The acquisition of such agricultural information as crop growth and output is of great significance for the development of modern agriculture. Recently, the techniques of remote sensing (RS) and geographic information system (GIS) have been widely used to estimate the crop yield and, as a result, a set of practical yield estimation methods are put forward. The yield estimation methods mainly include the yield estimation method combined with relative secondary data, the yield estimation method based on vegetation index, the yield estimation method based on the specific models, and the development of crop yield estimation platform (software). Among these means, the yield estimation method based on vegetation index is divided into two categories, i.e., the single vegetation yield estimation method and the multiple vegetation index yield estimation method. A few crop yield estimation methods are analyzed in this paper based on studying many recently published papers in this field, and the advantages and disadvantages of each method are reviewed. In addition, the orientations for further research in this field are discussed and forecast so as to provide some valuable references for researchers in this field.

Traditional hyperspectral image band grouping and reordering algorithms based on Prim require calculating the correlation coefficients between all bands, and full rank correlation coefficient matrix is used as the adjacent matrix for comparison, which causes high computational complexity. Combining the similarity measurement of fuzzy mathematics theory with the characteristics of the hyperspectral image, the maximum and minimum closeness(MMC)which possesses the characteristics of less computation is used as a parameter for measuring the correlation of the hyperspectral image bands. Then the adjacent matrix of MMC is processed into a sparse matrix and the effective bands is extracted for reordering. In this way, the number of bands used for ordering and the required times for band comparison will be significantly reduced. Experimental results show that, compared with the traditional Prim algorithm, the proposed algorithm greatly reduces the calculation complexity of the hyperspectral image band ordering while maintaining compression efficiency, and the average running time for band ordering has been reduced by 27%.

Owing to relatively serious irregular geometric deformation of the whole image, it is difficult to simulate the deformation property of the whole large HJ satellite image by using the global model. Neither the global nor the local calibration model based on traditional manual selection of the ground control point(GCP)is suitable for geometric accurate rectification of the large HJ satellite image, and hence the authors proposed an optimization local model of geometric rectification method for calibrating HJ satellite remote sensing image after selecting GCPs with the algorithm of features from accelerated segment test(FAST). This method can be described as follows: First, plenty of GCPs are automatically obtained based on FAST algorithm; Then, a polynomial model is employed to analyze and evaluate the points' matching ratio between non-matching GCPs and actual GCPs in the RMSE threshold with the correlation analysis method; In addition, the total error GCPs' numbers are calculated according to the analysis of the results and the choice of appropriate root-mean-square error threshold to eliminate error GCPs; Finally, the rectification is completed with local model of Linear Rubber Sheeting. Besides, the authors have established a criteria system which is suitable for the registration result by evaluating HJ satellite remote sensing image, including residuals scatter plot, spatial interpolation method and so on. The evaluation results show that the error of calibrated HJ satellite remote sensing image can be restricted within 1.5 pixels, and the calibrated image meets the requirements of mid-resolution's application satisfactorily.

From the shadow processing of high-resolution aerial remote sensing images, this paper analyzed the features of shadow in color space. Using combined thresholds of 3 channels in HIS color space and Gaussian function, the authors detected shadow area and its multi-scale geometric details which can compensate shadow area. The experiments prove that this method can maximize the retention of the original features in shadow area and get more reasonable compensation results, thus ensuring accuracy and reliability of the follow-up imaging.

Extracting road edge information from remote sensing image can simplify the conventional urban road mapping work. Based on the general road image features, this paper proposes a dual-threshold SSDA (sequential similarity detection algorithm) template matching method in an image processing model. And on the basis of the general SSDA, another algorithm is presented to reduce the excessive number of samples responsible for the error growth. Compared with other algorithms, this algorithm can more effectively access the road edge information extraction. As for some parts of the road which cannot be completely extracted through pretreatment process, the detection results can be corrected to reduce treatment, and hence the processing efficiency will be improved.

To solve the change detection problem of multi-channel remote sensing images, this paper proposes a method based on iterative estimation with weight selection (IEWS) and unsupervised classification (UC). Firstly, the primary change information is obtained according to the concept of IEWS, and the iteration scheme of the estimation is also similar to that of the iteratively re-weighted multivariate alteration detection (IRMAD). And then, the primary change information is classified by the UC and processed by the IEWS, which can get the eventual change information. The experimental results with multi-spectral data indicate that the method proposed in this paper is effective. By using this method, the spatial coherence between the change information and the change of land use/cover in this area is good. As for the detection of change in small regions, the method is especially obviouely better than the commonly-used methods of multivariate alteration detection (MAD) and IRMAD.

This paper presents a model for extracting water from remote sensing by using empirical mode decomposition(EMD)and fractal theory. The authors tried to improve accuracy with spectral information and texture characteristics. Principal component analysis was carried out on the image to obtain the biggest first principal component that contains effective information, then the fractal dimension of each pixel was calculated; at the same time, the first principal component was decomposed with the method of EMD to get the first three empirical mode functions, which, coupled with the original band information, served as the research data. With the method of maximum likelihood classifier, the waters were extracted. This method fully combines the advantages of EMD method in noise reduction and the advantage of fractal theory in texture information extraction. Experiment shows that this method can effectively improve the extraction accuracy, with the Kappa up to 0.932 5.

The development of high spatial resolution remote sensing makes it possible to describe the urban fringe landscape pattern at the small scales by using remote sensing images. In this study, focusing on the method for integrating describing landscape patch mosaic, continuum and connectivity characteristics, the authors tried to set up a Delaunay-Voronoi hybrid landscape model based on high spatial resolution imagery object-based analysis. This method was also compared with the traditional pixel aggregation method. The result shows that the image segmentation method can well preserve the tiny critical landscape characteristics and postpone their disappearance during the pushing-up of the scale, and that Delaunay-Voronoi-based data structure is suitable for representing the hybrid landscape model and its multi-scale analysis.

The classification accuracy of superpixel-based conditional random fields(CRFs) model greatly depends on segmentation scale parameters, which constitutes a problem that should be solved. Therefore, to answer the question "whether a pixel-based CRFs model performs well in HSR image classification with m level spatial resolution or not",the authors proposed a pixel-based CRFs model with the association term defined as an output of random forests classifier and the interaction potential defined as Potts function weighted by contrast function, and the definition of association and interaction terms adopted multi-cue features such as histogram of gradient, multi- scale and multi-direction Texton filter and multi-spectral information from HSR imagery. Finally, the proposed model was trained using piecewise training method and inferred using α-expansion algorithm based on graph cut. Experiments on a typical urban scene from QuickBird multi-spectral satellite imagery have shown that the proposed RF-CRFs model shows the classification accuracy of over 82.52%. In addition, the classification accuracy of the model is higher than that of the RF classifier by 3.35% on average.

Based on mini-tree models, the authors constructed forest stands with different distributions to measure bidirectional reflectance factor (BRF) by a mini goniometer. The results show that the observed BRF of simulated forest canopies is reasonable and inter-compared with a three-dimensional BRF model. The reflectance in different view directions indicates a typical "bowl" shape in the near-infrared band, with significant "hot spot" effects in solar principal plane. The study has confirmed that mini-tree models can be applied to the research on forest BRF. The comparisons between different spatial distributions and terrain conditions of tree models demonstrate that forest density and slope have certain effects on forest BRF. Therefore, their features and regularity can contribute to the inversion of the land surface parameters through modeling.

ZY-3 and Landsat8 are new satellites lunched recently. In terms of the two kinds of images acquired by the two satellites, the applicability evaluation of the common fusion methods is insufficient. In this paper, the adaptability evaluation of the 6 fusion methods including wavelet transform(WT), Gram_Schimdt transform(G-S), principal component analysis (PCA), Pansharp and HIS for ZY-3 and Landsat8 image fusion was discussed, and the spectral information fidelity and spatial information integration were used to evaluate the quality of image fusion. The results of quality evaluation show that, in terms of spatial information integration, IHS transform is the best, followed by PCA, Brovey, G-S and WT, and Pansharp is the worst transform for ZY-3 image; G-S transform is the best, and Pansharp is the worst transform for Landsat8 image. Nevertheless, in terms of spectral information fidelity, PCA transform is the best, followed by IHS, G-S and Brovey, and WT is the worst transform for ZY-3 image, G-S transform is the best, followed by Pansharp and Brovey, and IHS, WT and PCA are worse transforms for Landsat8 image.

SPOT6 is a new remote sensing satellite launched in 2012,with the characteristics of high spatial resolution and strong acquisition capability. However, a complete data preprocessing technology for the regulation of land resources has not yet been formed. According to the characteristics of SPOT6 satellite images, four different image fusion methods of Gram-Schmidt, HPF, Pansharp and PanSharpening were selected to conduct the experiment of comparison by using the software platforms of ENVI, ERDAS and PCI. For evaluating the results' performances, the authors compared them in three aspects. The image quality of experiment results was evaluated qualitatively and also assessed quantitatively by establishing evaluation indexes including mean,standard deviation,information entropy,average gradient and correlation coefficient. The application result of fused images was evaluated based on the evaluation of the classification accuracy. The analytical results show that these algorithms would work in different ways and could be used in different applications. The results achieved by the authors can provide the technical support for application of SPOT6 image to the land resources management.

This paper introduces a program called landsat ecosystem disturbance adaptive processing system (LEDAPS) for the image stacks creation of the atmospherically corrected Landsat dense time series standard products from 1987 to 2011. Landsat images were first calibrated to top-of-atmosphere (TOA) reflectance by using solar zenith, Sun-Earth distance, TM or ETM⁺ bandpass, and solar irradiance (using the MODTRAN solar output model). The interpolated aerosol optical thickness (AOT) which was interpolated spatially between the "dark dense vegetation (DDV)" using a spline algorithm, ozone, atmospheric pressure, and water vapor were supplied to the 6S radioactive transfer algorithm to convert TOA reflectance into ground surface reflectance for each 30 m pixel. The algorithm was applied to the LEDAPS standard data of Landsat7 ETM⁺ and non-standard data of Landsat5 TM to illustrate the data choice, data format unification and the algorithm implementation of the dense Landsat time series. Finally, a method for the validation of the corrected images was provided. The results show that the surface reflectance products resulting from the LEDAPS processing could effectively reduce the influence caused by ozone, water vapor, and aerosol particles in the atmosphere on the true image surface reflectance. The surface reflectivity is more precise and provides standard products for multiple scientific applications, such as land cover change or forest disturbance dynamic characterization and remote sensing based biophysical parameters retrieval, thus beneficial to formulating criteria for processing sequence image data in China.

With the popularization of high resolution remote sensing data of domestic satellite in such fields as land resources, geology, and environment, domestic high-resolution remote sensing data are likely to become the preferred data source for monitoring the development status of mining areas in the near future. Using the ZY-1 02C and GF-1 images, the authors designed an integrated solution for geodatabase building of remote sensing images, image processing, geometric correction, information extraction, spatial calculation, statistical analysis, and final mapping production, and successfully applied such means to the related work in Tibet. The results achieved by the authors can increase the depth and scope of the application of the domestic satellite remote sensing data, and provide technical support and paradigms for large-scale and multi-period dynamic remote sensing monitoring of mines.

At present, the aerial photographic quality inspection still uses the traditional method to check the digital frame images' quality, which prints the digital images on paper first and then checks them manually. The method greatly limits the advantages of digital aerial photography. This paper presents a fully digital aerial photographic quality inspection method, whose whole process is fully completed on computer. Firstly, index images are used to complete the image quality inspection, Then the aerial photography flight quality inspection software and airborne POS (position and orientation system) data are employed to check such quality factors as overlap, swing angle, strip deformation, and flying height, Finally, relevant documentation is collated and prepared according to the results. In order to verify the reliability and scientificalness of this method, the authors selected the manual quality inspection results of Hengyang area in Hunan Province to make comparison and analysis. The results show that this method can actually reflect the flight quality of aerial photography, is in good consistency with manual results, and has some other advantages such as simple operation, high efficiency and low cost.

Multi-track InSAR measurements provide the potential for 2D and 3D displacement field retrieval and are commonly applied to coseismic deformation and earthquake source parameters estimation. Actually it is not possible to estimate 3D displacement vector since we can't generate 3D observations for the same area. Joint analysis of ascending and descending PSInSAR data enables the retrieval of vertical and horizontal displacement according to the sensitivity of InSAR measurements in different directions. In this paper, the authors made an experimental study of vertical and horizontal displacement retrieval by joint analysis of ascending and descending PSInSAR data. A novel model has been adopted to estimate vertical and east-west displacement with the ascending and descending data. The retrieval displacement indicates that the difference between ascending and descending PSInSAR measurements is not clear and the single track PSInSAR can be well applied to subsidence monitoring.

The spatial distribution of the crown structure has important significance in forestry. Although fractal dimensions is a typical method for analyzing the spatial distribution, it has some defects. In this paper, a method for calculating lacunarity with simulated and real point clouds data for tree crowns is proposed. This method was developed using 3D convex hulls and 3D gliding-box algorithm. Lacunarity differences from different crowns were analyzed in detail. The application of the extension was also demonstrated using ground-based light detection and ranging (LiDAR) points for four tree crowns in the field. The results show that the differences between tree crowns can be revealed by lacunarity, and that lacunarity can be a potential measure for the classification of three-dimensional crown shapes using LiDAR point clouds.

Airborne laser scanning (ALS) data have been used to construct the digital terrain model under dense vegetation, but its reliability for recognition ground fissures in the tropics remains unknown. In this paper, Langshitan located in Lengshuijiang City was selected as the study area, and the method for extracting ground fissures and analyzing micro-topography features based on airborne LiDAR point cloud data in the dense vegetation were studied. First, the point clouds were separated into ground points and non-ground points through adaptive TIN filter method, elevation filter, echo intensity difference filter, to ensure that the bare-earth reserved micro-topography features in the dense vegetation. Second, on the basis of ground data, triangulated irregular network was built to generate digital elevation models by inverse distance weighted interpolation; afterwards, ground fissures identification parameters could be extracted, and then linear detection could be performed by the method of minimum curvature. Finally, ground fissures stability was analyzed by the profile information of LiDAR and identification parameters. The results achieved by the authors have shown that qualitative and quantitative identification parameters extracted by the LiDAR data can determine the location, slope and aspect as well as length and depth information of ground fissures and, on such a basis, ground fissures stability can be determined by the profile information of identification parameters and micro-topography features. It is thus proved that DEM constructed by ground points and low vegetation points could reserve micro-topography features.

To explore the role of Chinese single polarization SAR data in auto-recognition of manganese slag pools and improve recognition accuracy for manganese slag pools coupled with optical data, the authors chose confusing goals with manganese slag pools in the optical image, and analyzed qualitatively their scattering properties and the difference in SAR and optical images. Based on the results of analysis, the authors carried out the research on auto- identification of manganese slag pools. The optical image was segmented using object-oriented approach. The authors selected the typical manganese slag pools and confusing objects in optical image, and calculated the texture characteristics of the samples. The experiment results show that manganese slag pools recognition rules in the SAR image could be established effectively through SAR texture features, and this provides the basis for the realization of the combination of radar data with optical SAR data for automatic identification of manganese slag pools on computer.

A joint analysis of ascending and descending tracks of PSInSAR provides deformation measurements with average velocity and time series of each coherent target for the same deformation zone, which allows the inter-comparison of the velocity map and the fusion of deformation time series. In this paper, the authors present the method of PSInSAR measurement inter-comparison and time series fusion by using ascending and descending ENVISAT data acquired from 2006 to 2010 for the purpose of subsidence monitoring. The inter-comparison of subsidence velocity in ascending and descending tracks demonstrates that the precision is higher than 2 mm, indicating the accuracy of single track PSInSAR measurement for land subsidence monitoring. The fusion of ascending and descending deformation series of each coherent target enables a detailed analysis of temporal behaviors because it provides dense observations in time.

This paper focuses on soil moisture retrieval study based on the measurements from the microwave radiation imager (MWRI) on board China's second-generation polar-orbiting meteorological satellite (FY-3). The advanced integral equation model (AIEM) was used to simulate FY-3B/MWRI radiance data for multiple surface parameters, and a soil moisture retrieval model is built based on the simulated radiance data. The model was used to retrieve bare soil moisture from four imageries acquired respectively on October 8th and 18th and 28th and November 8th in Northwest China. The retrieved soil moisture were evaluated by measured data. The results show that the determination coefficient between the retrieved and measured soil moistures is 0.604, the RMSE is 0.030 5 cm³/cm³, and hence the retrieved soil moisture is in good agreement with the measured data.

With TM remote sensing data and topographic data as the main data sources, coupled with other statistical information obtained in the upper reaches of Minjiang River, the authors tried to apply the analytic hierarchy process(AHP) to reframing the vulnerability characteristics resulting from complicated factors and establishing the comprehensive evaluation index system and the model with multiple objective elements. Vegetation index change rate, population density, terrain relief, slope and soil type were five factors serving as evaluation index factors in the AHP to determine the weight of each evaluation index, and superimposition analysis of the indicators was made on the ArcGIS platform. The grade map of comprehensive evaluation on ecological environment in the reaches of the Minjiang River could be obtained, which was classified into five degrees in the environmental vulnerability. The results achieved by the authors indicate that environmental vulnerability of the upper reaches of the Minjiang River is extremely intense, caused mainly by natural factors and human factors. The results of his study provide the quantitative and qualitative scientific basis for the construction of the environmental vulnerability pattern and the comprehensive evaluation of ecological environment along the upper reaches of the Minjiang River basin.

Using remote sensing methods to assess regional ecological change can achieve a long cycle and immediate results. The authors employed remote sensing eco index (RSEI) method to monitor the erosion of the ecological changes, with Changning City as the study area. 1990, 2002 and 2009 Landsat TM remote sensing images were chosen as data sources, from which 4 ecological factors were extracted, i.e., green degree, humidity degree, heat degree and dry degree, as indicators of evaluation model. Combined with principal component analysis, the authors quantitatively and objectively assessed regional ecological changes in the past 20 years. The results show that remote sensing Eco Index (RSEI) method seems to be a good method for evaluating the effect of ecological restoration in soil erosion area. It is proved that RSEI eco-index value increased by 22.39%; nevertheless, excellent level of eco-area ratio decreased from 13.086% in 1990 to 4.006% in 2002 and then rose to 16.699% in 2009, which indicates that the ecological quality of this region has been greatly improved after 20 years' soil erosion control. Through the investigation and analysis of Changning City, the authors have found that main prevention measures, such as afforestation and construction, have exerted greater effects on the improvement of the ecological quality.

Urban construction and expansion constitute an inevitable process during the social-economic development, but urban development has some adverse impacts on regional ecosystems which cannot be ignored, particularly in fragile and sensitive wetland areas. In this paper, with the Nansi Lake and the surrounding three counties as the study area and on the basis of remote sensing (RS) data and geographic information system (GIS), the authors analyzed the land use and land cover change and the changes of eco-vulnerability from 1987 to 2010, and investigated the relationship between the urbanization and regional ecological fragility. The results show that, from 1987 to 2010, the growth of urban areas accounted for more than 60% of the effective regional landscape changes, and the largest regional eco-loss landscapes were water bodies and green fields, with the most obvious changes of ecological vulnerability occurring at the lakeside of the Nansi Lake.

The corridor effect is produced by transportation networks and gradually decreases from the central axis outwards, following the law of distance attenuation. The corridor effect of the traffic network on urban land use is arousing more and more attention. However, most people believe that the transportation network is mainly composed of rail and road networks, but they do not take metro into account, which is actually an increasing important transport way for people. In this paper, Panyu District in Guangzhou City was chosen as the study area. By using GIS and RS, the corridor effect of Guangzhou metro was analyzed. First, the authors made buffer for subway lines and subway stations with distance of 500 m, 1 000 m and 2 000 m. And then, the land use information in the distance was extracted. Finally, the results and statistics were displayed. The results show that so far the land-use corridor effect along Panyu metro line has not yet been obvious, but the corridor effect can be found around Panyu metro stations.

In this paper, the methods of Theil-Sen and Mann-Kendall were used to calculate land degradation intensity and trend in Central Asia in the past 14 years based on SPOT-Vegetation remote sensing data. In combination with the elevation value, the impacts of human activities on land degradation were analyzed. The result shows that the city zone around two deserts (Kalakum desert and Kyzylkum desert) and the saline-alkali land in the west of Kazakhstan are regions suffering from most serious land degradation. The city zone around two deserts has excessively emphasized the development of economy and thus damaged the environment. And because of the natural conditions, saline-alkali land in the west of Kazakhstan has degraded significantly. Vegetation around the sea and lake, in the interior desert and in he region under the snow line has tended to increase, which coincides with previous studies of global warming and the tendency that the climate in Central Asia has gradually turned to warm wet. Climate change has caused ice melting. The regions which are not suitable for vegetation growth, such as the region in higher elevation and desert, are now growing vegetation. However, in these region, vegetation is largely desert vegetation, which can't be utilized and does not help promote economic development, thus of little significance to humans. On the whole, the human survival environment is still deteriorating. At the same time, vegetation around the deserts has increased a lot, which suggests that people have paid attention to the environmental problem and implemented some environmental engineering projects and windbreak and sand fixation projects.

The discovery of the Ga'erqiong Cu-Au deposit is an important breakthrough of ore prospecting in western Bangong Lake-Nujiang River metallogenic belt. There are two types of orebodies discovered in this area: One is skarn type, and the other is structure-fracture zone type. Previous studies in this area noticed the genetic relation between granite porphyry and skarn. The authors hold that the Ga'erqiong area has a relatively large ore potential of porphyry deposits. In this paper, based on multi-spectral remote sensing data and aimed at finding new porphyry deposits, the authors carried out the interpretation of linear structure, circular structure, gossanand wall rock zoning, and conducted the extraction of ferric alterations and hydroxyl alterations by using principal component analysis method. The results show that there are NW-NNW trending, NE-NNE trending and nearly SN-trending linear structure groups developed in the study area. Circular structures can be classified into five circular structure systems according to the combined styles. Gossans are comparatively in agreement with mineralized alterations. The wall rocks are rather complicated, but they are favorable for copper mineralization in the Ga'erqiong copper deposit. It is considered that the circular structure systems are the key areas for further ore prospecting.

The 2008 Wenchuan earthquak led to fatal secondary geological disasters in the Yingxiu-Maoxian segments along the Minjiang River. Through using multi-phase high-resolution airborne remote sensing data obtained after the earthquake in combination with interpretation signs of various geohazards, we can analyze the distribution regularity and development tendency of earthquake secondary geohazards quickly and accurately,which is of great significance in guiding reconstruction of the disaster area scientifically. The distribution regularity of secondary geohazards finds expression in the following aspects: 1 avalanche, landslide and landslide-avalanche (the transition type between the landslide and avalanche) constitute the main types, with landslide-avalanche taking up over 90%; 2 the geohazards are widely distributed on the both slopes of the Minjiang River in the Yingxiu-Maoxian segment,but their scales and intensities are much larger in the Yingxiu-Maoxian segment than in the Wenchuan-Maoxian segment. Through continuous dynamic monitoring of the secondary geohazards after the earthquake by using high-resolution aerial imagery acquired from 2009 to 2011 and in 2013, the authors have revealed that 25 earthquake-induced landslides have been stable basically, but some potential landslides(total 21)show evident signs of activity, of which the Doucu potential landslides in Maoxian and Qidiguan potential landslides in Wenchuan deserve more attention. In addition, the debris flow will be the main geohazard type in the Yingxiu-Maoxian segment along the Minjiang River in the future; in the Yingxiu-Wenchuan segment, the frequency and intensity of the debris flow are especially obvious.

Located in Zhashui County of Shaanxi Province, the Lengshuigou polymetallic concentration area is rich in mineral resources related to intermediate-acid small intrusive bodies. In order to get a breakthrough of mineral exploration, the authors carried out large-scale geological survey of remote sensing based on high resolution and hyperspectral data, such as WorldView-I and ASTER. According to the survey results, four kinds of intrusive bodies with different lithologies and three types of linear structures as well as circular structures were interpreted from remote sensing images. Based on the classification of the altered minerals and analysis of the features of spectra, the authors extracted two kinds of remote sensing anomalies related to skarnization by using principal component analysis. The remote sensing geological features show that there exists a relatively large magmatic dome at the depth of the Lengshuigou body, that hidden rock bodies are distributed around the dome, and that ore-forming information of remote sensing anomalies is very obvious. Through a comprehensive analysis, two prospecting targets of remote sensing were delineated in the study area.

An open technological platform can promote public participation in reasonable formulation and implementation of land use master planning. Based on GIS, VR, and touch screen, the authors explored an open display platform for land use master planning which can popularize professional contents to the public in an imaging and intuitive form. Studies show that innovative integration of cross-domain technology is feasible. The coupling of 2-3D GIS with virtual reality can create a simulating scene of land use master planning that presents pictures, texts, figures, sounds simultaneously. This platform can break through the limitations of traditional paper posting, realize open planning, and promote the public service function of the government.