Dear Colleagues,

I am pleased to invite you and/or your colleagues to submit a paper to a Special Issue of Remote Sensing on topics related to the practical application of thermal and optical remote sensing (and allied sensors). My object in organizing this Issue of RS is (1) to update us on where we are today in this area of science and (2) to show how the research has or will have practical applications in a variety of environmental or social issues. As such, I do not want to encourage lengthy theoretical papers, such as the physics and mathematical representations of land surface models that physics are well known. Next to the science, clarity and focus must be our highest priorities.

Papers addressing issues mentioned below appended below would be appropriate. I would also welcome short (5–10 page) articles summarizing and synthesizing recently published work addressing the needs of this Special Issue. I would like to request that you keep the papers as short as possible and do not include any lengthy mathematical discourses. My object in organizing papers for this Special Issue is to provide the reader with a concise and illuminating overview of the subject.

Scores of papers have been published describing land surface models of various sorts that interface with remotely sensed optical and thermal measurements from aircrafts or satellites. I think it is now time to demonstrate to the scientific community and to society in general that this type of work has its practical applications. Therefore, I would like to devote this Special Issue of Remote Sensing to papers that address the practical applications of thermal and optical measurements to such applied topics as drought prediction, forest or brush fire prediction, water shed management, crop yield and crop management, weather and climate prediction, and other similar topics. Furthermore, papers focusing on the synergistic use of other types of remotely sensed measurements, such as microwaves, to optical and thermal measurements would be welcome.

My impression in this field is that non-specialist such as the agronomist, famer, architect, watershed manager, city planner, and forester would be unwilling and unable to, and therefore be uninterested in, making use of the sophisticated land use models often employed in analysis of thermal optical measurements, unless they were too simple to apply or they were interfaced with a user-friendly front end. Improved accuracy or the enhanced complexity of formulations may serve best for one application but not another, for instance, because added complexity may make the effort too costly and time-consuming to implement.

An ultimate objective of research on this subject should be to develop automated methods or user-friendly front ends in which whatever model that is employed can be executed operationally using intelligent algorithms to recognize patterns and perform computations without much human input.

We will entertain the submission of papers until October 31 2019. I look forward to receiving papers from my colleagues.

Prof. Dr. Toby N. Carlson
Guest Editor

Related References

1. Silva-Fuzzo, D. F, 2016: Simplified triangle method for estimating evaporative fraction over soybean crops. Applied Remote Sensing, 1-15.
2. Zhao-Liang Li et al., 2009: A review of curdrent methodologies for regional evapotranspiration estimation from remotely sensed data. Sensors, 9, 3801-3853.
3. Petropoulos, G., T. N. Carlson, M. J. Wooster, and S. Islam, 2009: A review of Ts/VI remote sensing based methods for the retrieval of land surface energy fluxes and soil surface moisture. Progress in Physical Geography, 33, 224-250.
4. Tang, R., Z. L., Li, and B. Tang, 2010: An application of the Ts-VI triangle method with enhanced edges determination for evapotranspiration estimation from MODIS data in arid and semi-arid regions: implementation and validation. Remote Sens. of Environ., 114, 540-551.
5. Sandholt, I., K. Rasmussen, and J. Andersen, 2002: A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sensing of Environment, 79,213-224.

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• Optical and thermal remote sensing
• Applications
• Land surface properties
• Surface dryness, evapotranspiration
• Vegetation fraction.