Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been...Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.展开更多
Africa is covered with extensive woodlands,savannas and rainforests.The tree cover of these biomes has been undergoing substantial changes in recent decades.However,the dynamics of forests in Africa are currently uncl...Africa is covered with extensive woodlands,savannas and rainforests.The tree cover of these biomes has been undergoing substantial changes in recent decades.However,the dynamics of forests in Africa are currently unclear,particularly in the woodlands and savanna areas covered by sparse trees.Here,we assessed the spatio-temporal trend of African forests from 2000 to 2020,using a 250-m resolution fractional tree cover product that can capture the variation of forest density in the widespread mixed vegetation landscapes of the continent.The tree cover trends,interannual change and hotspots of forest gain and loss were evaluated.Results showed that the African forest area increased at a rate of 3.59 million ha/year over the study period,reaching 589 million ha in 2020.Considerable forest gain and loss both occurred in Africa.The net change rate in woodlands’forest area was the fastest(2.28 million ha/year),followed by rainforests(0.80 million ha/year)and savannas(0.34 million ha/year).Hotspots of forest gain were concentrated in the north belt of woodlands and savannas,while forest loss primarily clustered in East and South Africa.This work would help African countries to monitor forest change and promote forest management to achieve the Sustainable Development Goals.展开更多
Unmanned aerial vehicles(UAV)based remote sensing is an emerging and important data source.Recently,the use of UAVs for remote sensing applications has been rapidly growing owing to their greater availability and the ...Unmanned aerial vehicles(UAV)based remote sensing is an emerging and important data source.Recently,the use of UAVs for remote sensing applications has been rapidly growing owing to their greater availability and the miniaturization of sensors.UAVs are surpassing satellites and aircraft in remote sensing data supply for many local requirements.In comparison with satellite remote sensing data,most UAV remote sensing data is characterized by high resolution,small coverage area,and heterogeneous multi-sources.However,UAVs lack a unified space–time framework and standardized data process.This paper describes a UAV remote sensing data carrier that can be used as an e-commerce platform for data sharing among registered members and a mission planner for new data acquisition.To the best of our knowledge,the data carriers described herein,are the first of their kind.Through seamless docking with UAVs,the data carrier will form a national UAV network,capable of dynamically obtaining very-high-resolution UAV remote sensing images.In practice,a pilot retrieval system of UAV meta data has been developed to provide a catalogue of data product services.展开更多
基金This work was supported by the National Natural Science Foundation of China(72221002,42271375)the Strategic Priority Research Program(XDA28060100)the Informatization Plan Project(CAS-WX2021PY-0109)of the Chinese Academy of Sciences.
文摘Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.
基金supported by the National Key Research and Development Program of China(No.2019YFA0606603)the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA19080303)+1 种基金the National Natural Science Foundation of China(No.42161144001)the Youth Innovation Promotion Association of Chinese Academy of Sciences(No.2019056).
文摘Africa is covered with extensive woodlands,savannas and rainforests.The tree cover of these biomes has been undergoing substantial changes in recent decades.However,the dynamics of forests in Africa are currently unclear,particularly in the woodlands and savanna areas covered by sparse trees.Here,we assessed the spatio-temporal trend of African forests from 2000 to 2020,using a 250-m resolution fractional tree cover product that can capture the variation of forest density in the widespread mixed vegetation landscapes of the continent.The tree cover trends,interannual change and hotspots of forest gain and loss were evaluated.Results showed that the African forest area increased at a rate of 3.59 million ha/year over the study period,reaching 589 million ha in 2020.Considerable forest gain and loss both occurred in Africa.The net change rate in woodlands’forest area was the fastest(2.28 million ha/year),followed by rainforests(0.80 million ha/year)and savannas(0.34 million ha/year).Hotspots of forest gain were concentrated in the north belt of woodlands and savannas,while forest loss primarily clustered in East and South Africa.This work would help African countries to monitor forest change and promote forest management to achieve the Sustainable Development Goals.
基金Strategic Priority Research Program of Chinese Academy of Sciences(No.XDA19050501)the National Natural Science Foundation of China(grant number 41771388,41971359)。
文摘Unmanned aerial vehicles(UAV)based remote sensing is an emerging and important data source.Recently,the use of UAVs for remote sensing applications has been rapidly growing owing to their greater availability and the miniaturization of sensors.UAVs are surpassing satellites and aircraft in remote sensing data supply for many local requirements.In comparison with satellite remote sensing data,most UAV remote sensing data is characterized by high resolution,small coverage area,and heterogeneous multi-sources.However,UAVs lack a unified space–time framework and standardized data process.This paper describes a UAV remote sensing data carrier that can be used as an e-commerce platform for data sharing among registered members and a mission planner for new data acquisition.To the best of our knowledge,the data carriers described herein,are the first of their kind.Through seamless docking with UAVs,the data carrier will form a national UAV network,capable of dynamically obtaining very-high-resolution UAV remote sensing images.In practice,a pilot retrieval system of UAV meta data has been developed to provide a catalogue of data product services.
