Decision Support System for Hyperspectral Remote-Sensing Data of Yellow River Estuary, China

There are many wetland resources in the area where the Yellow River enters the sea. This area has good ecological and economic value. Therefore, wetlands are precious resources. The accuracy of traditional wetland classification methods is low (for example, based on the support machine method). In order to explore ways to improve the accuracy of wetland classification, this paper selected the wetland at the mouth of the Yellow River as the study area. And, we used the hyperspectral data of “Zhuhai No. 1” as the research data. Then, we used the logarithmic transformation method to enhance the spectral characteristics of remote-sensing images. Finally, we used Markov random field method (MRF) and support vector machine method (SVM) to finely classify the wetlands in the Yellow River estuary area. We used these experiments to explore wetland classification methods for hyperspectral data. The results showed that the settings of the coupling coefficient and the initial value in the Markov model had a greater impact on the classification results. We found that the best result was when the initial classification number is 50 and the coupling coefficient is 0.5. Compared with the SVM classification method, the overall classification accuracy of our proposed method was improved by 3.9672%, and the Kappa coefficient was improved by 0.042.

Ecological drought and its state assessment: a case study in the Yellow River estuary

Water cycle has been intensified by global warming, leading to frequent extreme climate events. Drought is an extreme climate phenomenon. Runoff decrease and human water demand increase aggravate the water shortage of regional ecosystems, affecting regional water and land ecosystems and causing ecological drought, river cutoff and water pollution. Finally, the reverse succession and the imbalance of regional ecological structures take place. The clarification of the concept of ecological drought for effective evaluation of regional ecological drought degree has become an urgent important scientific issue to be resolved. Therefore, in this paper, the typical region of the Yellow River estuary was studied for the analysis of characteristics of regional ecological changes and the definition of the concept and connotation of ecological drought. Based on the representative monitoring and early warning indices to ecological drought, the evaluation method and the classification standard of regional ecological drought were proposed. The regional ecological drought includes four levels: I (Severe), II (General), III (Weak) and IV (None). The indicator thresholds of river runoff, biodiversity and vegetation coverage on different ecological drought levels were quantified. The research results can be technically beneficial for the improvement of global ecological drought emergent support capacity and reducing loss due to drought.