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Achieving sustainable development is an issue of global concern. Accounting for the gross ecosystem product (GEP) value can specifically quantify the value of ecosystems for people, which is conducive to the formulation of sustainable eco-management decisions. Multi-source data, including remote sensing images, geospatial data, and statistical bulletin information, were used to quantify the GEP value of material products, regulating services, and cultural services for Fujian Province, China, during 2000–2020. On this basis, the spatio-temporal characteristics of GEP and the coupling relationship between GEP and GDP were analyzed. The results showed that: (1) the value of GEP in Fujian Province increased by 27.9% from CNY 3589.04 billion in 2000 to CNY 4590.25 billion in 2020. Among the service values, the contribution rate of regulating services to GEP was always the highest during the study period. (2) The spatial distribution pattern of GEP in Fujian Province was higher in the west and lower in the east. Comparing prefecture-level cities, Nanping maintained its GEP at the maximum value level over the past 21 years, while Xiamen and Putian maintained their GEP at the minimum value level. (3) GDP grew faster relative to GEP over the past 21 years, and the difference between GEP and GDP decreased. GEP had a long-term positive effect on GDP, while GDP had a smaller effect on GEP in the short term. The research was not only enriched in relation to GEP accounting, but also the policy recommendations for improving the mechanisms related to the optimization of sustainable development goals have some practical significance.

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In this paper, the active disturbance rejection control (ADRC) approach is applied to a class of multi-input multioutput (MIMO) uncertain stochastic nonlinear systems. An extended state observer (ESO) is first designed for estimation of both unmeasured states and stochastic total disturbance of each subsystem which represents the total effects of internal unmodeled stochastic dynamics and external stochastic disturbance with unknown statistical property. The ADRC controller based on the states of ESO is further designed to achieve the closed-loop system's output regulation performance including practical mean square reference signals tracking, disturbance attenuation, and practical mean square stability when the reference signals are zero avoiding solving any partial differential equations in the conventional output regulation theory. Some numerical simulations are presented to demonstrate the effectiveness of the proposed ADRC approach.