The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover dens...The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover densities to their image properties according to their geographic coordinates. The principles and procedures for quantifying grassland cover density from satellite image data were presented with an example from Qinghai Lake, China demonstrating how quantification could be made more accurate through the integrated use of remote sensing and global positioning systems (GPS). An empirical model was applied to an entire satellite image to convert pixel values into ground cover density. Satellite data based on 68 field samples was used to produce a map of ten cover densities. After calibration a strong linear regression relationship (r2 = 0.745) between pixel values on the satellite image and in situ measured grassland cover density was established with an 89% accuracy level. However, to minimize positional uncertainty of field samples, integrated use of hyperspatial satellite data and GPS could be utilized. This integration could reduce disparity in ground and space sampling intervals, and improve future quantification accuracy even more.展开更多
Ecosystems can simultaneously provide multiple functions and services. Knowledge on the combinations of such multi-dimensional functions is critical for accurately assessing the carrying capacity and implementing sust...Ecosystems can simultaneously provide multiple functions and services. Knowledge on the combinations of such multi-dimensional functions is critical for accurately assessing the carrying capacity and implementing sustainable management. However, accurately quantify the multifunctionality of ecosystems remains challenging due to the dependence and close association among individual functions. Here, we quantified spatial patterns in the multifunctionality of alpine grassland on the Tibetan Plateau by integrating four important individual functions based on data collected from a field survey and remote sensing NDVI. After mapping the spatial pattern of multifunctionality, we extracted multifunctionality values across four types of grassland along the northern Tibet Plateau transect. Effects of climate and grazing intensity on the multifunctionality were differentiated. Our results showed that the highest values of multifunctionality occurred in the alpine meadow. Low values of multifunctionality were comparable in different types of grassland. Annual precipitation explained the large variation of multifunctionality across the different types of grassland in the transect, which showed a significantly positive effect on the multifunctionality. Grazing intensity further explained the rest of the variation in the multifunctionality(residuals), which showed a shift from neutral or positive to negative effects on multifunctionality across the different types of grassland. The consistently rapid declines of belowground biomass, SOC, and species richness resulted in the collapse of the multifunctionality as bare ground cover amounted to 75%, which corresponded to a multifunctionality value of 0.233. Our results are the first to show the spatial pattern of grassland multifunctionality. The rapid decline of the multifunctionality suggests that a collapse in the multifunctionality can occur after the vegetation cover decreases to 25%, which is also accompanied by rapid losses of species and other individual functions. Our results are expected to provide evidence and direction for the sustainable development of alpine grassland and restoration management.展开更多
基金supported by the National Basic Research Program of China (No. 2006CB400505) and the National NaturalSciences Foundation of China (Nos. 49971056 and 40171007)
文摘The principles of remotely estimating grassland cover density in an alpine meadow soil from space lie in the synchronous collection of in situ samples with the satellite pass and statistically linking these cover densities to their image properties according to their geographic coordinates. The principles and procedures for quantifying grassland cover density from satellite image data were presented with an example from Qinghai Lake, China demonstrating how quantification could be made more accurate through the integrated use of remote sensing and global positioning systems (GPS). An empirical model was applied to an entire satellite image to convert pixel values into ground cover density. Satellite data based on 68 field samples was used to produce a map of ten cover densities. After calibration a strong linear regression relationship (r2 = 0.745) between pixel values on the satellite image and in situ measured grassland cover density was established with an 89% accuracy level. However, to minimize positional uncertainty of field samples, integrated use of hyperspatial satellite data and GPS could be utilized. This integration could reduce disparity in ground and space sampling intervals, and improve future quantification accuracy even more.
基金The National Key Research and Development Program(2016YFC0502001)The Second Tibetan Plateau Scientific Expedition and Research(STEP)Program(2019QZKK0302)The National Natural Science Foundation of China(41671263)。
文摘Ecosystems can simultaneously provide multiple functions and services. Knowledge on the combinations of such multi-dimensional functions is critical for accurately assessing the carrying capacity and implementing sustainable management. However, accurately quantify the multifunctionality of ecosystems remains challenging due to the dependence and close association among individual functions. Here, we quantified spatial patterns in the multifunctionality of alpine grassland on the Tibetan Plateau by integrating four important individual functions based on data collected from a field survey and remote sensing NDVI. After mapping the spatial pattern of multifunctionality, we extracted multifunctionality values across four types of grassland along the northern Tibet Plateau transect. Effects of climate and grazing intensity on the multifunctionality were differentiated. Our results showed that the highest values of multifunctionality occurred in the alpine meadow. Low values of multifunctionality were comparable in different types of grassland. Annual precipitation explained the large variation of multifunctionality across the different types of grassland in the transect, which showed a significantly positive effect on the multifunctionality. Grazing intensity further explained the rest of the variation in the multifunctionality(residuals), which showed a shift from neutral or positive to negative effects on multifunctionality across the different types of grassland. The consistently rapid declines of belowground biomass, SOC, and species richness resulted in the collapse of the multifunctionality as bare ground cover amounted to 75%, which corresponded to a multifunctionality value of 0.233. Our results are the first to show the spatial pattern of grassland multifunctionality. The rapid decline of the multifunctionality suggests that a collapse in the multifunctionality can occur after the vegetation cover decreases to 25%, which is also accompanied by rapid losses of species and other individual functions. Our results are expected to provide evidence and direction for the sustainable development of alpine grassland and restoration management.
