[Ecosystem Services Assessment and Multi-Scenario Prediction in Liaoning Province from 2000 to 2020].

Ecosystem service assessment and prediction play a crucial role in sustainable regional development and resource management. Liaoning Province, as a typical representative of Northeast China, faces rapid development challenges such as urbanization, industrialization, and agricultural modernization. At the same time, there is an urgent need for a deeper understanding of the evolution trends of its ecosystems and their impact on ecosystem services. This study employed the InVEST-Markov-PLUS model to conduct simulated research on the assessment of past and future ecosystem services and multi-scenario predictions in Liaoning Province. Based on the land-use changes in Liaoning Province from 2000 to 2020, the InVEST model was used to evaluate the spatiotemporal variations in carbon storage, soil conservation, and water yield in the ecosystem services from 2000 to 2020. Additionally, the equivalent factor method was employed to calculate the value of ecosystem services in Liaoning Province during the same period. Furthermore, by integrating the PLUS and Markov models with the actual conditions of Liaoning Province, four land-use development scenarios for 2030 were constructed, including natural development, economic priority, ecological protection, and cropland protection. The land-use distribution and the quantities and values of ecosystem services under these scenarios were simulated. The study revealed the following findings： ① From 2000 to 2020, carbon storage and soil retention in Liaoning Province showed an overall increasing trend, whereas water yield exhibited a fluctuating decrease trend initially, followed by an increase and then another decrease. ② Carbon storage and soil retention in Liaoning Province showed higher values in the eastern mountainous areas and western hilly regions, with lower values in the central region. Water yield showed a decreasing trend from east to west. ③ The value of ecosystem services increased from 547.94 billion yuan to 565.53 billion yuan, with a total increase of 17.58 billion yuan during the study period. All four types of services showed an increase, with cultural services experiencing the fastest change. ④ In 2030, carbon storage and soil retention in Liaoning Province decreased in all scenarios except for in the ecological protection scenario. Water yield increased only in the cropland protection scenario, whereas it decreased in the other three scenarios. The value of ecosystem services in the study area increased in all scenarios except for in the economic priority scenario.

Research on the Impact of Absorption Feature Extraction on Spectral Difference Between Similar Minerals.

Diagnostic absorption features can indicate the existence of specific materials, which is the foundation of mineral analysis with optical remote sensing data. In hyperspectral data processing, the most commonly used method to extract absorption feature, is Continuum Removal (CR). As for multispectral data, Principle Component Analysis and other indirect methods were used to extract absorption information, and little research has been done on full-band absorption feature extraction. Classification of similar minerals is one of the major difficulties in mineral spectral analysis, while there is no valid index for spectral difference between similar mineral groups. Absorption feature extraction may improve the classification accuracy, but there is no research to investigate the impact of absorption feature extraction on spectral difference between similar minerals. This paper summarized the principle of mineral spectral difference, and proposed the concept of Class Separability Ratio (CSR), which was verified to be a valid index for spectral difference between similar mineral categories. Through comparison experiments on alunite and kaolinite spectra, including USGS spectral library spectra and resampled spectra in accordance with the band settings of HYPERION, ASTER and OLI, the impact of absorption feature extraction on spectral difference between similar minerals were investigated. Experimental results show that valid absorption feature extraction can greatly enhance the spectral difference between similar minerals, and the spectral difference is positively correlated with spectral resolution. Besides, the results of CR can be severely affected by spectral resolution and band center positions, and the absorption feature spectra extraction results for multispectral datasets need to be improved. This research laid the foundation of precise identification between similar mineral categories, and provided valuable reference for the band settings of future geology remote sensing sensors.

[Research on the model of spectral unmixing for minerals based on derivative of ratio spectroscopy].

The precise analysis of mineral abundance is a key difficulty in hyperspectral remote sensing research. In the present paper, based on linear spectral mixture model, the derivative of ratio spectroscopy (DRS) was introduced for spectral unmixing of visible to short-wave infrared (Vis-SWIR; 0.4 - 2.5 microm) reflectance data. The mixtures of different proportions of plaster and allochite were analyzed to estimate the accuracy of the spectral unmixing model based on DRS. For the best 5 strong linear bands, the Pearson correlation coefficient (PCC) of the abundances and the actual abundances were higher than 99.9%, while the root mean square error (RMSE) is less than 2.2%. The result shows that the new spectral unmixing model based on DRS is simple, of rigorous mathematical proof, and highly precise. It has a great potential in high-precision quantitative analysis of spectral mixture with fixed endmembers.