# Construction and Application of an Ecological Quality Evaluation System Based on a PIE-Engine +
###### Abstract  
Ecosystem services, including climate regulation and biodiversity maintenance, are vital for human well-being and sustainable development. The ecological quality evaluation system, based on the three dimensions of ecological function, ecological stability, and ecological stress, was established using the Pixel Information Expert Engine (PIE-Engine) and Moderate Resolution Imaging Spectroradiometer (MODIS) products to assess the ecological quality of the Taihu Basin from 2001 to 2020. The findings reveal that (1) the average Ecological Function Index (EFI) of the Taihu Basin showed a trend of initially decreasing and then increasing, with significant spatial differences. The highest EFI was observed in the western and southwestern regions of the Taihu Basin, which are mainly covered by forest and grassland, while the relatively lower EFI was found in the densely urbanized northeastern part of the basin. (2) The average Ecological Stability Index (ESI) of the Taihu Basin showed a similar trend to the EFI, with the rate of increase higher than the rate of decrease. The ESI was higher in the southwestern part, while in the southeastern and western parts of cropland and wetlands, the ESI was relatively low. (3) The Ecological Threat Index (ETI) of the Taihu Basin showed a fluctuating decrease followed by an increase, with the rate of increase higher than the rate of decrease. The reduction in grassland and the expansion of urban space are the main factors contributing to the increase in ecological stress. The research results of this paper will provide an important reference value for the coordinated and sustainable development of the economy and ecosystem in the Taihu Basin.  
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and the Vigor-Organization-Resilience (VOR) model proposed by [PERSON] [3], which fully reflects the function of ecosystems and has been widely used in different regions. With the development of remote sensing technology, the Remote Sensing Ecological Index (RSEI) has been developed based on quantitative remote sensing parameters, offering faster computation speeds and easier data acquisition [4]. However, most current ecological quality evaluation systems have complex structures and lack multi-angle analysis, making them inaccessible and limited in macro-scale evaluation and analysis. To address these problems, a comprehensive ecological quality index system was established based on the three dimensions of Function-Stability-Threat, leveraging the advantages of quantitative remote sensing data [5]. The use of the evaluation system can assess ecological quality from three perspectives: ecological function, ecological stability, and ecological threat, providing a rapid, comprehensive, and objective method for ecosystem quality detection and evaluation.  
The Pixel Information Expert Engine (PIE-Engine), a one-stop real-time Earth science big data computing platform, leverages cloud computing, Internet of Things, big data, artificial intelligence, and other technologies to build a parallel and efficient underlying architecture based on cloud-native technology, providing a convenient and powerful platform for remote sensing data processing. The platform hosts a large number of remote sensing data sets and enables online on-demand real-time computing. By utilizing back-end cloud resources, it can quickly batch process extensive remote sensing images, offering advantages such as low operational difficulty, stable performance, and high efficiency [6]. In this paper, the PIE-Engine was used to observe and evaluate the ecological quality of the Taihu Basin based on the Function-Stability-Threat ecological quality evaluation model. It will provide theoretical support for the governance and protection of the ecosystem in the Taihu Basin.