Continuous observations from ground station networks are important in the validation of remote sensing products and algorithms. However

owing to the spatial mismatch between the point observation of ground stations and the pixel observation of remote sensing products

a direct comparison tends to incur scale errors. Therefore

the evaluation of the representativeness of ground station measurements for the reasonable validation of remote sensing products is necessary. At present

various observation stations are situated all over the world

and many representativeness evaluation methods have been developed. To maximize the representativeness evaluation methods for the reasonable validation of remote sensing products

we review the present methods for evaluating observation representativeness. The indicators for evaluating observation representativeness can be divided into two classes: point-to-area consistency indicator and spatial heterogeneity indicator. The first indicator evaluates observation representativeness by analyzing the consistency between ground point observations and observations in the pixel area. Generally

three specific classes of methods calculate the point-to-area consistency indicator. The first class is based on physical models

such as the footprint model

and is used for evapotranspiration measurements. The second class evaluates representativeness based on distribution maps. The last class determines observation representativeness by combining multi-stations and multi-observations in the computation of the average difference between a specific station and other stations. The spatial heterogeneity indicator is applied to evaluate ground observation representativeness by assessing spatial variations. Generally

two classes of methods obtain spatial heterogeneity: first-order statistics and semivariogram. The application of representativeness evaluation methods in validating remote sensing products is reviewed. In the validation of evapotranspiration

surface albedo

radiation

LAI products

etc.

the representativeness of ground observations is evaluated to obtain the accurate validation data. A case study is then conducted in the middle reach of the Heihe River Basin for the LAI observations. The point-to-area consistency indicator SSE and the spatial heterogeneity indicator Sill are calculated at the product pixel scale. Result shows that the degree of representativeness characterized by the SSE and Sill is inconsistent for different pixels at the 1 km scale. Thus

the indicator for evaluating the representativeness of various stationobserved parameters should be properly selected. This paper reviewed the methods for evaluating the representativeness of ground station observations and their application in remote sensing product validation. The widely used indicators and the methods for calculating indicators were reviewed first

and the advantages and disadvantages of the methods were summarized. The applications of the methods in the validation of remote sensing products were analyzed

and a case study on the difference of the two indicators in evaluating spatial representativeness for LAI validation was performed in the middle reach of the Heihe River Basin. The review revealed that current indicators and methods are usually suitable for specific parameters and that individualized research on such parameters is necessary. Only a few studies on the evaluation of global ground station networks have been conducted for global product validation. Currently available methods for evaluating observation representativeness must be improved further.