NDLI: Application of remote sensing and GIS for assessing economic loss caused by frost damage to tea plantations

Content Provider	Springer Nature Link
Author	Lou, Weiping Ji, Zongwei Sun, Ke Zhou, Jianneng
Copyright Year	2013
Abstract	This study aims to develop a method to evaluate economic loss resulting from damage of spring frost to tea plantations, with the help of remote sensing and geographic information system (GIS) technology. The study site was the Yuezhou Longjing tea producing area in the Shaoxing region of China and evaluated the economic loss resulting from damage to Wuniuzao, Longjing-43 and Jiukeng tea plantations caused by frost on 10 March 2010. Based on a linear equation for representing the variations of each tea tree species with geographical factors, their beginning date of tea plucking (BDTP) were calculated at each grid points with a GIS database. Minimum temperatures were retrieved with four split-window algorithms and satellite remote sensing data was acquired at 06:29 and 12:57 on 10 March 2010. A variational correction method was performed with data from automatic weather stations. Mean absolute error between the retrieved minimum temperatures and actual minimum temperatures of only 0.3 °C was obtained. The BDTP for each species, based on minimum temperature values, and the frost index for each grid point were referenced to assess economic loss resulting from damage to Wuniuzao, Longjing-43, and Jiukeng tea plantations caused by frost. The economic loss estimated in our study was close to the actual value.
Starting Page	606
Ending Page	620
Page Count	15
File Format	PDF
ISSN	13852256
Journal	Precision Agriculture
Volume Number	14
Issue Number	6
e-ISSN	15731618
Language	English
Publisher	Springer US
Publisher Date	2013-05-23
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Crop frost damage assessment Economic loss Beginning date of tea plucking Minimum temperature Spatial distribution Agriculture Soil Science & Conservation Remote Sensing/Photogrammetry Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Atmospheric Sciences
Content Type	Text
Resource Type	Article
Subject	Agricultural and Biological Sciences

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