Assessment of unified models for estimating potato leaf area index under water stress conditions across ground-based hyperspectral data

2020 ◽  
Vol 14 (01) ◽  
pp. 1
Author(s):  
Shanjun Luo ◽  
Yingbin He ◽  
Qian Li ◽  
Weihua Jiao ◽  
Yaqiu Zhu ◽  
...  
Author(s):  
Rui Xie ◽  
Roshanak Darvishzadeh ◽  
Andrew K. Skidmore ◽  
Marco Heurich ◽  
Stefanie Holzwarth ◽  
...  

2013 ◽  
Vol 6 (3) ◽  
pp. 4603-4663 ◽  
Author(s):  
Z. Yin ◽  
S. C. Dekker ◽  
B. J. J. M. van den Hurk ◽  
H. A. Dijkstra

Abstract. A myriad of interactions exist between vegetation and local climate for arid and semi-arid regions. Vegetation function, structure and individual behavior have large impacts on carbon-water-energy balances, which consequently influence local climate variability that, in turn, feeds back to the vegetation. In this study, a conceptual vegetation structure scheme is formulated and tested in a new carbon-water-energy coupled model to explore the importance of vegetation structure and vegetation adaptation to water stress on equilibrium biomass states. Surface energy, water and carbon fluxes are simulated for a range of vegetation structures across a precipitation gradient in West Africa and optimal vegetation structures that maximizes biomass for each precipitation regime are determined. Two different strategies of vegetation adaptation to water stress are included. Under dry conditions vegetation tries to maximize the Water Use Efficiency and Leaf Area Index as it tries to maximize carbon gain. However, an important negative feedback mechanism is found as the vegetation also tries to minimize its cover to optimize the surrounding bare ground area from which water can be extracted, thereby forming patches of vertical vegetation. Under larger precipitation, a positive feedback mechanism is found in which vegetation tries to maximize its cover as it then can reduce water loss from bare soil while having maximum carbon gain due to a large Leaf Area Index. The competition between vegetation and bare soil determines a transition between a "survival" state to a "growing" state.


1997 ◽  
Vol 40 (3) ◽  
pp. 251-266 ◽  
Author(s):  
R. Gordon ◽  
D. M. Brown ◽  
M. A. Dixon

1997 ◽  
Vol 54 (spe) ◽  
pp. 39-44 ◽  
Author(s):  
D.A. Teruel ◽  
V. Barbieri ◽  
L.A. Ferraro Jr.

The knowledge of the Leaf Area Index (LAI) variation during the whole crop cycle is essential to the modeling of the plant growth and development and, consequently, of the crop yield. Sugarcane LAI evolution models were developed for different crop cycles, by adjusting observed LAI values and growing degree-days summation data on a power-exponential function. The resultant equations simulate adequately the LAI behavior during the entire crop cycle. The effect of different water stress levels was calculated in different growth periods, upon the LAI growth The LAI growth deficit was correlated with the ratio between actual evapotranspiration and máximum evapotranspiration, and a constant named kuu was obtained hi each situation. It was noticed that the kLAI must be estimated not Just for different growth periods, but also for different water stress levels in each growth period.


2003 ◽  
Author(s):  
Xiuzhen Wang ◽  
Jingfeng Huang ◽  
Yunmei Li ◽  
Renchao Wang

Author(s):  
Indu Indirabai ◽  
M. V. Harindranathan Nair ◽  
Jaishanker R. Nair ◽  
Rama Rao Nidamanuri

The Western Ghats regions of India are characterised by highly complex and biodiverse forest ecosystem with heterogeneous tree species. The integration of LiDAR data with multispectral remote sensing has limitations in the case of spectral information abundance. The objective of this study was to undertake biophysical characterisation in the Western Ghats regions of India by the integration of GLAS ICESat data and AVIRIS-NG hyperspectral data. The methodology of the study includes pre-processing of the hyperspectral and ICESat GLAS data followed by the integration of the two data sets based on pixel based fusion strategy in order to estimate the biophysical parameters of forests. Biomass was estimated by Support Vector Regression method. The structural characteristics extracted from the LiDAR data are integrated with spectral characteristics from the AVIRIS NG imagery based on the pixel level so that biophysical characteristics including canopy height, biomass, Leaf Area Index are estimated. The integrated product on further analysis revealed the applicability of this approach to extract more spectral information and forest parameters. The key findings of the study include biophysical parameters both structural as well as abundant spectral information can be retrieved successfully by the methodology used which have strong correlation with the in situ measurements. The study concluded that biophysical parameters including Leaf Area Index, biomass and canopy height can be effectively estimated by the integration of AVIRIS-NG imagery and GLAS data, which cannot be possible when used independently. It is recommended to have continuous retrieval of LiDAR foot prints instead of discrete, to make modelling of the biophysical parameters a little more effective.


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