학위논문 (석사)-- 서울대학교 대학원 농업생명과학대학 생태조경·지역시스템공학부, 2017. 8. 류영렬.Monitoring vegetation indices, fraction of absorbed photosynthetically active radiation (fPAR) and leaf area index (LAI) has advanced our understanding of biosphere-atmosphere interactions. Although there are continuous observations for each variable, monitoring vegetation indices, fPAR and LAI simultaneously is still lacking. Recent advances of technology provide unprecedented opportunities to integrate various low-cost sensors as an intelligent near surface observation system for monitoring ecosystem structure and functions. In this study, we developed a Smart Surface Sensing System (4S), which can automatically collect, transfer, process and analyze data, and then publish time series results on public-available website. The system is composed of micro-computers, micro-controllers, multi-spectral spectrometers made from Light Emitting Diode (LED), micro cameras, and Internet module. We did intensive tests and calibrations in the lab. Then, we conducted in-situ observations of normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), fraction of absorbed photosynthetically active radiation (fPAR), and leaf area index (LAI) continuously at a rice paddy field during the growing season. NDVI and EVI obtained by 4S showed linear relationships with those from a reference hyperspectrometer (R2 = 0.98NDVI, R2 = 0.96EVI). 4S derived fPAR and LAI were comparable to LAI-2200 and destructive measurements in both magnitude and seasonal trajectory. We retrieved vegetation indices, fPAR and LAI independently and continuously and show that after the reproductive stage, fPAR remained constant, whereas LAI and NDVI decreased continuously after their peak because of non-photosynthetic materials such as grain and yellow leaf. In addition, using vegetation index to estimate fPAR has limitation because the spectral reflectance could not capture the diurnal pattern. On the other hand, fPAR changes abruptly depending on the sky conditions and the amount of light transmitted. We believe that 4S will be useful in the expansion of ecological sensing networks across multiple spatial and temporal scales.1 Introduction 1
2 Method and materials 4
2.1 Development and calibration of 4S 4
2.2 Testing the 4S LED spectrometer 6
2.2.1 Site description 10
2.2.2 4S in-situ 12
2.2.3 Reference data collection 15
2.2.4 Satellite remote sensing data 16
3 Results 17
3.1 Seasonal variation in 4S LED sensor 17
3.2 Seasonal variation in 4S camera sensor 20
3.3 Comparison of NDVI obtained from 4S and satellite with different resolutions 22
4 Discussion 23
4.1 What are the advantages of 4S development 23
4.2 What are the advantages of observing vegetation indices, fPAR and LAI independently 25
4.3 What are the advantages of continuous observation compared to different sensors 29
5 Conclusion 32
6 References 33
7 Abstract (Korean) 38Maste
