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Vitex negundo is the native shrub species which was very popular in low mountain area of Taihang Mountains. It is widely used in such aspects as mountain greening, soil and water conservation, and ecological restoration due to its characteristics of strong resistance, and tolerance to barrenness. Studying on the water consumption of Vitex negundowas could not only reveal its water consumption dynamics and influencing mechanism, but also provide theoretical basis for local vegetation restoration and management. The water consumption of Vitex negundo and meteorological factors were measured with large weighing lysimeter and the automatic weather station, respectively. At the same time, reference evapotranspiration (ET0) was calculated by the Penman-Monteith equation recommended by FAO-56. The objective of the paper was to study the water consumption of Vitex negundo on different time scales, to find the adaption capacity to the arid environment, to reveal the relationship with ET0, and to provide empirical model for estimating the water consumption of Vitex negundo under the conditions of lacking measured data. The results showed that: (1) diurnal variation of water consumption of Vitex negundo showed single peak curve on typical days, which was consistent with solar radiation, air temperature, and vapor pressure deficit, but contrary to the relative humidity. Meanwhile, the peak time of water consumption of Vitex negundo. was 2 hours behind that of solar radiation, and time lag was found between them. Water consumption trendy of Vitex negundo on daily time scale showed low water consumption in the early and later growth period, and high in the middle growth period, and the value was 1.50mm, 2.00mm, and 4.00mm per day, respectively. Maximum and minimum of daily water consumption was found on 29th in August and 9th in October, with the value of 6.38mm and 0.20mm, respectively. The water consumption of Vitex negundo on monthly time scale showed the tendency of August >July > September > October> June > May. The total water consumption of Vitex negundo during the growth period was 513.5mm, and the rainfall was 526.6mm. The precipitation could meet the needs of water consumption Vitex negundo from the perspective of water balance. However, seasonal drought existed from May to June due to the less rainfall. (2) Vitex negundo has the feature of environmental adaptability and ecological plasticity. In rainy seasons, Vitex negundo was in prosperous growth period, the water transmission rate was high, and the water consumption was large. Adaptive mechanism started in arid season to reduce water consumption. (3) Good logarithmic relationship was found between daily water consumption of Vitex negundo and reference evapotranspiration in rainy seasons (July to October), while poor correlation was discovered between them in dry seasons (May to June). The estimated value of water consumption was calculated with the fitting equation, and was compared with the measured valued by the lysimeter. The good consistency and small error were found between the estimated and measured values, which conformed the precision of the fitting equation. It was indicated the fitting equation was accurate to estimate water consumption of Vitex negundo in rainy seasons of the local area, but inaccurate in dry seasons. [ABSTRACT FROM AUTHOR]

Solar radiation is an important parameter affecting light and thermal environment in solar greenhouse. Accurately obtaining the solar radiation value and variation of the interior wall and ground in the greenhouse can play an important guiding role in greenhouse design, construction, environmental regulation and crop production. On the basis of summarizing the previous models of solar radiation, a relatively perfect solar radiation model of solar greenhouse was established in this paper. Meteorological data, the laws of the earth and the movement of the sun, and the relationship between the sun's rays and the angle of the front roof were all considered in this solar radiation model. Internal radiation change of the greenhouse was analyzed based on the model. The model was verified in typical sunny days. The results showed that there were some differences between the calculated and measured solar radiation values, the MBE(mean bias error) was 63.46 W/m2, the MAE(mean absolute error) was 63.48 W/m2, the RMSE(root mean square error) was 79.18 W/m2 and the coefficient of determination R2 was high, ranged from 0.95 to 0.99. The model can be used to calculate the solar radiation intensity of the wall and the ground of solar greenhouse in any area anytime. Highly accurate analysis of the radiation change and the variation of light transmittance in the greenhouse in different seasons were achieved in this paper. It was found that the light transmittance is more affected by the solar azimuth and the solar elevation angle than by the roof angles at different positions. The solar radiation on the surface of the wall and the ground in greenhouse changes with the seasons. The spring equinox and autumn equinox are the days in which the wall and the ground received the longest solar radiation during the year. At this time, the surface of the wall is roughly equivalent to the solar radiation on the ground. From the spring equinox to the autumn equinox, the ground radiation is higher than the surface radiation, while it is opposite when it comes from the autumnal equinox to the vernal equinox. The daily accumulation of solar radiation on the wall changed little from the winter solstice to the start of spring, decreased from the start of the spring to the summer solstice and rose from the summer solstice to the start of winter. The time from winter to the start of the spring is the main production season in the greenhouse, and the heat accumulation of the wall is also the highest in the whole year. Therefore, it is of great significance to carry out research on the heat storage at this stage. Solar radiation in greenhouses in different regions is mainly affected by latitude. In lower latitudes, the amount of solar radiation in winter is large and the amount of radiation in summer is small. The research results can provide reference and related data for the study of wall heat storage, roof optimization, crop planting and energy balance of envelope in solar greenhouse. In addition, the change rule of solar radiation in greenhouse was analyzed just under clear and cloudless conditions. For the plant canopy shade, radiation under different weather conditions, insulation quilt position, different rear roof incline angles and lengths, azimuth angles, wall inclined angle and other aspects of the solar radiation change inside the greenhouse can be further explored by the method proposed in this paper. [ABSTRACT FROM AUTHOR]

Morphological characteristics of gully cross section are important in reflecting environmental factors of the development of the gully and understanding the mechanism of the gully erosion. Gully volume is a key parameter representing gully erosion amount, and the estimation model of the gully volume is the basic issue in the research of gully erosion. However, it has been rarely published as to characterizing gully cross section and modeling gully volume for the hilly loess region of western Shanxi Province, which has restricted the survey and evaluation of the regional soil erosion. The aim of this paper was to explore the features of the gully cross section, and to build a model to assess the gully volume with gully parameters that may be determined by high resolution satellite images. In this research, a 3-D (three-dimensional) laser scanner (TOPCON IS-IMAGING STATION) was used to measure the parameters of 31 dissected valleys, and an interval between 2 measurement points was set as 0.15 m. Then the DEM (digital elevation model) with the pixel size of 0.15 m × 0.15 m was created based on Delaunay triangulate irregular network (TIN) using ArcGIS 10.1. The morphological parameters were extracted from DEM and finally the volume, gully length, gully area, top width, bottom width, depth and cross-sectional area were calculated. The results showed that the maximum, minimum and average values of the gully top width were 19.8, 4.8, and 9.0 m, respectively; those of gully bottom width were 15.0, 0.4, and 3.8 m, respectively; those of gully depth were 10.9, 2.5, and 6.2 m, respectively; and those of cross-sectional area were 9.7, 139.2, and 41.8 m2, respectively. The values of top width, bottom width, depth and cross-sectional area at the gully mouth were higher than that at the gully head and middle, and, sequentially, there was no significant difference except the depth among gully head, gully middle and gully mouth with one-way analysis of variance (ANOVA). The ratio of gully top width to depth ranged between 0.37 and 5.0, with an average of 1.55, which was greater than 1, indicating the gully-wall collapsing was faster than the deep-cutting erosion. Among gully head, gully middle and gully mouth, the minimum value of the ratio of gully top width to depth was in the gully head. The regression analysis showed that there was a very prominent relationship of power function between gully volume and gully length, gully area, and the determination coefficients of the regression equation were 0.68 and 0.85, respectively, indicating the gully length and the gully area can be used to estimate the gully erosion rate at the large spatial scales because they can be easily determined from very high-resolution satellite images. The relative error and Nash-Sutcliffe efficiency between the measured and predicted gully volumes suggested that the gully volume-area relationship had a better predictive ability for the gully volume, and therefore the corresponding equation can be used to assess the gully volume in the hilly loess region of the western Shanxi Province. The results in this paper have a number of potential applications in modeling and mapping the gully erosion over a large scale, and will be critically helpful in the assessment of the soil and water conservation. [ABSTRACT FROM AUTHOR]

The microscopic images from leaf slices of Caragana stenophylla Pojark are inevitably corrupted by noise in obtaining, which will have a negative effect on its subsequent processes. The unpitched sound is usually treated as an additive Gaussian sound in order to denoise the natural images. It has not yet been known whether the unpitched sound and the additive Gaussian sound display the same distribution. The choice of the unpitched sound model will determine the estimation on its noise level and its subsequent choice of the denoising algorithm. BM3D (block-matching and three-dimensional filtering) is universally regarded as the best denoising algorithm, since it keeps the maximum information about texture, border, and other details of the image while denoising effectively. But the speed of BM3D is limited owing to too much calculation and its practical use is also limited because it needs the noise variation as a pretested input. SVD (singular valuable decomposition) is one of the best denoising algorithms but the noise of the image and its information can not be completely separated. The type of image, the level of the noise, and the change of color all affect the validity of the algorithm. This paper proposed a process, involving the estimation on the image type, the noise level and the algorithm of denoising, to solve the problems mentioned above and to denoise the microscopic images from leaf slices of Caragana stenophylla Pojark. The noise type was recognized as Gaussian noise by the rebuilding and fitting of the smooth histogram domain. The values, abstracted from the smooth histogram domain of 15 randomly selected microscopic images from leaf slices of Caragana stenophylla Pojark, were fitted with the Gaussian function, with the R2 value of 0.996 and the RMSE (root mean squared error) value of 0.144 6. And then the standard deviation of the noise was estimated via the estimation on noise level with the help of SVD domain image block. In the algorithm estimation, an initial estimative value was obtained from the SVD domain image block with the smallest entropy, and a more accurate value was got from its subsequent self-adapting correcting of the algorithm values. A two-step simulation experiment proved that this algorithm was much better in speed and accuracy in denoising than the other two estimation algorithms. When the standard deviation of noise was lower than 10, the proposed algorithm had the best accuracy; when the standard deviation of noise was higher than 10, this algorithm had the same accuracy with the estimation method of sliced image noise level, but had a better accuracy than SVD. This paper got a standard deviation of the image noise of between 2.5 and 4.0 for its estimation on the microscopic images from leaf slices of Caragana stenophylla Pojark. The image was denoised via GMF-BM3D, a joint algorithm by GMF (geometric mean filtering) and BM3D. GMF was used to denoise the background of images and then BM3D was applied to denoise the target area. Experiments proved the algorithm introduced in this paper was good at denoising and remaining detailed information of the image, such as border and texture, with a much greater speed. The average value of the BRISQUE (blind/referenceless image spatial quality evaluator) of the processed image was 10, equivalent to half of that of the original image. The algorithm also had an equivalent effect in denoising with the traditional BM3D, but eight ninths of time was saved. It was better than WT (wavelet threshold) denoising in BRISQUE, which was lowered by about 4. Therefore, the algorithm in this paper accurately denoises the microscopic images from leaf slices of Caragana stenophylla Pojark and provides a reliable technical support for its subsequent image processing. [ABSTRACT FROM AUTHOR]

For estimating aerosol optical thickness* many constructed attributes from remote sensing data generally are used as inputs for a regression model. However, there might he noisy and correlated attributes in heterogeneous high dimensional inputs. They lead to the loss of estimation accuracy and reduction of robustness. To solve the problem, this paper proposed a feature selection approach by integrating Least Absolute Shrinkage Selection Operator (LASSO) and remote sensing priori knowledge. We validated our approach based on the spatial temporal synchronization data between MODIS and 197 global observation sites in the aerosol robotic network during April 2* 2009 and April 1. 2011. Back propagation neural networks are used as regression models. The experimental results showed that the proposed feature selection approach can group remote sensing attributes according to remote sensing knowledge and effectively select informative features from groups gradually by an iterative LASSO procedure. In this way. the proposed approach significantly improves the estimation accuracy of aerosol optical thickness. [ABSTRACT FROM AUTHOR]

Automatic target detection of immature mangoes on the trees is one of the key steps of early estimation or intelligent spraying of mangoes. In orchard scenes, it is extremely difficult to detect immature mangoes because of variability of light, complex background and high color similarity between mangoes and leaves. Especially, detection of occluded and overlapped mangoes is a challenging task. An immature mango detection model based on improved YOLOv2 with high speed and accuracy was proposed. By introducing dense connectivity pattern into Tiny-yolo, Tiny-yolo network with dense blocks (Tiny-yolo-dense) was designed. And the dense block was used to replace the 7thconvolutional layer with low-resolution feature map in Tiny-yolo to avoid adding more extra computational complexity. In the dense block, each layer receives the feature-maps of all preceding layers and passes on its own feature-map to all subsequent layers, which improves flow of information, and encourages feature reuse and multi-level features fusion. To overcome the difficulty of occluded or overlapped mango detection, foreground region samples of occluded or overlapped fruits were manually labeled, and then the foreground region samples were used to train YOLOv2 model. Feature extraction only for foreground region can avoid extracting redundant feature of non-target region in bounding box, which can enhance feature learning from foreground region of occluded or overlapped fruits. The steps of our work were stated as follows: Firstly, to reduce the influence of natural lighting variations on mango images, adaptive histogram equalization was used to improve the quality of training sample images and the variety of illumination. And foreground region and bounding box of training samples were manually labeled. The original training set including 3 702 bounding box labels of all mango targets and 1 077 foreground region labels of occluded or overlapped fruits from 660 images was constructed, and testing set for model validation including 1 713 bounding box labels of mango targets from other 300 images was also set up. In addition, training data size was augmented by horizontal flipping and multi-angle rotating according to the variety of suspension postures of mangoes. Image rotation with angles of ±10° and ±20° was used for data augmentation. And then, Tiny-yolo-dense was applied as a basic network to design the improved YOLOv2 for the mango detection. Moreover, by higher resolution inputs and multi-scale strategy, foreground region and bounding box of training samples were used to train improved YOLOv2 network. Every 10 batches, the present training scale was exchanged randomly by another one before continuing training. In this paper, input scale of 512×512 and training scales of {384, 416……672} were selected. Lastly, the trained networks were used to detect mango on testing set. The experimental results showed that the proposed algorithm had better performance for mango detection in natural scenes. At a detection rate of 83 fps, the precision rate reached up to 97.02%, and the recall rate reached up to 95.10%. Our algorithm was 11 times faster than the Faster RCNN(circular convolutional neural network), and achieved better detection performance in condition of complex scenes with occlusion and overlapping of mangoes. Moreover, our method also significantly outperforms YOLOv2 and Adaboost classifier based on HOG(histogram of oriented gradient) features. Our work provides an effective method to quickly detect mango under orchard scenes. [ABSTRACT FROM AUTHOR]

[ Objective ] This paper aimed to test the application of GF-1 remote sensing images for estimating soil organic matter content. [ Method] Taken the fanning area soil of Fuvu city as tested samples, the organic matter contents of soil samples in laboratory tests were detected, the correlation of GF-1 band reflectance and transforming form with the content of soil organic matter were analyzed to determine organic matter sensitive bands, the spectral estimation models of a single band or multi band of soil organic matter content were established, and the area estimation model of the optimal content of soil organic matter in the study was chosen compared with the accuracy and stability of these estimation model. [ Result] The GF-1 band reflectance had a significantly negative correlation with organic matter content and reached the maximum value in the third band, the correlation coefficient was -0. 805 , and the RMS error was 0. 362; The reflectivity of power index would transform and could effectively improve the correlation with the content of organic matter, its correlation coefficients were increased to -0. 886 and -0. 872, and root mean square error decreased to 0. 283 and 0. 342 ; The 3 yuan to establish reflectance index transformation estimation model,model determination coefficient( R2 ) reached 0. 851 , and the RMS error of test samples was reduced to 0. 172 , which indicated that this model had a high accuracy, good stability estimation. [ Conclusion] The GF-1 remote sensing image could be used as a remote sensing data source for estimating soil organic matter content and would provide a reference for the study of GF-1 remote sensing image estimation of soil components. [ABSTRACT FROM AUTHOR]

As a major part of agroforestry ecosystem, windbreaks play an important role in agroforestry ecosystem. Porosity is one of the most important structural parameters and usually used to the study of the wind protection of windbreaks. However, a small amount of investigation data and the high cost limit the extension of the related studies. It is desired to have a rapid and cost-effective method of identifying and mapping structural parameters of windbreaks on a large field scale. With the characteristics of high spatial resolution and repetition observation, remote sensing technology helps to fill in gaps of field investigation. In this paper, the porosity was described and estimated by using high-resolution satellite imagery. First, 11 parameters describing windbreaks structure characteristics were summarized. They were average tree height, average tree crown length, average crown breadth, width of windbreak, aboveground biomass, volume, density of biomass volume, leaf area index, gap fraction, the product of average tree crown length and leaf area index, and the product of average tree crown length, leaf area index and width of windbreak. A variable with the highest correlation with the porosity was selected by using statistical analysis and then the porosity estimation model was established. The results indicated that variable combining the average tree crown length, leaf area index and width of windbreaks was highly related to the porosity and the correlation coefficient was -0.941. The average prediction accuracy of statistical model was 85.413%. First, the average tree crown length, leaf area index and width of windbreaks were estimated by using remote sensing data, respectively. The average tree crown length was estimated by using the first principal component of GF-1 data with the average prediction accuracy of 82.788%. The leaf area index was estimated by using the ratio vegetation index with the prediction accuracy of 84.159%. The width of windbreaks was identified by using the object-based image analysis (OBIA) approach. Then, the porosity was calculated by using these 3 variables obtained from the high-resolution satellite imagery. The estimated results indicated that there was a good agreement between the estimated values and the measured data. Following this method, the porosity of windbreaks was estimated, and at the same time its spatial distribution in the study area was obtained. Generally, the windbreaks with a high porosity have more pores, and it indicates that more wind can pass through the windbreak and wind reduction is less effective. According to this, the porosity as a good indicator was used to evaluate the barrier shelter effect. According to the estimated porosity value, the windbreaks were grouped into 3 types, i.e. dense (porosity less than 20%), medium (porosity ranging from 20% to 50%) and sparse (porosity larger than 50%), and the efficiency of wind protection was evaluated. The result showed that the main type of windbreaks was the medium and its area occupied 60.733% of the total area of the windbreaks in study area. Medium type windbreaks usually have the optimum efficiency of wind protection. This study can provide useful guide to wind protection of windbreaks based on remote sensing technology. [ABSTRACT FROM AUTHOR]

Reference crop evapotranspiration (ET0) is an important part of water cycle and water balance. Accurate estimation of ET0 becomes vital in planning and optimizing irrigation schedules and irrigation systems management. Numerous methods have been proposed for estimating ET0, among which Penman-Monteith (P-M) model recommended by Food and Agriculture Organization of the United Nations (FAO) in 1998 since it provids the highest accurate results across the world wherever in an arid or humid environment. But the main problems computing ET0 by P-M model are its complicated nonlinear process and requirements of many climatic variables. Thus, there is an urgent need to develop a much simpler and more appropriate model in areas with limited data, such as the Hargreaves-Samani (HS) method, which is modified in this paper. In order to obtain more accurate HS model of ET0 in hilly area of central Sichuan Basin, 3 parameters(including temperature index, temperature coefficient and temperature constant) were calibrated based on Bayesian Theory using daily meteorological data from 1953 to 2002. Then, the daily and monthly ET0 from 2003 to 2013 were computed by the modified HS model, original HS model and PM model. Compared with the value recommended by FAO (the temperature index, temperature coefficient and temperature constant are 0.0023, 0.5 and 17.8, respectively), the 3 parameters obtained from the modified HS model were much smaller, and increased by latitude (0.00213, 0.46 and 16.5 in north zone, 0.00217, 0.44 and 16.36 in central zone, 0.00212, 0.44 and 16.21 in south zone). The ET0 calculated by PM model was taken as the standard, the relative error of modified HS model decreased form 14.2%-60.9% to -1.1%-33.4% in north, 40.6%-92.6% to 16.9%-61.1% in central, 31.3%-96.0% to 8.5%-64.4% in south, and 32.1%-82.7% to 9.5%-52.6% in whole hilly area of central Sichuan Basin. Through the correlation analysis, the slope of regression curve between ET0 calculated by PM model and ET0 calculated by modified HS model were 1.16 in north (R² = 0.91), 1.02 in central (R² = 0.88), 0.99 in south (R² = 0.88), and 1.13 in whole hilly area of central Sichuan Basin (R² = 0.91), respectively. The trend analysis based on monthly ET0 showed that the trend of ET0 based on modified HS model was the same as that from PM model, which performed as the downwards Quadratic parabola in one year but increasing slightly in years from 2003 to 2013. The relative error of ET0 obtained from the modified and original HS model was above zero, and the former was smaller. Therefore, the modified Hargreaves-Samani model based on Bayesian Theory is more adaptive and accurate, and can be used as a simple method for the calculation of ET0 in hilly area of central Sichuan Basin. [ABSTRACT FROM AUTHOR]

Plastic mulching film plays an important role in development of agriculture. However, a series of problems such as pollution of plastic film residue left in the field occur. It is required to make a reasonable assessment on film mulching and rationally utilize it. Based on its application, this study proposed a concept of crop safety period of plastic film mulching, and its estimation methods. Crop safety period through plastic film mulching means the appropriate choice of a photo-selective mulch film according to the transplant season, to the pedoclimatic conditions of the area under cultivation and, finally, to the type of crop. In the days before the transplant, the plastic mulching film should be basic whole, and it works to decrease soil moisture evaporation, to warm soil and to prevent weeds. Successively, these functions almost reduce. The selection of crop safety period of plastic film mulching is helpful to manage agricultural activities efficiently; guiding film makers to produce both meet the demand of production and lower cost of plastic products; to help farmers due to the types of crop and production conditions choosing appropriate plastic mulch film. Based on measurement of function of plastic film mulching, and crop canopy density, 2 kinds of method were established. The first one is to continuously monitor soil moisture, temperature and weed control, to build relationship between the function of soil temperature, moisture, weed suppression and mulching treatments, with that to seek the intersection of them. The coincidence point means functions disappear of plastic mulching and the days from starting mulching to this date is a certain crop safety period in a certain site. The second is crop canopy density to determine crop safety of plastic film mulching period, which includes 2 steps: to measure the change of crop canopy density, and the functions (soil temperature and moisture etc.) of mulching under no mulching and mulching at same time, to establish the curve of crop canopy density and the main function of plastic film in order to cross the best condition between crop canopy density and the contribute of mulch films aimed to the determination of the ideal crop safeguard period. All in all, plastic mulching film has been widely used in global, especially in China, in the past 30 years, and its application area and efficacy works better than any other agronomic practices. Concept of crop safety period of plastic film mulching has been firstly proposed in this paper, and further research in the connotation and extension of its definition still need to be developed. Moreover, the mentioned estimation methods around crop safety period of plastic film mulching showed some usefulness in cotton in Xinjiang, corn in Northeast and tobacco in southwest planting, but more extensive research, application and improvement were needed by far. The findings from this research provide an important information base for improving adaptability evaluation system of plastic mulching film, investigating the spatial pattern of plastic mulching film utilization, and biodegradable plastic film production and application. [ABSTRACT FROM AUTHOR]

Little reports focus on estimating soils with organic matter content smaller than 2% using hyperspectral data. However, it is important for desert soils where most soil organic matter is low. Due to low organic matter content (<2%) in deserts soil, it is difficult to identify spectral features of soil organic matter and to determine sensitive bands. Therefore, this study aimed to establish a method for organic matter content of desert soils using Hyperspectral data. Thirty-two soil samples were collected from the Eastern Junggar Basin, China. The soil organic matter of these samples was determined. Meanwhile, the reflectance of samples was measured. The correlation between soil spectrum and its organic matter content was analyzed. Twenty-four of 32 samples was used for establishing hyperspectral models of estimating deserts soil organic matter content (SOMC) and the other 8 samples was for model verification. The results showed all the soil samples had the organic matter content <2%, in agreement with the study requirement here. Through comparing with response bands of soil organic matter with its content of 2% above, we found that spectral sensitive region 640-790 nm for deserts soil organic matter <2% was most sensitive. The correlations between reflectance spectra, inverse-log spectra (log (1/A)) and SOMC were low. Their correlations were improved after conducting the first-order differential and second-order differential transformation on soil spectra data. The correlation of partial spectrum bands by F test was significant (p<0.01). Thus it could be used to estimate deserts SOMC. The accuracy of linear regression model was rather low (R2<0.60) and not suitable to estimate deserts SOMC. Compared to the linear regression model, the R2 of second-order differential model and inverse-log second-order differential model based on multiple stepwise regressions was increased by 0.22 and 0.21, respectively, and their RMSE were decreased by 0.66 and 0.88, respectively. As such, the estimation accuracy of multiple stepwise regression models was higher than that from the linear regression model. Compared with the multiple stepwise regression models, the R2 of first-order differential model and second-order differential model based on partial least square regression was increased by 0.07 and 0.04 but the RMSE was reduced by 0.11. Therefore, the second-order differential model based on partial least square regression was the optimal model among the 12 estimation models established in this paper. For both multiple stepwise regressions and partial least square regression, the second-order differential estimation model was best in all the estimation models established. Therefore, the estimation of deserts SOMC using multiple stepwise regressions was feasible. The results here provide valuable information for hyperspectral remote sensing analysis on deserts soil organic matter, realize timeliness and accuracy of monitoring deserts soil organic matter, and helps with regional ecological environment restoration. [ABSTRACT FROM AUTHOR]

The solar radiation at different points within a solar greenhouse is not only an important parameter for the simulation of crop photosynthesis and transpiration, but also an essential factor for wall energy balance in a solar greenhouse. In this paper, the shadowing effect of a solar greenhouse enclosure structure on solar radiation was analyzed, and the preventing-view's angle of any points within a solar greenhouse was calculated by using the main parameters of a solar greenhouse and the solar azimuth. Any point could be obtained by direct solar radiation if the preventing-view's angle was smaller than the solar altitude. A hypothesis is that any point obtains isotropic diffuse solar radiation form the sky, diffuse solar radiation was calculated by accumulating the non-preventing- view's angle .Based on these analyses, the direct solar radiation, diffuse radiation, and the total solar radiation at any points within a solar greenhouse on sunny days were estimated. The estimated values at certain points within a solar greenhouse were compared with measured values at that point, which were measured within a Liaoshen II type solar greenhouse. The estimated values were higher than the measured values by 6.4% and 8.8% respectively for scatter radiation and total radiation, and the possible reasons that caused estimated errors were discussed. Results showed that the daily variation of estimated direct solar radiation, diffuse solar radiation, and total solar radiation tended to agree with that of the measured values, and the estimated values overestimated the measured values. The estimated errors maybe resulted from an error of the atmospheric transparency coefficient, transmittance of solar greenhouse plastic film, shadowing of load-bearing framework, and artificial observation errors. Using software surfer 8.0, a total radiation distribution map at 2 m was provided on 2011-12-24 at 10:00 within the greenhouse. At this height, the width was 7.05 m, and the length was 60 m. Total radiation had a decreasing trend from north to south. The shadow parts meant no direct radiation. The research results can supply theoretical solar radiation at different points within a solar greenhouse for the simulation of crop and transpiration, distribution of light within crop canopy, and energy balance of an enclosure structure in a solar greenhouse. [ABSTRACT FROM AUTHOR]