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Populus Euphratica is a haloduric desert vegetation growing in arid regions. It is a drought-en- during plant and it is also a wind barrier to fix sands in desert areas. The distribution of Populus Euphratica forest is required to carry out the management of water resources in the arid region, such characteristics make it play an important role in maintaining the hydrological ecological balance in desert. However, they are dis- tributed discretely and the single tree is very small, so it is difficult or even impossible to be extracted at a large scale based by using moderate to high spatial resolution remote sensing data. Thus, the high spatial resolution remote sensing data are required for extracting Populus Euphratica. However, the utilization of high and very high spatial resolution remote sensing data in a large area is usually not implementable because of the high costs and low processing speed. In addition, the manual procedure is usually incorporated, which is further lower its implementalbilty. Therefore, there is hardly any related research for extracting Populus Euphratica in a large area. In this context, this paper proposes an automatic method to extract the populus euphratica forest in lower-stream of the Heihe River (total area of approximately 21646.6km 2 ) by using object-oriented classifi- cation method. Firstly, high spatial resolution data (higher than 2 m) are extracted from Google Earth (the data are used for free and the high level product based on Google Earth images don't have copyright issues). The extracted images are mosaicked automatically using the application programming interface provided by Google Earth. Thirdly, based on analyzing the characteristics of Populus Euphratica as image objects, a set of rules for extracting Populus Euphratica by employing object oriented method are constructed. Finally, the manual in- spection method is employed to verify the accuracy of the extracting results and it shows an accuracy better than 87%. The proposed method is capable of extracting populus euphratica forest using Google Earth auto- matically with low-cost and high-precision and it will become a feasible technical solution to extract thematic information automatically with low-cost and high-precision. Moreover, it will lead a large amount of applica- tions, which are able to provide high-precision and high-resolution thematic products at a very low cost for the sic-economic development in the future; therefore, it has great values on remote sensing applications. KEYWORD: Google Earth; Populus Euphratica Forest; Object-oriented Classification; Automation; High spa- tial resolution

An automatic method to extract Populus Euphratica forest in a large area using remote sensing