Remote Sensing in Land Management

Dear Colleagues,

Global climate change, natural disasters and technological problems have great impacts on the development of agriculture in certain areas around the world. This is especially true for risky agricultural areas (for example, such as the Russian Far East, the Northeast China, etc.). It is important to adapt methods and technologies that allow the development of information systems for monitoring the condition and management of land resources in order to meet the tasks of such territories. The modern remote sensing systems that have become widespread in recent years are the basis for such solutions. The joint use of the results of the processing and analysis of remote sensing data, in combination with methods of mathematical modeling and with geoinformation platforms, makes it possible to adopt effective solutions aimed at the sustainable development of territories and ensuring the well-being of their population.

A special section of this Special Issue, entitled “Remote Sensing Methods and Technologies in the Study of Natural and Technical Systems”, will be organized for a comprehensive discussion of the results of research on these issues during the VII Conference “Information Technologies and High Performance Computing” (ITHPC-2023) (Russia, Khabarovsk) (http://conf.ccfebras.ru/en/).

We aim for researchers to discuss a wide range of issues related to the peculiarities of vegetation and cropland research in certain regions using digital methods. Priority topics include automated crop and vegetation recognition, cropland classification using machine learning methods, and the construction of time series of vegetation indices using multispectral and radar data. Particular attention should be paid to examples of approbation of the above solutions in the regions of Northeast Asia. The best research results presented at the conference will be published in this Special Issue after undergoing independent peer review.

We are also open to engaging in dialogue with the scientific community on the publication of scientists’ works on the declared topics outside the context of the ITHPC-2023 events.

This Special Issue focuses on research into the use of remote sensing data for vegetation and crop monitoring. Topics may range from solving problems of cropland and land cover classification to comparative analysis of remote sensing data processing methods, machine learning techniques, and time series processing methods. Reports on information systems based on the integration of data from multiple sources (e.g., multispectral, hyperspectral, and radar), multiscale approaches, or studies aimed at vegetation monitoring are welcome. Articles may focus on, but are not limited to, the following topics:

• multispectral and radar image processing;
• analytical studies and approximation of vegetation indices time series;
• methods of crop and vegetation species recognition using remote sensing data;
• solution of problems of cropland classification on the regional and interregional levels;
• studying peculiarities of crop phenology in different regions on the basis of remote sensing methods.

Dr. Aleksei Sorokin
Dr. Alexey Stepanov
Prof. Dr. Xiuliang Jin
Guest Editors

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