Jiang-Lin Qin1, Xiu-Hao Yang2, Zhong-Wu Yang3, Ji-Tong Luo2, Xiu-Feng Lei4. 1. Guangxi Institute of Meteorological Disaster-Reducing Research, Nanning, Guangxi, China. 2. Department of Guangxi Forest Pest Management, Bureau of Guangxi Forest, Nanning, Guangxi, China. 3. Guangxi Guilin Forest Pest Management Station, Guilin, Guangxi, China. 4. Guangxi Nanning Forest Pest Management Station, Nanning, Guangxi, China.
Abstract
BACKGROUND: Near surface air temperature and rainfall are major weather factors affecting forest insect dynamics. The recent developments in remote sensing retrieval and geographic information system spatial analysis techniques enable the utilization of weather factors to significantly enhance forest pest forecasting and warning systems. The current study focused on building forest pest digital data structures as a platform of correlation analysis between weather conditions and forest pest dynamics for better pest forecasting and warning systems using the new technologies. RESULTS: The study dataset contained 3 353 425 small polygons with 174 defined attributes covering 95 counties of Guangxi province of China currently registering 292 forest pest species. Field data acquisition and information transfer systems were established with four software licences that provided 15-fold improvement compared to the systems currently used in China. Nine technical specifications were established including codes of forest districts, pest species and host tree species, and standard practices of forest pest monitoring and information management. Attributes can easily be searched using ArcGIS9.3 and/or the free QGIS2.16 software. CONCLUSIONS: Small polygons with pest relevant attributes are a new tool of precision farming and detailed forest insect pest management that are technologically advanced.
BACKGROUND: Near surface air temperature and rainfall are major weather factors affecting forest insect dynamics. The recent developments in remote sensing retrieval and geographic information system spatial analysis techniques enable the utilization of weather factors to significantly enhance forest pest forecasting and warning systems. The current study focused on building forest pest digital data structures as a platform of correlation analysis between weather conditions and forest pest dynamics for better pest forecasting and warning systems using the new technologies. RESULTS: The study dataset contained 3 353 425 small polygons with 174 defined attributes covering 95 counties of Guangxi province of China currently registering 292 forest pest species. Field data acquisition and information transfer systems were established with four software licences that provided 15-fold improvement compared to the systems currently used in China. Nine technical specifications were established including codes of forest districts, pest species and host tree species, and standard practices of forest pest monitoring and information management. Attributes can easily be searched using ArcGIS9.3 and/or the free QGIS2.16 software. CONCLUSIONS: Small polygons with pest relevant attributes are a new tool of precision farming and detailed forest insect pest management that are technologically advanced.