with a hierarchical classification method for mapping land cover in the water source area.The changes in land cover were illuminated by transfer matrixes,single dynamic degree,slope zones and fractional vegetation cover(FVC).The results indicated that the area of cropland decreased by 31%and was replaced mainly by shrub over the past 15 years,whereas forest and settlements showed continuous increases of 29.2% and 77.7%,respectively.The changes in cropland were obvious in all slope zones and decreased most remarkably(–43.8%)in the slope zone above 25°.Compared to the FVC of forest and shrub,significant improvement was exhibited in the FVC of grassland,with a growth rate of 16.6%.We concluded that local policies,including economic development,water conservation and immigration resulting from the construction of the MR-SNWDP,were the main drivers of land cover changes;notably,they stimulated the substantial and rapid expansion of settlements,doubled the wetlands and drove the transformation from cropland to settlements in immigration areas. | GAO Wenwen ZENG Yuan ZHAO Dan WU Bingfang REN Zhiyuan | 2020 | Chinese Geographical Science2020，30，1： | 2 |
| 9 | Crop classification using multi-configuration SAR data in the North China Plain显示文摘 | Kun Jia Qiangzi Li Yichen Tian Bingfang Wu Feifei Zhang Jihua Meng | 2012 | International Journal of Remote Sensing2012，，1： | 2 |
| 10 | Combining Spot4-vegetation and meteorological data derived land cover map in China显示文摘 | Wu Bingfang Xu Wenting Huang Huiping | 2004 | IEEE International Geoscience and Remote Sensing Symposium Proceedings2004，4，： | 1 |
| 11 | Building African Ecosystem Research Network for Sustaining Local Ecosystem Goods and Services显示文摘A new form of producing and sharing knowledge has emerged as an international(United States of America,Asia,and Europe) research collaboration,known as the Long-Term Ecological Research(LTER) Network.Although Africa boasts rich biodiversity,including endemic species,it lacks the long-term initiatives to underpin sustainable biodiversity managements.At present,climate change may exacerbate hunger and poverty concerns in addition to resulting in ecosystem degradation,land use change,and other threats in Africa.Therefore,ecosystem monitoring was suggested to understanding the effects of climate change and setting strategies to mitigate these changes.This paper aimed to investigate ecosystem monitoring ground sites and address their coverage gaps in Africa to provide a foundation for optimizing the African Ecosystem Research Network(AERN) ground sites.The geographic coordinates and characteristics of ground sites-based ecosystem monitoring were collected from various networks aligned with the LTER implementation in Africa.Additionally,climatic data and biodiversity distribution maps were retrieved from various sources.These data were used to assess the size of existing ground sites and the gaps in description,ecosystems and biomes.The results reveal that there were 1089 sites established by various networks.Among these sites,30.5%,27.5%,and 28.8% had no information of area,year of establishment,current status,respectively.However,68.0% of them had an area equal to or greater than 1 km2.Sites were created progressively over the course of the years,with 68.9% being created from 2000 to 2005.To date,only 41.5% of the sites were operational.The sites were scattered across Africa,but they were concentrated in Eastern and Southern Africa.The unbalanced distribution pattern of the sites left Central and Northern Africa hardly covered,and many unique ecosystems in Central Africa were not included.To sustain these sites,the AERN should be based on operational sites,seeking secure funding by establishing multiple partnerships. | Armand Sedami Igor YEVIDE WU Bingfang YU Xiubo LI Xiaosong LIU Yu LIU Jian | 2015 | Chinese Geographical Science2015，25，4： | 1 |
| 12 | Ecology and environment information system for yangtze three gorges project with remote sensing and GIS 显示文摘 | WU Bingfang MA Xinhui Meng Jihua | 2004 | International Geosciences and Remote Sensing Symposium (IGARSS)2004，，： | 1 |
| 13 | Water body mapping method with HJ-1A/B satellite imagery显示文摘 | Shanlong Lu Bingfang Wu Nana Yan Hao Wang | 2010 | International Journal of Applied Earth Observations and Geoinformation2010，，3： | 1 |
| 14 | Evenness is important in assessing progress towards sustainable development goals显示文摘Sustainable development goals(SDGs)emphasize a holistic achievement instead of cherry-picking a few.However,no assessment has quantitatively considered the evenness among all 17 goals.Here,we propose a systematic method,which first integrates both the evenness and the overall status of all goals,to distinguish the ideal development pathways from the uneven ones and then revisit the development trajectory in China from 2000 to 2015.Our results suggest that,despite the remarkable progress,a bottleneck has occurred in China since 2013 due to the stagnant developments in some SDGs.However,many far-reaching policies in China have been targeting these deficiencies since then,providing a perspective on how a country approaches sustainable development by promoting evenness among all SDGs.Our results also indicate that regions with the slowest progress are the developed provinces,owing to the persistent uneven status of all goals.Our study demonstrates the importance of adopting evenness in assessing and guiding sustainable development. | Yali Liu Jianqing Du Yanfen Wang Xiaoyong Cui Jichang Dong Yanbin Hao Kai Xue Hongbo Duan Anquan Xia Yi Hu Zhi Dong Bingfang Wu Xinquan Zhao Bojie Fu | 2021 | National Science Review2021，8，8： | 1 |
| 15 | Object-oriented Land Cover Information Extraction in Emigration Area of Zigui County Using High Resolution Imagery显示文摘 | Zhu Liang WU Bingfang Zhou Yuemin Zhang Lei Zhang Ning | | 0，，06： | 1 |
| 16 | Constructing a 30m African Cropland Layer for 2016 by Integrating Multiple Remote sensing,crowdsourced,and Auxiliary Datasets显示文摘Despite its essential importance to various spatial agriculture and environmental applications,the information on actual cropland area and its geographical distribution remain highly uncertain over Africa among remote-sensing products.Each of the African regions has its unique physical and environmental limiting factors to accurate cropland mapping,which leads to high spatial discre-pancies among remote sensing cropland products.Since no dataset could cope with all limitations,multiple datasets initially derived from various remote sensing sensors and classification techniques must be integrated into a more accurate cropland product than individual layers.Here,in the current study,four cropland products,produced initially from multiple sensors(e.g.Landsat-8 OLI,Sentinel-2 MSI,and PROBA-V)to cover the period(2015-2017),were integrated based on their cropland mapping accuracy to build a more accurate cropland layer.The four cropland layers’accuracy was assessed at Agro-ecological zones units via an inten-sive reference dataset(17,592 samples).The most accurate crop-land layer was then identified for each zone to construct the final cropland mask at 30 m resolution for the nominal year of 2016 over Africa.As a result,the new layer was produced in higher cropland mapping accuracy(overall accuracy=91.64%and cropland’s F-score=0.75).The layer mapped the African cropland area as 282 Mha(9.38%of the Continent area).Compared to earlier crop-land synergy layers,the constructed cropland mask showed a considerable improvement in its spatial resolution(30 m instead of 250 m),mapping quality,and closeness to official statistics(R^(2)=0.853 and RMSE=2.85 Mha).The final layer can be down-loaded as described under the“Data Availability Statement”section. | Mohsen Nabil Miao Zhang Bingfang Wu Jose Bofana Abdelrazek Elnashar | 2022 | Big Earth Data2022，6，1： | 1 |
| 17 | Maize acreage estimation using ENVISAT MERIS and CBERS-02B CCD data in the North China Plain显示文摘 | Li Qiangzi Wu Bingfang Jia Kun | 2011 | Computers and Electronics in Agriculture2011，78，2： | 1 |
| 18 | Using NOAA/ AVHRR and Landsat TM to estimate rice area yem'-by-year显示文摘 | Fang Hongliang Wu Bingfang Liu Haiyan el al | 1998 | International Journal of Remote Sensing1998，19，3： | 1 |
| 19 | Challenges and opportunities in remote sensing-based crop monitoring:a review显示文摘Building a more resilient food system for sustainable development and reducing uncertainty in global food markets both require concurrent and near-real-time and reliable crop information for decision making.Satellite-driven crop monitoring has become a main method to derive crop information at local,regional,and global scales by revealing the spatial and temporal dimensions of crop growth status and production.However,there is a lack of quantitative,objective,and robust methods to ensure the reliability of crop information,which reduces the applicability of crop monitoring and leads to uncertain and undesirable consequences.In this paper,we review recent progress in crop monitoring and identify the challenges and opportunities in future efforts.We find that satellite-derived metrics do not fully capture determinants of crop production and do not quantitatively interpret crop growth status;the later can be advanced by integrating effective satellite-derived metrics and new onboard sensors.We have identified that ground data accessibility and the negative effects of knowledge-based analyses are two essential issues in crop monitoring that reduce the applicability of crop monitoring for decisions on food security.Crowdsourcing is one solution to overcome the restrictions of ground-truth data accessibility.We argue that user participation in the complete process of crop monitoring could improve the reliability of crop information.Encouraging users to obtain crop information from multiple sources could prevent unconscious biases.Finally,there is a need to avoid conflicts of interest in publishing publicly available crop information. | Bingfang Wu Miao Zhang Hongwei Zeng Fuyou Tian Andries B Potgieter Xingli Qin Nana Yan Sheng Chang Yan Zhao Qinghan Dong Vijendra Boken Dmitry Plotnikov Huadong Guo Fangming Wu Hang Zhao Bart Deronde Laurent Tits Evgeny Loupian | 2023 | National Science Review2023，10，4： | 1 |
| 20 | Integrated spatial-temporal analysis of crop water productivity of winter wheat in Hai Basin 显示文摘 | Nana Yan Bingfang Wu | 2014 | Agricultural Water Management2014，133，11： | 1 |
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