Based on the SPOT/ NDVI data and meteorological data of Jianghuai watershed area, the temporal and spatial variation characteristics of NDVI and their correlation with climate factors (temperature and precipitation) are analyzed from 1998 to 2013 by utilizing the maximum value composite and linear regression method. The results showed that the vegetation growth has changed year by year with an overall trend in Jianghuai watershed region, and the number of pixels in the growing area accounts for 85.8% of the total. From the space point of view, expect for some regions in Hefei, Chuzhou and Luan are obviously decreasing, most of the other regions showing a growth trend. Vegetation was not positively correlated with temperature and precipitation, and the correlation between NDVI and temperature was higher than that of precipitation. Due to the differences of topography, geography and human activities, the correlation in different regions is different. In addition, human activities are also the influencing factors of vegetation change.
Desertification is a worldwide concern and the assessment of aeolian desertification has become one hotspot in global ecosystem research. In this paper, hyperspectral data acquired from modular OMIS-I imaging spectrometer, combined with ETM data and field survey data, was used to assess the aeolian desertification in Korqin Sand, Inner Mongolia, China by pixel-level. The results indicated that hyperspectral image, combined with ETM image and little field works, is capable to monitor and assess desertification through quantitative retrieval of assessing parameters directly from hyperspectral data or indirectly from the encoding map by visual interpretation of hyperspectral image and ETM image. For the retrieval of vegetation biomass and coverage, polynomial fit curve is suitable to regions where shrubs and grasses coexist, while linear fit curve is suitable to single vegetation type and was highly restricted by region. The retrieval of surface soil water content based on soil thermal inertia is suitable in flat terrain and sparse vegetation, and it can resist vegetation disturbance. The algorithms for numerical evaluation and quantitative retrieval for hyperspectral image are also practicable for aeolian desertification in Korqin Sand, China.
NPP is not only the original driver of carbon cycle, but also has significance in global change research. In this study, NPP data from GLO-PEM model and Chinese plantation data were used to explore the spatial and temporal changes of NPP in Chinese plantation area from 1981 to 2000. As the results, mean annual NPP in Chinese plantation area was about 663.37gCm-2yr-1 in the past 20 years, with higher NPP in several provinces in South China, and lower NPP in some arid and semi-arid regions in Northeast China, North China and Northwest China. NPP increased more in the eastern part of North China and in Central China and South China, but decreased in most regions of West China, North Liaoning, East Jilin and North Heilongjiang. Monthly variation of plantation NPP was mainly in phase from June to September, especially in July and August during the 4th times from 1996 to 2000, monthly NPP increased most. Mixed plantation had the highest mean annual NPP and coniferous plantation had the least. Plantation in East China had higher mean annual NPP, annual NPP increase rate and monthly NPP variation than that in West China. The increment of total annual NPP in Chinese plantation from 1980's to 1990's was 84.51×104tCyr-1. Plantation in Hainan province had the highest mean annual NPP and NPP increase, and plantation in Guangdong province had the largest total annual NPP increase in the past 20 years, but in Xinjiang province, mean annual NPP in plantation area was lowest and decreasing.
A classifier of great capabilities and a good-selection of different features are two key and difficult keys answering for a high accuracy classification result. On the classifier, although there are all kinds of algorithms, most of them couldn't be used widely because of multifarious theoretical limitations. In this paper, based on the TM data, several representative interpretation features, including original bands, texture measurements and spatial metrics, are compared systemically for landcover/landuse classification test with the same classifier and the same training samples. The results show that different feature source has different relationship with the original band and they play the different roles. Summarily, the original bands are the most useful and essential feature source and play the important role and the others can only be seen as equivalent or enhanced feature source. Among which, the texture mean have equivalent capability as that of the original bands, and the spatial metrics and other texture measurements can be seen as compensatory source. For the combination of different features, the classification accuracy can be improved by using the texture measurements or the combination with original bands. As a sort of newly features, the classification accuracy was very poor if only landscape metrics were used, comparatively the accuracy can be greatly improved by combing with the original bands. So, the combination of original bands and texture measurements is the preference for TM dataset.
Study on seasonal change of terrestrial net primary production (NPP) and its responses to climate are to help understand the responses of terrestrial ecosystem to climate change and mechanisms of annual NPP increases. In this study, GLO-PEM simulating NPP data and corresponding climate data were used to explore the seasonal changes of terrestrial NPP and their geographical differences in China from 1981 to 2000. As the results, seasonal total NPP in China showed a significant increase for all four seasons during the past 20 years. The spring NPP indicated the largest increase rate, while the summer NPP was with the largest increase in magnitude. The area of NPP increase was largest in summer, and that of NPP decrease was largest in autumn. Seasonal NPP changed differently in different regions. Increased temperature or precipitation or their comprehensive functions might contribute to the NPP increase, and decreased precipitation might answer for the decreased NPP in most regions. South China had the largest NPP increase in spring, autumn and winter and the highest NPP increase rate in autumn, North China had the largest NPP increase rate in spring and winter, while Central China had the largest NPP increase and increase rate in summer.
Artificial object identification and image classification are two basic issues in remote sensing (RS) information extraction. All kinds of methods, from the pixel-based to window-based, have been tried respectively in two domains for many years, but the accuracy is not well until now. Two obvious limitations explain the reasons. One is that the processing cell can’t correspond with the true target in the real world, and the other is the feature, which participates in the identification procedure, is far from enough to describe the intrinsical characteristics of the object of interest. During recent two years, an object-oriented classification method is put forward to supply these gaps of the conventional classification method. On the one hand, by using the segmentation technique, the pixel clusters are extracted based on their similarities to form so-called object having thematic meaning; on the other hand, vectorization of these objects is performed by integrating the GIS (geographical information system) idea into the RS which makes it possible to describe the various features of each object, such as shape information and its spatial relationship to neighboring object. In this study, the authors attempt to use this new method to artificial object identification by taking example for ship extraction with the help of one spectral feature and eight shape features. Results indicate the object-oriented classification is feasible in practice, and it opens a new way for artificial object extraction.
Based on the GLO-PEM simulation data, Net primary productivity (NPP) and its spatiotemporal patterns in Northeast China were studied from 1981 to 2000. Our research indicated that the distribution of annual NPP in Northeast China was obviously different from east to west. The averaged annual total NPP is 0.50PgC, with an annual increasing rate of 0.55%. NPP increased in most parts of Northeast China from 1981 to 2000, with the largest increase in the western part of Liaoning province, but it decreased in eastern Hulun Buir Plateau, Horqin Sandy Land, Changbai Mountains and northern Da Xingan Ling mountains. The early 1990s (1991-1995) is the time with fastest NPP increasing. NPP varies in different seasons. It increases mostly in summer, with an annual rate of 0.65%, but it decreasing in non-growing
Hyperspectral image possesses incomparable advantage over spaceborne multispectral image when it is employed to quantitatively retrieve these parameters such as vegetation type, coverage, biomass, bare soil moisture, etc. This paper focuses on crucial issues present in the pre-processing of hyperspectral image: band selection, edge radiant correction, tangent correction and spectral reflectivity conversion, exemplified by a case study in which modular airborne OMIS-I imaging spectrometer data are employed to evaluate desertification. The author gives comprehensive consideration to the statistic characteristics of each spectral band, diagnostic spectral reflection of different targets and the purpose of practical application, and fixed upon 41 applicable bands after trying different bands. In the course of edge radiant correction, one correction method based on histogram matching was used, and its result was satisfactory. In addition, tangent correction directing against tangent distortion was carried out, which enriched the normal geometric rectification. Lastly, during the process of surface feature spectral reflectivity conversion, the author converted symbolic model into statistic model by employing some necessary theoretical inference and parameter-setting. The result suggests the quality of OMIS-I data get better improved after these processing and basically can meet the requirements of quantitative retrieval for desertification evaluation.