 to this short introduction to the course syllabus that is expected to be taught as part of this course on Microwave Remote Sensing and Hydrology. So this course it shall include both lectures which shall introduce the theoretical concepts as well as a tutorial sessions in Python open source programming language wherein you shall be introduced to processing microwave data in Python. And again the tutorials they are conceptualized from the beginner point of view with the installation of Python and other packages followed by downloading the data and finally processing it. And we shall be having a separate section introducing you to each of the 12 tutorials planned. But for now let me show you the outline of lectures which are shown here wherein the syllabus they have been divided into 6 modules. Let me walk you through a quick preview of the syllabus in each of the modules beginning with module 1. So through module 1 we shall try to answer the question, microwaves what are they and where do they come from. See the fundamental reasons for preferring microwaves in remote sensing shall be covered in this module along with the basics of electromagnetic waves and microwaves have several advantages and some can penetrate clouds and even the top few centimeters of dry soil. So all that are part of this module and microwave wavelengths you know they can be chosen for atmospheric sounding such that cloud and ice have negligible effects on the signals. So as part of this module we shall also cover some fundamental laws like the Stefan Boltzmann law or the Wien's Displacement law etc. After learning the fundamentals the second module shall try to answer the question, microwave imaging radars how do I interpret. So as part of the second module we shall learn about the active microwave systems of synthetic aperture radar abbreviated as SAR. See if I show you a SAR image like this you can admit of course you can admit that interpretation is rarely simple, isn't it? By the way this is an image of Mumbai region. So through this module we shall learn about the fundamental properties of synthetic aperture radar image, the different types of SAR imagery, few terminologies like azimuth, ground range, swath, nadir etc. And in addition we shall also get introduced to speckle which is a salt and pepper noise that is inherent in SAR imagery. Now note that a typical SAR system for earth observation is the largest, it is the heaviest and the most power consuming instrument that can be onboard any satellite. Even then SAR has been aggressively being used for remote sensing when it comes to hydrology and meteorology. So these fundamentals shall be covered as part of this module along with image defects like foreshortening, radar shadow, layover effects all this is part of the second module. So moving on to module 3, let me ask a question. If I cannot see the features how do I classify them? Does this image what you see on the screen does it inform a user something of interest to them? Because we as humans we use a large amount of knowledge and experience in interpreting images which means any means of extracting information from synthetic aperture radar data must emulate this knowledge isn't it? And as part of this module we shall try to answer the question let me re-itrate. If I cannot see the features how do I classify them? In addition through this module we shall also try to understand about SAR image classification through supervised, unsupervised and fuzzy classification and also learn about accuracy assessment. So till now we have gotten a preview of what is being planned as part of module 1, module 2 and now module 3. See remote sensing in the visible and the infrared regions of the electromagnetic spectrum you know it is dominated by visual metaphors. If you open any standard textbook on remote sensing and image interpretation the eyes are used as a very popular example which is introduced as analogous to a remote sensing instrument. When it comes to microwave remote sensing I want you to think of ears as analogous to a microwave system. Just as how humans detect and analyze sound you can think of radar systems which collect information from different directions. So through module 4 the concepts of radar shall be introduced and we shall try to answer the question radars in hydrology how do they contribute? The different types of antennas shall be discussed as part of this module such as the parabolic antenna, the phased array and the dipole antenna. You see radars they have an innate ability to detect water and we shall learn through this module about radar altimeters what they are and what they measure and about the applications of radar remote sensing in hydrology. So, so far you know we have been discussing about active microwave remote sensing is not it? We generate their own illumination by transmitting microwaves that hater target get reflected or scattered to be precise to be measured by radar on board a platform. Moving on through module 5 we shall learn about passive microwave remote sensing. We shall learn about passive sensors or radiometers on board a satellite that measure the microwave energy that is radiated by thermal emission or reflected from the sun or from the earth surface or from the atmosphere. So here we shall learn about the fundamental principles of passive microwave remote sensing and we will try to answer the question passive microwave remote sensing and hydrology are they useful? In particular we will try to see how passive radiometers can be used to measure ocean salinity, ocean wind, sea surface temperature, precipitation, soil moisture and so on. Alright, so in addition I will also introduce you to the in-house experiments which were conducted with an L band radiometer. Moving forward we know that phase of a wave changes with distance is not it? Phase of a wave it changes with distance which means the properties of microwaves can be utilized to compare two or more waves but can phase be used as a relative distance measure? This is what we will try to understand as part of module 6 where we shall learn about radar interferometry. Radar interferometry, we will try to understand through this module on what is the fundamentals of radar interferometry, what are interference pattern, what is meant by INSAR interferometrics are? We will also try to understand about digital elevation models what they are and how they are applied in the field of hydrology. Moving on to a few references which you may find useful throughout this course. Alright, so with this background let us see what is contained in the tutorials. Welcome to the tutorial sections of this course and firstly let me give you a bird's eye view of the tutorials which are being planned through this course at the week's commence. Overall we shall have 12 tutorials the outline of which is shown here and these sessions are expected to act as hands-on sessions wherein you get to follow the exercises as performed by me. The exercises utilize a wide range of data from microwave sensors both in situ and satellite bond and the data used are relevant in hydrology and water resources of course as the course title specifies. Now let us delve a bit deeper into each exercise. Tutorial 1 shall encompass installation of python using anaconda environment and it shall also cover the basic commands used in python from a beginner perspective. In the second tutorial we will understand about synthetic aperture radar imagery or SAR imagery as complex numbers having both amplitude and the phase information. We shall also try to access the LO's pulsar data and work on multi-looking using python. Moving on, so in tutorial 3 we shall work with SNAP that stands for Sentinel Application Platform which is a tool that is used for Earth observation processing and analysis. Now the SNAP provides processing tools for all the 3 Sentinel toolboxes that is Sentinel 1, Sentinel 2 and Sentinel 3. So we shall cover from how to download the images, how to install the toolboxes of SNAP before moving on to the different product types and product levels. And of course once you learn how to download the Sentinel SAR C-band data we shall start with performing preprocessing which shall cover radiometric and geometric corrections. Tutorial 4 shall cover statistics using python. Here both univariate as well as multivariate statistics shall be covered using time series data of relevant hydrological variables. In addition we shall also learn about spatial plotting, hypothesis testing and regression analysis. Moving on, so radar images as such they have a very distinctive characteristic that looks like salt and pepper noise which gives it a grainy appearance called as speckle. So through this particular tutorial 5 we shall understand more about speckle and how to perform speckle reduction through filtering. So spatial convolution using different filters shall be dealt with in python. Coming on to tutorial 6 which shall deal with synthetic aperture radar geocoding and classification using supervised as well as unsupervised methods. Through the next tutorial that is tutorial 7 we shall learn how to handle active microwave data from satellites. And in particular the focus shall be on visualizing and analyzing data from gravity recovery and climate experiment that is GRACE and also the water level data from satellite ultimetry missions. Now talking about GRACE a bit, so the twin satellites of GRACE launched in year 2002 offer detailed measurements about the earths gravity field changes enabling one to investigate more about the water stored over land, ice and oceans. So a little bit about satellite ultimetry that is we will learn how microwaves can estimate water surface elevations and in this regard data processing using surface water and ocean topography that is a SWAT mission proposed to be launched in the year 2022 shall be shown using the CNES that is CNES large scale simulator. Of course more details of these shall be shared in tutorial 7. Doppler weather radars are largely used for monitoring the occurrence and movement of rainfall patterns. So through this tutorial 8 we shall learn to visualize and understand the weather patterns captured by the Doppler weather radar instrument and for this we shall be using the freely accessible level 2 data from NEXRAD which stands for Next Generation Weather Radar Archives. And as before we shall cover details from downloading of data from the archives, coordinate conversions, interpretation of reflectivity, radial velocity data and finally moving on to rainfall estimation using reflectivity data. Now in tutorial 9 we shall learn more about the soil moisture and ocean salinity that the SMOS satellite soil moisture retrievals. We will learn how to read and process multiple net CDF files of SMOS and Python to visualize the time series and to conduct the trend analysis using manned candle test. In tutorial 10 our focus shall be on precipitation estimates from passive microwave satellites and how to analyze them using Python. So for this tutorial we shall be using the precipitation estimates from global precipitation measurement mission, GPM satellite and in addition we shall also learn about preliminary data analysis using tropics that is the time resolved observations of precipitation structure and storm intensity. So this mission is proposed to be launched in year 2022. In tutorial 11 shall explain interferometric synthetic aperture radar which is popularly known as INSAR that is used to estimate information about the earth surface by using the phase difference between two complex SAR measurements. So in this particular tutorial we shall use the single look complex that is SLC SAR observation which consists of an amplitude and phase information and also the exercise of generating interferogram shall be carried out in SNAP. So now you may be wondering that so far we have been individually analyzing the products from microwave sensors be it precipitation or soil moisture or water levels etc. But how does it fit into hydrological modeling? So this is precisely what we explained through tutorial 12 where we give you a glimpse of land surface models which simulates the exchange of water and energy fluxes at the earth surface atmosphere interface. So that was an overview of what is planned throughout the tutorial sessions of this course. Let me wish you a productive learning. Thank you.