[Division of winter wheat yield estimation by remote sensing based on MODIS EVI time series data and spectral angle clustering].

Crop yield estimation division is the basis of crop yield estimation; it provides an important scientific basis for estimation research and practice. In the paper, MODIS EVI time-series data during winter wheat growth period is selected as the division data; JiangSu province is study area; A division method combined of advanced spectral angle mapping(SVM) and K-means clustering is presented, and tested in winter wheat yield estimation by remote sensing. The results show that: division method of spectral angle clustering can take full advantage of crop growth process that is reflected by MODIS time series data, and can fully reflect region differences of winter wheat that is brought by climate difference. Compared with the traditional division method, yield estimation result based on division result of spectral angle clustering has higher R2 (0.702 6 than 0.624 8) and lower RMSE (343.34 than 381.34 kg x hm(-2)), reflecting the advantages of the new division method in the winter wheat yield estimation. The division method in the paper only use convenient obtaining time-series remote sensing data of low-resolution as division data, can divide winter wheat into similar and well characterized region, accuracy and stability of yield estimation model is also very good, which provides an efficient way for winter wheat estimation by remote sensing, and is conducive to winter wheat yield estimation.

[Evaluation of remote sensing extraction methods for vegetation phenology based on flux tower net ecosystem carbon exchange data].

Taking the vegetation phenological metrics derived from the net ecosystem carbon exchange (NEE) data of 72 flux towers in North America as the references, a comprehensive evaluation was conducted on the three typical classes of remote sensing extraction methods (threshold method, moving average method, and function fitting method) for vegetation phenology from the aspects of feasibility and accuracy. The results showed that the local midpoint threshold method had the highest feasibility and accuracy for extracting vegetation phenology, followed by the first derivative method based on fitted Logistic function. The feasibility and accuracy of moving average method were determined by the moving window size. As for the MODJS 16 d composited time-series normalized difference vegetation index (NDVI), the moving average method had preferable performance when the window size was set as 15. The global threshold method performed quite poor in the feasibility and accuracy. Though the values of the phenological metrics extracted by the curvature change rate method based on fitted Logistic function and the corresponding ones derived from NEE data had greater differences, there existed a strong correlation between them, indicating that the vegetation phenological metrics extracted by the curvature change rate method could reflect the real temporal and spatial variations of vegetation phenology.

[Winter wheat area estimation with MODIS-NDVI time series based on parcel].

Several attributes of MODIS (moderate resolution imaging spectrometer) data, especially the short temporal intervals and the global coverage, provide an extremely efficient way to map cropland and monitor its seasonal change. However, the reliability of their measurement results is challenged because of the limited spatial resolution. The parcel data has clear geo-location and obvious boundary information of cropland. Also, the spectral differences and the complexity of mixed pixels are weak in parcels. All of these make that area estimation based on parcels presents more advantage than on pixels. In the present study, winter wheat area estimation based on MODIS-NDVI time series has been performed with the support of cultivated land parcel in Tongzhou, Beijing. In order to extract the regional winter wheat acreage, multiple regression methods were used to simulate the stable regression relationship between MODIS-NDVI time series data and TM samples in parcels. Through this way, the consistency of the extraction results from MODIS and TM can stably reach up to 96% when the amount of samples accounts for 15% of the whole area. The results shows that the use of parcel data can effectively improve the error in recognition results in MODIS-NDVI based multi-series data caused by the low spatial resolution. Therefore, with combination of moderate and low resolution data, the winter wheat area estimation became available in large-scale region which lacks completed medium resolution images or has images covered with clouds. Meanwhile, it carried out the preliminary experiments for other crop area estimation.

[Effects of Prostate Water Pellets on the number of colonies, NO concentration and NOS activity in the prostate tissue of CBP rats].

OBJECTIVE: To investigate the effects of Prostate Water Pellets (PWP) on the number of colonies, NO concentration and NOS activity in the prostate tissues of rats with chronic bacterial prostatitis (CBP). METHODS: A total of 120 healthy adult male Wistar rats weighing 250-300 g were equally randomized into 6 groups: blank control, model control, positive control, high-dose PWP, medium-dose PWP and low-dose PWP. The CBP rat models were established by injecting colibacilli (10(7)/ml) into the prostate. A month later, the high- , medium- and low-dose PWP groups were treated intragastrically with PWP at 4.4 g/kg, 2.2 g/kg and 1.1 g/kg per day respectively, the positive controls with levofloxacin at 0.018 g/kg per day, and the blank and model controls with normal saline, all for 35 days. Then the numbers of colonies in the prostate tissues were measured, and the changes in NO concentration and NOS activity detected by the nitrite reductase method. RESULTS: Compared with the model controls, the number of colonies, NO concentration and NOS activity were significantly reduced in the prostate tissues of the rats of the high- , medium- and low-dose PWP groups (P < 0.01). CONCLUSION: PWP was proved to be efficacious for CBP in rats, whose mechanism might be related with its inhibitory effect on bacterial growth and decreasing effect on NO concentration and NOS activity in the prostate tissues.

[Farmland parcel extraction based on high resolution remote sensing image].

A new method of farmland parcel extraction from high resolution remote sensing image based on wavelet and watershed segmentation was proposed in the present paper. First, classification results were used to enhance the contrast of gray-scale value of typical pixels in the original image using the high resolution remote sensing image's spectral information. Second, wavelet transform and watershed segmentation were applied to the enhanced image, then improved region merger algorithm was used to solve the problem of over-segmentation. Finally, inverse wavelet transform was taken to get the reconstructed image, then Canny operator was introduced to add the edge information, and the result of farmland parcel segmentation was obtained. To validate the proposed approach, experiments on Quickbird images were performed, we rapidly extracted the farmland parcel from the test image, and the results had a high accuracy. Despite it had a lot to do in extracting the small size parcels, on the whole the method this paper proposed had a very good robustness. Compared with the traditional methods, it had the following advantages: (1) it was an automatic extraction method, did not need too much manual intervention, and could extract the large area of farmland parcels accurately and effectively. (2) It was a very good solution to the problem of over-segmentation by using improved region merger algorithm, and improved the accuracy of the extraction. All these indicated that the proposed approach was an effective farmland parcel extraction method based on high resolution remote sensing image.

[Estimation of vegetation coverage based on an improved sub-pixel model].

Vegetation coverage is an important parameter in terrestrial ecological process, meteorological, and climatic models. By eliminating the errors from the precision of image classification and the noises of remote sensing images, and by using the actual data from fieldwork, this paper determined the maximum and minimum values of normalized difference vegetation index (NDVI), improved the sub-pixel model, and verified this model by calculating the vegetation coverage of Beijing. The results showed that the estimation value of the improved model was very close to the measurements, especially for the herbaceous plants whose vegetation types were the same but the densities were different. However, the estimation error of arborous vegetation coverage was relatively large, probably due to the effects of remote sensing image resolution, vegetation fragmentation, and mixed pixel model.

[Biomass structure analysis of Atractylodes lancea in different ecological environments].

OBJECTIVE: To study the ecological environments of Atractylodes lancea by biomass structural analysis. METHOD: Through the scientific investigation in Maoshan, the sampling spots were set up, the relation between growth and ecological environments was researched and the ecological environments of A. lancea were divided as following: the vegetation layer, the shrub layer, the shrub-weed layer and the weed layer. The ramet biomass, height, leaves and coverage of A. lancea were studied. RESULT: The several factors (ramet biomass, height, leaves and coverage) showed the regular change. Among maximum, minimum and average, the shrub layer was the biggest, the shrub and weed layer was the second biggest and the vegetation layer and the weed layer was the least. CONCLUSION: A. lancea tends to distribute in the shrub layer and the shrub-weed layer.

[Analysis in distribution of Atractylodes lancea at Maoshan regions].

OBJECTIVE: To Investigate the distribution of Atractylodes lancea at Maoshan regions. METHODS: To combine the plot sampling with GIS technology in the analysis of distribution and its factors. RESULTS: The biomass of Atractylodes lancea was related to the growth of Ouercus serrata var. brevipetiolata, slope and humidity. The distribution of Atractylodes lancea which was less in north Maoshen region, most in south region, least in middle region. CONCLUSION: The main factor of distributing sintuation is the human beings. The leading factors in the biomass of Atractylodes lancea are Ouercus serrata var. brevipetiolata and slope.

[Comparing of different methods on habitat adaptive division of Chinese material medica].

OBJECTIVE: To comparing two kinds habitat adaptive division of Chinese material medica with different models. METHOD: The habitat adaptive divisions of A. lancea according essential oil accumulation with two kinds pattern, model pattern and template pattern were carrid and compared. RESULT: Two habitat adaptive divisions of A. lancea maps according essential oil accumulation were gotten. CONCLUSION: Both model pattern and template pattern were efficient on habitat adaptive division of Chinese material medica, but they shoud bu used with different processesd and based different background [corrected]

[Remote sensing resource monitoring on Atractylodes lancea].

Remote sensing technology was used for investigation of the resources of Atractylodes lancea. Firstly, the general situation of Jiangshu Maoshan and A. lancea in Maoshan was introduced; Secondly, the methods of remote sensing on the resource of the wild drugs were explained. Thirdly, the TM images were interpret according to the differences of the objects reflex spectrum, and growth environments in Damao mountain, Ermao mountain and Xiaomao mountain were divided into different sub-areas according to the results of the field investigations. Finally, the resource of A. lancea in Jiangshu Maoshan was estimated.

[Study on dynamical changes of Ginkgo biloba resources in Pizhou city of Jiangsu Province base on RS and GIS].

OBJECTIVE: To analyse the dynamical changes of the Ginkgo biloba's resources from 2001 to 2006, in Pizhou city, Jiangshu province by useing spatial analytical function of GIS and RS technology. METHOD: Use the GIS and RS technology, extracted the information of G. biloba by scientific investigation, researched the spatial distribution and dynamical changes of G. biloba based on landsat 5 TM: the Apr. 3rd, 2001; Jan. 16th, 2005; July 30th, 2006. RESULT: Ginkgo biloba's resource was 1.61 x 10(5) hm2 in 2001, 1.84 x 10(5) hm2 in 2005, 1.88 x 10(5) hm2 in 2006. CONCLUSION: Ginkgo biloba's resource rised from 1.61 x 10(5) hm2 to 1.88 x 10(5) hm2 from 2001 to 2006, showed the gradually rise.

[Remote sensing monitoring methods for medicinal plants resource in different types of ecological environment].

Different remote sensing monitoring methods are needed for the medicinal plant resource in different types of ecological environment. This paper explained remote sensing monitoring methods for the resource of the wild medicinal plants and cultivated plants, and analyzed the rare species, generous species and species in special ecological environment in detail. It provides a new method to all kind of medicinal plants resources' remote sensing monitoring.

[Optimizing management on degraded grassland in Xilin River Basin based on ecological risk assessment].

By the methods of remote sensing (RS) and geographic information system (GIS), and based on the estimations of degradation degree, risk degree and easy-restoration degree of degraded grasslands, an ecological management index (EMI) model of grassland was established to approach the practical ways of optimizing management of degraded grassland. A case study in the Xilin River Basin of Inner Mongolia showed that this model could quantitatively analyze the degradation degree, risk degree and easy-restoration degree of the grasslands under different optimizing management levels, which was of significance for applying rational measures with pertinence, and beneficial to the optimal allocation of resources during the management of degraded grassland. The EMI model could integrate most concerned information, which made it applicable widely.

[Measurement and dynamic analysis of ecological capital of terrestrial ecosystem in China].

Based on remote sensing and ecological principles, an estimation model of ecological capital was established in this paper. The estimation showed that the ecological capital of terrestrial ecosystem in China was 8.148, 10.86 and 12.44 trillion yuan (RMB) in 1992, 1995 and 2000, respectively. Forest had the highest value (24 673 yuan x hm(-2)), and followed by wetland (21 353 yuan x hm(-2)), both of which gave the most contribution to the ecological capital. According to its spatial distribution, the ecological capital of terrestrial ecosystem in China descended from east to west, and ascended from middle to northeast and south of this country, which was accordant with the vegetation distribution. Owing to the climate change and human activity, the ecological capital of Chinese terrestrial ecosystem ascended from 1992 to 2000, and the spatial distribution of its largest value moved obviously from north to south, with a total change rate of about 20%. However, the ratio between ecological capital and GDP descended significantly in the 1990s.