[Application of hyper-spectral remote sensing technology in environmental protection].

Hyper-spectral remote sensing (RS) technology has been widely used in environmental protection. The present work introduces its recent application in the RS monitoring of pollution gas, green-house gas, algal bloom, water quality of catch water environment, safety of drinking water sources, biodiversity, vegetation classification, soil pollution, and so on. Finally, issues such as scarce hyper-spectral satellites, the limits of data processing and information extract are related. Some proposals are also presented, including developing subsequent satellites of HJ-1 satellite with differential optical absorption spectroscopy, greenhouse gas spectroscopy and hyper-spectral imager, strengthening the study of hyper-spectral data processing and information extraction, and promoting the construction of environmental application system.

[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.

[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.