The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure...The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.展开更多
Spectral index methodology has been widely used in Leaf Area Index(LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect ...Spectral index methodology has been widely used in Leaf Area Index(LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers(SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition(VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index(NDVI), Modified Simple Ratio Indices(MSRI) and Triangle Vegetation Index(TVI), although the coefficient of determination R^2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.展开更多
Quantitative analysis of time scale effects is conducive to further understanding of vegetation water and soil conservation mechanism.Based on the observation data of the grass covered and bare soil( control) experime...Quantitative analysis of time scale effects is conducive to further understanding of vegetation water and soil conservation mechanism.Based on the observation data of the grass covered and bare soil( control) experimental plots located in Hetian Town,Changting County of Fujian Province from 2007 to 2010,the characteristics of 4 parameters( precipitation,vegetation,RE and SE) were analyzed at precipitation event,month,season,and annual scales,and then the linear regression models were established to describe the relationships between RE( SE)and its influencing factors of precipitation and vegetation. RE( SE) means the ratio of runoff depth( soil loss) of grass covered plot to that of the control plot. Results show that these 4 parameters presented different magnitude and variation on different time scales. RE and SE were relatively stable either within or among different time scales due to their ratios reducing the influence of other factors. The coupling of precipitation and vegetation led to better water conservation effect at lower RE( < 0. 3) at precipitation event scale as well as at season scale,while the water conservation effect was dominated by precipitation at slightly higher( 0. 3- 0. 4) and higher( > 0. 7) REs at precipitation event scale as well as at annual scale( R2> 0. 78). For the soil conservation effect,precipitation or / and vegetation was / were the dominated influence factor( s) at precipitation event and annual scales,and the grass LAI could basically describe the positive conservation effect( SE <1,R2> 0. 55),while the maximum 30 min intensity( I30) could describe the negative conservation effect more accurately( SE >1,R2> 0. 79). More uncertainties( R2≈0. 4) exist in the models of both RE and SE at two moderate time scales( month and season). Consequently,factors influencing water and soil conservation effect of grass present different variation and coupling characteristics on different time scales,indicating the importance of time scale at the study on water and soil conservation.展开更多
The scaling relationship between leaf area and total mass of plant has important implications for understanding resource allocations in the plant.The model of West,Brown and Enquist(WBE model)considers that a 3/4 scal...The scaling relationship between leaf area and total mass of plant has important implications for understanding resource allocations in the plant.The model of West,Brown and Enquist(WBE model)considers that a 3/4 scaling exponent of metabolic rate versus total mass to be optimal for each plant and has been confirmed numerous times.Although leaf area is a better proxy of the metabolic rate than leaf mass,few studies have focused on the scaling exponent of leaf area versus total mass and even fewer have discussed the diversification of this scaling exponent across different conditions.Here,I analyzed the scaling exponent of leaf area versus total mass of sample plots across world plants.I found that as the plant grows,it allocates fewer resources to photosynthetic tissues than expected by the WBE model.The results also empirically show that this scaling exponent varies significantly for different plant leaf habit,taxonomic class and geographic region.Therefore,leaf strategy in response to environmental pressure and constraint clearly plays a significant role.展开更多
The rapid growth and early development period of the dual-scale surface topography was studied on the adaxial leaf surfaces of two aspen tree species with non-wetting leaves: the columnar European aspen (Populus tremu...The rapid growth and early development period of the dual-scale surface topography was studied on the adaxial leaf surfaces of two aspen tree species with non-wetting leaves: the columnar European aspen (Populus tremula “Erecta”) and quaking aspen (Populus tremuloides). Particular attention was focused on the formation of micro- and nano-scale asperities on their cuticles, which was correlated with the development of superhydrophobic wetting behaviour. Measurements of the wetting properties (contact angle and tilt-angle) provided an indication of the degree of hydrophobicity of their cuticles. Scanning electron microscopy and optical profilometry micrographs were used to follow the growth and major morphological changes of micro-scale papillae and nano-scale epicuticular wax (ECW) crystals, which led to a significant improvement in non-wetting behaviour. Both species exhibited syntopism in the form of small and larger nano-scale ECW platelet morphologies. These findings provide additional support for earlier suggestions that due to fluctuations in leaf hydrophobicity throughout the growing season, canopy storage capacity may also vary considerably throughout this time period.展开更多
基金One Hundred Talents Program of CAS No.CXIOG-C00-01+1 种基金 National Natural Science Foundation of China No.39970613
文摘The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995.
基金National Natural Science Foundation of China(No.41401002)Jilin Province Science Foundation for Youths(No.20160520077JH)
文摘Spectral index methodology has been widely used in Leaf Area Index(LAI) retrieval at different spatial scales. There are differences in the spectral response of different remote sensors and thus spectral scale effect generated during the use of spectral indices to retrieve LAI. In this study, PROSPECT, leaf optical properties model and Scattering by Arbitrarily Inclined Layers(SAIL) model, were used to simulate canopy spectral reflectance with a bandwidth of 5 nm and a Gaussian spectral response function was employed to simulate the spectral data at six bandwidths ranging from 10 to 35 nm. Additionally, for bandwidths from 5 to 35 nm, the correlation between the spectral index and LAI, and the sensitivities of the spectral index to changes in LAI and bandwidth were analyzed. Finally, the reflectance data at six bandwidths ranging from 40 to 65 nm were used to verify the spectral scale effect generated during the use of the spectral index to retrieve LAI. Results indicate that Vegetation Index of the Universal Pattern Decomposition(VIUPD) had the highest accuracy during LAI retrieval. Followed by Normalized Difference Vegetation Index(NDVI), Modified Simple Ratio Indices(MSRI) and Triangle Vegetation Index(TVI), although the coefficient of determination R^2 was higher than 0.96, the retrieved LAI values were less than the actual value and thus lacked validity. Other spectral indices were significantly affected by the spectral scale effect with poor retrieval results. In this study, VIUPD, which exhibited a relatively good correlation and sensitivity to LAI, was less affected by the spectral scale effect and had a relatively good retrieval capability. This conclusion supports a purported feature independent of the sensor of this model and also confirms the great potential of VIUPD for retrieval of physicochemical parameters of vegetation using multi-source remote sensing data.
基金Supported by National Natural Science Foundation Project(41071281)Natural Science Foundation of Jiangsu Province(BK20131078)"Qing Lan Project" of Jiangsu Provincial Department of Education
文摘Quantitative analysis of time scale effects is conducive to further understanding of vegetation water and soil conservation mechanism.Based on the observation data of the grass covered and bare soil( control) experimental plots located in Hetian Town,Changting County of Fujian Province from 2007 to 2010,the characteristics of 4 parameters( precipitation,vegetation,RE and SE) were analyzed at precipitation event,month,season,and annual scales,and then the linear regression models were established to describe the relationships between RE( SE)and its influencing factors of precipitation and vegetation. RE( SE) means the ratio of runoff depth( soil loss) of grass covered plot to that of the control plot. Results show that these 4 parameters presented different magnitude and variation on different time scales. RE and SE were relatively stable either within or among different time scales due to their ratios reducing the influence of other factors. The coupling of precipitation and vegetation led to better water conservation effect at lower RE( < 0. 3) at precipitation event scale as well as at season scale,while the water conservation effect was dominated by precipitation at slightly higher( 0. 3- 0. 4) and higher( > 0. 7) REs at precipitation event scale as well as at annual scale( R2> 0. 78). For the soil conservation effect,precipitation or / and vegetation was / were the dominated influence factor( s) at precipitation event and annual scales,and the grass LAI could basically describe the positive conservation effect( SE <1,R2> 0. 55),while the maximum 30 min intensity( I30) could describe the negative conservation effect more accurately( SE >1,R2> 0. 79). More uncertainties( R2≈0. 4) exist in the models of both RE and SE at two moderate time scales( month and season). Consequently,factors influencing water and soil conservation effect of grass present different variation and coupling characteristics on different time scales,indicating the importance of time scale at the study on water and soil conservation.
文摘The scaling relationship between leaf area and total mass of plant has important implications for understanding resource allocations in the plant.The model of West,Brown and Enquist(WBE model)considers that a 3/4 scaling exponent of metabolic rate versus total mass to be optimal for each plant and has been confirmed numerous times.Although leaf area is a better proxy of the metabolic rate than leaf mass,few studies have focused on the scaling exponent of leaf area versus total mass and even fewer have discussed the diversification of this scaling exponent across different conditions.Here,I analyzed the scaling exponent of leaf area versus total mass of sample plots across world plants.I found that as the plant grows,it allocates fewer resources to photosynthetic tissues than expected by the WBE model.The results also empirically show that this scaling exponent varies significantly for different plant leaf habit,taxonomic class and geographic region.Therefore,leaf strategy in response to environmental pressure and constraint clearly plays a significant role.
文摘The rapid growth and early development period of the dual-scale surface topography was studied on the adaxial leaf surfaces of two aspen tree species with non-wetting leaves: the columnar European aspen (Populus tremula “Erecta”) and quaking aspen (Populus tremuloides). Particular attention was focused on the formation of micro- and nano-scale asperities on their cuticles, which was correlated with the development of superhydrophobic wetting behaviour. Measurements of the wetting properties (contact angle and tilt-angle) provided an indication of the degree of hydrophobicity of their cuticles. Scanning electron microscopy and optical profilometry micrographs were used to follow the growth and major morphological changes of micro-scale papillae and nano-scale epicuticular wax (ECW) crystals, which led to a significant improvement in non-wetting behaviour. Both species exhibited syntopism in the form of small and larger nano-scale ECW platelet morphologies. These findings provide additional support for earlier suggestions that due to fluctuations in leaf hydrophobicity throughout the growing season, canopy storage capacity may also vary considerably throughout this time period.
