{"title":"果园中的地理数据收集和可视化:以疾病为例(欧洲苹果溃疡病,新树病)连接科学-种植者数据","authors":"Juliane Buhrdel, M. Walter, R. Campbell","doi":"10.30843/nzpp.2020.73.11721","DOIUrl":null,"url":null,"abstract":"The collection and visualisation of data in orchards are important for management of many orchard processes, including pests and diseases. We present methods combining visualising data with efficient, accurate, standardised data collection, using European canker in apple orchards as an exemplar. Using growercollected current and historical disease data, we investigated Environmental Systems Research Institute (ESRI) ArcGIS tools to analyse and visualise data. Historical data were collected by growers on paper and current data, also collected by growers, using Survey123. ArcGIS Pro was the operating software for analysis, and ArcGIS Online, Web Maps and ArcGIS Dashboards, for visualisation. Data collection, summarising and visualisation were more efficient using Survey123, than paper collection and subsequent data entry. Higher quality data, including spatial location of the disease, informed disease patterns. A standardised geodatabase enabled efficient data querying and analytics to understand disease distribution and temporal dynamics. This study exemplars a standardised disease and pest database to benefit both scientific and industry data management. Geodata collection, combined with visualisation, facilitates the use of data to understand disease and pest dynamics. These techniques offer opportunity for a cohesive industry approach to area-wide disease and pest monitoring and management, integrating previously disparate datasets by using location.","PeriodicalId":19180,"journal":{"name":"New Zealand Plant Protection","volume":"50 1","pages":"57-64"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Geodata collection and visualisation in orchards: interfacing science-grower data using a disease example (European canker in apple, Neonectria ditissima)\",\"authors\":\"Juliane Buhrdel, M. Walter, R. Campbell\",\"doi\":\"10.30843/nzpp.2020.73.11721\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The collection and visualisation of data in orchards are important for management of many orchard processes, including pests and diseases. We present methods combining visualising data with efficient, accurate, standardised data collection, using European canker in apple orchards as an exemplar. Using growercollected current and historical disease data, we investigated Environmental Systems Research Institute (ESRI) ArcGIS tools to analyse and visualise data. Historical data were collected by growers on paper and current data, also collected by growers, using Survey123. ArcGIS Pro was the operating software for analysis, and ArcGIS Online, Web Maps and ArcGIS Dashboards, for visualisation. Data collection, summarising and visualisation were more efficient using Survey123, than paper collection and subsequent data entry. Higher quality data, including spatial location of the disease, informed disease patterns. A standardised geodatabase enabled efficient data querying and analytics to understand disease distribution and temporal dynamics. This study exemplars a standardised disease and pest database to benefit both scientific and industry data management. Geodata collection, combined with visualisation, facilitates the use of data to understand disease and pest dynamics. These techniques offer opportunity for a cohesive industry approach to area-wide disease and pest monitoring and management, integrating previously disparate datasets by using location.\",\"PeriodicalId\":19180,\"journal\":{\"name\":\"New Zealand Plant Protection\",\"volume\":\"50 1\",\"pages\":\"57-64\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"New Zealand Plant Protection\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.30843/nzpp.2020.73.11721\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Agricultural and Biological Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"New Zealand Plant Protection","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.30843/nzpp.2020.73.11721","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
Geodata collection and visualisation in orchards: interfacing science-grower data using a disease example (European canker in apple, Neonectria ditissima)
The collection and visualisation of data in orchards are important for management of many orchard processes, including pests and diseases. We present methods combining visualising data with efficient, accurate, standardised data collection, using European canker in apple orchards as an exemplar. Using growercollected current and historical disease data, we investigated Environmental Systems Research Institute (ESRI) ArcGIS tools to analyse and visualise data. Historical data were collected by growers on paper and current data, also collected by growers, using Survey123. ArcGIS Pro was the operating software for analysis, and ArcGIS Online, Web Maps and ArcGIS Dashboards, for visualisation. Data collection, summarising and visualisation were more efficient using Survey123, than paper collection and subsequent data entry. Higher quality data, including spatial location of the disease, informed disease patterns. A standardised geodatabase enabled efficient data querying and analytics to understand disease distribution and temporal dynamics. This study exemplars a standardised disease and pest database to benefit both scientific and industry data management. Geodata collection, combined with visualisation, facilitates the use of data to understand disease and pest dynamics. These techniques offer opportunity for a cohesive industry approach to area-wide disease and pest monitoring and management, integrating previously disparate datasets by using location.
期刊介绍:
New Zealand Plant Protection is the journal of the New Zealand Plant Protection Society. It publishes original research papers on all aspects of biology, ecology and control of weeds, vertebrate and invertebrate pests, and pathogens and beneficial micro-organisms in agriculture, horticulture, forestry and natural ecosystems of relevance to New Zealand.