One, two, three, four. Jaya, jaya, jaya, jaya. Bak chan, bak chan, bak chan, bak chan. Jaya, jaya, jaya, jaya. Bak chan, bak chan, bak chan, bak chan. That's her song. Na na na na na na na na na na. Josh!  Jaya Bak Chan. So, I've said this before. I'll say it again. I want to know what it's like to be a woman. Say it again. I want to know what it's like to be a woman. I just said it was Jaya Bak Chan, but I really do. I want to know at every level of existence, what is that like to be a woman? You know, God's a woman. Ariana Grande has a song about it. My wife wouldn't disagree with you. Ma Durga, baby. Today, we got an interesting one. We got one of those tape cast. Oh, yeah! Got it. Yes, you pressed the button. We started doing those very early. The first one we had was with Kalki and Anurag. Yeah, I think we did one with Vicky and his wife. We did. This is Shahid Kapoor and... And Rajkumar Harani, who is now doing that new film with Shahrukh Khan. He's the director of 3 Idiots, PK. And so, I thought it was... I'm assuming they've worked together. I don't think so. No. Because he's only done five films, I believe. Like those films that were in the teaser? Or alls were it? Those are all the films. So, he's only ever done bangers. Wow. So, talk about a track record. Seriously. So, I think that's why everybody wants to work with him. And that's what everybody says. Because he specifically writes out all of his own stuff and then does all the preparation, directs it, and then edits it. And so, he takes a long time per. And that's why he only has five or six credits. God bless him. That's crazy. Cool. But anyways, we love these. Yeah, this is always great. We enjoy these a lot. I think it's a really interesting format. You don't have a host ruining the vibe. We are the first bakras on this show. I'm really worried. I am also very worried. This beautiful... Let's go. I have no idea. Yeah, neither do I. Should we just... Yeah, let's make it presently. We'll see what happens. Good afternoon, gentlemen. Welcome to Tatecast. My name is... Well, never mind who I am. What matters is who you are. Shahid Kapoor meets Rajkumar Hirani, one of Bollywood's most celebrated filmmakers, one of Bollywood's most respected writers, and one of Bollywood's most underrated actors. One of his finest performances as an actor can be seen in an ad for Febikol. Raju Hirani meets Shahid Kapoor, arguably one of the most versatile actors of this generation. From playing Shy Loverboy Braem to an unstable drug addict pop star, Tommy, to draping a dupatta around a Shwaryarai. Shy Kapoor can do it all. Gentlemen, what have you like to boxes? The boxes contain questions. You pick the topic and answer the questions. Absolutely. Choose failures. I'm here to take you on a journey. I guess he doesn't have any, though. At least not in film. There is no limit to their creativity. They are the room breakers. The no-makers. Seems like a sweet guy, honestly. Yeah. Let's find out what makes them go beyond. Grey goose. Failure. It sounds pretty simple. Except we're doing it with cassettes, which used to exist while I was a teenager, which makes me feel rather old. Same. Don't worry, Shahid. You'll feel older soon. So, sir, I'm going to start with the topic of relationships. I hope the tape recorder doesn't eat your tape. I'm scaredy. Now, Mr. Hirani, in an industry like yours, what do you feel are the qualities that define your true friends, the ones you value the most? At least I can speak for myself. I think they're so obsessed or caught up with their own work that all our relationships are usually with people you're working with. If I have to look at my life I've spent, I think, more time with Abhija Joshi than I've spent with my wife. So, if my wife is hearing this, I'm going to be in trouble. You can say Raju. Raju also does that. Usually, they say, you know, you make friends when you're in school or in colleges. And those are your true friends. Later, all the kind of acquaintances, you never make friends after that. But I feel I've made friends after that whom I've spent time with. Like with Baman, also, I've taken some tea and Palli days. He'll just call up and say, like, once our film was being screened in UN. Lagerh Munna Bhai was in the UN and I was in New York. He happened to call me. He asked me, where are you? And he was close to my office in Bandra. He said, where are you? I'm close to your office. I'll join you for lunch.  What are you doing? I said, Lagerh Munna Bhai is screened at the UN. So, why don't you tell me? I would have come. I said, come, come. He said, I thought he was joking. Then he spoke for five minutes and disconnected. Next day, one hour before the screenings happened, I'm about to leave. There's a knock on the outer door. I was standing there. Wow. And I couldn't believe that. Wow. There. And we had such a lovely time. So, I guess our work defines our relationships. But it's a great space to be in. A great space to be in. The industry's a hard place to find friends. So, what do you want? Real friends. Real friends. I have no idea what's in it anyway. Shall I begin with the same relationships? Meera won't be as safe as I thought. Here we go. That sound is nostalgic. Yeah. Do you think stardom affects relationships? Tell me, you had an arranged marriage. How were you able to gauge that Meera was interested in the human being and not in the star? Interesting. Stardom impact relationships. I didn't even know he was in an arrangement. Whatever profession you're in will have an impact on your relationship, especially if you're working a lot. Stardom comes with a lot of things which are probably beneficial for an actor in many ways. But they're quite a burden for his life partner. A lot of things I also didn't know will come along with being a star. I was 20, 21 when I did Ishwish. And at that time, all I wanted to do was be in front of the camera and be able to perform and act and do what I've grown up watching these great actors and these great movies. And I just want to be a part of that. I mean, I love what I do so much that what comes with it is something I've learned to live with. I'm not very natural with it. For example, I was a bit of introvert. So to be able to interact and engage with people was something I found very difficult in the beginning. Because even though my father's Pankaj Kapoor, but my parents separated when I was very young and I didn't really grow up with him, so nobody knew I'm his son. So when I entered the fraternity, I was pretty much an outsider. Interesting. That answer to the question we had about it. Interesting. I think a lot of the people within the fraternity have grown up together.  The kids of stars and makers and producers or distributors or whatever. So they kind of know each other. There's that fraternity feeling between them. You know what Muhammad Ali had once said? I want to go to a place where nobody knows me.  That's amazing. Actually, I think that sums up deep down what most actors feel because you always wonder whether the people you're meeting are first of all receiving you as the personality as opposed to wanting to discover who you are. So yeah, so when we... So you never felt threatened? Who am I dating? I mean, how... Are you dating an actor? Yeah, I mean, honestly, when I was single, almost everybody I met, of course that's the first thought that crosses your mind.  And that holds true for other people as well, as friends as well. Is he wanting to know me because I am Shahid Kapoor? So that thought is always there. Absolutely. I think it's simple, I didn't overthink it. And yeah, when I met Meera, actually she is very unassuming. I honestly didn't know whether we'd be able to talk also because she was 21 and I was 34. And so, you know, she's from Delhi. I'm from Bombay. I'm an actor. She's just passed out of college. So I really didn't know what we would talk about, but we ended up speaking for seven hours. We really got along and there was no conversation about movies. There was no conversation or questions or curiosity towards how is my life? What happens in the film industry? What is it when you go to star parties? And how is it when you're on a set? How do you feel when you come out of air? What do people come running? None of those questions were asked. So that's what got you? Yeah, completely. Because sir, you spend your entire life on set. You're in a bubble, treated in a certain way which is so different from reality. So the one thing that you're craving as an actor is to talk normally. I'm walking in the middle of the street.   We talk about life. Those are the things that you're craving. Now you will end up giving a lot of tips to all these people who are watching this show. Every girl will come in with every actor they want to talk about cinema. Well, if it works, God bless them. Because I think that's what most actors want. At least I hope they do. Because that's what makes you feel normal. So yeah, so it was very normal with Neera. And I'm sure there's a lot of things which come along with being a star which were difficult for her to adjust to. Like the first few times she went out, I used to always keep telling her that I think you should take a security person with you. She used to always look at me like, what's wrong with you? Why? You know? So I was like... Until? And then after four, five times she went to the mall once. She went to the supermarket once. And she came back saying maybe there are people sitting at me and they randomly walking up to me and touching me and all. And so, you know, so... So I was like, yeah, now you know why. And remember there was an article in the paper which said that why does Meera need a security guard? She's not a star. You know, and she came to show it to me. Yeah, I wish it was that simple.  Professional hazard. Why is it professional hazard? And I'm sure there were many things like that. And our biggest concern was Misha. Because we wanted her to feel normal. And that will always be our concern. And I will always ask myself this question whether I have bolded her because of who I am. And that's something I have to live with and try and undo as much as I can. But I can't change it. Now I have to ask. So let's talk about... So I think many of these don't... Failures. Failures, that's what I said. Do not please Aaroh sir, man. I mean, you shouldn't have done that. I'm surprised you picked this one. What's the one thing you're comfortable cheating on, Mr. Hirani? I didn't say a good thing or a bad person. Yeah, exactly. What's the one thing you're comfortable cheating on? If my wife is listening to this, I'm very curious to hear this answer. What I do cheat on her is... I actually love her with myself a lot of times. Sometimes I actually come home and I'm thinking I want to be with myself so I just get into the car alone with some music and drive down. I've driven from where she knows or she'll discover this with this show. I don't know. But I'm curious to know. I've done that twice at some nights just traveling. That's pretty normal. I've heard a lot of people do that. I've never used that. I can totally connect with that. My commute is not very far, so... Then you need to stay with yourself. I remember when I was getting married I was shooting Kolda Punjab. So I was in Amaritsar and Meera was living in Delhi with her parents. So it was just a 40-minute flight and we were at that stage getting to know each other. She said, should I come see you? I said no for the first 10 days. I don't want you to come. She at that time was so thrown off because she was like, what kind of a guy are you? We're kind of getting to know each other and we're supposed to get married and we're thinking about getting married too. Not to come see you. What does that mean? I was like, I can't explain this to you but I hope someday you will understand why I need this space because it's one of the most difficult characters in my life and I don't want any distraction. I need to be able to only be here. And many years later actually when we were seeing the film so by then we were married. When I shot the film I saw it on TV in a small editing room. It was so big. So we went inside next to each other. I got involved. I was very nervous about my performance. When the interval happened I looked here and there was a distance of 10 feet between me and Meera. From here she had actually moved there because she got up and she said I don't think I know you because who's that guy?  So she was actually so thrown off by the punch up. I could feel that whenever we were at home even if I would come close to her she would give me that energy of I need time. Just keep your distance. Cheating is something so subjective. What is cheating? Cheating is something you want to do for yourself because you like to do it. And you don't know how to hurt the other guy. So you're saying I'm hiding it and doing it. But even not giving yourself time is cheating yourself. I remember I had my first cigarette and I never smoked before that. So my friends told me don't buy a cigarette. Bump from us. We would start buying and smoking. I was drinking from that day. Now I started going home to take a train from Pune to Nagpur. Now in the train I felt like so that's the first time I bought my pack of cigarettes. Now I have to hide it from my dad and mom. I hid it in my house. Next morning dad walks up to me and he came with a carton of cigarettes. Some expensive cigarettes. Smoke up Johnny. I looked at him and said dad I don't smoke. It's a good one. Mom found it. I said you come here for limited time anyways. And all the people who smoke then you know walk out. I have a cigarette. What kind of cigarettes did you smoke Rick back in the day? That was also cheating but I tried to smoke. Vantage. And then unfiltered camels as an acoron steak. Unfiltered? That's a mistake. Yeah it was. Which film company had subs for all these? I'm surprised. You picked this question. I picked it by your director. Calmly. How honest is being is good. That is a question right now. You can cheat on them now. There have been a couple of films I would say where I felt cheated for the very reason that I felt that the filmmakers were not in it. They are very successful filmmakers through the time. There are two people who come to mind right now. They are very successful at that time. And I think that was the problem. And I actually have huge respect for you sir for this one thing. Because I don't know anybody who has seen success the way that you have seen it and I have not seen any change in you sir. And it is so inspiring because over the years one understands that finding success in the career then keeping it. Your true character defines where you get eventually. I feel talent can bring you success but talent can't keep it for you. And it's very important to know how to keep your focus. Because do you start while the film is being made any film? I start freaking out sir. In the journey you start knowing that this is going wrong. Oh you can tell. Easily. But when the process is flawed when you are seeing that everything is in okay take sometimes the filmmaker is looking at his phone while the shot is going on. Oh my god. I thought maybe these days filmmakers are discovering themselves. You know. I was like I don't know because this guy is very good. He has made very good films. I have heard him as an actor. The film body was straightforward. It was not a triple film. So it's very frustrating and it's very painful because I don't think anybody wants to give one year of their life to a process which is flawed. And I always feel that in this profession we should always be process oriented and not result oriented. Because the result is not up to anybody. So just be true to the process. And then if it's wrong we'll try again. We were all together in the journey. So what's your best? Yeah, exactly. Intention is good. Yeah exactly. He won't. Oh the one and only Mr. Raj. We are having a wonderful time learning from this beautiful interview. All through us. Thank you. Raju, a friend of yours has a question for you. The success of your past films make you feel scared when you make a new film. How do you deal with the pressure of expectation? Oh I bet it's high. See how I guessed it. I can't forget his voice. That's such an original voice. And now you're about to have one with SRK. As a matter of fact, it's only your first film which you make completely fearlessly. Orson Wells would say and you tasted success tasted the appreciation and you want that to happen all the time. But all I tell myself in that period of success. Historical look at every director in the world made successful films. People have made films which have not succeeded. So it's going to happen to me. Someday I'll make films which will succeed. Someday they won't succeed. All I can try and do is be true to myself and not think of a formula for success. The moment you think of a formula for success you try to pre-empt what the world is going to like that's going to be the undoing. It actually makes sense that he told Shahrukh Khan not to do that. This works, this works.  That's your recipe for disaster. In fact, once you start doing stuff that you know you're not true to the story. Every time try and find one a unique story and try and find inspiration from your life. So then they're true. The moment you start picking from other films or other sources it's never reflections of life. I'm not saying that there's any formula. We will still fail. You create from the real space. Basically you take something that you connect with and then you start evolving. So then it's just new. It's like how Rocky did that first when he's going. Every sports film you see, they replicated that. You watch every film, every film has that. So it's boring.  They constantly see identifications of life, reflections of life and they're picking up from what people do. So when you sit in the theater and see that, it does something. There's a whole language barrier sometimes just used for the toss. You can totally relate. All you can do is continue making films and it's amazing. Be ready to fail someday. Read inside. Just not with SRK. That's a challenge for you. Shahid, I have a surprise for you. A fan of yours has an interesting question. It's me. I love the trailer. You're looking great. With time, ideologies of people change. The way people used to think earlier they don't anymore. So how does it affect you as an actor to assume the character of a person who is from another century and his ideology is so different so much so that he could have multiple wives? Nice question. Very nice question. This is similar to what Sour said. I think if you cannot relate to a character at any level, you can spend time trying to reach a point where you can find something that you can connect with and that can come from the filmmaker or from the script. It's essentially saying you can't judge the character. And if you do, don't do it. You can find something where you feel you can connect with it and therefore you can represent it and play it. It's an interesting thing. If you're playing Hitler, you have to relate to Hitler. Yes. And he's, I think, the best in this country at that. Absolutely. Is that he believes that if us, while we are sitting and discussing a scene, cannot relate to it, we should not write that scene or we should not do that scene because we are making it for an audience in 2017, not 2015, 2010. It's an experience which can be understood, appreciated, which people can relate to and I think eventually every story is a human journey. Every film is about relationships and universal truth. And I think that's why cinemas somehow never goes out of fashion. Great films will always be great films. Films that might be technically laughable are still classics. Because even though they were made at a time where sometimes a camera is going like this or the quality is really bad or the sound sometimes is not good when you see it and we're used to all those things being so good today. What holds you in a film, I think, is the humanity of it. Amen. The end. Yeah. Amen. Now we'll get really relaxed. Yes, the end is good. Well, it was great chatting with you fine gentleman. Stupid. New faces, new tips and more. There's a lot more questions I'd like to ask. There's a lot more questions I'd like to ask both of you. But I feel like they had some really good answers. Especially towards the back when they started to get into the craft a little bit. I was really enjoying that and it's no surprise. I know we've saw him very early but he's not a name that kind of stuck in my head. Me too. Yeah. I think it's a good thing that we're used to Indians. Because after we did that thing with SRK and him, people were like, I love SRK but this is a... I'm more excited for the fact that it's him. He's a new film of his than I am for Shahrukh Khan. Just because of his track and the kind of films he makes.  I mean, you've talked about a lot on the channel with acting. If you reach into your bag of tricks you're going to be able to tell. Even though they might be really good tricks you're not being honest anymore. Yeah, the people who know. And are the movers and shakers of the art form and if you want to be part of that they'll recognize the difference and it is, you pointed out rightly so. It explains there's a truth in that teaser when SRK said romance and he said, yeah, we're not going to spread the arms. It makes me wonder how much SRK is going to allow himself to start stepping into some new thespianatic places like we've wanted. Where he's given permission to not be who he's been because it works. Because that's the line you have to draw artistically is on the one hand you have fans who have an anticipation of what you're going to provide. Yet at the same time are you just going to become a stereotype and a cliche or are you going to continue to reinvent yourself and find as Shahid said humanity and yourself in each character because are you a performer or are you an actor? Yeah, and then obviously Shahid's answers weren't shocking at all to me. That's the style of actor that I've known he is since we first saw him. And I've seen snippets of him talk about the craft and he understands and loves the craft. And the fact that he said about the character he's like you have to relate to this character is a very true statement. If you're playing a rapist a mass murderer you have to be able to relate to this character in some way to play him authentically. Absolutely, otherwise you've prejudged him.  I've just come up in different classes I've had with Howard Fine where an actor has said those very things and he will specifically give people roles that will challenge that and they'll say how am I supposed to play this when I would never do that and he'd say like for example a rapist he'd say okay you may not go out and rape someone but you've got that in you have you ever had the thought in your mind of doing something vitriolically and horrifically illegally violent in a moment with someone or had that fantasy be honest with yourself and they'd say of course there's a rapist in you if you're honest with yourself you could find an evil dark place where when push came to shove you might flip that switch and find that dark place in you and if you can't don't take the role. And I've heard him say it a lot especially when Kabir Singh was coming out and there was that whole controversy because he hit the heroin in the film and people were like why is the hero doing that why are you encouraging and he's like I'm not he's a flawed character exactly we're not saying it's good to hit people this is just this character story and he hit his significant other and it's really one of the things that we love most about complex characters is that human beings are flawed so even the greatest hero can be a flawed hero man don't ever I just watched this film called Naked I don't know if you ever saw it 1993 film David Lee I think is the director but the lead in it is David he plays Lupin in Harry Potter 1993 tough that film there's rapin going on in there there's the whole thing it's like a philosophical style film so you're like what does this mean what does that mean all this kind of stuff it's a very film school students favorite kind of film everything means something yeah I enjoyed it talk about terrible character you know what movie you'd probably like too that's a very similar thing in terms of what you just described is the film Titan oh yeah I've never seen it it's do not let Leland get his eyes anywhere near the screen yeah it is it shows you the darker side of human nature through metaphor and imagery that's mostly mostly metaphorical the whole thing itself is a metaphor but it's it's hard to sit through and one of those films that when it's over you will feel like you were almost violated and that's what it's intending to do it's the intention of the film anyway it's great conversation I'd love to have a conversation with both of them both of those gentlemen I think it would be a really interesting talk for different reasons for each of them I don't know if there are others of these oh they look like Rajkumar and Farhan Khan who is that Farakhan Bashwarya Raya and Abhisak Bakjan where? oh that's just a joint interview sorry it's not a tape test I don't know how many of these they did but Rajkumar would obviously be a really interesting one I'd love to see Rajkumar Rao and Fahad Fasil yeah I think they usually try to get people of different well I guess not because they had Vicky and his wife but they weren't anyways let us know what other ones we can rack to and what should be both of their next films that we should watch please let us know down below


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Hey guys, this is Hydro from Xtraits and I'm back with another weekly video and Yeah, this week was a pretty significant one and yeah, I'll go over the general market Overview and why I'll go over why this week was significant and I'll go through top tickers that We should be watching for the upcoming week So to start off as always we'll go over the indices wall. So we'll start off with SPY and QQQ So pretty significant week for the SPY We finally are trying to reach this 418.5 level and Yeah, we've been consolidating for what one two three four four weeks and this week We were finally able to break it or touch it at least and not the strongest close, but really good action Overall this week, right? So we were finally able to break it on Thursday and then on Friday we put in a consolidation bar Which is perfectly normal action and right now it looks really really good for the bulls Yeah, this is perfect action what what you want to see for bulls and Next week we want to see maybe a little bit more consolidation hold this 418.5 level and then Continue to push up and make another leg up. But right now the SPY looks really really good here And the next target would be 430 Yeah around 430 Yeah, overall it looks pretty pretty good here So we'll take a look at Q's So again QQQ's doing Denominally well right really really nice break out last week and it actually had four updates in a row And then on Friday I put in a consolidation bar. Yeah, this is just really really good action Bulls have been holding up really really well and very Watch the weekly. Yeah, they've been able to break out of this 331 level very easily. So yeah, this is looking really good for tech in general because Yeah, the big tech has been holding up really well, but recently road stocks have also been performing pretty well and They'll go more in depth in that later on but right now You have really good action for QQQ and tech in general has been killing it the last couple of weeks Four up weeks in a row. So a really good action Let me check what the next target would be so again like SPY you want to see some more consolidation And then you want to see if we can set up for set up for another leg up So yeah, next target would be 362 so a lot of room to the upside here so there's definitely a lot of potential here and In this could be the start of the uptrend And the reason I say that is because this entire time we've been basing out and we're finally just breaking this This base this 331 level. So this is very significant. This is the first time that you actually made a higher high So yeah, really good action This was the downtrend that started forming in 2021 this is when we first broke it and Yeah, ever since then we've been in the uptrend But if we've if we actually break the space then it would be the start of the new bull trend or new New bull market. Yeah, here we go But yeah overall it looks really good and now we'll go into some of the big cap tech stocks start off with Amazon Amazon also had a really good week finally took out this one 13 level and next target would be 125 Let's go to the daily chart Yeah, Amazon had a really strong week really strong rally on Tuesday Wednesday Thursday last week Friday put in or it started pulling back and started pulling back a little bit But that's as expected But yeah, Amazon looks really really good here You want to see some more consolidation and then yeah next target would be 120 121.3 and then 125 but yeah overall Amazon looks pretty good only took out this one 13 resistance. So yeah, really good stuff brands on Next up we'll take a look at the do Microsoft Microsoft didn't have as big of a week, but Actually, I take that back Microsoft didn't have a pretty good week So Microsoft had a really big move on this week from earnings and then it consolidated and very nicely for two weeks And then this week it followed through and yeah, this is really really good action we finally took out this 315 level and Yeah, now that we're we took this level out the only resistance level would be all-time highs So yeah, that's pretty crazy Microsoft has room all the way back up to all-time highs now and yet has no real Resistance and is acting really really well Put it in a Inside bar on Friday. It didn't even close or it did close right, but it opened it closed higher than open So really good action ultra supporting it even on a consolidation day They're really really good action for Microsoft and this one looks ready to get back to all-time highs Yeah, really nice really nice action Next up we'll take a look at Apple Apple looks pretty good here as well took out this 175 resistance level and We should see a lot of Resistance around the 180 level so might take a lot to move Apple now since it already made such a big move this year, but Yeah, it's nearing it's all-time highs right so we should see more resistance and Some more consolidation would be good had a really strong uptrend So I'd expect a couple of weeks of chop and then we could be we could see a big base breakout but overall looks really really good and Yeah, major resistance at 180 181 level Next up we'll take a look at Tesla Tesla finding started turning back up this week good action So yeah, I finally retook this 177 level which has been struggling to do the last couple of weeks But finally did that now We could see another uptrend start so it took out this downtrend last week and Yeah, now we can see an uptrend finally start again for Tesla first resistance level would be Would be around this 189 or 190 level and then second resistance level would be around 207 There is also psychological resistance. So like 200 But yeah, those are the key levels for Tesla, but right now Tesla looks pretty good And I think we can see one 190 easily for next week Next up we'll take a look at Google Google has also had a really nice breakout the last two weeks really really strong breakout Yeah, really strong with the last two weeks finally took out that 120 level and Yeah, from here has Has some resistance around 129 and then from there it can get back to 143 and then all-time highs. So yeah, Google has a lot of room up here Or a lot of room to continue moving forward here, but really really good action from Google Started getting extended on Friday. So pulled back in but overall really really strong action from Google You want to see some more consolidation wait for some sort of flag to build and it would be a good setup to take for another let go Take a look at Meadow Meadow is also shaping up nicely here finally took out previous highs And I was consolidating right there. So this 244 level could actually be a really good buy the depth area and Yeah, 244 would be there you to buy and next next area of resistance Would be 256 and then after that 295 and Then from there it can get back to 340 a and then all-time highs So yeah matters should I think matter has a very good chance to see in 256 the next week And then we should see some more consolidation, but right now this looks really good I think 244 would be a good area to buy and Ride to 256 and then sell take profit for some more consolidation See if it forms a flag again, and if it does then you can take that setup, but right now matter looks pretty good as well Next up we'll take a look at Take a look at Midia everyone's favorite and Midia had a really really strong breakout last week They're with no weekly bar really really good action From here it has room all the way back up to all-time highs really Yeah, it has yeah has no real resistance here But it's getting a little bit extended so you want to see some consolidation form after that consolidation forms then You would want to see if it forms a bull flag and then buy on the bull flag And then yeah, this has room back to all-time highs. So they're really nothing to say for any video But this does have earnings coming up on by 24 So watch out for that AMD same thing as Nvidia but not as strong and video is already back to almost all-time highs while MD still still It's still in this first base, right? so MD also really good action that last two weeks really strong move but a lot of resistance at the 104 level So we'll see how it handles that currently it's doing really well Just they put on a consolidation bar and it closed above on the weekly chart above that level So we'll see if we can build some sort of flag the next couple of days We can just consolidate Put in more bars here and then break double flag and that would be an eight plus that Yeah, and he looks pretty good here as well Now we'll go over some of the tickers that Some of the growth tickers that have been acting really well the last couple of days So first let's take a look at ARKK ARKK. You can't really see much. It still looks like it's in consolidation, but If this level breaks then it could be a good buy setup 39.3 It's been it's been rejected multiple times right one two three here recently So if it takes that level out, it could be a good buy So yeah, that's it for ARKK now. We'll take a look at UPSD So UPSD had really nice Gap up on earnings then it pulled back in pretty hard, but on this day, it rallied really hard Really nice volume and then put in a tight consolidation bar and then from the little flag here and then on here It was a really nice breakout play But yeah for now you want to see you I think UPSD can easily get back to this 26th level and once it does that if it forms a nice flag right below it, then that would be a good setup to stop AI was another good one this week really nice move a really nice volume And now this one setting up the flag here So we'll see what happens with that, but this one also has earnings coming up by 31. So do watch out for that But if this one can tighten up more then this looks like an A plus setup as well And the AI theme is very strong. So this is another one Really really strong volume really nice move up last couple of days and I was starting to consolidate here So we'll see what happens, but clear resistance at that 9.17 level And if we can get some more consolidation, then this would be a really good setup as well next up tool This one also had a really nice breakout on Thursday Made you all-time highs for not all-time highs, but 52 week highs Then on Friday putting a consolidation bar. So also watching this one If it can take out that 152 level, then this should be good to go for another leg up as well Yeah, really good action from this one Volunteer this one had an incredible move last week So again, like UPSD strong learning scap up made a move Consolidated both the low flag here and this was the perfect buy setup So yeah on 5.17 would have been a good buy And then it followed through very nicely and then started getting a little extended So on Friday it did pull back a little bit, but still closed pretty strong and on the weekly You can see that if it takes out this 11.5 level x resistance would be 14.2 So this one has a lot of room up and again take a look at that weekly volume, right? This is this is a sign that institutions are buying. This is clear Uh, yeah, it's a clear sign that institutions are buying because look at these volume bars compared to the volume bars before They're like skyscrapers compared to the volume bars before so Yeah, clear sign that institutions are loading up into the stock once again and Last stock Take a look at uber Uber also made a really nice move on thursday And if it can take out this 39.25 level 39.5 and this one looks good for breakout Breakout higher again to break out higher again. Um, but yeah, but it looks really really good Very strong stock since that earnings gap up And that would say next resistance level would be Would be 44 And yeah, that would be a pretty good risk reward trade So yeah, those are my top watches for upcoming week. Thank you guys for tuning in and I hope you guys have good Next week. Yeah


Hello everyone, welcome to the NPTEL course on Remote Sensing and GIS for Rural Development. This is week 9, lecture 4. In this particular lecture series, we are looking at remote sensing tools that aid us in assessing the changes to the land and groundwater which affect rural development. There are multiple satellites and images that are available for terrestrial change assessment, but when it comes to groundwater there is only a few. So, in the last lecture especially we looked at, India has been the highest groundwater extractor in the world, followed by US and China, but if you put the water extractions of US and China together, still India's budget is much, much more. So approximately like 220 kilometer cube per year extraction or billion cube big meter per year extraction of the second and third place which is US and China together, whereas India is 245 kilometer cube or billion cubic meters. This is very unsustainable given the size of India and the size of US and China put together. So, if we continue to access such water, there will be drastic impact on rural development starting from drinking water where people are forced to drink polluted water which is polluted by anthropogenic or geogenic contaminations. This is above and beyond the course so I will just stop here on the water quality part, but quantity is very important. A lot of wells are drying up in India and people have to walk farther away from the wells to identify new water resources for extraction. This is highly unsustainable in a developing scenario and even though the government takes multiple steps, we need to do our part in managing water resources for rural development. So on that note, we looked at water budgets across the world and we found Asia region has the highest groundwater extraction and then we said, okay, let's look at the data issues. So groundwater data issues are tremendously high. We need to focus on methodologies to monitor groundwater leading to sustainable use of groundwater. Of that, there are data issues. So we said, okay, let's look at some remote sensing satellites that can aid and only one satellite is available which is the GRACE. So in today's lecture, we will look at in detail, what is the GRACE satellite? Why is there a big information around it? And what can be understood by the GRACE data mission? So without further ado, let me start the GRACE mission method and then we'll go into some results, et cetera. I'll also share results from my previous studies as a attachment in this one of the weeks. We'll have only case studies using the data sets that we have looked upon in this lecture. So here's the GRACE satellite. As I said, unlike other missions, the GRACE satellite has two satellites together. The mission has two satellites and very humorously, it is named Tom and Jerry. I hope everyone knows the cartoon Tom and Jerry. Jerry runs Tom Catches. Jerry is the mouse, Tom is the cat. So this cartoon has a very big hit from my days also. So a lot of people watch this cartoon. The basic simple hypothesis is the mouse runs, Tom follows and catches. So that is the name given. So we have Jerry in the front and Tom catching. There are multiple sensors in both these two missions. But the most important aspect about GRACE is that it's not very complicated instruments in the machine, in the satellite. It's a very, very highly sophisticated accelerometer. What is an accelerometer? It measures the speed, change in speed and acceleration. So that is all we have for GRACE. So first let's look at how satellites move around the globe. So once a rocket takes a satellite and launches it in space, then due to the gravitational pull of the planet, the satellite gets slowly placed in orbit. And then a small push is given. The centrifugal force keeps it rotating with momentum, with a constant momentum, and it goes around the planet. And one thing which is very smartly understood by the GRACE team is that the gravitational force acting on the satellite is not the same. For example, we have some satellites are very sensitive to this gravitational force. So that is why this mission is called gravity recovery and climate experiment. So using gravity, how do you assess climate parameters in a very, very sophisticated way? It's very, very advanced technology, very smartly done. It is very different from other satellites. There is no image that is taken and then produced. It is mostly every pixel at every pixel. It is monitoring the change in mass. So let's come back. So this is your globe. In the globe, around the globe, the satellite goes up because of the gravitational force. And we know that the mass is not distributed across the planet evenly. For example, let me put my pointer. So the mass here is not the same as the mass here, because here it is water. Here it is land. And within the land, this peak has higher mass. And then the next land, this part has lower mass. So the point is at every grid in the planet, the mass is not the same. So if the mass is not the same, gravity is due. The gravitational force is because of the mass. So if the mass changes, the gravitational pull also should change. Let's say this is the surface. So it is not even surface. It is like bumpy and then it goes up. So when the satellite comes, it sees a bigger mass that gets pulled. When it gets pulled, it moves faster on the orbit. And then it goes slows down because here it is smooth. It is almost the same mass, so it slows down. And then when it sees another big mass, it goes faster. So this is where we need to be careful about using the gravitational force of gray satellite mission. So what happens here is the planet is not having the same mass. And because of the change in planet mass, the gravitational pull on the spacecraft is changing. So both of them go equally in a forward speed. So this is Jerry. It runs in front because of the gravitational pull, whereas Tom only is pulled by this satellite. So it wants to maintain a constant distance. That red arrow mark is a constant distance. So when the satellite moves and then it sees a big gravitational mass pulling, so it gets pulled. So you can see that Jerry is accelerating. So this satellite accelerates in the front. And then the second satellite, oh, Tom says, oh, Jerry is moving the front. Let me catch him. So this also accelerates and tries to maintain the same distance that initially was there, the same distance. So it quickly goes and then comes back. It also gets affected by this gravity, but fine. It wants to maintain that distance. So while this is moving on the influence of gravity, this Tom monitors the acceleration and de-acceleration of Jerry, and that is converted to a gravity, a mass. So now if we know the mass, change. So every time, let me draw it. So every time it goes along the surface, so this is the surface. And this is the core of the earth. So we have all this is lithosphere. And until the lithosphere, the satellite says, this is the mass here. Let's say this is five units, whatever x is. And then here it is less mass, 4x. So now the satellite goes slower here and faster here. So this is how it accelerates and re-accelerates. And then that acceleration is used to find the mass under the surface. So this is fine, but people can ask, so where is the water part? You said mass, mass is fine, but where is the water part? Or where is the snow melt that is being reported by grace and or a lot of other data sources are reported by grace, like groundwater and soil moisture, et cetera. How is this done? This is done on a very simple aspect that when you take the earth's surface one time, you get the mass. When you come in the next month, it takes a month for a satellite to come back to the same location, then you have a reading. Let's say you take in May and June. So May you come, this is 5x. And then you come in June, this is 5, let's say 4.8. 4.8x in June. So now what has happened is 0.2x has been reduced. And this change in a particular area cannot happen over anything else because the area is big, 100 kilometers, right? So if you have to affect gravity at that mass, it's not like a tree falling down, the mass changes, no. It's something big that should affect the mass. And the only thing that can affect the mass on a monthly scale is water. So this is the very simple hypothesis that the NASA team with their collaborators found out, saying that between months, the only thing that could change in the gravity field, in the mass field is the mass of water. The mass of water could be snow, the mass of water can be glaciers, ground water, anything, but mass of water. The other aspects like dams and stuff are small compared to how many dams every pixel doesn't have a dam. So it's about mass of water. So even the same ocean. So there's two products for grace. One is land and water. So you have not all the parts of the ocean in the same depths. For example, the Mariana French is the deepest. It goes very, very deep, right? So if it's going very deep, then there's a big mass of water on top. So that mass pulls, whereas here there is less water, but it pulls less. So this is the very smart way of getting at grace. And what happens is every month the satellite goes and the change, the change in mass, which is found out by the gravity pull and how the satellite is moving is converted to a water mass change. So it is called terrestrial water storage and change in terrestrial water storage. So at the end of the day, what grace gives you is TWS, which is terrestrial water storage in equivalent water thickness, centimeters. That's the unit. It's in centimeters, but a thickness. So for example, you have the mass here, a land, okay? And there is porous space. There is space here where water is stored. Now if you remove the water using groundwater pump, then what happens? The weight of this land parcel changes. The height may be same, but the weight changes because now instead of water, there is air. Air doesn't have very much mass. It's negligible. So water has mass, right? So now this water is being taken out and that is where the change between months is calculated as TWS, TWS as terrestrial water storage. And from this, you can get groundwater. I'll write the equation later. A very, very simple equation. And you could get groundwater thickness as a thickness. And from there, you can also get groundwater levels. Those are more advanced level thinking, but terrestrial water storage is very important. So whatever water is stored from here, from the surface to the ground is called terrestrial water storage. It can include your lakes, your ponds, your dam water, et cetera. But most, as I said, not all pixels have lakes, dams and ponds. So most of the time it is groundwater that is changing. Groundwater plus soil moisture. So if you remove the soil moisture and the dam water out, then you get change in groundwater storage. There's a lot of, a lot of papers on this. The very, very famous ones are in Nature by Rodel et al. And that is where I picked up this particular satellite and started working and writing a lot of research articles on this satellite. It's a very, very important satellite for India because the data, the aquifer mapping, everything that is going on consumes a lot of time and money. Whereas this is open source. You can quickly understand the principle, which is what I explained, and look at the data for groundwater estimation. So basically what I'm saying is here that the mass is taken and the change is every month, if you come in, so every time the satellite pair goes, it gets pulled differently by these two masses. So there is acceleration, de-acceleration. So this change in acceleration, de-acceleration by Jerry is monitored by Tom. That is a very, very fine, very accurate, precise accelerometer. That's all it is. An accelerometer will quickly accelerates and monitors the acceleration and that is converted to gravity. Gravity and gravity is because of mass, right? So now if it comes every month, so this is May and then June, now there could be some snow melted. And so what happens is, the gravity is not the same as May month. And so it moves a little bit slower than May. So this change is attributed back. So the gravity acceleration is converted to a mass equivalent and the mass equivalent is nothing else but water because on a snow cap, this is land snow. This is the mountains and the hills and then you have snow on the top, right? So only the snow will change because the land is same. So if you subtract, what happens is the land mass goes away and only the snow part is taken in for consideration. So this is what we will be using in explaining these data sets, okay? When we visualize it, you'll get more information about it. So what happens later is then this, there is a pre-processing of the data which is cleaning and then making sure data is correct by the JPL and NASA, Colorado team, JFC team in Germany. Then what they do is they add some correction algorithms to convert it into a water thickness, terrestrial water thickness, and then they add scaling solutions and some other solutions to make it very robust. The resolution is a bit coarse, coarse means very, very large. So it's 100 by 100 kilometers around the equator which is where India is there. So it is not as useful as a plot scale analysis but given that it is monthly, it is the only data for India that can do monthly and assess both the surface waters changes, the shallow groundwater and the deep aquifers, right? Now the shallow and the deep aquifers are kind of disconnected. When you see block estimations, you don't see a block estimation for shallow and deep, it's clubbed together, right? So that is kind of tricky to understand what is happening but here this satellite, especially this satellite data can capture the change between the deep aquifer and the shallow aquifer using some data. So now we don't want to use this just as a standalone because of the resolution size. The pixel size is too big. So for example, as I said, you have only one hectare per farmer and 100 by 100 kilometers is too big. Sometimes even a district doesn't come under 100 by 100 kilometers. You'll be seeing the resolutions pretty soon when I open it up. So in that case, what do you have to do is you'll have to merge this data with some observation data and make a new product. And that is what we'll be recommending for future researchers and scientists that just NASA's grace data may not capture the variability in the ground as a satellite mission. But if you mix it with observation data, it is the best data. And this is true for almost all remote sensing data. If you add this with observation data, we call it data augmentation, then our value addition for data, then the product is really, really a hybrid product which is very good for management. So let's move on to see what has grace data been doing over the past few years. 2002, it started. Now it's 20 years. There was a little bit gap in between because not five years is this image might be a little bit old, but there's a lot of credit for this satellite, this special mission, which I know very, very closely. I've worked with this data a lot and it establishes me how it captures the data and almost accurate when we do some calculations which I will show in the later versions. So there are two satellites, one that is seven miles apart, almost two billion miles traveled. It's a lot of distance traveled. It measures the ice loss in the Greenland areas. It was one of the first satellites that captured the Greenland loss of ice. Just an image cannot see, an image is only qualitative. An image will show, oh, there is ice and now there's no ice, but how much was lost? The thickness of ice lost cannot be measured. Only the satellite can measure. So that is what this was done. And it also measured how much lost in gigatons, 1,550 gigatons in Antarctic. So also the most inaccessible locations where observation data may not be available, this satellite can take it. And if we know that the satellite is accurate at 80 to 90% along the equator, along the Northern America regions, then it should be also the same for the Arctic regions also. So the Antarctic is 1,550 gigatons lost ice, whereas in Greenland, 3,400 gigatons of ice is lost. So this is where with the ice melts, then it goes into the seas and oceans and the ocean level rises. When the ocean level rises, the coastal communities are getting affected. And the key coastal communities are the rural communities. Almost all communities are rural communities, except if you are in cities like Mumbai, Chennai, where there is a coastal component, but it's only very small, very small city compared to rural coverage of coastal areas. So moving on, I will open some links to show you how this data is available. So let me open this particular link in a minute. So you will see that the first link will open the data for the grace data months. It will tell you when the months, which month's data is available, and also you will be able to, and also you will be able to look at the first link conflict and then it looks into data months, when which are the months that the data is available, which months are not available, et cetera. And also you could look at where the studies are done, as I said, NASA finds new ways to monitor underground, what laws, missions at 20 years, what is the mission being doing, and there's a lot of metadata that has been done. So now the second mission is there. The first mission was from 2002 to 2016, and then there was a gap, and then another satellite was launched. While the satellite is in the last phase, so normally a satellite runs 15 years or something. So while the last phase is being there, then NASA funds a new satellite, the same satellite with advanced features, and then they set it up. So there's a grace satellite and a grace follow-on satellite mission. So that is what we have. You can see that the groundwater monitoring has been very, very successful using this satellite. This is the California part, where a lot of groundwater is being depleted due to growing of almonds and orchids. So these are very, very interesting information and data that cannot be accessed in normal scenarios. So we'll have to be very careful in assessing these data and using them for a particular application. So this is where we will be looking at in detail. As I promised, I'll show one study which was very, very important to sensitize grace data. So it was the NASA satellite data for India, and you could see that maybe I'll just open it in a browser version image. This was very, very well debated across scientific communities, and you could see that the northern region has high pumping. That is what the satellite has estimated from 2002 to 2008. There's a lot of groundwater pumping in this region, and the most scary part is it is at very unsustainable rates. So now if you compare this with the CGWB data, there is some correlation. So we also saw that there's a lot of red blocks in Haryana, Punjab, and which is also showing here in this image. So the ways forward is, but those data is only once in four months. So CGWB data is collected four times to three times in a year. Let's say three times, so every quarter you get data. So four times data in a year, whereas grace data is monthly. So every month you get this estimate and equivalent water height anomaly, you could see in centimeters. So there's nothing blue. There's nothing to be happy about. Everything is red. So over 2002 to 2008, in November, it is being red. The change is negative, and which is not a good sign of sustainable agricultural practices. So all this land is going to be affected by groundwater depletion and has been affected. So it is a, not a prediction, but an assessment of how much water has been lost. So the second link is the CCR coloradoe.edu.grace. And when you open this, there's a visualization tool. So you don't have to process the data. Everything is processed for you in this particular visualization tool. You can go to GSFC, the German algorithm, there are multiple different algorithms or the JPL, Caltech, Colorado's US version. I normally use the US version because a lot of papers have used the US version. And then we'll go here. Again, the boundaries are very different. So please don't look into the boundaries, how the boundaries are made. We don't know, but we'll just look at the regions. So these are the regions. So now the grace satellite data has been applied. We will show you how to access information. Let's go to basins. As I said, each pixel is 100 by 100 kilometers. I'll go to show you how each pixel is. So now the basins, the water river basins are being shown. So if I zoom in using my mouse, you can see that this is one data. So this whole pixel is one data and they would have done some anomaly calculations in smaller regions. So the 100 by 100 kilometers is really, really big in terms of looking at data in a very specific format. So let's look at, if you want trend, we can see how these are each pixels, 100 by 100 kilometer pixels. You can click on a pixel and it automatically populates the data and shows you what is the total terrestrial water storage change. So I'm gonna click and you have water equivalent. And you could see that this is the time when the satellite was decommissioned. So there is some gap here, but on the whole for the past 20 years, no other mission has such good data for groundwater and terrestrial water. So you could see that the water resources are increasing. The net water resources are increasing over the past 20 years. Initially it was almost stable and it goes down. So you can see a sinusoidal curve. It goes up, down, up, down. That is because in the monsoon it recharges and then in the summer season, the water is being taken off, right? So you could see that and you can also truncate and see which parts you want to see. So you can just say that, oh, I want to just see this part or maybe this part we can see this closely. And I'm going to show you, if I move the pointer, it will see that 2002 April it started and then it picked up the data picked up in September 15. So almost every 15th day of the month, the data is accumulated and then these maps are made. And then you could see that 15 September, the peak total terrestrial water storage was there. And then if it comes down during the summer season, so this would be around May. May is the peak summer in the Maharashtra region. And then June, the monsoon kicks in. So June you have this data and then July, et cetera. So this monsoon comes up. And so each time you could put a trend line to see if it is increasing or not and then look at it. So this is the trend. So the first one is the mask. You can actually put a region, you can draw a mask and then take data out. So each pixel you can click, it gives you the lat long of the pixel. Along the pixel, it's one value. As per remote sensing rules, each pixel has only one value. So within the location, whatever value it is, you have to take it up. And then you could see that these are called maskons. Part of a NASA satellite graces, data product is called maskons. So you can just download the data and work on it or you can download the maskons. Maskons have a higher efficiency, less errors as per the NASA website. So you could see here actually that there is a depletion, sudden depletion, and then now it's increasing in this part of the world. Let's say, okay, Rajasthan, this part was more Punjab and you can see definitely going down. There is no way this can be sustainable. Just look at from 2002 to now, how much of thickness of water has been gone. So if you just do a calculation from 20 to minus 60, so around 80 centimeters of water is gone, almost a meter, a meter of groundwater thickness. It's not just a groundwater fall of one meter, no. It's a thickness. So if you add the land inside the specific yield calculation, so this would be around 200 meters of decline. And that is what is happening if you go to these regions, you will see if you ask the people, they will say that the groundwater declined. And so we have increased the depth of water by 100 meters or 200 meters in the last 10, 15 years. This is very unsustainable and this is also falling in the same analysis as the CGWB data, even here, along the Punjab, Haryana and Delhi regions, there's a lot of pumping, a lot of groundwater depletion happening. You can save the data as an image. This you can save as an image or get the data as an Excel file as a month for that particular pixel you can take and use. You can also do these calculations as regions. So this is an Asian region and then see how the water has been used. But since we're focusing on India, let's look at India. So the whole of Ganges basin. So it's an average for the Ganges basin. You can see the location says Ganges Brahmaputra location. Wherever you click, it's the same. It doesn't change because it's average for the Ganges region. So if you click on the pixel, you can see that the location might say the number of mask on might differ, but this doesn't differ. So if I click outside, this changes. So Ganges, what is the overall outcome? The groundwater is depleting. It's very, very sad to see the basin which supports one seventh of the population. One billion population is depleting very, very unsustainably. So something has to be done. It's a terrestrial water change. We need to know what is actually changing. Is it the groundwater or the surface water? So that is the next step that one has to do in an analysis. What normally is the equation of the analysis is, let me just write it down so that you can also do it if needed. So I'm just gonna say, so basically your terrestrial water storage is given by grace. So the change in groundwater storage is del groundwater. Okay, let's say groundwater is equal to TWS minus soil moisture minus all the storage terms, storage. Surface storage, okay? So basically the terrestrial water storage is from here to ground, correct? Now I just want to need the ground, the core ground part of the groundwater, how much is gone? So for that, what do I have to know? I have to remove the other parts. So you have, if I draw it as layers, it will be like this. So this is the earth's surface and then you have your dams and other water resources that is part of the surface water storage.  Up to 400 centimeters, you have to take it out and after that you can assume it is groundwater. So your terrestrial water storage, if you remove the soil moisture, if you remove the surface water storage components, one is the dams, one is the tree water storage, canopy storage we call, the other is snow because snow is on the top, not on the ground. So if you remove all these and most of Indian locations do not have snow.  And as I said, the surface storage can be snow melt plus, we can also add that. As surface storage is equal to any combination of canopy storage, storage plus snow melt, melt, okay, plus dams, surface water storage. All these are there. And where do you get the data for it? That you'll have to use observation data or GLDS, NOAA, some kind of model data for it. So some grace data cannot give you all of it separately, only the total is given. And from the total, if you take out these components, you will arrive at groundwater. Groundwater is TWS minus SN minus surface storage and these soil moisture can also be taken from your NASA satellite data, radar data, which we discussed in the earlier sections. There are four components, you can add them and remove them from TWS to get at groundwater storage. So this is how we can actually look at different components of groundwater storage and then see how the change happens. So you can see that, let's quickly look at Ganges. So it's a transponder in nature. You have India, Nepal, Tibet, China and Bangladesh. So all of it is covered by this basin. So it is depleting. Your other basin which is depleting is the Sabarmathi is also depleting. And then here is your Narmada, Narmada, Mahi basin, Tapti basin is slightly increasing, which is good. And then in the central region, you have the Godavari, which is increasing, which is good. And then you have the Mahanadi, which is also increasing slightly, which is also okay. And then the Brahmani, these are the major basins, is also stable or slightly decreasing. And then you have the Krishna basin, almost stable and most importantly, the most widely used Pernar and Kaveri. So if you look at Kaveri, it's almost stable, slightly declining, but see the zero. So above the zero is okay. At zero is the average is equivalent. It's not changing much, but now it is changing. So if you come down also, it is the West Coast rivers. So these are taken from the NIH National Institute of Hydrologies Basins of India. So most of the basins of India, the big basins of India are covered and the data can be taken as an image. You can save the image of this data itself and or you can get the data as an Excel file, a CBI file and get it and then use it. So you have to download now or cancel if you want to download later. So I used to download these type of data, but one more time I use this data platforms of NASA, get data and then it'll ask you which type of solutions do you want? You want the interactive browser. This is another interactive browser also you can use. I'll go to monthly mass grids. And then in the monthly mass grids, as I said, please read this. This is the metadata of the data. It'll tell you what are the corrections that you need to do, what are the, these are more advanced level. You have to correct the data. They don't want to give you the corrected data. They'll give you the data, raw data plus the correction term. You'll have to multiply it so that you understand the process and then you get the scaling data also how to scale it and where it's not usable, what not suitable, et cetera. And then citations, you can cite these people who have developed the data and software and you can download the data. So you can also pick the months that are given and give the data, okay? So this is very important. You can take each of these solutions and give the data and as a net CDF or ASCII, net CDF is a combination of remote sensing images. You can download the data from here. You can also use the previous Earth Explorer data sources, GLDS, GES disk that we use in the previous versions to collect the data. As I said, there are multiple, multiple ways to collect the data. You can go here, race mission and then download the data. Each level is highly advanced. So you always have to go for the highly advanced level. So 2002 to April 17th, April 17th to present is the data so I can click here. If you want ocean, ocean data is given separately because that's also a mass and you are given the land data also separately. You can pick and choose which data you want to use and use it for your study because you can also do a lot of people to mass changes in the oceans that can be done. So there's a lot of platforms that you can download the data. You can also email them, they're pretty good in emails. You can have direct access, just granules which is each tile you can take out, search the tiles and take it out in Earth data. As I said, the Earth data is also working and you can also download the subsets, okay? So sometimes it doesn't work, all systems may be upgrading. So just wait for it to open out and then you'll have some good data. So with this, I hope you have understood a very, very complex data system but very, very useful data. So you can see here the Earth data explorer that we've used in the past. I just click the link for data explorer, it comes and there is two data from 2004 to 2020 and then we just download all and all this data will come. With this, I would like to conclude today's lecture. We did a little bit more than the current timing. I hope you enjoyed the session on Grace Data Analysis. In the next lecture, I will see you with more remote sensing data. Thank you.


So, I was here today at the Leadership Forum at the Future at the ITU 2014 conference to explore how governments need to respond to this very fast pace of change in ICT over the next five to ten years and I outlined 25 different strategies that we see governments adopting around the world to build local research capability, to encourage the creation of new startups in technology to accelerate the research and development process in industry and perhaps most importantly to build the capability at the top of government to actually understand what's coming next and to be able to make decisions quicker, execute them quicker and accelerate growth and development in their countries and we focused in particular on how the ICT ministries can work with other ministries to drive that change agenda because nothing they do now sits in isolation whether it's education, finance or manufacturing, it costs as many boundaries and they have to work together. This was a very important event because it brought together leaders from government, from the telcos, from their service providers to explore what's going to shape the next decade and it really provided them with an opportunity to dive deep into those forces and issues that they need to confront and to really provide a mirror against which they can test themselves to say how far down the line are we, where are the gaps in our strategy and what are the priorities we need to pay most attention to in the next five to ten years. I think three big disruptions are really going to shape the agenda over the next five to ten years. The first is the rapid rise of digital currencies where we're seeing almost entirely parallel systems being created to the existing financial and economic ones. Governments need to learn how to adapt to that and how to take advantage of what those technologies are creating. Secondly, we see the incredible speed of advancement of artificial intelligence and robotics penetrating every walk of life and we need to firstly understand what this means and how it could impact everything from the way we educate our children to the way we run our organisations and finally I think there is this kind of really interesting convergence now of technology and communications into everything in our world and every business now is really becoming a technology company whether you make cars, whether you do banking or whether you're a food company, essentially you're a technology company that happens to have some sort of product at the end of it and we all have to be world class now in terms of our capabilities to manage that technology and execute it quickly before it becomes out of date.