Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-Series Remote Sensing Data and Ground Measurements

Li, Ainong; Bian, Jinhu; Lei, Guangbin; Huang, Chengquan

doi:10.3390/rs4123857

Cited by 66 publications

(45 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The LUE theory introduced by Monteith (1972) has been extensively applied because of the simplicity of its mechanisms, and the fact that it requires fewer physiological and ecological parameters, and can be easily combined with the remote-sensed data (Li et al, 2012). LUE is considered as constant for certain vegetation types or even entire eco-regions (Myneni & Williams, 1994;Turner et al, 2002).…”

Section: Light Use Efficiency (Lue) Modelmentioning

confidence: 99%

“…The LUE describes how efficient vegetation fixes solar energy. Thus, the LUE combined with remote sensing data can model the vegetation productivity on a small or large scale (Li et al, 2012).…”

Section: Introductionmentioning

confidence: 99%

“…Previously, the GIS and RS have been applied to ascertain forest habitat status (Dewan & Yamaguchi, 2009;Li et al, 2012;Reusing, 2000). The LUE theory was introduced by Monteith (1972) and later developed for further application in Remote Sensing technology.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Evaluating the Conservation Efforts of Multi-Projects Using Remote Sensing and Light Use Efficiency Model: A Case of Nyungwe Forest National Park, Rwanda

Rutebuka¹,

Zhang²,

Asamoah³

et al. 2018

OJF

View full text Add to dashboard Cite

This paper investigates the effectiveness of conservation efforts in the Nyungwe Forest National Park (Nyungwe). The forest is one of the six key landscapes identified for conservation in the Albertine Rift because it hosts many threatened species. As such, a number of different stakeholders have been involved in its conservation since 1987; yet, studies that emphasize and evaluate the success of these conservation efforts are limited. We combined a rapid and relatively low cost remotely-sensed data and the Light Use Efficiency model to generate forest conservation indicators such as NDVI, forest canopy Net Primary Productivity and carbon sequestered from 1986 to 2010. The influence of topographic and climatic factors on these indicators was examined. The supervised classifier was used to catalogue the area into Forest, Wetland, and Bareland. The forest was the major category (above 90%) of Nyungwe relative to wetland and bareland. Based on degradation intensity, two distinctive periods were realised; the first period spans 8 years (1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994) whereas the second spans 16 years (1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010). The former degradation intensity period is 10 times higher than the latter period. Although the size of forest recovered up to 90%, the daily NPP and carbon sequestration capacity decreased by 37.1% (i.e. NPP 6. (high altitude) had a higher degradation. Guided by our indicators, there is an overall success in conservation efforts, but efforts were mostly concentrated in accessible areas. Therefore, conservation efforts that aim to respond to degradation of the inaccessible areas of the forest should be stressed in the management plan of the park.

show abstract

Section: Light Use Efficiency (Lue) Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluating the Conservation Efforts of Multi-Projects Using Remote Sensing and Light Use Efficiency Model: A Case of Nyungwe Forest National Park, Rwanda

Rutebuka¹,

Zhang²,

Asamoah³

et al. 2018

OJF

View full text Add to dashboard Cite

show abstract

“…A typical wetland degradation transect in the Zoige Wetland National Nature Reserve on the Zoige Plateau, the largest high-altitude marsh area in the world, which is located in the northeast area of the Tibetan Plateau in China [26], was selected as the study area in this study (Figure 1). The transect, from the southwest to the northeast, has an obvious water gradient inducing land surface changes from the large water surface of the lake, permanent wet marshes close to the lake, a transition zone covered by meadows that are temporary inundated by water, and permanent dry grasslands ( Figure 2).…”

Section: Study Areamentioning

confidence: 99%

Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China

Xia

Zhao

et al. 2017

Remote Sensing

Self Cite

View full text Add to dashboard Cite

Abstract:Wetland inundation is crucial to the survival and prosperity of fauna and flora communities in wetland ecosystems. Even small changes in surface inundation may result in a substantial impact on the wetland ecosystem characteristics and function. This study presented a novel method for wetland inundation mapping at a subpixel scale in a typical wetland region on the Zoige Plateau, northeast Tibetan Plateau, China, by combining use of an unmanned aerial vehicle (UAV) and Landsat-8 Operational Land Imager (OLI) data. A reference subpixel inundation percentage (SIP) map at a Landsat-8 OLI 30 m pixel scale was first generated using high resolution UAV data (0.16 m). The reference SIP map and Landsat-8 OLI imagery were then used to develop SIP estimation models using three different retrieval methods (Linear spectral unmixing (LSU), Artificial neural networks (ANN), and Regression tree (RT)). Based on observations from 2014, the estimation results indicated that the estimation model developed with RT method could provide the best fitting results for the mapping wetland SIP (R 2 = 0.933, RMSE = 8.73%) compared to the other two methods. The proposed model with RT method was validated with observations from 2013, and the estimated SIP was highly correlated with the reference SIP, with an R 2 of 0.986 and an RMSE of 9.84%. This study highlighted the value of high resolution UAV data and globally and freely available Landsat data in combination with the developed approach for monitoring finely gradual inundation change patterns in wetland ecosystems.

show abstract

“…We specified the prior density function as a uniform distribution over the following ranges: ) were assigned on the basis of previous findings [32,100]. In the optimization, these parameters were assumed uniformly distributed in the given limits with equal probability for all possible values.…”

Section: Parameter Optimizationmentioning

confidence: 99%

Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales

Zhou

et al. 2015

Remote Sensing

View full text Add to dashboard Cite

Abstract:The reliable simulation of gross primary productivity (GPP) at various spatial and temporal scales is of significance to quantifying the net exchange of carbon between terrestrial ecosystems and the atmosphere. This study aimed to verify the ability of a nonlinear two-leaf model (TL-LUEn), a linear two-leaf model (TL-LUE), and a big-leaf light use efficiency model (MOD17) to simulate GPP at half-hourly, daily and 8-day scales using GPP derived from 58 eddy-covariance flux sites in Asia, Europe and North America as benchmarks. Model evaluation showed that the overall performance of TL-LUEn was slightly but not significantly better than TL-LUE at half-hourly and daily scale, while the overall performance of both TL-LUEn and TL-LUE were significantly better (p < 0.0001) than MOD17 at the two temporal scales. The improvement of TL-LUEn over TL-LUE was relatively small in comparison with the improvement of TL-LUE over MOD17. However, the differences between TL-LUEn and MOD17, and TL-LUE and MOD17 became less distinct at the 8-day scale. As for different vegetation types, TL-LUEn and TL-LUE performed better than MOD17 for all vegetation types except crops at the half-hourly scale. Remote Sens. 2015, 7 2240At the daily and 8-day scales, both TL-LUEn and TL-LUE outperformed MOD17 for forests. However, TL-LUEn had a mixed performance for the three non-forest types while TL-LUE outperformed MOD17 slightly for all these non-forest types at daily and 8-day scales. The better performance of TL-LUEn and TL-LUE for forests was mainly achieved by the correction of the underestimation/overestimation of GPP simulated by MOD17 under low/high solar radiation and sky clearness conditions. TL-LUEn is more applicable at individual sites at the half-hourly scale while TL-LUE could be regionally used at half-hourly, daily and 8-day scales. MOD17 is also an applicable option regionally at the 8-day scale.

show abstract

Estimating the Maximal Light Use Efficiency for Different Vegetation through the CASA Model Combined with Time-Series Remote Sensing Data and Ground Measurements

Cited by 66 publications

References 47 publications

Evaluating the Conservation Efforts of Multi-Projects Using Remote Sensing and Light Use Efficiency Model: A Case of Nyungwe Forest National Park, Rwanda

Evaluating the Conservation Efforts of Multi-Projects Using Remote Sensing and Light Use Efficiency Model: A Case of Nyungwe Forest National Park, Rwanda

Subpixel Inundation Mapping Using Landsat-8 OLI and UAV Data for a Wetland Region on the Zoige Plateau, China

Performance of Linear and Nonlinear Two-Leaf Light Use Efficiency Models at Different Temporal Scales

Contact Info

Product

Resources

About