Remote sensing technology is the major method for monitoring temporal and spatial changes of regional agricultural drought, from which both the vegetation index(NDVI) and the surface temperature (Ts)derived can reveal information of soil water content and drought-suffering status of crops via indicating the response of green vegetation to drought intimidation habitat. Nevertheless, there still exist some limitations when only one of the two parameters is used. The two-dimensional feature space based on NDVI and Ts integrates the physiological and ecological connotations of both parameters, and hence can not only indicate the water-heat threat environment when drought occurs but also display the symptom of crops, thus effectively improving the precision and efficiency of agricultural drought monitoring. Based on a detailed description of the principle of applying NDVI-Ts space to the evaluation of agricultural drought, this paper deals with four representative models for drought monitoring, preliminarily analyzes some non-soil-moisture factors affecting the space, and sums up their advantages and disadvantages in application. Some problems worthy of further attention in this field are also discussed.

 Cokriging, a multivariate best unbiased linear estimator, has been widely used in many fields. This paper has applied cokriging methods to remote sensing image fusion. The variograms from low-resolution and high-resolution images and the cross-variogram between the images were calculated, and then theoretical models were formulated for the extraction of structural information from the images. Three cokriging variants were used for image fusion, namely, simple cokriging, ordinary cokriging and standardized ordinary cokriging. The experimental results indicate that the simple cokriging yields the best spatial quality result whereas the ordinary cokriging produces the best spectral quality compared with the other cokriging variants. The cokriging methods were further compared with principal component analysis in terms of fusion quality, and the result shows that the fusion quality of the cokriging methods is fairly satisfactory.

The linear spectral mixture model (LSMM) is usually used to study the urban environmental biophysical composition. The development of high-quality fraction images depends greatly on the selection of suitable end-members, which constitutes a key step. Spectral variability is obvious in the heterogeneous urban area, especially for high albedo objects, and this phenomenon affects the accuracy of LSMM. The study in this paper is based on the key assumption that the same pure land cover types exhibit obvious spectral similarity. The objective of this study is to examine the applicability of optimizing end-members selection based on spectral similarity. Four end-members, namely, vegetation, soil, low albedo and high albedo, were selected to model urban land cover by using Landsat Thematic Mapper data. Impervious surface abundance was estimated by adding low albedo fraction and high albedo fraction. Quantitative validation using impervious surface abundance measurement derived from high resolution multispectral QuickBird imagery indicates that the optimized end-members can reduce the residual error caused by end-member spectral variability. The results of this study reveal that impervious surface abundance distribution can be derived with a promising accuracy.

 A multiple-band algorithm is proposed in this paper to separate land surface temperature and emissivity from ASTER data. Three methods can be used to solve the equations. The first is the performance of classification for the images and the formulation of  different equations, followed by the solution of the equations. The second is least-squares. The third is the simulation of the database according to the characteristics of object emissivities and the utilization of the neural network to solve equations. An analysis indicates that the neural network can improve the practicability and accuracy of the algorithm. The accuracy of neural network proves to be very high for the test data simulated from MODTRAN 4. An application example is given in this paper, and the analysis suggests that the neural network also possesses the self-study capability. The simulation data show that the average error of land surface temperature is below 0.5℃, and the error of emissivity in band 11~14 is below 0.007(band 11，12)and 0.006 (band 13，14), respectively.

 Using Landsat 5 TM remotely sensed data and field calibration in Beijing performed on July 6, 2004,

the authors detected the temperature distribution through the single-window algorithm and field validation. Nine

patterns were recognized on the basis of the temperature data, namely, ①water body normal temperature area, ②

water body abnormal temperature area, ③vegetation normal temperature area, ④vegetation and construction mixed

normal temperature area, ⑤vegetation and construction mixed abnormal temperature area, ⑥construction low

temperature area, ⑦construction normal temperature area, ⑧construction high abnormal temperature area， and ⑨

bare soil normal temperature area.  The abnormal areas were sampled and tested in situ in detail so as to extract

the factors responsible for the abnormality.  A new way has thus been found to monitor the city environment and

the living status.

Surface deformation has become a global problem. The traditional geodetic technique is increasingly

proved to be incapable of monitoring the large-scale and serious surface deformation. The new radar interferometry

technique provides an effective tool for the large coverage area and a high spatial and temporal resolution for

the monitoring. This paper describes the synthetic aperture radar (SAR) interferometry technique for surface

deformation monitoring. The time series method based on the permanent scatterers technique is also discussed in

detail with Tianjin as a test area. The result of the test shows that the time series method has a very good

application value.

 Based on a detailed study of the spectrum characteristics of snow, cloud and their shadows, in

combination with the situation of snow monitoring researches in China and abroad as well as characteristics of

CBERS, this paper deals with the application of CBERS data to snow monitoring. A method in this aspect is

presented in this paper based on abundant data analyses. The data processing technique and the possible error

sources are also discussed in detail in this paper. Verification of the method was carried out by using the data

obtained from Nagqu in Tibet. The results show that this snow monitoring method is feasible and of high precision.

It can therefore provide a theoretical support for the operation of snow monitoring.

 Aimed at solve the spectrum distortion problem of the IHS method that exists in the QuickBird data

fusion, this paper proposes the utilization of both the visual-pan band method and the linear weighted matching

method for its improvement, and provides the best value range of the coefficient α in the Visual-Pan band method

as well as the best weighted values of Pan and I when the spatial characteristics and the spectral characteristics

of the linear weighted matching fusion image achieve the best result. Tests show that when the value of α is

between 0.2 and 0.25, satisfying fusion effect can be obtained, and when the weighted values of Pan and I are 3/4

and 1/4, the spatial characteristics and the spectral characteristics of fusion image can achieve the best result.

 Being one of the important factors responsible for image quality，the band to band registration error

of high resolution imagery affects considerably the application precision of remote sensing. The guideline of band

to band registration error is an important parameter for developing the remote sensing satellite. In the

experimental studies, the authors analyzed the influence of band to band registration error on remote sensing

application in such aspects as geometry registration, vision effect, image interpretation, unsupervised

classification, and data fusion. The guideline of band to band registration error of high resolution imagery is

summarized in this paper.

This paper provides a new method for the automatic removing of aberration in the CBERS CCD image.

Tests show that the new method can not only remove aberration efficiently and replace manual work but also improve

obviously the speed of image-processing. This method has therefore established the foundation for the extensive

application of the CBERS CCD image.

In order to extract the leaf area index (LAI) information from the canopy reflectance spectra of rice,

the authors tentatively simulated the canopy reflectance based on the radiative transfer model PROSPECT+SAIL and

compared several vegetation indices to define the correlation between the chlorophyll content and LAI.  The

observation of the spectral signature near the red edge showed distinguished behavior for chlorophyll content and

LAI.  Therefore, the principal component analysis was used as a supplementary method when vegetation indices could

not reach good results in getting LAI information.  An analysis of the ground measurement of rice spectra and LAI

also substantiates this method.

Based on an interpretation of linear and ring structures and the extraction of alteration information

from TM imagines, in combination with ore deposit geology and geochemical data, the authors formulated a linear-

ring structure model for ore deposit location in the Laochang ore zone according to the theory of remote sensing

deposit geology. Under the background of the regional NNW-trending tectonic belt, the cross overlapping ringed

structure is formed by the superimposition of the NS-trending axial Nanlao ring reflecting the Hercynian volcanic

depression and a series of EW-trending axial lenticular structures reflecting the Yanshanian-Himalayan concealed

intermediate-acid rock bodies. The anomalous hue zones controlled by NNW-striking lines show the alteration

information. The overlapping segments are places favorable for mineralization.

 The ecological environment of the drainage area of the Lijiang river has been degenerating rapidly in

the past 30 years, and hence an experimental research on the long-term and short-term dynamic monitoring of

ecological environment variation of the drainage area of the Lijiang river was carried out by using the TM, ETM+

and MODIS. Rapid degeneration is attributed to two aspects: the headwater forest in the upper reaches of the

Lijiang river has been destroyed continually, and the riverbed sand layer has been mined out on the large scale.

This conclusion is based on information extraction, pattern analysis and recognition as well as comprehensive

explanation of TM and ETM+ images obtained from three periods of time (1986, 1998 and 2002) together with field

investigation. The variation law of water quality of the Lijiang river and the gross of the vegetation were

discovered, and the optimal monitor bands of MODIS were determined by spectrum analysis of water-body based on

pixels and calculation of MODIS-NDVI image data.

Based on American SRTM-DEM(90m) data and geological information and adopting color-dye, density-class

and GIS spatial statistic analysis technology，the authors studied geomorphological characteristics of the Altay

Mountain by means of topography-elevation analysis, surficial-slope analysis and terrain-section analysis.

According to the results of the study, the Altay Mountain has an average altitude of 1 790 m and an average

surficial slope of 21°, and the current geomorphological characteristics of high altitude and steep slope are

mainly attributed to strong tectonic activities; the mountain range is strictly affected or controlled by the NW-

trending fault activity, and hence the geomorphological cells mostly extend in the NW direction; the mountain

assumes obvious ladder-like modern geomorphology, and has developed 5-level denudation-planation surfaces with

different altitudes, with the northeast denudation-planation surface  higher than the southwest surface, and the

east and central denudation-planation surface higher than the west surface.

 The soil moisture, organic matter and iron oxide have a considerable effect on the red soil spectrum.

This paper studied characteristics of organic spectrum indices, moisture contents, iron oxide contents and red

soil field spectrum. It is concluded that the moisture content has the most intimate relationship with the red

soil field spectrum in the infrared wave band of short wave, that the close relationship between iron oxide

contents and red soil field spectrum exists in the near-infrared wave band, and that the organic matter exerts a

significant affect on the red soil field spectrum in the visible light wave band.

 Based on an analysis of characteristics of sediment transportation and flow field in sea areas of

Hanjiang estuary by using the multi-temporal landsat image, this paper deals with the hydrodynamic condition of

Hanjiang estuary and its impacts on sediment transportation. Some conclusions have been reached: ①Sediment

concentration in the Hanjiang estuary is low; ②In the estuary, the tidal current runs from southwest to

northeast; ③ Outside of the estuary, the flow  from the Hanjiang river is affected by the southwest current, and

the suspended sediments are transported along the boundary. 

 In land use/land cover classification, the utilization of large-scale routine approaches in diverse

areas often fails to obtain satisfactory results. In this paper, the Qiantang river watershed was chosen as the

study area. A stratified and regionalized supervised classification (the Maximum Likelihood Classification)

approach was employed. With this approach, water and mountain areas were first stratified and extracted through a

set of equations that were used to compute parameters from Landsat TM bands. Subsequently, by using the mask

method, the authors obtained plains and foothills, which were subdivided into six sub-regions according to the

geomorphic features and land use/cover characteristics. Additionally, the plains and foothills should be

classified separately in the case the images were acquired in different seasons. The supervised classification

could be carried out after respective signatures in every region were identified. The classification accuracy

reached 90. 7% with a Kappa coefficient of 0.881, which was much higher than that obtained from the routine

classification approach that had a classification accuracy of 51.6% and a Kappa coefficient of 0.411. This study

shows that the stratified and regionalized approach is very efficient in land use/cover classification in a fairly

large region, such as the watershed level in southern China.

 Based on the Landsat TM5 and TM7 images by GIS and the basic theory and method of landscape ecology,

the present agro-landscape pattern and its changes in the Sanjiang Plain during 1996~2000 are discussed in this

paper. According to an analysis of patchiness of different land use/cover types and the transition characteristics

among the main types, the cultivated land increased while the natural landscape types such as forestland,

grassland and marshland decreased considerably. The number of patches of grassland, forest and marsh increased,

but the patch area decreased, which shows a highly fragmented pattern in the study area.

 TM image, digital topographic maps on the scale of 1︰10000, and other ancillary materials were used

in this study. Land use type, vegetation cover rate and slope were selected as impact factors to make a rapid

evaluation of soil erosion intensity in Honghu, Yujiang County, supported by remote sensing and GIS. As a result,

the classification map of soil erosion intensity was obtained. On such a basis, the situation of soil erosion

intensity in the study site was analyzed, and the results show that the soil erosion intensity information derived

from the method in this paper is quite close to the real situation.

Mining activity is responsible for the deterioration of the vegetation environment, and the variation

of vegetation environment reflects the information of mining area expansion. With the Panzhihua vanadium-titanium

magnetite ore deposit area as a study case, the authors extracted the mining area expansion information by using

the SARVI difference model and then used the supervised cassification method. The results of the two performances

were superimposed upon each other and analyzed under the condition of ArcView 9.1 so as to obtain the dynamic

information of mining area expansion. A comparison was made with the manual interpretation classification result

of seasoned expert in 2005, and it is shown that the precision can reach 95.3%. The experimental results show that

this method is very simple and effective in the extraction of the mining area expanding information, and is also

very important both in theory and in practice. This method proves to be very promising in dynamic inspection of

mining area.

 Sand drift is of vital importance in water-depth remote sensing, as shown by an analysis of the

reflectance spectral data and measured water depth data. The concentration of the sand drift decides the direction

of the correlation coefficient between the water depth and the reflectance spectra: the correlation coefficient is

lower than 0 in the clear area and higher than 0 in the high turbidity area. On such a basis, the water body can

be classified before depth extraction so as to improve the depth extraction precision. The high spectral remote

sensing technique can raise the extraction precision based on the simulation analysis of different spectra.

 This paper deals with the technique of dynamic remote sensing monitoring of the ground collapse water

log situation in the Kailuan coal mine by using MSS, TM/ETM and CBERS-2 data. With this technique, the dynamic

information of the ground collapse water log situation of the Kailuan coal mine in the past 28 years was obtained.

It is found that the remote sensing technique is quite effective in monitoring the ground collapse water log

situation in the mining area, and the information obtained can reveal the development of the ground sinking in the

mining area. The CBERS-2 data obtained in the extraction of the water log information prove to be fairly valuable.

ESRI is a pioneering and leading technique in GIS domain, and Google Earth provides the global image database.  It is therefore of important practical significance to unify these techniques. This paper has dealt with the method for transforming the ArcGIS Vector Data to KML file, proposed the means for transformation, and completed the program realization.