B. Sc. Andhra University, India, 1987.
M. Sc. (Tech), Andhra University, Faculty of Engineering, India, 1990.
Ph.D., 1994, Faculty of Engineering, Andhra University, India. Thesis Title: Applications of Remote Sensing, Mathematical Morphology, and Fractals to Study Certain Surface Water Bodies. (Thesis Advisors: Prof. B. S. Prakasa Rao (Andhra University College of Engineering) and Prof. S. V. L. N. Rao (IIT-Kharagpur))
Mathematical Morphology, Theoretical GIS, Spatial Information Retrieval, Analysis, Reasoning and Modelling, Satellite Remote Sensing data analysis, Digital Image Processing, Geocomputation, Spatial Analysis and Geographic Information Systems, Complex geomorphic systems, Geomorphic dynamical systems, Modelling the behavior of certain geomorphic systems via Chaos and Bifurcation theories, Fractals and multifractals in the quantitative analysis of certain geomorphic phenomena.
Terrestrial surfaces of Earth and Earth-like planets exhibit variations across spatio-temporal scales. Recent advancements in remote sensing technologies that take the advantage of wavelength bands of wide ranging electromagnetic spectra paved a way to properly sense the terrestrial-oceanic-atmospheric fields. Now various different satellites provide optical and microwave remotely sensed data. Optical images are usefully acquired by employing the solar radiation as main energy to sense the terrestrial and/or ocean surfaces. While such optical data have limitations due to cloud cover, microwave sensing mechanisms that are operated via backscatter strength of the radar signal provide data that are useful under all weather conditions. It is recently mentioned that such data that are being acquired with huge expenditure are being underutilized. Dr. Sagar's works mainly address the (i) feature retrieval from remotely sensed data of both the types, (ii) analysis, (iii) reasoning and (iv) modeling phenomena that are retrieved at multiple spatial and temporal scales. To address the four topics, which are intertwined, Sagar's research works in the past and present involve development of original algorithms and modeling techniques that are mainly based on mathematical morphology, fractal geometry, and chaos theory concepts. In order to develop models, synthetic data sets are considered. The success of the model is further validated through testing the model on realistic data such as remotely sensed data.