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Published in last 1 year |  In last 2 years |  In last 3 years |  All Please wait a minute... For Selected: Download Citations EndNote Reference Manager ProCite BibTeX RefWorks Toggle Thumbnails Select Extraction of Eeannis jacobssoni disaster area based on MODIS-MOD09Q1 data and analysis of its adaptive climate characteristics QING Ge-le, HUANG Xiao-jun, BAI Li-ga, Ganbat Dashzebeg, Tsagaantsooj Nanzad, Altanchimeg Dorjsuren, Davaadorj Enkhnasan, Mungunkhuyag Ariunaa HUBEI AGRICULTURAL SCIENCES    2024, 63 (1): 169-176.   DOI: 10.14088/j.cnki.issn0439-8114.2024.01.031 Abstract （73）      PDF （2449KB）（57）       Knowledge map    Save Using MODIS-MOD09Q1 remote sensing data, three easily obtainable and responsive indicators, namely Normalized Difference Vegetation Index （NDVI）, Ratio Vegetation Index （RVI）, and Near Infrared Reflectance （NIR）, were used to classify the changes in vegetation index for the degree of damage in disaster areas, and a comprehensive pest index （PCI） model was constructed to achieve rapid extraction of information from the Eeannis jacobssoni disaster area. On this basis, with the help of temperature and precipitation data, combined with GIS spatial overlay analysis method, the climate characteristics suitable for pest growth were revealed. The results showed that using the comprehensive pest index could accurately extract the severity information of pest disaster areas, with an overall accuracy and Kappa coefficient of 85.00% and 0.81, respectively;Eeannis jacobssoni was suitable for climates with less precipitation in winter and spring, more precipitation in summer, and temperatures that should not be too high, which was consistent with its biological characteristics. This climate was similar to the Greater Khingan Mountains forest area, with a high risk of invasion, and should be highly valued by the Chinese forestry department. Reference | Related Articles | Metrics Select Design and implementation of IoT intelligent irrigation system for agriculture based on AT80C51 microcontroller CHE Peng-fei HUBEI AGRICULTURAL SCIENCES    2024, 63 (1): 177-184.   DOI: 10.14088/j.cnki.issn0439-8114.2024.01.032 Abstract （122）      PDF （8175KB）（66）       Knowledge map    Save An IoT irrigation system based on the AT80C51 microcontroller had been developed to address the issues of unintelligent and untimely irrigation in traditional artificial irrigation methods,the system could obtain the environmental conditions of farmland through temperature and humidity sensors and transmit them to remote data centers through wireless communication modules. At the same time, the system was equipped with irrigation system threshold control equipment, which could adjust and control the pumping pump as needed. When the system determined that the farmland soil was dry, the environmental conditions triggered the system threshold and pumped water for irrigation in a timely manner, ensuring that the soil always maintained a suitable temperature and humidity.Through simulation experiments and actual testing, greenhouse lettuce at different growth stages in spring and summer was taken as the research object. Under intelligent irrigation, the average fresh weight of each plant above ground increased by at least 11.31% compared to traditional artificial irrigation;the average drainage of intelligent irrigation in spring and summer was 64.96% and 63.47% lower than that of traditional artificial irrigation, respectively;the irrigation water efficiency of intelligent irrigation in spring and summer was 68.03% and 98.61% higher than that of traditional artificial irrigation, respectively. The system operated stably, and the relevant experimental data and phenomena met expectations. Reference | Related Articles | Metrics page Page 1 of 115 Total 229 records First page Prev page Next page Last page