 Welcome everyone for today's session. We're bringing to you another masterclass in our series of agriculture and environment masterclasses here from the University of Western Australia. So we're based in Perth, Australia. My name is Kirsty Brooks and it's been my pleasure to host this series where we've heard from several of our UWA experts on how they're tackling global, regional and local issues in our natural environment. I'd just like to welcome our presenter for today, Associate Professor Nick Callow and he's going to talk to us today about how we can and are using remote sensing to tackle global problems. Nick is both a lecturer and a researcher here at the University of Western Australia in physical geography and he'll get into a bit more of the details about what he does and who he works with throughout his talks. So I'm not going to keep you any longer. We'll hand over to Nick and get started with the presentation. Super, thanks a lot, Kirsty. I hope everyone's hearing me loud and clear and welcome to you all. It's very exciting to be able to talk with you and looking forward to the engagement process at the end of the talk. I just wanted to start the talk by acknowledging the traditional owners on the land which UWA is situated on, the Nungawajak people and pay my respects to their elders, past, present and emerging. So I wanted to start off just a little sort of quick introduction so you can understand a little bit about what I do at UWA and as Kirsty sort of mentioned, I'm both a lecturer and a researcher and really interested in how we use a whole range of different technologies in sensing, remote sensing to answer a whole pile of questions. So a real focus on where my own research lies is really like Kirsty said, I'm a physical geographer. So really physical geography is about studying these key environmental processes that operate within landscapes and also the way that humans interact with them and that's I guess what defines geography as opposed to things like environmental sciences which are much more the technical understanding of the processes. So I'm interested in big sort of changes, so how people and climates change and particularly interested in hydrology and water resources and geomorphology or the way that landscapes form and the processes that control landscapes and so a really big part of sort of my work and some of the research you can see some of the partners that I work with across a whole range of different areas is using these what we call novel and emerging techniques. So things like drones and that's a big part of what I do in my own research and we've also got some of that that we include in some of the teaching programs at UWA and using those technologies and techniques we've got this remote sensing platform so platforms at UWA are basically facilities that provide infrastructure for researchers or also for students who are maybe undertaking research projects and so we've got a whole pile of equipment related to remote sensing and drones and also more broadly so using different sorts of sensing techniques and you see a little photo there on the left hand side of the screen that's this distributed temperature sensing so using optic fibre cable to measure temperature and I'll talk a little bit about that it's another you know one of these more more interesting novel sort of techniques that we can use. So really you know for me these big picture global questions there's always a spatial data element to them in understanding environmental processes and people and solving these these big problems and so that's where I wanted to come at this session at. So you know really in broad terms remote sensing is just you know encompassing a huge range of different sorts of techniques which are really about collecting information or data about something by sensing so using you know computers and equipment that measures some sort of attribute when you're not in contact with it and broadly you know this means that we're talking about a huge range of different sorts of things so they can be active or passive sensors in terms of whether they've got their own energy source or whether they're using the sun's energy to be able to measure things and really it fits also within this whole area which we would talk about being sort of earth observation so we're using remote sensing techniques to study these big picture questions climate change water resources coral bleaching and climate change influences on the ocean all of these sort of fit within this broader topic of earth observation. When we think about remote sensing we might often think about satellites or drones have become super popular nowadays but sensing is a much broader field and remote sensing can include a whole pile of other techniques so one of them is this distributed temperature sensing and that's an interesting one I just sort of talked about that briefly before but really what it does is it's one of these more active methods so you can get a laser pulse and send it down optic fibre cable and and measure temperature so sensing can be a whole range of different things and we can collect different sorts of data with different sensors this little diagram on the right hand side shows different parts of the electromagnetic spectrum so we might be collecting data in the visible light range we might be collecting it down in the microwave range all sorts of different information that we can collect across this sort of spectrum and that's only one type of data we could also collect other sorts of of information using sensors so it's not just necessarily satellites and using the sun's reflected light to undertake remote sensing so remote sensing is a really big really broad field and there's a whole pile of different techniques and methods so sorry to sort of disillusion anyone who's planning a career in drone flying but as you can see here these primates are doing a very good job of managing to control the drone themselves so what I would say is that you know drones are one technique and and one thing that we do come across I guess is a whole pile of of different types of what we call platforms or ways of of moving a sensor through a landscape or collecting data and you can see these images here move from the very close to ground to the very far away from ground from methods that you know my friend refers to affectionately as camera on a stick you can see an image there of me just using a painter's pole to hold a multi-spectral sensor above the ground to collect some information there equally we might use autonomous self-driving vehicles to navigate through landscapes that might be a really appropriate way to move a sensor through a landscape drones obviously have become quite popular and and drones can form a whole range of things right the way through these super light micro drones that can weigh a couple of hundred grams right the way through there's an example here of a drone that that nasa use which is effectively a civilian going version of a military drone but you know at the cost of about 250 million dollars so you know they can be you know quite substantial and quite expensive platforms and then obviously right the way through to satellites and satellites form a whole pile of different types so there's a couple here that I've just illustrated with those diagrams which in terms of you know ones that are using maybe light and lasers to measure height so radar altimeters here measuring the height of water or maybe we're collecting land surface land cover information so it's really important in this field to really understand how different types of platforms and different types of sensor are going to collect different types of data and understanding how that data might answer your question depending on what it is so one thing we start to to think about within this sort of geography and gis spatial data sort of area is understanding when we apply different platforms and sensors to collecting data what sort of data we're going to get to answer our questions and so I put up here a couple of different diagrams of some work this one here on the left hand side is related to looking at coral bleaching and other sorts of events within the marine environment but thinking about the different sorts of scales that we might like to study things on so you know we use traditional methods like like diver based methods and that can include collecting remotely sense data by divers just swimming across you know a little area of reef really looking at the micro scale of corals which is going to be really important for understanding them and how they work and change right the way through to we might want to try and collect data across the entire great barrier reef to understand how the reefs responding to threats like climate change or crown of thorn starfish or responding to nutrient runoff and and turbidity and other sorts of stresses so really this question about different remote sense data there's no single type of data that we can use and this principle applies right the way across agriculture marine environmental questions all of these really is about understanding things like the size of the data or the pixel size the scale the area that it's covered and also the frequency and this is something that's constantly changing and evolving i'll talk a little bit about that i'm just going to play a short video here from one of our phd students he's going to talk a little bit about his work in this area so dan you're working for your phd using spatial data you want to tell us a little bit about the sort of spatial data that you're using and sort of skills that you need to do that sure ala so i use gis and remote sensing pretty much every day and we work with data from many different scales and that means looking at maybe images from small fields with drones or from collected from satellites well i think today there's no absence of data i think there's so much data available to us and most a lot of it's free it's out there you can just go and download it but to have the kind of programming and geospatial statistical tools to be able to interrogate the data not everybody has that and so that's where the imbalance is and i think taking advantage of those tools mainly programming and dealing with big data like time series so yeah i think dan makes some really good good points there and sort of highlights some of that work and and this is some of his work on the right hand side here and and looking at different sorts of methods so he's trying to look and understand how climate change is changing flowering patterns of vegetation in in the southwest or western australia so he could do this a whole pile of different technologies techniques different sorts of satellites but understanding how frequently they sort of revisit areas the scale that they cover all of these different compromises and niches is really important to answering his question and it's something i'll talk about in a second but this is also changing and has changed dramatically over the last few years so remote sensing often collects these very rich what we call data cubes so data cubes are data that's got all these different dimensions so here's a good example of some data which has basically been stacked up on a cube and you can start to think about how complex and and large these data sets and time series start to get so you know when i certainly started off in this area we might get one or two you know images of an area whereas now things have changed quite quite significantly we can get really frequent data and this maybe exists across an area and so that's if you like that sort of flat plane in the diagram but also these data set can be stacked up over time and then they also might include a whole pile of different information so for example satellite information we might have seven or nine different bands of information that might tell us different different things so you can start to appreciate the data gets very large but really really powerful so one of the lecturers at UWA Shireen Hickey Dr Shireen Hickey she's going to talk to us a little bit about some of her work and and some of the skill sets and things that she seizes very important in this area so Shireen the people that you work with what skills do you sort of use and what sorts of questions do you find that you're able to answer with your background in GIS and remote sensing? Yes I use my GIS remote sensing background to look at the marine coastal environment so to look at changes and drivers of what changes so mainly looking using satellites so the benefit of using satellites is that we can monitor anywhere in the world so we can see if what we see one coastline for instance are on the WA coast is also occurring um elsewhere in the world. At the moment it's quite interesting it's a lot of the skill sets around coding and being able to code but also understanding that data so lots of people coding is quite important it's being taught in different areas of the university but the with the GIS side is that having that geography and that understanding of spatial data because all of our data we can collect it but it all has a location so understanding that location and being able to integrate that with the different data that we get. It's been interesting I guess through a part of mine we've seen Landsat come become open data source for having freely available data but also having nano satellites and drones being having so much more data available is definitely something that I've been across since when I started my undergrad to now and just having that amount of data means we can do so much more analysis with it so I think a lot of that skill set that probably has changed is around being able to use coding to do that but also it still has that same basis in geography so understanding those geographical concepts is still really important. Yeah so I think she's in you know is sort of flagging some really interesting things so really the way that data you know certainly agree with what she said they're the way that it's changed she's got much more powerful time series but then the skill set that we need to do that is probably changed whereas before we might have done a lot of manual processing because of the amount and the volume of data that we've got we've really needed to develop and change and develop these skills in in coding to be able to automate a lot of the processes. I think the other thing that she's flagged that's really important within this is this idea of understanding the fundamentals so down here I've kind of summarised a whole pile of different sort of questions or problems or challenges with geographic data so understanding things like you know the the way or the scale at which you represent or resample data spatially can have a really huge impact on on your data set the way that you project data sets overlap data sets represent and sample data sets all of these really fundamental geographical ideas even right down to what's called Tobler's first law of geography this you know rather simplistic but but fundamentally deep sort of statement that you know everything is related to everything else but near things are more related than distance things understanding those you know kind of geographic principles and ideas is really fundamental so if you're an ecologist or a biologist or someone else who's picking up a geographic data which is increasingly easy easy to do really important that you know you're also balancing those fundamentals so again those fundamentals remain really core to to understanding what you're trying to do and then thinking back to those other past slides so thinking about the right technology for the for the question so one of the things I certainly come across a lot is people saying oh I've just gone out and bought a drone I'm trying to think about how I can solve my problem with the drone whereas what we'd really I guess encourage students to do with within our courses and and encouraging out our PhD students and we do in our own research is really to say well here's my question what types of data do I need how frequently what size what scale and then what's the right technique so you know really I'd say you know core thing is understanding these principles and driving solving big global problems from the question of the problem not the not from the perspective of the tool or the technique so I think that's a really important one that is is important to keeping in your mind so I think Sharon did a really nice job flagging some of these and I've got a sort of great example from some of her work that that I know of so for example you know with this availability of Landsat for example and also things like cloud computing capabilities so she's got a fantastic paper that she published from a couple of years ago and she pulled down and downloaded a whole pile of different scenes and balance them and adjusted them for the impacts of atmosphere so she could do you know a nice time series analysis of how mangroves are responding to to change and then the implications of stored carbon within those mangrove ecosystems which is really important that took her about eight months to do that work to give you an idea about sort of four or five years later now because of the power of open Landsat and platforms cloud computing platforms like Google Earth Engine that store all of that data the work that took her eight months to complete she can now complete that in 15 seconds so that's the sort of nature of how some of these cloud computing platforms have have revolutionized and changed things so things like Google Earth Engine store a massive archive of different remotely sensed datasets on their engine and then have this computational power that you know just you know allows you on a on a you know a couple of hundred dollar laptop in in any country in the world to connect in and to utilize that capability so where universities were investing millions and millions of dollars in high performance computing to answer these big global problems things like cloud computing platforms in the last you know three to four years have just revolutionized this area the other thing that we started to see you know certainly when I started off you know it was a lot of proprietary software so things like Esri really had locked up the market in GIS software so really open access software so things like the QGIS program which is really fantastic and also geospatial capability within things like Python and are really really powerful really really powerful so really we've also fundamentally shifted in that you know GIS and spatial data is now a lot more accessible to people so money to some degree has become not so much of a barrier and that's been a really important development the other ones that we've seen have been this sort of changing of the nature of of collection of satellite data so in the past you know we'd have very large research programs hundreds of millions or billions of dollars of government funding to build very dedicated high quality satellites things like the Landsat platforms or the Sentinel platforms you know requiring huge amounts of cooperation and funding and really centrally driven that business model only in the last again couple of years has really been flipped on its head so things like nanosatellite clusters have really revolutionized this area and these are more kind of private companies that are investing in a different way of collecting data so instead of launching one single satellite that collects a whole pile of information so Planet for example have have launched a nanosatellite cluster that allows us to collect data every single day so where methods before gave us data every couple of weeks now we can get it every day and then to give you an idea again how this whole area is changing again you can actually now go online and design and get built your own nanosatellite and then you can also go online to another provider this rocket lab down the bottom right hand side and you can actually book in a launch and send it over to New Zealand and they'll pop it up into space for you so if you've got about you know something in the order of a hundred hundred and fifty thousand Australian dollars you can you know go and launch your own satellite now so this sort of capability was not even dreamed of the other thing we have happened and particularly within Australia is Australia probably getting a bit more sort of catching up and was maybe a bit of sleep at the wheel but the Australian space agency has been established in the last couple of years and really looking at building the sovereign space capability and this is something that's being repeated right the way across the world and that's within dedicated space agencies or within the way that the sort of diversification commercialization openness and freeness of data has really allowed different people across every part of the developed and developing world to be able to access huge amounts of spatial data and you know something that continues to change dramatically also seen obviously with drones they've become really quite quite popular and really revolutionize the way that we can go out to particular areas we can be in control of collecting data ourselves you know where we want it to collect it at particular you know high resolution and and over modest sorts of areas and I guess with drones and with a whole pile of those other technologies it's trying to understand where they're where they're going so I really like this quote from the economist that says trying to predict where drones are going at the moment is a bit like trying to forecast you know for example what mobile phones were going to be like in the 1980s and to sort of put this in into the context of a mobile phone um we're at the point where we haven't even invented you know relatively cheap consumer phones and it took us basically 25 years to invent the modern smartphone from the first origins of you know of commercial mobile phones so we're sitting at around about the 10 year mark for commercializing drone usage so really this these other sorts of methods are rapidly changing and are fundamentally shifting the way that we go about you know how we go about solving these these big global problems and you know where before you know there was quite a modest number of jobs you know the drone industry is is predicted to you know grow by billions and billions tens of billions of dollars over the next few years and there are jobs and opportunities there that never existed across a whole range of areas and they might be for people that want to do and design the drones the hardware and the software systems within them and the robotics and systems integration type people people that are going out and collecting drone data although I've already flagged that as being not not the major part of the question but really in more the you know drone sort of logistics area but then really those those core areas so GIS spatial data remote sensing you know developing the workflows and the smarts to get data out of drones it's very very simple to go and fly a drone it's quite complex to get really good usable data to answer your questions out of a drone that is certainly the the trickiest part of the operation if you can play a PlayStation you can fly a drone but not necessarily everyone has the right skill set and background to be able to to process that so that's really where you know developing your skill set can be really important so I wanted to sort of flag some of the sort of different scales or ranges of questions some of the stuff that I work on and and happy to sort of return to these but that's a really big question right the way across the world within Australia other continents where we've got very large dry land areas so dry land areas the potential evaporation is much greater than rainfall and so we have really acute water stress in these areas but we don't necessarily have the data to understand those water resources and so this foundational paper here really setting in set out a whole pile of challenges that we we sit sort of facing and that we're still trying to work to to you know provide industry with the tools to to solve problems about water but really you know there's some really nice stuff that we've been working on doing taking data from satellites using that to make in this case down the bottom here predictions of water level without any water level data whatsoever the other thing is starting to do really sort of interesting stuff in trying to get again satellite data and calibrate hydrological models that tell us where water is in the landscape and how much is driving a whole pile of ecological questions and things like that by using remotely since data so again these are questions that we just didn't have any ability to answer and a fundamental you know right the way across you know things like providing solutions to the mining industry on you know where they should put you know billions of dollars of infrastructure right the way through to addressing challenges set out by the united nations and then right the way into things like the sustainable development goals around water and how that underpins a whole pile of things so this distributed temperature sensing is another sort of interesting area again it uses these pulses of light down optic fibre cables but in this case we you know did some some sort of pretty cool research his picture of Bonnie Stutzel one of the phd students so she and and we sort of went out and built this basically three point six kilometer long fence of optic fibre cable through through crops to measure frost events and try and better understand frost events and how they work and and try and address something that that costs you know hundreds of millions of dollars a year in in lost production some work on the right hand side here with some fire ecologists are using these really cool emerging techniques putting optic fibre cable through soil and understanding how things like different litter loads affect temperature in soil and survival of plant species how weed species are affected by the fire regime you know how do we control burning in in landscapes and how do we use that and and how do we look at things like you know the big issues of bushfires that we had within Australia that happened within you know much of of the sort of dry parts of North America South America and Europe and and and understand these sorts of process so again you know really important the spatial data the temporal data and using a sensing to to use that one here of some of the work we've been doing in more alpine landscapes so in this case a whole pool of data that's collected as at one specific location so in this case what's the depth of snow it doesn't necessarily relate to the depth of snow right the way across these alpine regions and these sorts of areas are really important globally so around about 20 of the world's population relies on water that runs off from seasonal snow packs annually and faces this problem and within Australia it's pretty huge one so about a third of the renewable energy to the east coast of Australia comes out of the snowy hydro scheme there's a huge number thousands of irrigators but understanding the actual quantity of water and how climate change is impacting this isn't just a matter of going out and measuring snow or looking at the long-term records because in fact those long-term records have got a whole pile of spatial bias problems fundamental geographical problems with the data set that mean you can't just take that data set and do those analysis so again there's this really important element to understanding the data and what's sitting behind it here's another one this is using a drone with a thermal camera we can develop these complex thermal maps of ecosystems in this case we've got different types of tree species some eucalypt species bankshire species some others and and looking at the temperature of those species and how they respond to things like water stress and drought stress trying to understand really fundamentally critical question of in a globally warming climate and in this really important ecosystem that's listed as as threatened what is it that drives the decline is it hot events or is it the water stress and or the combination of those so really the scale at which from this case drone data can can help us answer something is really changed change things dramatically so I wanted to kind of wrap these up a little bit I've got one last little sort of interview here I did with Ben Radford he works for the Australian Institute of Marine Science and also UWA he's involved in our teaching programs and asked him to sort of talk a little bit about what he does but also for example some of the graduates that he employs what skill set does he look for in those? Ben you work with Ames the Australian Institute of Marine Science you're also involved with University of WA just a little bit about how you use spatial data and sort of questions you're answering. Nick so we use spatial data implicitly for all our questions around things like climate change so for example looking at temperature events looking at changes on coral reefs using things like rain shifts so that's changing of communities in response to these sort of climatic level changes also how that interacts with people so that can be industry it can be different bits of planning so it's really fundamental for decision support so really everything we do is spatial data eventually feeds into that decision support space good question so there's been a couple of big changes one of which is that is the amount of data that we now have to access so I do a lot of work in the satellite space so we've gone from having data once a month for having satellite information daily which has made a that's been a huge acceleration in data and to deal with that we've had to go to online processing so a lot of the work we do now is not done on desktops or laptops it's done online things like Google Earth Engine or Amazon tools and to be able to do that we've had to go we basically have to learn the program so a lot of what we do now with or a lot of analysis is done with with one and one programming languages so we may have not done computing science in the past but that's a big interplay with our geography and our spatial analysis fundamentals haven't changed and that's really what that's the difference in a spatial scientist or spatial data scientist and a data scientist is that you still need to understand all the fundamentals around spatial analysis geography his ideas around scale both in space and time there's still they haven't changed so that's really what that sort of nexus is is the fundamentals and then these new technologies and these new new modelling approaches it's basically bringing them all together so to make sure you still have robust and meaningful results at the end I actually have employed a number of graduates myself I think it's a combination of things I think that it's good theoretical knowledge it's also the ability the kind of analytical skills the ability to to process and be quite flexible but with analytical skills a process a lot of data but I think that one real fundamental that hasn't changed is this ability to basically describe analyse and communicate your results in a really meaningful manner so it's a combination of the old skills of actually theoretically understanding what you're doing and have good good communication skills but being able to combine that with the analysis skills that we are now commonly needed and commonplace I think that in today's job market and academic I think having analytical skills is really key you're never going to not benefit from having some basic programming languages some analytical some analytical background or some analytical courses and being able to do things online as well I think is really important and that really enhances whatever other thing that you're really passionate about you can always bring those those skills to to any any sort of either job or or project or or course that you're using at university I think the other thing about them is those skills are quite universal and you may go through many different types of career trajectories or particular projects and you can apply them and enhance them at each stage but yeah they're really fundamental yeah so I think Ben sort of bought a whole pile of the themes that we've talked about in the in the seminar together so really here I want to sort of end off on things and I'll throw it across to Kirstie in a second so you know I think there's a whole pile of different things that you can do if you're interested in this area if you've got some skills or you want to develop some skills I think there's a whole pile of different free tools and opportunities to drive your own learning if you want to I've certainly learned a hell of a lot watching YouTube videos and and playing with things and finding a problem and throwing myself at it so things like Python I think are really fundamental and some of those geospatial packages and and using and getting familiar with that really helpful using things like QGIS you can download that you've got a whole working GIS system you don't need to pay hundreds or thousands of dollars in in in fees to access really high quality GIS software nowadays a Google Earth engine again is free to learn how to use that it's an amazingly powerful tool we use it a lot in our research and you know you can develop those skills yourself against some self-guided work using packages for for processing different datasets you know either collecting your own data if you happen to have a drone yourself or you can actually go to the manufacturer's website so a whole pile of different manufacturers actually provide trial datasets so go and grab those datasets go and grab a demonstration version of some of the software packages and actually just you know start to develop the skills to to process yourself the other things would be you know just trying to understand you know the spatial data we've talked talked a lot about you know you can go out and all of these things are free and they're out there but developing the smarts to understand how to use this stuff appropriately is really where it where it lies so I know that might be you know if you're within you know sort of UWA or some sort of other university environment there's a huge range of different options and that might be right the way within a sort of you know actual geography GIS spatial sciences sort of area and we've got a whole pile of range of options within the undergraduate and postgraduate sort of areas into some of the more data sciences and electronic mechatronic engineering areas or in very applied sense so things like our agricultural science and agricultural technology specializations in our undergrad and masters programs again at UWA so these are you know more in an applied context so looking at agriculture looking at a particular area but looking at those you know techniques things like precision agriculture is going to need all that data but you know doing it in an applied sense so really yeah that's that's about it I'll throw it back to Kirsty to to coordinate things and yeah thanks a lot for your attention it's been really super opportunity that was awesome thanks Nick I love getting a deep dive on some areas that I'm not so familiar with I especially found it interesting that last slide with Ben on there the the resolution that you had on that reef there being someone who does diving and stuff you can actually see like individual colonies of coral and being able to get that now as opposed to you know back in the day it was you know what you remembered what you were measuring when you under the water then we've got to a point where we're able to take pictures which is still quite two-dimensional and now we're in a place where we can actually create these 3D images and you know we are out in the field and being able to get them but then we can also analyze them to a much more rigorous standard back in back in our offices in the comforts of the home I think the interesting one that goes with that question is you know anyone can go and grab a camera and take overlapping photos on the reef environment now and then it's also that skill set to put it together to understand some of those challenges of managing the geographic data so you can then answer the really cool you know applied marine biology marine ecology you know climate change sorts of questions on those on those systems but yeah the the scale of data you know you're talking millimetre pixel three-dimensional reconstruction of reef environments and then being able to monitor how individual colonies and individual species are maybe responding to a bleaching event so yeah the capabilities now you know that you can do you couldn't even answer that question three or five years ago no no you couldn't we were doing much more broader stroke kind of conclusions without the technology but as it seems like the technology is now caught up and we need to catch up to the technology or invent something that's going to help us catch up to the technology yeah all right we're going to get to some questions we're going to get to some questions guys so we've got a question in there so this is more in that agriculture specific area what do you see as being the most important uses of kind of remote sensing technology in agriculture especially in countries or areas where you know being able to use the land for different agricultural purposes is difficult and the question was also asked can you use the technology to fix soil by controlling plants but i guess it's more knowing what are we at what information are we actually getting from this technology in those kind of spaces yeah i think no the agriculture space is really sort of rich and right for this and that exists across a whole pile of different sort of scales if you like in terms of like big broadacre farming through to you know intensive horticulture i think you've got different types of farming systems so within say western Australia for example we're talking a lot about no large grain farming operations where we've got access now to tractors that have precision agriculture capability and we can do really interesting things like bury the amount of herbicides and fertilizers that we use we can be a lot smarter about that but the gap that we've got we've got the capability in the tractors we don't have the ability to actually tell the tractors what to do in more developed environment countries i think you can do some really you know interesting stuff you know across a whole range of things so some of these you know cloud computing platforms for example you know before it was really difficult to access a lot of you know time series data to look at land cover change or to look at you know productivity of land understanding you know how you know land was productive through different droughts or understanding you know different technologies so really you know i kind of almost throw the question back on on on on itself in terms of i think you can answer any question some questions are more suitable than others but it's them thinking through the types of data satellite data or is it grown data or on-ground data and utilizing these technologies and techniques and understanding you know how to how to use them yeah and i guess what this what this space is allowing us to do is that concept of work smarter and not harder being able to create better management to the practices that we want to do and i really liked how you mentioned that you get the students or your new if any new project to okay what's your question what's the best way we're going to be able to answer that question let's not just go out and get a plethora of data and then figure out how we're going to answer the question let's be much more systematic about it in thinking about how we get that also understanding you know remote sensing techniques or you know using a drone for example might actually not be able to answer your question so trying to understand yeah which which which techniques are gonna are gonna benefit yeah okay got another question here the ability to use remote sensing to measure rates of carbon sequestration towards moving toward that net zero emissions within our state climate policy specific for WA as 92% is not is crown land so that potential there's massive so do you know of any work that's been done in that space yeah or sure in that we had the interview with is more more sort of in the coastal environment but the nice little picture behind me here of one of field sites that i've worked on with her up in in xmouth that looking at sequestration of carbon of of carbon in mangrove environments and that's certainly something that sure in's been working on as a focus of her research i guess the question's more more focus on the on the range lands and those sorts of areas so again yeah the capability to do land cover land surface assessments looking at land condition and monitoring that over time and then trying to understand that it is a huge potential and obviously the markets for carbon and biodiversity farming have started to mature and some really important opportunities there um so yeah i think you know there's certainly a focus uh and a huge opportunity to develop those methods to do those sort of greenhouse gas and carbon accounting um works and and monitoring land cover um depending upon you know those sorts of things whether they're local markets whether it's um you know accounting for biodiversity offsets that people might be engaging in people you know looking at carbon farming opportunities or you know just accounting for whether australia is meeting our international obligations around uh you know carbon and and other emissions and and related to land cover change yeah yeah so um for those of you that weren't in the room last week we actually had um merit merit crag uh and she spoke a little bit about carbon farming and she comes from it from a much more uh she's a she's an economist an environmental economist so she comes from that angle so she works closely with um the scientists when coming up with those kind of economical ideas around the whole idea of carbon farming and being able to use the data that people like nick and others um come up with to uh provide information into that so i guess we've probably we did have a um while you were answering that last question we had another one come through that asked about the prediction of uptake of greenhouse gas emission monitoring using satellite data so that's um something that's already in practice yeah i can see see there's also a follow-up one also talking about co2 NOx and and methane emissions and things like that so again it's using these different types of methods so um jason behringer who's within our our school here at uwa for example he runs a flux tower uh and is actually the director of of a group called uh osflux so osflux is a series of flux towers flux towers are measuring basically the exchange of a whole pile of gases and and things from the land surface to the environment um and that's really these very detailed sensing of point measurements and then remote sensing is certainly able to look at some of those different elements of you know co2 emissions um and uh yeah and so if you look at um people are interested you can look at leap leap is jason's network of flux tower sites there's some really cool stuff um out there with that so you know remote sensing is about basically being able to sense or measure often some surrogate so things like uh lamb cover change where we can understand that um directly uh trying to understand and sense you know NOx or or methane emissions directly um you know you can be done with with sensors but doing it with with big large scale sort of remote sensing platforms but certainly you know the capability and needing to do that and understand it you know understanding you know emissions from you know different land surface cover types dams reservoirs um you know our farming land you know livestock and grain operations all of these things across the australian landscape is really critical to to understanding and addressing you know climate change uh as as a partner in in the globe yeah so making um observations that micro scale and applying them to a macro scale is really important you can't again broad brush strokes isn't going to give us answers we need to understand local environments as well yeah it's being able to dance between those different scales of saying you know we might need you know flux towers that are measuring a very limited area but give a huge amount of understanding the processes and then trying to scale that across the whole of australia using other surrogates that have been remotely sensed at that continental scale so yeah potentials there yeah a hundred percent so for those of you not um very familiar with the australian landscape or the size of australia where we are basically um how many is it like the size of france germany basically the whole of main mainland europe um is how we compare ourselves or um similar to the stretch across the united states again but only a population of minuscule amount compared to those areas uh and mainly populate populated around the coastline so um we're in perth which is on the west coast uh for those who might have heard of melbourne and sydney they're over on the east coast currently three hours behind us in the time zone so yeah we're a huge country with a very varied types of environment that we are monitoring and helping to make these um these conversations happen i'll grab one are you reading richard's question i am can't answer the choral question in in detail on the south side of wroughtness but if you're interested richard i could uh put you in some contact with some uh people that might be able to but certainly you know real time sea surface temperatures um you know for tourists or for or for anyone you know understanding that you know marine ecology you know understanding in real time where you know bleaching events are happening you know we can you know got much better understanding of prediction you know i'm not a not a marine person that certainly work with those people but the capability now to understand where sea surface temperatures are tracking uh and understand and and to kind of foreshadow some of those big bleaching events is now pretty um unprecedented you know understanding the ocean currents and how they interact with climate um you know being able to send big big um oceanic you know changes things like the indian ocean dipole and La Nina El Nino events uh in real time that we can inform climate models we know that these are really really important you know sort of climate patterns that we've entered into particularly in the east of australia um you know would suggest our our summer this summer is not going to be as bad as the last one in terms of being very dry uh very hot and severe bushfire risk so some of these things you know really you know really sort of capable certainly different remote sensing techniques being used to answer whole pile of questions who you're talking about sort of marine uh sort of megafauna things like humpback whale migration so ben talked a little bit in that video about looking at at range ships and and you know whole pile of things from you know humpback in in the marine environment for example you know from humpback whales you know um large sharks these whale sharks you know through to sort of kelp beds uh corals uh and looking and analysing these range ship uh patterns um you know understanding that understanding some of the other variables that might be driving it becomes uh you know really really powerful uh ways to start to understand the processes as well yeah so i've just popped a couple of um links into the chat for everybody um the last two that i've linked in there noa n o a is a really great um international source of data um so if you are just interested in your local um local sea surface temperatures noa actually provides uh data that you can look at and analyse yourselves at different scales and then i've also popped in a um link to a another online session that we did earlier this year with another uwa academic jeff hanson where he talks about um marine and coastal uh movement so he looks at um coastal processes along the different coastlines and he has a great example in that talk about how they're really uh lucky enough to um grab the an event that happened here in may where we had a huge storm come through and you can actually see those changes immediately from some some uh photographic data that he got along the w a coastline so pop them in there i also linked in the osflux um and leap websites that uh nick mentioned for one of our other academics jason barringer and his group um of where they're doing so i've got a got a question in the in the chat there from uh who is it's edwin in zambia so hello to edwin out there uh in a dryland location and just saying um i've seen areas that had water or so 15 years ago with drylands now and buildings are being erected what effects will this uh be how do we reverse this going forwards i mean i think it's no great question no drylands are really interesting places um you know zambia australia very similar sorts of things in terms of you know places that can have be very wet at times and then be very dry i don't know zambia in detail but within australia we even struggle to have enough data to to look at um questions around you know water and where it covers floods and those sort of flood risks what we do know is that everywhere around the world is becoming increasingly more populated and unsurprisingly we picked the you know the best and the safest spots to settle first so people um are being displaced and moved or or choosing to shift into areas where they become vulnerable so you know within drylands on flood plains and things like that it's certainly something that we see and and different techniques and that's a motivation for some of that work that we've done in trying to use different remote sensing techniques to try and measure these floods uh or flood potential in in areas and using different methods like satellite altimeters and and different optical satellite platforms to try and pull in data to understand these questions where we just don't have that kind of raw on the ground observational data so it's a real big um sort of challenge um to try and address um yeah another one in there a follow-up from richard's talking about how can we increase public access to the data well i think we're getting a hell of a lot better than that at at that um and kind of foreshadowed a whole pile of those different tools so you know if i look back you know five or ten years ago you know you needed to be part of the university you needed tens of thousands of dollars worth of software and you had to pay for a lot of your satellite data so um you know this you know to a degree i think we've moved along why i think governments have really come to the party in making a lot more of their data sets open uh and uh and online and um i think that's really gone a long way to um you know helping to address it but you know now i think you know now now more than ever we know more of those tools are in people's hands and they can uh you know those sort of list of of different options you know picking picking up and learning google earth engine you know you can go and and analyze land cover change to in fact there's data sets in there that people have already done all the hard work for you so there's a whole pile of questions you can go and answer that again you know two three years ago you didn't have the data you didn't have the processing capability you didn't have uh access to licensing uh to actually do these things and you know it's really exciting that we've actually cracked the nut of a lot of these problems uh and are continuing and and i can only see them improving from now fingers crossed let's answer one last question um there is one that's come in from uh maybe in the philippines judging off their their questions so um he said thank you it's an interesting topic topic and it's interesting how that this tech can actually play a role a pivotal role in the agricultural sector however for developing countries such as the philippines where farmers hold only small areas of land it may cost too much is that something is there different ways that different technologies being used at a smaller scale to help the ag industry yeah i think um again things have changed and and and different you know techniques or um methods have really come about so um first more small scale you know horticultural type you know activities that made more happening in those sort of wet tropical sorts of of areas it's really about thinking through this this way that we approach it so thinking through your question so you know what what do you want to answer you know is it you know about productivity is it about what areas are being used by different crops or farms to understand that and then think at the scale are you talking about you know understanding a whole field or you understanding you know like individual plants within fields you know do you need data that's a meter across or 30 meters across and you know do you need data every day or once a week is fine so really you know i'd say you can answer potentially any sort of question so i'd i'd go back and and work your way through that question say you know what's what do i want to know over what area what scale of data am i going to need and if you want to look at something typically you know you might want three four maybe six pixels that cover an area so if i want to look at a field i don't just want one pixel that covers my you know 100 meter field i might want pixels that are you know 20 or 30 meters across and that will then say well you know land-sat or sentinel data might be really useful to answer that question or if it's at a much finer scale there might be other satellites out there and some of them are free and some of them are not free um but i think again for you know countries like the philippines or or or a whole range of other countries that may be you know price and and access to you know computers to process it to the data sets which has been a real obstacle and certainly an obstacle even within australia and and for a lot of the you know phd students that we work with you know money is is very difficult to to fund so you know a lot of the innovation is being driven by by people and a lot of the effort that's being put into um developing these tools is very much under the spirit of open access to the data to the software tools and this is probably really the exciting area that we've now you know got tools and got capability at at at free or or very very low cost that um again three five years ago you never would have had won the computational capability or um or the um or the funds and resources to answer these questions so yeah it's it's a super exciting area yeah it's amazing i will there is one last question that i do want to get your answer on just to aware of who the audience might be in the room uh what can the w a government do to help develop applications of remote sensing in w a yeah i mean you know within the the landgate uh group there's certainly uh you know capability and some expertise within the w a government um the w a government you know the people that i know that i work with across a whole range of different agencies you know the department of primary industries regional development um particularly the agriculture space but also knowing the marine space in department of water environmental regulation department of biodiversity conservation attraction all of these state government agencies have some really amazing staff that have fantastic skill sets in it i think um you know there's really good opportunities um yeah i think we could do do a lot more i think you know providing you know more resourcing i think the w a and local state government um buying in and and partnering with things like the Australian space agencies are really exciting uh opportunity so you know we've got the opportunity in the next five or 10 years to decide what are the questions we want to answer and go and design and launch our own satellites that we want to to do this instead of just relying on all the other things that that other people have put into space so you know the the whole area is really opening up it's a case of of having the um you know a bit of um sort of entrepreneurial sort of spirit a bit of um you know i can do attitude and having the skill set and the motivation and and and getting you know the politicians and the public you know the public are the ones who who elect the politicians you know we can get enough people uh to understand the capability you know and all of the industry sectors you know across agriculture and whatever you know there's a whole range of different um datasets and uh information that supports decision making so you know as people understand the capability and the production benefits where we're going to get from it um it's just a really exciting time and an opportunity with with a huge amount of upside yeah that's awesome i'll leave you to it and enjoy the rest of your day or night or morning wherever you're coming from around the world thanks again nick for taking the time and uh stay safe and healthy guys so far thank you