The red-edge position (REP) was extracted from reflectance spectral data at canopy and leaf scale using six different methods in the temperate typical steppe of Inner Mongolia with relatively high species richness. The results suggested that the REPs varied with the extraction methods, sampling sites, plant species, and estimation scales. At the canopy scale, chlorophyll content (CC) was estimated with the linear extrapolation method, and the polynomial fitting technique had coefficients of determination (R 2 >0.4 ). The chlorophyll estimates at Leymus chinensis- and Stipa grandis-dominated sites were slightly better than those from the large sampling sites with multiple dominant plant species. At the leaf scale, the linear extrapolation method and the polynomial fitting technique presented high coefficients of determination (R 2 >0.6 ). CC estimated at L. chinensis-dominated sites was substantially higher than at S. grandis-dominated sites as well as the large sampling site. The results using the maximum first-derivative method and Lagrangian interpolation techniques revealed a discontinuity, whereas the REPs, as extracted by the linear interpolation method, were shifted toward longer wavelengths. The linear interpolation and inverted Gaussian method were easily saturated. The results obtained with the polynomial fitting technique and the linear extrapolation method had higher sensitivity and accuracy for estimation of CC.
The paper distinguished the impacts of land use and arid process on the Natural Potential Productivity of Cultivated Land
(NPPCL) in the North Farming - Pastoral Zone of China (NFPZC) from 1990 to 2000 with the integration of remote
sensing technique and Geographical Information System (GIS). The arid processes in NFPZC from 1970 to 2006 were
analyzed. The land use processes from 1990 to 2000 were investigated. The NPPCL in NFPZC from 1990 to 2000 were
calculated by using the Thornthwaite-Memorial model. And finally the influences of land use and arid process on the
NPPCL in NFPZC from 1995 to 2007 were distinguished by using the powerful spatial analysis function of GIS. The
main results were as follows:
(1) In spite of some climate variation, it still had an obvious arid process in the NFPZC during the past three decades.
Such arid process made the NPPCL in the NFPZC decrease 16.61 million tons from 1990 to 1995 and 19.55 million tons
from 1995 to 2000.
(2) From 1990 to 2000, cultivated land in NFPZC changed intensively. It expanded from 231907 km2 in 1990 to 238032
km2 in 1995 and 244109 km2 in 2000. Such land use process caused the NPPCL in the NFPZC increase 5.36 million tons
from 1990 to 1995 and 4.48 million tons from 1995 to 2000.
(3) Influenced simultaneously by land use and arid process, NPPCL also changed obviously in NFPZC from 1990 to
2000 with 11.24 million tons decrease during 1990 and 1995 and 15.08 million tons decrease during 1995 and 2000
respectively. Spatially, the NPPCL is sensitive to arid process in the Northwest area of NFPZC, governed by Shanxi
province, Gansu province and Ningxia autonomous region. While in the Northeast area of NFPZC governed by Hebei
province and Shanxi provinces, land use play the dominate role to influence NPPCL. It suggested that the impacts of
both the cultivated land loss and the climate change on cultivated land productivity should be simultaneously concerned
to avoid food problems in China.
Vegetation fraction, the ratio of vegetation occupying a unit area, as a significant parameter in the development of climate and ecological models, is indispensable information of many global and regional climate numerical models. It is also an important basic data of describing ecosystem. However, It is also a wasting manpower and financial resources with low-precision work to measure the vegetation fraction by fieldwork, especially in large areas. This study explores the potential of deriving vegetation fraction from normalized difference vegetation index (NDVI) using the TM data. Under the assumption that the pixel of TM image is a mosaic structure, sub-pixel models for vegetation fraction estimation have been introduced firstly. Then the idea of utility of different sub-pixel model for vegetation fraction estimation based on land cover classification is proposed. The model for vegetation fraction estimation has been established under many assumptions, and there is the complex relationship of vegetation index vegetation fraction and leaf area index, so it is unrealistic to obtain vegetation fraction with high precision. But it is helpful to improve estimation precision to some extent by probing into application of assistant information and finery parameters of model.
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