Remote Sensing and Artificial Intelligence Techniques for Ecological-Environment Quality (EEQ)

Dear Colleagues,

Anthropogenic activities and climate change are two major factors that are affecting the environment. In the context of sustainable development, the assessment of Ecological Environmental Quality (EEQ) has provided an important knowledge base for environmental health. The improvement in EEQ seems to be an urgent but long-term topic. Therefore, how to support EEQ improvement is crucial.

Recent advances in Remote Sensing (RS) technology have provided abundant satellite data with various spatial and temporal resolutions. EEQ evaluations with RS are carried out by various measures such as Normalized Difference Vegetation Index (NDVI), Environmental Quality Index (EQI), Environmental Sustainability Index (ESI), Environmental Performance Index (EPI), Ecological Environment Carrying Capacity (ECC), and Remote Sensing Ecological Index (RSEI). Similarly, advancements in computing technology with artificial intelligence (AI) has made big data processing and extracting information about eco-environmental changes possible over time from local to global scales. A combination of these two popular techniques can provide real-time or near real-time information on the assessment of EEQ, with a higher performance in most cases.

In this Special Issue on “Remote Sensing and Artificial Intelligence Techniques for Ecological-Environment Quality (EEQ)”, we welcome papers focusing on the application of RS and/ or AI in the assessment of EEQ as described above. Both general methodological contributions and case studies on RS and AI covering different regions are welcome. We also welcome reviews and technical notes that support EEQ.

Dr. Tri Dev Acharya
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Artificial Intelligence (AI)
• Remote Sensing (RS)
• multi-spectral and hyperspectral remote sensing
• active and passive microwave remote sensing
• lidar and laser scanning
• ecological environment
• environmental change
• environment quality assessment
• ecosystem services
• Normalized Difference Vegetation Index (NDVI)
• Environmental Quality Index (EQI)
• Environmental Sustainability Index (ESI)
• Environmental Performance Index (EPI)
• Ecological Environment Carrying Capacity (ECC)
• Remote Sensing Ecological Index (RSEI)
• Ecological Environmental Quality (EEQ)