Agricultural geospatial information is critical for agricultural policy formulation and decision making, land use monitoring, agricultural sustainability, crop acreage and yield estimation, disaster assessment, bioene...Agricultural geospatial information is critical for agricultural policy formulation and decision making, land use monitoring, agricultural sustainability, crop acreage and yield estimation, disaster assessment, bioenergy crop inventory, food security policy, environmental assessment, carbon accounting, and other research topics that are of vital importance to agricul- ture and economy. Remote sensing technology enables us to collect, process, and analyze remotely sensed data and to retrieve, synthesize, visualize valuable geospatial information for agriculture uses. Specifically, remote sensing technology empowers capability for large scale field level or regional assessment and monitoring of crop land cover,展开更多
Remote sensing, in particular satellite imagery, has been widely used to map cropland, analyze cropping systems, monitor crop changes, and estimate yield and production. However, although satellite imagery is useful w...Remote sensing, in particular satellite imagery, has been widely used to map cropland, analyze cropping systems, monitor crop changes, and estimate yield and production. However, although satellite imagery is useful within large scale agriculture applications (such as on a national or provincial scale), it may not supply sufifcient information with adequate resolution, accurate geo-referencing, and specialized biological parameters for use in relation to the rapid developments being made in modern agriculture. Information that is more sophisticated and accurate is required to support reliable decision-making, thereby guaranteeing agricultural sustainability and national food security. To achieve this, strong integration of information is needed from multi-sources, multi-sensors, and multi-scales. In this paper, we propose a new framework of satellite, aerial, and ground-integrated (SAGI) agricultural remote sensing for use in comprehensive agricultural monitoring, modeling, and management. The prototypes of SAGI agriculture remote sensing are ifrst described, followed by a discussion of the key techniques used in joint data processing, image sequence registration and data assimilation. Finally, the possible applications of the SAGI system in supporting national food security are discussed.展开更多
Unmanned aerial vehicle(UAV)has the advantages of good repeatability and high remote sensing(RS)information acquisition efficiency,as an important supplement bridging the gap of high-altitude and ground RS platforms.A...Unmanned aerial vehicle(UAV)has the advantages of good repeatability and high remote sensing(RS)information acquisition efficiency,as an important supplement bridging the gap of high-altitude and ground RS platforms.A quadrotor UAV was developed for the agricultural RS application in this study.The control system consists of a main processor and a coprocessor,integrating a three-axis gyroscope,a three-axis accelerometer,an air pressure sensor and a global positioning system(GPS)module.Engineering trial method(ETM)was used to tune the parameters based on the active disturbance rejection control(ADRC)method.Also a ground control station(GCS)adapted to the quadrotor was developed realizing autonomously take-off and landing,flight route planning,data recording.To investigate the performances of the UAV,several flight tests were carried out.The test results showed that the pitch angle control accuracy error was less than 4°,the flight height control accuracy error was less than 0.86 m,the flight path control accuracy error was less than 1.5 m overall.Aerial multispectral images were acquired and processed.The reflected digital number(DN)values obtained from a height of 10-100 m with 10 m interval could be referenced to classify objects.The normalized-difference-vegetation index(NDVI)values obtained from the aerial multispectral images acquired at 15 m were compared with those obtained by the GreenSeeker(GS)and PSR-1100F.The maximum error was 20.37%while the minimum error was 1.99%,which demonstrated the developed quadrotor UAV’s satisfactions for low altitude remote sensing practice.This study provided a low-cost platform for agricultural remote sensing.展开更多
文摘Agricultural geospatial information is critical for agricultural policy formulation and decision making, land use monitoring, agricultural sustainability, crop acreage and yield estimation, disaster assessment, bioenergy crop inventory, food security policy, environmental assessment, carbon accounting, and other research topics that are of vital importance to agricul- ture and economy. Remote sensing technology enables us to collect, process, and analyze remotely sensed data and to retrieve, synthesize, visualize valuable geospatial information for agriculture uses. Specifically, remote sensing technology empowers capability for large scale field level or regional assessment and monitoring of crop land cover,
基金supported by the Opening Project of the Key Laboratory of Agri-Informatics,Ministry of Agriculture of China(2012004)the National Basic Research Program of China(973 Program,2010CB951500)+2 种基金the Innovation Project of Chinese Academy of Agricultural Sciencesthe National Natural Science Foundation of China(41301365)the National High-Tech R&D Program of China(863 Program,2013AA12A401)
文摘Remote sensing, in particular satellite imagery, has been widely used to map cropland, analyze cropping systems, monitor crop changes, and estimate yield and production. However, although satellite imagery is useful within large scale agriculture applications (such as on a national or provincial scale), it may not supply sufifcient information with adequate resolution, accurate geo-referencing, and specialized biological parameters for use in relation to the rapid developments being made in modern agriculture. Information that is more sophisticated and accurate is required to support reliable decision-making, thereby guaranteeing agricultural sustainability and national food security. To achieve this, strong integration of information is needed from multi-sources, multi-sensors, and multi-scales. In this paper, we propose a new framework of satellite, aerial, and ground-integrated (SAGI) agricultural remote sensing for use in comprehensive agricultural monitoring, modeling, and management. The prototypes of SAGI agriculture remote sensing are ifrst described, followed by a discussion of the key techniques used in joint data processing, image sequence registration and data assimilation. Finally, the possible applications of the SAGI system in supporting national food security are discussed.
基金This research was financially supported by the National Natural Science Foundation of China(No.31701327)the National Key Research and Development Program of China(Grant NO.2017YFD0701000)Collaborative Innovation Plan of Scientific and Technological Innovation Project(Grant No.CAAS-XTCX2016006).
文摘Unmanned aerial vehicle(UAV)has the advantages of good repeatability and high remote sensing(RS)information acquisition efficiency,as an important supplement bridging the gap of high-altitude and ground RS platforms.A quadrotor UAV was developed for the agricultural RS application in this study.The control system consists of a main processor and a coprocessor,integrating a three-axis gyroscope,a three-axis accelerometer,an air pressure sensor and a global positioning system(GPS)module.Engineering trial method(ETM)was used to tune the parameters based on the active disturbance rejection control(ADRC)method.Also a ground control station(GCS)adapted to the quadrotor was developed realizing autonomously take-off and landing,flight route planning,data recording.To investigate the performances of the UAV,several flight tests were carried out.The test results showed that the pitch angle control accuracy error was less than 4°,the flight height control accuracy error was less than 0.86 m,the flight path control accuracy error was less than 1.5 m overall.Aerial multispectral images were acquired and processed.The reflected digital number(DN)values obtained from a height of 10-100 m with 10 m interval could be referenced to classify objects.The normalized-difference-vegetation index(NDVI)values obtained from the aerial multispectral images acquired at 15 m were compared with those obtained by the GreenSeeker(GS)and PSR-1100F.The maximum error was 20.37%while the minimum error was 1.99%,which demonstrated the developed quadrotor UAV’s satisfactions for low altitude remote sensing practice.This study provided a low-cost platform for agricultural remote sensing.