# Validation of Regional-Scale Remote Sensing Products in China: From Site to Network
### Validation Guidelines and Technical Specifications
#### 3.2.2 Validation Technical Specifications  
As shown in Table 1, it is well known that different RSPs can be preferably derived using different remote sensing methods, such as LAI or soil moisture, which are observed via optical or microwave remote sensing. In this case, related validation efforts such as ground sampling design, site selection, site extent, validation method (direct/indirect/inter-comparison) and specific evaluation metrics to be used are varied. Compared to the validation guidelines providing general conditions and universal methodologies, technical specifications of validation are more specific and technical. These specifications refer to a set of procedures/protocols that benchmark for implementing validation exercises towards 16 RSPs/variables of interest (as shown in Table 1). Each individual RSP/variable has one dedicated technical specification. Here, we give an example of validation technical specification of ET. The content is as follows:  
* Validation criteria are data completeness, product accuracy, spatial and temporal variation, spatial and temporal consistency.
* Validation metrics are bias, RMSE, MAPE, mean relative error (MRE) and R.
* Procedures and approaches used in direct validation include the following: The first step is the acquisition of ground truth. At the watershed/regional scale, based on the measurements of water budget components (e.g., precipitation, runoff), water balance equation can be used to calculate yearly averaged ET result as ground truth. At small (point-, footprint- and pixel-) scales, direct flux measurements from Lysimeter, EC system and LAS, etc. are recommended. In the second step, at the river basin/watershed scale, spatial and temporal characteristics of long-term ET estimates are evaluated. At small scales, the accuracy of remotely sensed ET with instantaneous and daily/monthly averaged values as well as temporal variability are evaluated. Error sources and uncertainties are quantitatively assessed.
* Procedures and approaches used in indirect validation are the following: The goal of indirect validation is to validate ET estimates derived from low resolution (e.g., MODIS, NOAA/AVHRR pixel level) satellite observations. This involves using ground-based measurements and multi-source remote sensing information with different levels of spatial resolution, which is capitalised on a step-by-step concept, ranging from high resolution (e.g., airborne mission), medium resolution (e.g., Landsat, ASTER pixel level) to low spatial resolution, considering scaling effect correction in the upscaling process.
* Procedures and approaches used in inter-comparison are the following: Given multiple ET products, well-studied products can be used to evaluate others in need of validation. Evaluation  
Figure 2: Sketch map of the two levels of validation considered in the validation guidelines [161].  
process biases are observed when assessing product accuracy and consistency, spatial and temporal characteristics and regional applicability. In terms of multiple ET estimation models, the same input data (e.g., RS observations and forcing data) are used to drive different ET estimation models. Apart from assessing the accuracy and spatial-temporal characteristic of derived results, the validation process also compares the impact caused by diverse model structures, mechanisms and parameterization schemes, etc., to acquire knowledge regarding the applicability, limitation, and uncertainty of different models.
* Ground instruments are recommended, such as Lysimeter, EC system, and LAS as well as related measuring protocols and data processing instructions.
* Finally, an evaluation report should be generated with respect to the above validation efforts and product performance.