Ecosystem Service Value Estimation of Paddy Field Ecosystems Based on Multi-Source Remote Sensing Data  
[PERSON]  
1 Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; [EMAIL_ADDRESS] (T.H. ); [EMAIL_ADDRESS] (Y.L.) [PERSON]  
1 Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; [EMAIL_ADDRESS] (W.H. ); [EMAIL_ADDRESS] (Y.L.) [PERSON]  
1 Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; [EMAIL_ADDRESS] (W.H. ); [EMAIL_ADDRESS] (Y.L.) [PERSON]  
1 Key Laboratory of Digital Earth Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China; [EMAIL_ADDRESS] (W.H. ); [EMAIL_ADDRESS] (Y.L.) [PERSON]  
2 International Research Center of Big Data for Sustainable Development Goals, Beijing 100094, China 2  
such as environmental pollution, desertification and species extinction [4]. Therefore, the appreciation and correct evaluation of ES have become an urgent global problem. The ES are the benefits that human beings obtain directly or indirectly from the ecosystem and can be divided into four types and 17 sub-types of provisioning, regulating, cultural and supporting services [4]. Researchers have tried to estimate the economic value of some ES since the 1980s [5; 6] and [PERSON] [3] established the ES monetization accounting framework for 17 sub-types of 16 global ecosystems in 1997. Since then, the evaluation of ecosystem service value (ESV) has become a hot topic in academia. Due to the divergence of views among scholars on the evaluation of ESV, the most popular methods are the equivalent value per unit area (EVA) and the ecological service function equivalent (ESFE) methods. The former is the method proposed by [PERSON] that uses the value of ES per unit area of each ecosystem type multiplied by the total area of each ecosystem type to obtain the ESV of ecosystems in the region. [PERSON] [7] criticized this method because land use types were used as proxies for ES; although they do not always match perfectly with biomes, and the unit area value equivalent of some types of ES was unreasonable. [PERSON] [8; 9] improved the method based on a survey of 500 Chinese ecologists, gaining wide application. This approach is based on land use/land cover (LULC) data with relatively few input parameters and is suitable for static or dynamic studies at different ecosystem types or different scales, such as global [10; 11; 12], national [13; 14; 15; 16; 17; 18], small regions [19; 20; 21; 22; 23; 24]. This application is not only limited to multiple types of ecosystems but also has a wide range of applications for single types of ecosystems, such as forests [25] and wetlands [26]. The shortcoming of the EVA method is that it does not consider the differences in habitats of ecosystems. For example, although the EVs that forest ecosystems in sloping and flat areas can provide to prevent soil erosion must be different, the EVA method cannot reflect this difference. The gross ecosystem product (GEP) method was proposed by [PERSON] [27; 28; 29] to calculate the accounting value of ES using market price surrogates. It first quantifies the ES in various types of ecosystems, and then uses economic assessment methods to estimate their values. This method is more suited to obtain the number of ES through ecological process simulations and has stronger explanatory power for ES. The GEP method has been applied to many pilot areas in China and has been selected as the basis of green development strategic planning and the index of government performance evaluation by many provinces. The shortcoming of the GEP method is that the transition depends on the statistical data with administrative divisions as the unit and requires many parameters, which leads to the cumbersome accounting process of ESV and low spatial resolution.