[Soil Moisture Monitoring Based on Angle Dryness Index].

Soil moisture content (SMC) is one of the most important indicators influencing the exchange of energy and water among vegetation, soil, and the atmosphere. Accurate detection of soil moisture content is beneficial to improving the precision of crop yield evaluating and field management measures. In this paper, a novel method ADI (Angle Dryness Index) based on NIR-RED spectral feature space used for calculating SMC was proposed, which improved the accuracy of calculating SMC with red and near infrared band reflectance. It was found that an intermediate parameter θ in NIR-RED feature space was significantly related to SMC, and independent of vegetation coverage according to the linear decomposition of mixed pixel and the empirical correlation between SMC and red/NIR band reflectance which were achieved by previous researches. Then, ADI was proposed with the feature discovered in the paper. The mathematical expression on SMC is nonlinear, and the newton iterative method is applied to ADI for calculation SMC. Then, the newly proposed method was validated with two kinds of remote sensing imagery data (Thematic Mapper (TM) and moderate resolution imaging spectrometer (MODIS)) and the synchronous observed data in the field. Validation results revealed that the ADI- derived SMC was highly accordant with the in-situ results with high correlation (R2=0.74 with TM and R2=0.64 with MODIS data). We also calculated MPDI (Modified Perpendicular Drought Index) developed by Ghulam, which is also proposed with the red and near infrared reflectance. The result showed that the accuracy of MPDI was lower than that of ADI. The most likely reason was that ADI was insensitive to fv, but the calculation errors of fv would reduce the accuracy of SMC estimation. MODIS had a low spatial resolution, thus there may be more than two end members in a mixed pixel. In this case, the linear decomposition of mixed pixel was not applicable and the errors would finally be enlarged. ADI achieved good results in monitoring SMC in vegetated area because it was less influenced by vegetation coverage than other similar approaches. ADI only requires the satellite image data including the red and near infrared band which are available from most of the optical sensors. Therefore, it is an effective and promising method for monitoring SMC in vegetated area, and would be widely used in agriculture, meteorology, and hydrology.

[Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

[Modeling Soil Spectral Reflectance with Different Mass Moisture Content].

The spatio-temporal distribution and variation of soil moisture content have a significant impact on soil temperature, heat balance between land and atmosphere and atmospheric circulation. Hence, it is of great significance to monitor the soil moisture content dynamically at a large scale and to acquire its continuous change during a certain period of time. The object of this paper is to explore the relationship between the mass moisture content of soil and soil spectrum. This was accomplished by building a spectral simulation model of soil with different mass moisture content using hyperspectral remote sensing data. The spectra of soil samples of 8 sampling sites in Beijing were obtained using ASD Field Spectrometer. Their mass moisture contents were measured using oven drying method. Spectra of two soil samples under different mass moisture content were used to construct soil spectral simulation model, and the model was validated using spectra of the other six soil samples. The results show that the accuracy of the model is higher when the mass water content of soil is below field capacity. At last, we used the spectra of three sampling points on campus of Peking University to test the model, and the minimum value of root mean square error between simulated and measured spectral reflectance was 0.0058. Therefore the model is expected to perform well in simulating the spectrum reflectance of different types of soil when mass water content below field capacity.

[Super-low-frequency spectrum analysis for buried faults in coalfield].

Based on the super-low-frequency (SLF) electromagnetic detection technology, the advanced detection for the buried fault in the coalfield is still at the exploratory stage, while the technology has a strong practical significance for production and design of the coal mine. Firstly, in this paper, the SLF electromagnetic detection signals were collected in study area. Spectrum analysis of SLF signal by wavelet transform can remove high-frequency noise. Secondly, the profile of the measuring line across the fault was analyzed and interpreted geologically. Accordingly SLF spectrum characteristics of the buried fault could be researched. Finally, combined with the geological and seismic data, the characteristics and distribution of fault structures can be verified in the mining area. The results show that: the buried fault could be detected quickly and effectively by SLF electromagnetic detection Hence, SLF electromagnetic detection technology is an effective method for buried fault detection.

[Extraction of bridge over water from high-resolution remote sensing images based on spectral characteristics of ground objects].

Bridge over water is a typical man-made target. Using the high-resolution optical remote sensing images, to extract bridge over water appears significant for civilian, military, and commerce. First, in the present paper, according to the spectral characteristics of water in near-infrared spectrum, water information is extracted using the iterative method for the threshold value, to limit the spatial extent of bridge extraction. Second, mathematical morphology is performed on the water information, to connect the separated water bodies due to the presence of bridges on the image. Third, overlay analysis is conducted between the two images before and after mathematical morphology operations, to extract the potential bridge. Finally, based on priori-knowledge of the bridge, the false bridge is removed. In this paper an experimental area is selected to verify the effectiveness and applicability of the method. Experimental results show that the method is effective for bridge extraction over water by using high-resolution remote sensing images based on spectral characteristics of ground objects.

[Monitoring of farmland drought based on LST-LAI spectral feature space].

Farmland drought has the characteristics of wide range and seriously affecting on agricultural production, so real-time dynamic monitored has been a challenging problem. By using MODIS land products, and constructing the spectral space of LST and LAI, the temperature LAI drought index (TLDI) was put forward and validated using ground-measured 0-10 cm averaged soil moisture of Ningxia farmland. The results show that the coefficient of determination (R2) of both them varies from 0.43 to 0.86. Compared to TVDI, the TLDI has higher accuracy for farmland moisture monitoring, and solves the saturation of NDVI during the late development phases of the crop. Furthermore, directly using MODIS land products LST and LAI and avoiding the complicated process of using the original MODIS data provide a new technical process to the regular operation of farmland drought monitoring.

[MTCARI: A kind of vegetation index monitoring vegetation leaf chlorophyll content based on hyperspectral remote sensing].

The chlorophyll content of plant has relative correlation with photosynthetic capacity and growth levels of plant. It affects the plant canopy spectra, so the authors can use hyperspectral remote sensing to monitor chlorophyll content. By analyzing existing mature vegetation index model, the present research pointed out that the TCARI model has deficiencies, and then tried to improve the model. Then using the PROSPECT+SAIL model to simulate the canopy spectral under different levels of chlorophyll content and leaf area index (LAI), the related constant factor has been calculated. The research finally got modified transformed chlorophyll absorption ratio index (MTCARI). And then this research used optimized soil background adjust index (OSAVI) to improve the model. Using the measured data for test and verification, the model has good reliability.

[Decomposition and analysis of the natural source SLF spectrum using curvelet transform method].

Because natural source super low frequency (SLF) electromagnetic detection equipment receives wideband multi-source signal, how to decompose the signal to filter out the interference signal was a key factor for the application of natural source SLF electromagnetic detection technology. In the present article, the detection equipment developed by Peking University was used to survey the coal bed methane data in the Qinshui basin, Shanxi province, and the curvelet transform method was employed to decompose those data. The analysis results indicated that the high-frequency information coming from the decomposition is the interference signals mainly generated by lightning in the atmospheric and directly received by the detection equipment, while the low frequency signal mainly contains the target information. So the reconstructed curve based on the low-frequency information was more favorable for the interpretation of the target, compared with the original spectrum curve. But the curvelet transform method could not remove the artificial frequency signal.

[Passive SLF spectrum analysis for tracing the mining dynamic of CBM].

Exploration and development of the coal-bed methane (CBM) is very important to economics, environment and society. It is a key factor to trace and assess the process of the coal-bed gas mining dynamically for its efficient development. In the present article, based on the theory of natural resources super low frequency (SLF) electromagnetic detecting, the method that uses the SLF to trace the coal-bed gas mining dynamic is introduced. The field tests in 2007 and 2010 in the Qin-Shui basin, Shanxi province of China indicate that this method is efficient for the dynamic of the coal-bed gas mining.

[Research on photometric calibration and reflectance calculation of CE-1 IIS data].

The interference imaging spectrometer (IIS) is an important payload of the Chang'e-1 (CE-1) lunar satellite to achieve the distribution and content analysis of major elements and mineral types on the lunar surface. Due to the different observing conditions, the obtained lunar brightness varied significantly from place to place. Thus, photometric calibration is required to eliminate the radiance difference caused by the different observing conditions. In the present paper, based on the analysis of IIS-2B data (after radiance calibration) of CE-1 satellite, we introduced the improved Lommel-Seeliger model to calibrate the IIS-2B radiance data pixel by pixel. Subsequently, an area adjacent to Apollo16 site was selected as the calibration target, and the bidirectional spectrum for soil sample 62231 was used as a calibration standard to obtain the reflectance from radiance data. Finally, soil sample 71501 was selected to take the accuracy evaluation on the reflectance results. Our work is useful for mineral identification and information extraction, as well as for the mapping of different minerals and rocks distribution on lunar surface.

[Research on using a mono-window algorithm for land surface temperature retrieval from Chinese satellite for environment and natural disaster monitoring (HJ-1B) data].

Land surface temperature(LST) is a key parameter in earth environment, the thermal infrared band that can detect LST plays an important role in spectroscopy. Aiming to the latest optical and thermal bands of HJ-1B satellite, the LST retrieval over Ningxia plain was implemented using a mono-window algorithm without atmospheric water vapor content input, based on the COST model for atmospheric correction. Considering the difficulty of obtaining simultaneous ground measured data, the MODIS LST product was adopted as a standard to test the approach. The comparison and validation indicate that this method has good reliability with accuracy of less than 1 K. In addition, the sensitivity analysis is performed for land surface emissivity, and the result shows that this variable was not sensitive to LST, because the LST error is less than 0. 5 K when it varies at me dium level. This study proves that the satellite data has higher availability for detecting LST.

[New index for soil moisture monitoring based on deltaT(s)-albedo spectral information].

Monitoring soil moisture by remote sensing has been an important problem for both agricultural drought monitoring and water resources management. In the present paper, we acquire the land surface temperature difference (deltaT(s)) and broadband albedo using MODIS Terra reflectance and land surface temperature products to construct the deltaT(s)-albedo spectral feature space. According to the soil moisture variation in spectral feature space, we put forward a simple and practical temperature difference albedo drought index (TDADI) and validate it using ground-measured 0-10 cm averaged soil moisture of Ningxia plain The results show that the coefficient of determination (R2) of both them varies from 0.36 to 0.52, and TDADI has higher accuracy than temperature albedo drought index (TADI) for soil moisture retrieval. The good agreement of TDADI, Albedo/LST, LST/ NDVI and TVDI for analyzing the trends of soil moisture change supports the reliability of TDADI. However, TDADI has been designed only at Ningxia plain and still needs further validation in other regions.

[Effect of different snow depth and area on the snow cover retrieval using remote sensing data].

For the needs of snow cover monitoring using multi-source remote sensing data, in the present article, based on the spectrum analysis of different depth and area of snow, the effect of snow depth on the results of snow cover retrieval using normalized difference snow index (NDSI) is discussed. Meanwhile, taking the HJ-1B and MODIS remote sensing data as an example, the snow area effect on the snow cover monitoring is also studied. The results show that: the difference of snow depth does not contribute to the retrieval results, while the snow area affects the results of retrieval to some extents because of the constraints of spatial resolution.

[The new method monitoring agricultural drought based on SWIR-Red spectrum feature space].

Drought was a chronic, natural disaster, and Remote sensing drought monitoring had become a potential research field. In the present, short-wave infrared and red bands which sensitive to moisture variation were selected to monitor farmland drought conditions by analyzing the spectral characteristics of vegetation and soil. The goal of this paper was to provide a new method of drought monitoring--normalized drought monitoring index (NPDI), based on new constructed spectrum feature space by the difference of SWIR and Red and the sum of SWIR and Red. Field surveyed soil moisture verified NPDI model, and the result showed that NDPI and MPDI model could effectively monitor agricultural drought, and that had high correlation with soil moisture. The R2 was 0.583 and 0.438 with soil water of 10 cm. The monitoring effect of NPDI model was better than the MPDL. This model was further improvement to PDI and MPDI, and it could monitor the drought condition of different vegetation coverage and whole growing season. It has high application potential and popularization value.

[A snow depth inversion method for the HJ-1B satellite data].

The importance of the snow is self-evident, while the harms caused by the snow have also received more and more attention. At present, the retrieval of snow depth mainly focused on the use of microwave remote sensing data or a small amount of optical remote sensing data, such as the meteorological data or the MODIS data. The small satellites for environment and disaster monitoring of China are quite different form the meteorological data and MODIS data, both in the spectral resolution or spatial resolution. In this paper, aimed at the HJ-1B data, snow spectral of different underlying surfaces and depths were surveyed. The correlation between snow cover index and snow depth was also analyzed to establish the model for the snow depth retrieval using the HJ-1B data. The validation results showed that it can meet the requirements of real-time monitoring the snow depth on the condition of conventional snow depth.

[Investigation of Paeonia sinjiangensis resources using remote sensing and expert knowledge].

OBJECTIVE: To study the effectiveness and feasibility of remote sensing technology in the rare species of wild plant resources. METHOD: The mechanism and characteristics of Paeonia sinjiangensis were analyzed to find the possibility of extracting from TM imagery. An expert system has been used with Landsat Thematic Mapper data to derive P. sinjiangensis. Then logical decision rules were used with the various datasets to assign values. RESULT: The land for P. sinjiangensis possible growth were mapped and accuracy tested was approving. CONCLUSION: The results suggest that the remote sensing expert interpretation system using satellite imagery and ancillary data will be feasible for research of rare wild medicinal plants distribution.