对当前我国地理信息系统(Geographic Information System,GIS)技术在农作物病虫害监测预警系统中的应用现状进行了分析,概括了其随着GIS技术的发展从基于桌面GIS到基于WEBGIS的发展轨迹,以及GIS技术在农作物监测预警系统中的主要应用,...对当前我国地理信息系统(Geographic Information System,GIS)技术在农作物病虫害监测预警系统中的应用现状进行了分析,概括了其随着GIS技术的发展从基于桌面GIS到基于WEBGIS的发展轨迹,以及GIS技术在农作物监测预警系统中的主要应用,总结现有基于GIS的农作物病虫害监测预警系统存在的问题与不足。结合当前信息技术的发展,对今后基于GIS技术的农作物监测预警系统的发展进行了展望。展开更多
Over the last three decades, special purpose “entomological” radars have contributed much to the development of our understanding of insect migration, especially of the nocturnal migrations at altitudes of up to ～1...Over the last three decades, special purpose “entomological” radars have contributed much to the development of our understanding of insect migration, especially of the nocturnal migrations at altitudes of up to ～1 km that are regularly undertaken by many important pest species. One of the limitations of early radar studies, the difficulty of maintaining observations over long periods, has recently been overcome by the development of automated units that operate autonomously and transmit summaries of their observations to a base laboratory over the public telephone network. These relatively low cost Insect Monitoring Radars (IMRs) employ a novel “ZLC” configuration that allows high quality data on the migrants' flight parameters and identity to be acquired. Two IMRs are currently operating in the semi arid inland of eastern Australia, in a region where populations of migrant moths (Lepidoptera) and Australian plague locusts Chortoicetes terminifera (Orthoptera) commonly originate, and some examples of outputs from one of these units are presented. IMRs are able to provide the data needed to characterize a migration system, i.e. to estimate the probabilities of migration events occurring in particular directions at particular seasons and in response to particular environmental conditions and cues. They also appear capable of fulfilling a “sentinel” role for pest management organisations, alerting forecasters to major migration events and thus to the likely new locations of potential target populations. Finally, they may be suitable for a more general ecological monitoring role, perhaps especially for quantifying year to year variations in biological productivity.展开更多
文摘对当前我国地理信息系统(Geographic Information System,GIS)技术在农作物病虫害监测预警系统中的应用现状进行了分析,概括了其随着GIS技术的发展从基于桌面GIS到基于WEBGIS的发展轨迹,以及GIS技术在农作物监测预警系统中的主要应用,总结现有基于GIS的农作物病虫害监测预警系统存在的问题与不足。结合当前信息技术的发展,对今后基于GIS技术的农作物监测预警系统的发展进行了展望。
文摘Over the last three decades, special purpose “entomological” radars have contributed much to the development of our understanding of insect migration, especially of the nocturnal migrations at altitudes of up to ～1 km that are regularly undertaken by many important pest species. One of the limitations of early radar studies, the difficulty of maintaining observations over long periods, has recently been overcome by the development of automated units that operate autonomously and transmit summaries of their observations to a base laboratory over the public telephone network. These relatively low cost Insect Monitoring Radars (IMRs) employ a novel “ZLC” configuration that allows high quality data on the migrants' flight parameters and identity to be acquired. Two IMRs are currently operating in the semi arid inland of eastern Australia, in a region where populations of migrant moths (Lepidoptera) and Australian plague locusts Chortoicetes terminifera (Orthoptera) commonly originate, and some examples of outputs from one of these units are presented. IMRs are able to provide the data needed to characterize a migration system, i.e. to estimate the probabilities of migration events occurring in particular directions at particular seasons and in response to particular environmental conditions and cues. They also appear capable of fulfilling a “sentinel” role for pest management organisations, alerting forecasters to major migration events and thus to the likely new locations of potential target populations. Finally, they may be suitable for a more general ecological monitoring role, perhaps especially for quantifying year to year variations in biological productivity.
