scholarly journals Aboveground biomass and leaf area index (LAI) mapping for Niassa Reserve, northern Mozambique

2008 ◽  
Vol 113 (G3) ◽  
Author(s):  
Natasha S. Ribeiro ◽  
Sassan S. Saatchi ◽  
Herman H. Shugart ◽  
Robert A. Washington-Allen
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Area Index

scholarly journals Estimating leaf area index and aboveground biomass of grazing pastures using Sentinel-1, Sentinel-2 and Landsat images

2019 ◽  
Vol 154 ◽  
pp. 189-201 ◽  
Author(s):  
Jie Wang ◽  
Xiangming Xiao ◽  
Rajen Bajgain ◽  
Patrick Starks ◽  
Jean Steiner ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Landsat Images ◽  
Area Index ◽  
Sentinel 2

Impact of spectral saturation on leaf area index and aboveground biomass estimation of winter wheat

2016 ◽  
Vol 49 (4) ◽  
pp. 241-248 ◽  
Author(s):  
Chao Wang ◽  
Mei-Chen Feng ◽  
Wu-De Yang ◽  
Guang-Wei Ding ◽  
Hui Sun ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Biomass Estimation ◽  
Area Index

Estimation of forest aboveground biomass in California using canopy height and leaf area index estimated from satellite data

2014 ◽  
Vol 151 ◽  
pp. 44-56 ◽  
Author(s):  
Gong Zhang ◽  
Sangram Ganguly ◽  
Ramakrishna R. Nemani ◽  
Michael A. White ◽  
Cristina Milesi ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Satellite Data ◽  
Aboveground Biomass ◽  
Canopy Height ◽  
Area Index ◽  
Forest Aboveground Biomass

scholarly journals Facilitation by Tree Species in Variable Retention Harvesting for the Restoration of Monoculture Plantations in Southern China

2019 ◽  
Vol 12 ◽  
pp. 194008291882483 ◽  
Author(s):  
Jun Jiang ◽  
Yuanchang Lu ◽  
Ling Wang ◽  
Xianzhao Liu ◽  
Daoxiong Cai ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Tree Species ◽  
Soil Conditions ◽  
Target Species ◽  
Positive Interaction ◽  
Area Index ◽  
Variable Retention ◽  
Variable Retention Harvesting

Facilitation can drive the successional dynamics and change the restoration trajectory of degraded forests. However, the relative importance of facilitation by tree species after variable retention harvesting is unclear. We used a field experiment to evaluate the effect of two facilitator species, Castanopsis fissa (C. fissa) and Manglietia glauca (M. glauca), managed with variable retention harvesting, on the development of two target species, Castanopsis hystrix (C. hystrix) and Erythrophloeum fordii (E. fordii), in a Masson pine ( Pinus massoniana) monoculture. The following variables were measured for all of the four interplanted tree species: structural growth, regeneration, aboveground biomass accumulation, leaf area index, and soil conditions. The results indicate that the abundance, growth, and aboveground biomass were relatively greater in plots planted with C. fissa compared with M. glauca and that the target species performed best with 50% retention harvesting of C. fissa, with an improved establishment of both target species indicating a positive interaction. In addition, the regeneration, leaf area index and soil conditions differed between the two facilitators in the variable retention harvesting treatments because of the different intrinsic characteristic of the facilitators. In summary, our results imply that managers have considerable flexibility to employ various types of facilitation schemes coupled with different harvesting systems for successful short-term restoration within a monoculture.

scholarly journals Monitoring the nitrogen nutrition status of rice plants using spectral and image technologies

2020 ◽  
Author(s):  
Ye Chun ◽  
Liu Ji Zhong ◽  
Liu Ying ◽  
Li Yan Da ◽  
Cao Zhong Sheng ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Nitrogen Nutrition ◽  
Nutrition Status ◽  
Nitrogen Accumulation ◽  
Area Index ◽  
Plant Nitrogen ◽  
N Nutrition ◽  
Rice Plants

Abstract Background: We aimed to investigate methods to estimate the nitrogen (N) nutrition status of rice plants using data obtained using a digital camera and a spectroradiometer. The overall aim was to compare the advantages and potential of image technology and spectral technology to monitor rice N indexes accurately, inexpensively, and in real time to optimize fertilization strategies. Realizing the technical selection of definite spectrum or image diagnosis aiming at different rice nitrogen nutrition indexes. We conducted field trials of rice plants grown with different levels of N fertilizer in 2018 to 2019. Spectral information and images of the rice canopy were obtained, various image and spectral characteristic parameters were selected to construct models to estimate rice N status.Results: The determination coefficients of the models constructed using the ratio vegetation index (RVI[800,550]) and cover canopy (CC) as dependent variables were most significant. Among the models using spectral parameters, those constructed using RVI[800,550] to estimate rice N indexes had the obviously coefficient of determination (R2) values, which were 0.69, 0.58, and 0.65 for the models to estimate leaf area index(LAI), aboveground biomass(AGB), and plant N accumulation(PNA). As for image parameter, those using CC to predict rice N indexes showed the highest R2 values (0.76, 0.65, and 0.71 for the models to estimate LAI, AGB, and PNA, respectively) (P < 0.01). The model using the spectral parameter RVI[800,550] had a good fit and stability in estimating plant nitrogen accumulation (R2 = 0.65, root mean square error (RMSE) = 1.35 g·m-2, relative RMSE (RRMSE) = 14.05%), and the model using the image parameter CC had a good fit in predicting leaf area index (R2 = 0.76, RMSE = 0.28, RRMSE = 7.26%) and aboveground biomass (R2 = 0.65, RMSE = 22.03 g·m-2, RRMSE = 7.52%). Different detection technology should be adopted for different rice varieties and rice N nutrition indexes. Conclusions: Spectral and image parameters can be used as technical parameters to estimate rice N status. The spectral parameter RVI[800,550] can be used to accurately estimate plant nitrogen accumulation, and the image parameter CC can be used to accurately estimate leaf area index and aboveground biomass.

scholarly journals Optimizing nitrogen fertilizer amount for best performance and highest economic return of winter wheat under limited irrigation conditions

PLoS ONE ◽  
2021 ◽  
Vol 16 (11) ◽  
pp. e0260379
Author(s):  
Pin Zhang ◽  
Yi-kang Qi ◽  
Hong-guang Wang ◽  
Jian-ning He ◽  
Rui-qi Li ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Grain Yield ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Harvest Index ◽  
Application Rate ◽  
N Accumulation ◽  
N Application ◽  
Area Index

Inappropriate water and fertilizer management can lead to unstable crop yields. Excessive fertilization can potentially cause soil degradation and nitrogen (N) leaching. The aim of this study was to explore the optimal N application rate on two wheat varieties with different nitrogen responding under limited water irrigation at three experimental sites in the Piedmont plain of the Taihang Mountains, China. A two-year field experiment was conducted to explore the effects of five N application rates (N0, N120, N180, N240, and N300) on winter wheat growth, leaf area index, aboveground biomass, grain yield, grain N accumulation, and net return. The results showed that N application rate significantly affected leaf area index, aboveground biomass, grain yield, and harvest index. Variety and variety × N rate interactions had a significant effect on few indicators. Compared with N0, N180 improved leaf area index, aboveground biomass, grain yield, and grain N accumulation. Compared with N240 and N300, N180 increased the harvest index and N harvest index, without significantly reducing grain yield or grain N accumulation, while enhancing a higher N use efficiency. Fertilizers applied in the ranges of 144.7–212.9 and 150.3–247.0 kg ha-1 resulted in the highest net return for the KN199 and JM585 varieties, respectively. Our study provides a sound theoretical basis for high-efficiency fertilizer utilization in sustainable winter wheat production in the Piedmont plains of the Taihang Mountains of China.

Increases in aboveground biomass and leaf area 85 years after drainage in a bog

Botany ◽  
2014 ◽  
Vol 92 (10) ◽  
pp. 713-721 ◽  
Author(s):  
Julie Talbot ◽  
Nigel T. Roulet ◽  
Oliver Sonnentag ◽  
Tim R. Moore
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Aboveground Biomass ◽  
Reference Site ◽  
Carbon Sink ◽  
Tree Canopy ◽  
Optical Measurements ◽  
Leaf Biomass ◽  
Climate Change Scenarios ◽  
Area Index

Climate change scenarios suggest that northern peatlands could become drier. To address the type and magnitude of vegetation change associated with persistent drying, we studied changes in biomass and leaf area index following drainage 85 years previously of a bog, using destructive sampling, allometric relationships, and optical measurements. Our results show a 10-fold increase in aboveground biomass between the reference site and the most severely drained site, resulting from the growth of a tree layer. The total leaf biomass increased slightly as a result of drainage, thus an increase in woody biomass was the main cause of the increase in aboveground biomass. Leaf area index approximately tripled in sites where trees grew. Sphagnum L. moss biomass decreased from 120 g·m−2 at the reference site (20% of all aboveground biomass) to 8 g·m−2 under the tree canopy (<1% of all aboveground biomass). The percentage of deciduous shrubs increased from 3% of the total shrub biomass in the reference site to 72% in the most severely drained site. Our results show that lowering the water table of a bog can have a profound effect on vegetation but the net effect of these changes on the role of the peatland as a carbon sink remains difficult to assess.

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