Limits...
Identification of land-cover characteristics using MODIS time series data: an application in the Yangtze river estuary.

Zhang MQ, Guo HQ, Xie X, Zhang TT, Ouyang ZT, Zhao B - PLoS ONE (2013)

Bottom Line: However, these methods often have a mathematical basis, and more effort is required to better illustrate the ecological meanings of land-cover characteristics.Improvement was also made in parameter extraction, inspired by a method used for determining the hyperspectral red edge position.Five land-cover types were chosen to represent various ecosystem growth patterns and MODIS time series data were adopted for analysis.

View Article: PubMed Central - PubMed

Affiliation: Coastal Ecosystems Research Station of the Yangtze River Estuary, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai, PR China.

ABSTRACT
Land-cover characteristics have been considered in many ecological studies. Methods to identify these characteristics by using remotely sensed time series data have previously been proposed. However, these methods often have a mathematical basis, and more effort is required to better illustrate the ecological meanings of land-cover characteristics. In this study, a method for identifying these characteristics was proposed from the ecological perspective of sustained vegetation growth trend. Improvement was also made in parameter extraction, inspired by a method used for determining the hyperspectral red edge position. Five land-cover types were chosen to represent various ecosystem growth patterns and MODIS time series data were adopted for analysis. The results show that the extracted parameters can reflect ecosystem growth patterns and portray ecosystem traits such as vegetation growth strategy and ecosystem growth situations.

Show MeSH

Related in: MedlinePlus

Diagram of parameter extraction from time series vegetation index (VI) data.Blue points represent time points separating different vegetation growth stages, while red points are parts of the extracted parameters.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3722099&req=5

pone-0070079-g003: Diagram of parameter extraction from time series vegetation index (VI) data.Blue points represent time points separating different vegetation growth stages, while red points are parts of the extracted parameters.

Mentions: The time at which aboveground biomass reaches its maximum (MT, a date) was first identified. MT was extracted by extrapolating two straight lines across the time points that discriminate phenological stages (Fig. 3). This process was inspired by a technique used in hyperspectral analysis, which stabilizes the red edge position when there are multiple peaks in the first derivative curve of hyperspectral data [19]. The EVI2 extracted on day MT was used to represent the maximum vegetation coverage (VImax, dimensionless). If MOD09Q1 data were missing for that day, VImax was linearly interpolated between the previous and following data.


Identification of land-cover characteristics using MODIS time series data: an application in the Yangtze river estuary.

Zhang MQ, Guo HQ, Xie X, Zhang TT, Ouyang ZT, Zhao B - PLoS ONE (2013)

Diagram of parameter extraction from time series vegetation index (VI) data.Blue points represent time points separating different vegetation growth stages, while red points are parts of the extracted parameters.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3722099&req=5

pone-0070079-g003: Diagram of parameter extraction from time series vegetation index (VI) data.Blue points represent time points separating different vegetation growth stages, while red points are parts of the extracted parameters.
Mentions: The time at which aboveground biomass reaches its maximum (MT, a date) was first identified. MT was extracted by extrapolating two straight lines across the time points that discriminate phenological stages (Fig. 3). This process was inspired by a technique used in hyperspectral analysis, which stabilizes the red edge position when there are multiple peaks in the first derivative curve of hyperspectral data [19]. The EVI2 extracted on day MT was used to represent the maximum vegetation coverage (VImax, dimensionless). If MOD09Q1 data were missing for that day, VImax was linearly interpolated between the previous and following data.

Bottom Line: However, these methods often have a mathematical basis, and more effort is required to better illustrate the ecological meanings of land-cover characteristics.Improvement was also made in parameter extraction, inspired by a method used for determining the hyperspectral red edge position.Five land-cover types were chosen to represent various ecosystem growth patterns and MODIS time series data were adopted for analysis.

View Article: PubMed Central - PubMed

Affiliation: Coastal Ecosystems Research Station of the Yangtze River Estuary, Ministry of Education Key Laboratory for Biodiversity Science and Ecological Engineering, Institute of Biodiversity Science, Fudan University, Shanghai, PR China.

ABSTRACT
Land-cover characteristics have been considered in many ecological studies. Methods to identify these characteristics by using remotely sensed time series data have previously been proposed. However, these methods often have a mathematical basis, and more effort is required to better illustrate the ecological meanings of land-cover characteristics. In this study, a method for identifying these characteristics was proposed from the ecological perspective of sustained vegetation growth trend. Improvement was also made in parameter extraction, inspired by a method used for determining the hyperspectral red edge position. Five land-cover types were chosen to represent various ecosystem growth patterns and MODIS time series data were adopted for analysis. The results show that the extracted parameters can reflect ecosystem growth patterns and portray ecosystem traits such as vegetation growth strategy and ecosystem growth situations.

Show MeSH
Related in: MedlinePlus