Abstract
Optimum band and band combination for retrieving total nitrogen, water and fiber content in tealeaves with remote sensing data is investigated based on regressive analysis. Based on actual measured data of total nitrogen, fiber and water content in tealeaves as well as remotely sensed visible to near infrared reflectance data with 5nm of wavelength steps and ASTER/VNIR onboard Terra satellite, regressive analysis is conducted. As the results, it is found that 1045nm is the best wavelength for retrieving total nitrogen content while 945nm is the best wavelength for fiber content retrieval. Also it is found that 545nm is the best wavelength for water content. On the other hand, it is found that 350 and 750nm wavelength combination is the best for estimation of total nitrogen content while 535 and 720 wavelength combination is the best for fiber content estimation. It also found that 545 and 760nm wavelength combination is the best for water content retrieval.
Highlights
It is highly desired to monitor vitality of crops in agricultural areas automatically with appropriate measuring instruments in order to manage agricultural area in an efficient manner
This paper describes a method and system for estimation of quantity of crop products by using Vegetation Cover: VC and Normalized Difference Vegetation Index: NDVI and Bidirectional Reflectance Distribution Function: BRDF because the VC and NDVI represent vegetated area while BRDF represents vegetation mass, or layered leaves
Near Infrared: NIR camera data shows a good correlation to total nitrogen and fiber contents in tealeaves so that tealeaves quality can be monitored with network NIR cameras
Summary
It is highly desired to monitor vitality of crops in agricultural areas automatically with appropriate measuring instruments in order to manage agricultural area in an efficient manner. This paper deals with automatic monitoring of a quality of tealeaves with earth observation satellite, network cameras together with a method that allows estimation of total nitrogen and fiber contents in tealeaves as an example. Near Infrared: NIR camera data shows a good correlation to total nitrogen and fiber contents in tealeaves so that tealeaves quality can be monitored with network NIR cameras. VC, NDVI, BRDF of tealeaves have a good correlation to grow index of tealeaves so that it is possible to monitor expected harvest amount and quality of tealeaves with network cameras together with remote sensing satellite data. In order to determine appropriate wavelength bands for estimation of total nitrogen, fiber and water contents in tealeaves, regressive analysis is conducted. The regressive analysis results are summarized followed by conclusion and some discussions
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