 Namaskar and welcome back to the video course on Watershed Management. In module number 6 lecture number 23, today we will discuss remote sensing and applications in watershed management . So, some of the important topics what will be covered in today's lecture includes remote sensing, basics, features of remote sensing, remote sensing process and advantages, important satellites, image processing, applications of remote sensing in surface water and ground water, applications remote sensing in watershed management. Some of the keywords for today's lecture include remote sensing, features, image processing, electromagnetic spectrum and satellites. So, as I already mentioned earlier, when we deal with the watershed management or watershed management plans, we will be dealing with a large area just like a watershed river basin or a catchment. So, it is a very huge area. So, where we have to get so much of data like the topographic data, land use data, land cover data, soil data. So, like that so much of data are needed to develop appropriate management plans or to develop models to study the various behavior of the system just like a related to water resource management or land management or the development of various rainwater harvesting structures like that. So, since we need a huge amount of data, so if you go to field and collect data there is limitations since we cannot get to entire data in an appropriate way which requires for a modeling or which requires to develop appropriate managing plans. So, that way as we discussed earlier the remote sensing helps in a big way for hydrological related modeling or watershed related planning and management. So, in this context, in today's lecture we will discuss some of the basic aspects of remote sensing. Remote sensing is a big area where so much details we have to discuss, but today's lecture we will be discussing only the important perspectives which are related to watershed management and some of the basics and applications related to watershed management. So, let us now look into the some basic aspects of remote sensing. So, remote sensing as already discussed earlier remote sensing is an arch and science of obtaining information about as features from measurements made at a distance. So, here as the definition shows we are not directly going and getting the data or we are not coming to contact with the various the data which you are directly collecting, but we are getting the data remotely say from a distance say that it can be just like an aircraft flying over the area or a satellite passing over the area. So, at a remote distance say through various means we are getting the data required. So, that arch and science is called a remote sensing. So, that where remote sensing is a science of making inferences about objects from measurements made at a distance without coming into physical contact with the objects under study. So, when a satellite is passing over an area a watershed or a river basin, then it is sending certain signals or it is collecting certain data based upon its movement and various other parameters. So, that data we are processing and utilizing. So, that way the there is no direct contact with the objects, but we are getting the red data remotely. So, generally remote sensing means sensing of the earth's surface from space by making use of the properties of say electromagnetic wave emitted, reflected or diffracted by the sensed objects for the purpose of improving natural resource management, land use and protection of the environment. So, this is a general definition in modern times with respect to remote sensing. So, earlier there used to be a number of ways we used to get this data remotely either using some balloons or we use aircraft. So, nowadays we are using mainly satellites remote sensing satellites. So, in this say we are getting the data in such a way that the electromagnetic waves emitted, reflected or diffracted by the sensed objects we get back this data and then we process this data and then we use it in an appropriate form. So, that is the modern day remote sensing, but earlier times we used to get data through say through using flying over the by using the aircraft or by using balloons or other kinds of mechanism. So, that way remote sensing now plays a major role in most of the water shed development management plans. Since we can get to so much of data, since one scene gives may be a spectro of the water shed which we consider and then once we process those data we can get on our computer the details like land use, land cover, soil map or the slope map. So, all this after processing in a remote sensing package or the GIS package we can make it in appropriate format. So, that way the modern remote sensing using satellites we are using the electromagnetic spectrum. So, that means say you can see that the various spectrums of electromagnetic spectrum are listed here. So, here we use the bands that refers to spectrum channels in the electromagnetic spectrum. So, here we can see that as per the wavelength in micrometer there are various electromagnetic spectrum bands. So, like a cosmic rays x rays then gamma rays ultraviolet visible near infrared, mid infrared, thermal infrared, microwave. So, then the wavelength used for television and radio. So, actually for remote sensing purpose we use these ranges starting from alpha value to sometimes to microwave. So, here I have listed various bands. So, the band means here bands refers to spectral channels in the electromagnetic spectrum. So, bands 1 to 7. So, my wavelength are given in a micrometer. So, starting from 0.5 to say 1 meter. So, the nominal spectrum location say for example, within the wavelength of 0.45 to 0.52 it is blue and then 0.5 to 0.62 green. So, like that. So, correspondingly the principal applications are also listed say for example, in this range point for band 1.45 to 0.52 we can use for coastal water mapping soil or vegetation then 0.5 to 0.62 which is the nominal spectral location in the green range. So, we can use for vegetation discrimination then 0.62, 0.69 the range of red bands. So, we can use for chlorophyll absorption region then 0.7 to 7.6 to 0.9 near infrared to identify or to get the application the field of vegetation, water, body, soil moisture etcetera. So, like that here various for various applications what kinds of bands which we are using are listed here. So, principally the bands start for remote sensing generally it is starting from this ultraviolet or this range to going up to microwave. So, that is the main region of the or the band of the electromagnetic spectrum where we generally use for remote sensing. Say for example, 1 centimeter 1 meter 7th band which is in the microwave. So, there we can use it for soil moisture. So, some of the advanced say remote sensing satellites use this band and that can be used for even for soil moisture study. So, that way we use particular bands for particular applications. So, depending upon where we are using the remote sensing satellites for whether land use land cover or soil moisture ocean application or coastal region applications. So, like that accordingly we can choose specific bands of the electromagnetic spectrum or specific satellites are put for that particular bands. So, like a Cartosat or the the the microwave region. So, like that. So, that way we can choose particular satellite remote sensing satellite in particular bands for the specified applications which we are trying to do for that particular application. So, now within this background let us look into what are the important features as far as remote sensing is concerned. So, here in the slides. So, the various features are listed here. So, we can see that since say here in this figure which is taken from Marwan and Kottmani 2004 modified. So, here this is the satellite or this is the aircraft which is flying over or this is a satellite moving over the surface. So, you can see that this is the way the scanning or the the reception or the of the particular electromagnetic spectrum band is which is the receiver obtained. This remote sensing that way you can see that provides a regional view. So, if this is the watershed. So, that entire region within one passage of the of the satellites we are obtaining. And then another important aspect is it provides repetitive looks at the same area. So, once the satellite is passing over this and again say after few days say or 1 week or 2 weeks like that then again the same area to the satellite may be passing. So, that way we get the data again in a repetitive manner. And then the remote sensors see over a broader portion of the spectrum than the human eye. So, that is advantage. So, when we are in an aircraft we can see larger area or say the satellite which is further above the aircraft say this range. So, it will be getting much broader portion of the. So, area which is it is taking and that way may be a watershed or a river basin scale we can easily get the data required for the say various hydrological modeling or development of watershed management plans it is possible. The sensors can focus in on a specific bandwidth in an image as I already mentioned the previous slide. So, they can also look at a number of bandwidths simultaneously. So, some of the satellites it can look into the area at a number of bandwidths simultaneously. So, that is the advantage. So, nowadays the modern satellites. So, the remote sensors often record signals electronically and provide your referenced digital data. So, say the data which is say either through a diffraction or reflection or whatever way it is getting back to a satellites. So, data is obtained to your reference. So, that we can easily identify what is the location and this data will be digital and then that data we can process and then we can develop appropriate maps or appropriate data requires for hydrological modeling or the development plans. Some of the other advantage like remote sensors nowadays the with modern techniques we can have remote sensing or remote sensors operate in all seasons at night and in all even bad weather. So, that way like microwave or the advanced types of satellites remote sensing satellites can give the data all time at night or in any bad weather like a heavy rainfall or cyclonic or whatever the weather conditions. So, in all these these data can be obtained. So, that way this remote sensing technology has developed in the last few years and we can see that now very sophisticated data, higher resolution data even up to one meter resolution or even some of the satellites from USA or Russia it can even go say higher resolution further to one meter say like a 0.5 meter level things are available nowadays depending upon say whether the usage depending upon whether it is climate or the army or navy or whichever the agencies are using. So, accordingly various remote sensing satellites are available say various agencies like NASA or India Space Research Organization. So, now since we are not going to cover in all the aspects of remote sensing it is not possible I am planning to give only one lecture dedicated to this remote sensing application as far as watershed management is concerned. So, that way we will be only going some some of the important aspects which is relevant to the applications related to watershed management. So, now we have seen the basics. So, now let us see how the remote sensing is done and what are the important processes taking place. So, these details are given in the slides. So, the remote sensing process. So, actually to get the remote sensing data there should be an energy source which is either reflected or diffracted like that as I mentioned the previous slide and then this energy interaction with the atmosphere space and then this after the interaction the satellite is getting back. So, according of energy by sensor and then that data to be transmitted to the to the the stations on the earth and then that data to be processed. So, that way remote sensing process is quite complicated process. So, first the satellite should be there remote sensing satellite should be there and then that satellite is collecting the the say sending either sending certain signals or say for example, with respect to the the heat from the solar say solar heat which is reflected over that way also some satellites are there or infrared region whatever it is. So, this energy source. So, first of all the remote sensing satellite passing over particular area and then the energy source and then energy interaction with the atmosphere and then once that satellite has to get back this the the data and then that data is to be transmitted to the station and then that data to be processed for further utilization. So, that way remote sensing process is a complicated process number of steps are there and then there are specified senders remote sensing senders say for example, say in India it is national remote sensing space sender NRC located at Hyderabad. So, that way say as far as watershed management plans are concerned we are looking directly the data from the agency consent for the specified date or for specified location by providing the latitude longitude for that particular location. So, that way only we get we request the data to the the NRC or specified agencies and we collect the data and then that data we have to process in a say specified softwares like say ERDAS or other kinds of specified softwares. So, that process is called image processing. So, image processing and analysis so specific softwares are nowadays available. So, here what we are doing is we are doing the image restoration and correction then we enhance the image. So, that is called image enhancement then image transformation and then we do image classification. So, this image classification can be either supervised classification. So, we can compare with the ground tooth at few locations that is how called supervised classification or we can do unsupervised classification. So, these are the fundamental steps involved in the image processing starting from image restoration correction. Once we get the image then image enhancement then image transformation and then image classification and then we can utilize this particular image for various applications. Say for example, this is say for a particular water shed say the the data is obtained and then we get a CCO parts color composition is done and then based upon that we can get the surface features of that particular water shed like the drainage pattern or the river location or the or the land use land cover like that. Nowadays various softwares are available and that softwares like air blasts can be used for this image processing and analysis. So, since our aim in this lecture is not to go into more details about the remote sensing, but we are mainly looking within the perspective of applications to water shed management. So, that way now let us look into what are the important advantages of remote sensing. So, here some of the few advantages are listed here. So, here first one is we can have a synoptic view. So, like that when a satellite is passing that specified area wherever the scanning is taking place that that particular water shed is there. So, we get a total view of that particular area. So, we get a synoptic view and then a temporal. So, that means when the satellite is again coming back after few days say especially various plans for agriculture or the flooding problems. So, these kinds of temporal say variations we can easily obtain for that using the that the particular satellite data. So, that is the another advantage. And then of course, this remote sensing is multiple multidisciplinary applications. So, various applications are there in hydrology like land related applications, ocean related applications, climate prediction or weather predictions or atmosphere related applications. So, number of applications are there which we will be discussing in the coming slide. So, now within the perspective of remote sensing data. So, some few terms like spatial resolution, spectra resolution, temporal resolutions and radiometric resolutions. So, these terms are important. So, let us look into the definitions of these terms. So, spatial resolution means a measure of smallest angular or linear separation between two objects that can be resolved by the sensor. So, that way we can consider the spatial resolution which we consider using the specific satellite which we use for remote sensing. And then spectral resolution means the number and dimension of specific wavelength intervals in the electromagnetic spectrum to which a sensor is sensitive. So, that is how called spectral resolution. And then temporal resolution means it refers to how often a sensor records imaginary of a particular area. So, the area which we are covering that particular area say after few few hours or few days or few weeks how the we are getting the data. So, that is how called a temporal resolution. And the last one is radiometric resolution which shows the sensitivity of a detector to differences in signal strength. So, what is the signal strength which is getting back? So, accordingly the data resolution will be varying. So, that way when we deal with the remote sensing data we have to see the spatial resolution, spectral resolution, temporal resolution and the radiometric resolution. Since we are now discussing only some preliminary aspects of remote sensing. So, anyway let us look into what are the available satellites some of the important satellites internationally available and then also some of the satellites available remote sensing satellites available in the let us have a brief look into this. So, here this data are given here. So, may one of the major sets of satellites which we use for remote sensing called the Landsat satellites. So, a series of satellites put into orbit around the earth to collect environmental data about the earth surface are called as Landsat satellites. So, this is specifically for remote sensing. So, it can be for land related, ocean related or weather related satellites are there. So, various Landsat how multi spectral scanners MSS then return beam video cone RBV scanners and thematic mapper scanners. So, this same actually various countries like US and other countries came together and that is the system of a series of satellites available for remote sensing. So, that series called Landsat satellites. So, each type has its own spectral range and spatial resolution as far as Landsat is concerned. So, three important methods of information extraction and interpretation using Landsat data is say like a photo interpretation, spectral analysis data integration like that. So, Landsat is series of satellites are a very commonly used for remote sensing. And then say depending upon the purpose whether we are looking to topography or the related to climate related parameter or vegetation. So, then accordingly also specific satellites are available. So, say if you are looking for topography then the satellites called LIDAR. So, which is airborne laser scanning based satellites. So, for say high resolution data we can use LIDAR data. So, highly accurate say even up to the level of 1 meter. So, we can get 1 meter deep elevation models using this data, but the cost will be high and special software and expertise needed to process such data. So, this is actually we can use say for example, say to get to the end air say for specified area how the topographic features changes even into up to 1 meter resolution. So, maybe same defense purpose that kind of data can be used. And then another series so called shuttle radar topographic mission so called SRTM related satellites and data. So, here 100 meter deep elevation model with almost global coverage. So, here under SRTM the which is say the data in provided by NASA in collaboration with other countries is called SRTM data and it is available in the internet which is applied by NASA. And here the interval is it is very coarse data of 100 meter resolution. So, this is actually free data. So, for say hydrological purpose or watershed marine purpose this data even we can utilize, but the resolution is very coarse, but still in many of the applications this SRTM data can be used. And another series of satellites called ERS 1 by 2 tandem inforometry. So, here it is somewhat higher resolution 32 100 meter deep elevation model can be obtained from this. So, data from years 1995 to 98 available for most parts of the world accuracy vary depending on land cover and topography. And reasonable accuracy say even say less than 10 meter can be obtained for non vegetated or flat array. And data course moderate so here the cost is less and special software and expertise are needed to process this data from the ERS satellite data. Then another one say related to vegetation say if we are dealing with the land use land cover and later data and we can further use the LUDAR airborne laser scanning. So, here actually this is a new series of satellite data which is having high resolution with say even up to 1 meter resolution we can have the data. And some of the satellites already giving started to give data and further say agencies like NASA and European Space Agency and Japan Space Agency is including Indian Space Agencies are also now in the process of having further satellites in this LUDAR related satellites they are putting and then getting the data. So, here full wave form satellites LUDARs for vegetation mapping have been proposed. So, the high quality data we can obtain even 1 meter resolution. But this data will be expensive and then for large areas it is difficult to get for a larger water shed or larger rubber basins, but for small areas we can get the data and process. Then another satellite one series of satellite is SAR data. So, synthetic apparatus or SAR system SAR interferometry. So, here broad vegetation categories can be distinguished and this is not suited for local scale I mean less than 100 meter and data course moderate neuro specialized software and high level of expertise is required to process this data. So, that way various system is available to say for specified problems or specified say cases we can get a specified satellite data and then process it and then utilize for that particular applications. So, now let us look into the Indian remote sensing satellites. So, here I have listed some of the important series of satellites put by Indian Space Research Organization ISRO. So, the beginning is in 1988 with Indian remote sensing satellite 1A then 1B has been put in space and then there the resolution was up to 72 or 36 meter with the 4 bands. And then 1994 IRS P2 has been put and then IRS 1C in 1995 and then IRS P3 in 1996, then IRS 1D in 1997 which is even have a higher resolution like 5.8 meter. Then IRS P4 then resource SATS say which is given 23 meter resolution say in 2004. Then the latest development is so called CARTO SATS. So, where even some satellites proposed satellites may give the resolution of 1 meter and for larger applications later to either hydrology or watershed management or ocean studies or atmosphere studies this series of satellites can be used. So, this shows some of the important satellites available from India provided by Indian Space Research Organization. So, this is about the available satellites say internationally or say from India. So, now let us look into what are the important applications as far as remote sensing is concerned. So, as I mentioned earlier. So, here in this lecture we are mainly concentrating later to water related applications. So, like a surface water ground water and then watershed later application. So, mainly we are looking to the application sites. So, here in this slide remote sensing applications for surface water the various applications have been listed here. As far as the remote sensing is concerned form say pure water reflects radiation in the visible bands of the retro market spectrum and absorbs almost all of it in the near and middle infrared bands. So, in the infrared water appears dark and is easily distinguishable from other land features. So, that way remote sensing data easily identifies the pure water bodies like lakes or rivers or the the ponds to that level. And then a spectra response of water may vary with the presence of suspended sediments which increase the amount of radiation reflected. So, if any sedimentation is there or the sediment problem is there that also in a different way to be reflecting. Then surface runoff modeling of a watershed with land use from remote sensing we can use in hydrologic modeling which we will be discussing later lectures also. So, like we can obtain the land use land cover for the particular area and then that from that we can obtain the reference coefficient like manning's reference coefficient that can be directly used in the watershed based modeling. Then a type of land use land cover significantly affects the runoff characteristics of a watershed. So, that way this data land use land cover for a watershed or a river basin we can directly utilize. The acquisition of land cover information is of a significant value to water resource planners. So, that way we can utilize the remote sensing in an effective way for say watershed based or water resource based planning and management. Then the in surface water resource development and management remote sensing data provides catchment characterization better modeling surface water resource like rainfall to runoff. So, we need to identify for the given rainfall how much should be the runoff. So, that we can say either distributed models or say lambo models we can utilize this remote sensing data in various ways say for the hydrologic modeling to identify how much will be the runoff for the given rainfall condition. Then remote sensing data collects. So, whatever remote sensing that whatever that we collect multi spectral multi resolution and multi temporal data and turns them into information like land use land cover data sets. So, which we can directly utilize. And then as far as surface water applications concerned we can identify the snow melt runoff say if a particular area if snow fall how much is the snow fall is taken place and how is the snow is melting. So, repeat in a repeated way temporal variation we can obtain and that gives lot of information as far as snow melt snow fall snow melt and runoff is concerned. And then for surface water we can identify mapping of monitoring of surface water bodies. So, like if a reservoir is there how much area is flooded or if any flooding problem is there say how the flooding is increasing or decreasing. Then we can also river basin scale or for large areas we can assess how the water logging is taking place in that area. Then water temperature and other qualities of water we can identify even water pollution or sedimentation or even say related to ocean oil spillage in ocean. So, all those things we can identify using the remote sensing techniques. The detection of depth of shallow water and wet load also nowadays with modern remote sensing techniques we can obtain say how much is the wet load taking place in a particular river and then the depth of shallow water. And then another area is say particular river whether what river or lake or a pond is polluted that also with by using multi multi resolution or multi temporal or multi spectral data we can easily identify. So, like that say for surface water related remote sensing have number of applications as I already shown in the previous slide. So, now let us look what are the important applications related to groundwater. So, groundwater is you can see that actually it is one of the very complex problem as far as hydrology is concerned since most of the groundwater details say we can obtain through mainly modeling since data collection through bore wells or bore holes are very very difficult process. So, with the limited field data we have to say go for computer modeling and then we get say various aspects of groundwater variation, groundwater flow and transport say by running the models. So, these models generally require huge data. So, that data can be given by remote sensing. So, groundwater model needs spatial and temporal distributions of input and calibration data. So, that we can obtain from the remote sensing. So, patterns from remote sensing can be translated into a deterministic distribution of input data on a cell by cell basis or in the form of zones. So, it can be for a small area like grid say 50 meter by 50 meter 100 meter by 100 meter or various zones like zone 1, zone 2 like in particular homogeneous zones we can identify the data. So, some of the raw remote sensing data present special patterns like features of process above the surface then on the surface how the evapotranspiration taking place, then how the cloud variation is taking place, then shallow subsurface like hydraulic conductivity or soil moisture variation. So, all those things we can identify using the remote sensing and then in combination with the pattern information with the point information at ground observation stations allow spatial distribution of parameters to be obtained. In a especially in groundwater modeling if we can identify the linear means fowls, dykes etcetera. So, that we can easily put into our models a groundwater models and that will be very helpful in the overall groundwater model development. So, that way remote sensing have number of applications as far as groundwater is also considered. So, now let us look into further applications of remote sensing various applications I have listed here for the applications. Like we can identify number of climate parameters using remote sensing same like a precipitation say using ground based radars or satellite images. So, nowadays instead of getting the rainfall or precipitation for using the automatic or non-automatic gauges we can use radar based system which the which can give a the variation rainfall variation in a larger area in a very accurate way. So, that way radar data can be used or satellite images can be used and then snowfall and melting as I already mentioned that can be obtained through either radars or satellite data and then glacier conditions. So, whether the movement of the glaciers or the melting of the glaciers that can be easily identified using the satellites then cyclone prediction. So, we can identify the cloud movement and then whether any cyclone formation is taking place. So, that can be easily identified by the satellites remote sensing satellites and that we can easily use say for a cyclone prediction. So, how the movement is taking place with hourly movement or a daily wise movement. So, that particular area will be affected by cyclone. So, that way we can easily predict and then the temperature variation we can obtain through modern remote sensing satellites then as I mentioned cloud movement or drought prediction. So, say as far as weather predictions or climate parameters we can use remote sensing satellites in a very huge way at various for various cases we can utilize and then some other applications like flood variations if further particular area due to rainfall or breaking, breaching of dam whether that particular say if some flooding situation takes place how the flood is progressing. So, all those variations we can easily obtain from the remote sensing data and then vegetation cover type then huge applications are there in forest management. So, say how the particular time how the forest is spread and then with respect to time how the various is taking place after say for example, in winter summer or say from year to year how the forest various is taking place. So, that we can easily obtain from remote sensing and then also even we can identify forest fire then we can identify soil moisture using remote sensing either directly or through indirect measurements. Then evapotranspiration assessment can be done. Then of course, another area important area is agricultural management like we can identify other than helping through climate predictions or the rainfall predictions we can also assess the agriculture conditions and then say the crop health or the cropping pattern. So, all those things we can use the remote sensing. Then say the drought management like a desertification then sand dunes or a dust storm. So, all those things we can identify using the remote sensing and then another area where huge applications are there is ocean or coastal regions. So, if there is a say for example, if there is a oil spillage say how much area is affected and where the this plume is moving. So, that we can easily identify and then lot of applications related to fishing or related to various behavior say that can takes place in the ocean. So, these are all we can obtain through say remote sensing. And then another area is environmental impact assessments. So, there say if a particular system is built say how the river basin or the watershed is behaving. So, that also we can identify say in the environmental impact assessments using the remote sensing. So, now say whatever we discussed is the remote sensing application for surface water, groundwater or ocean applications or further applications. So, now let us come back to the watershed management is concerned. So, how remote sensing can be effectively utilized either in the development of watershed management plans or the implementations or the evaluations. So, here in this slide I have listed various applications. First one is watershed delineation. So, we have already discussed about the watershed delineation in one of the previous lecture. So, we can obtain the remote sensing data and then we can process and with the help of of course, the toposheet and other maps we can delineate the watershed either in software like RPU or other GIS software. Then some of the other important areas are resource mapping identification of erosion prone areas, modeling sediment yield, conservation prioritization, conservation planning, monitoring watershed for environmental impact assessment. So, all these say points we will discuss in detail in the next slides. So, first one is resource mapping using the remote sensing. So, as I already mentioned in the earlier lectures. So, we are dealing with a larger area as far as a watershed or river basin is concerned. So, to get a synoptic view for that particular area in a total view if we can get like land use land cover or soil related issues or the the vegetation then that will be very useful for watershed development management plans. So, that way using remote sensing the remote sensing enables easy accurate time and cost effective mapping as far as the watershed is concerned. And remote sensing updates several resources information such as like a stream network map within the watershed, surface water map, land use map, vegetation map, physiographic soil map, then erosion prone area map, snow cover map, soil moisture map, then land form map, groundwater prospect map. So, like that say based upon the remote sensing data say once we put this after processing in software like ERDAs and then putting to appropriate GIS packages and manipulating with respect to the various input data. We can generate a series of maps like land use map, land cover map, vegetation map, then erosion prone map, snow cover map, soil moisture map like that. So, various maps resource maps can be generated using the remote sensing. So, that way remote sensing is very important in in watershed management development plans. And then second application is identification of erosion prone area. So, as we discussed earlier, so the soil erosion is a major problem and then related sedimentation issues. So, remote sensing as it uses synoptic view on a temporal basis, I mean in repetitive basis. So, that way we can if we analyze appropriately this remote sensing images, we can get a lot of data to identify what the erosion prone areas. So, some of the important aspects are listed here in this slide. So, remote sensing facilitates identification of existing or potentially erosion prone areas. Remote sensing help in planning, reclamation or preventive measures. So, based on satellite image, various erosion intensity classes can be assigned. Say like a nil to slide or slide to moderate or moderate to severe or severe can be delineated and mapped. So, that way we can say even work for prediction using the remote sensing images. Then wasteland information are also possible using high resolution multi-spectrum and multi-temporal satellite images. So, that way we can use the remote sensing data. Then another application is related to watershed is modeling sediment yield. So, due to the soil erosion, sedimentation takes place in reservoirs that is a major problem in watershed development plans or river basin development plans. So, generally we use empirical models or numerical models for to identify how much is the sediment yield for particular area or particular reservoir. So, for that purpose we need a lot of data. So, this data can be given by the remote sensing. So, that way the empirical models are used to estimate, empirical or numerical models are used to estimate the sediment yield. So, average annual soil loss and conservation planning for soil or erosion control in agricultural lands, construction sites, reclaimed mines or forest management, since it requires small areas, low cost, short project span and there is literally risk of failure. So, these models require input parameters in terms of spatial information on land use, vegetation cover, soil, rainfall density, runoff and rainfall density which are time consuming and costly by conventional surveys. So, this data we can get from the remote sensing satellites. So, this data provide convenient tool to derive this information. So, that way we can utilize the remote sensing data to model sediment yield. Then another area is conservation prioritization watershed. So, identification of erosion prone areas to areas to evolve appropriate conservation management strategies. So, hence maximum benefit can be derived out of any such money or time effort making schemes. So, we can prioritize which one is the first priorities and second one like that. So, we can make a say priority and then we can classify. So, priority classification can be obtained using the remote sensing. So, priority classification means arrangement of different units of a watershed in decreasing order of their sediment yield. Say for example, if we consider sediment yield, sediment yield potentials arrived through sediment yield modeling and then provide a threshold values through frequency distribution of such data into the priority classes. This can be either for sediment yield or water resource assessment or water resource planning for the particular watershed. So, that way we can have the applications of remote sensing for conservation prioritization in watershed. So, then another application is conservation planning in watershed. So, here one of the key sectors for conservation planning in watershed is rainwater harvesting. So, rainwater harvesting can be used to improve the waterway between the area or also can be used to reduce the soil erosion problems. So, rainwater harvesting say we need optimal site selection for constructing check dams and storage of water. So, site investigation need following resource information. So, these informations we can obtain through remote sensing. So, like drainage area and stream network, physiography and relief land use, vegetation and soil, then rainfall intensity duration recurrence interval, then water utilization potential, then socio-economic aspects, then watershed management practices already in the area. So, these resources information can be extracted using the remote sensing data and that can be directly utilized. So, that way remote sensing data can be used for conservation planning as far as a watershed is concerned. Then another important application is monitoring watersheds for environmental impact assessments. So, as I mentioned if we implement any scheme in a particular watershed, so what will be the effects, all those things can be studied using the remote sensing. So, water resource development projects are essential for agriculture industrialization and economic growth of a region. Large scale water resource projects may induce adverse impact on environment. So, a sound approach for environmental impact assessment is required to assist engineers and decision makers. So, to choose a proper alternative source to decrease environmental impact due to water resource development, we can use the remote sensing. So, we need to monitor what will be happening if a particular scheme is implemented if a reservoir is there. So, with respect to the effect of reservoir, what will be happening? So, this data we can repeat it will collect for that area and then we can process it and use. So, that way remote sensing will be very useful in the EIA. So, monitoring is essential to know adverse impact of water resource development projects and beneficial impact of subsequent watershed management programs. So, this is possible by time series analysis of satellite data of the watershed over a period. So, say monsoon time what will have been happening and in summer time what will be happening and then year by year say with respect to that particular project a dam project how the system is behaving. So, that we can study and then we can analyze. So, that way remote sensing is very useful for environment impact assessment. So, now before closing today lecture, let us look into one case study where remote sensing is extensively used. So, this case study is taken from Patmaja, Upla and others paper in environmental informatics archive archive volume number 2 2004 page number 885 to 892. So, this is remote sensing applications for management of water and land in Prakasham districts of Andhra Pradesh, India. Some of the features of this area is listed here. So, the Rakerla Mandal of Prakasham district farce under semi-arid shown in penicillar India the total area is about 670.8 square kilometer identified as chronically drought affected area in the state with the agroecological situation and characterized by single crop system due to predominately rainfall cultivation with low and erratic rainfall. Climate is dry tropical semi-arid type with hot summer during March to May followed by southwest monsoon from June to September. So, here we say the detailed steps as far as remote sensing analysis and applications I have listed here. So, it begins the process begins with accuracy the accurate we say we obtain the data from the satellites. So, we begin begins with a curing the satellite image and toposheet of the required study area. So, this is as reported by the others in the reference. So, the following steps are adopted for the watershed management of this particular area using remote sensing and GIS techniques. So, step one preparation of drainage map using survey of India toposheets and satellite imagery to determine the drainage pattern and for calculating various drainage characteristics say drainage density basin slope etcetera. Then step number two preparation of land use land cover map using survey of India toposheets and satellite imagery to know the various uses of the land in that particular area. So, this also we can through this we can obtain the crop area or the watershed area etcetera for that particular region as used by the others. Then step number three preparing preparation of hydro geomorphology map using survey of India toposheets and satellite imagery which is used for finding the groundwater prospects and suggest water harvest structures. So, this is the particular area as given by the others in this paper. So, this shows the land use land cover details. So, here the say my aim of presenting this case studies the various steps involved in this such studies and then how effectively remote sensing is used. So, that is the question which I am trying to answer here. So, step number three the hydro geomorphological maps are generated and land use land cover maps are generated and then step number for preparation of slope map using survey of India toposheets and the remote sensing data. Then step number five a GIS detail system in the arc info is used for input and manipulation and creation of error free digital database for all natural source within the area. So, that is the step number five as reported by the others and then step number six depending on the combination of above mentioned resources themes action plans for land and water resource and treatment plans for catchment area generated for the development of the watershed. So, here based upon this various steps mentioned here. So, the main purpose is to come up with the plans for rainwater harvesting and then other water related resource developments. So, depending upon the soil climate in step number 7 local practices and keeping in view of the long term market prospects roping battens are determined based on crop water requirement in view of the water availability. So, the plans using the remote sensing and GIS the plans were made where the particular check dumps should be constructed where should be various rainwater harvesting measures should be adopted and these locations were identified to generate watershed development plans and then say it has been identified the cropping battens existing cropping battens and then how the cropping battens can be improved with respect to soil climate and then local practices. So, all the above steps are aimed for optimum development of land and water resource to meet the basic minimum needs of people thereby improving their socio economic conditions. So, that way the others did the study as mentioned in these seven steps and the information generated from such a studies can be used by decision makers for sustainable development plans. So, for particular watershed. So, as put in this using these steps using the remote sensing data and within the GIS framework. So, we can propose watershed development plans say and then say which area should be say going for specified crops and then. So, that overall socio economical impacts should be there for the concentrate area. So, that way remote sensing is very remote sensing data is very effectively used for this particular area by the others. Before finishing this lecture so remote sensing applications some concluding remarks. So, as I already mentioned in this lecture remote sensing data could be assessed without restrictions in many cases. So, we can use for various purposes and as I mentioned already it gives a synoptic view and a temporal variations with respect to repetitive way with respect to time. The advantage of remote sensing we can effectively utilize for the development of various watershed development plans. And remote sensing data is not biased and is available shortly after satellite overpass in that area. So, that has some of the further advantages. So, special purpose remote sensing products that can directly support various watershed management projects like hydrology, water accounting, disaster management, irrigation management, wetland management, watershed management and landing relations are possible using the remote sensing. So, that way we can effectively utilize the remote sensing. So, some of the important references used for today's lectures are listed here. So, the case study is taken by from this paper by Padma Jaapula, Shiva Shankar, Asadhi, Pawani and Anjire D published in Environmental Informatics Archives. And before crossing few questions total question critically study various remote sensing satellite available, example landsata, ERS etcetera and its capabilities resolution of images etcetera. So, these details we can get from the internet. Evaluate the capabilities of each satellite for watershed management plans. Then explore how effectively the remote sensing data can be used for development of watershed management plans. Then some self evaluation questions discuss the basics of remote sensing, how the remote sensing data is obtained? What are the important features of remote sensing? What are the advantages of remote sensing for various problems? Describe how the describe about the Indian Satellites program available for remote sensing? What are the important applications for remote sensing for groundwater related problems? Describe the various applications for remote sensing for watershed management or watershed development problems. So, if we assignment questions discuss the evolution in remote sensing for the last few decades, explain the range of electromagnetic spectrum used for remote sensing. Discuss the various steps in remote sensing and image processing. Discuss the details about the important satellites available for remote sensing in various countries. What are the important applications for remote sensing for surface water related problems? What are the important applications remote sensing related to atmospheric or climate related studies? So, finally, the one unsolved problem say from Aster as given in this website or SRTM given in this website or Bhuvan or IRS data as given in this website. Obtain the remote sensing image of your watershed area based upon you can get based upon the latitude, longitude. Delay at the watershed area based on top or sheet and images and other available data generate detailed elevation model, land use land core map, slope map, soil map etcetera for your area. And the next part how effectively this remote sensing data can be used for like hydraulic modeling or watershed development plans. So, today what we discussed is how effectively remote sensing can be used for watershed management plans. So, as we have already seen number of applications are related to watershed. So, anyway say due to lack of time since our say related to remote sensing I cannot give much time since only one lecture has been planned. So, further some applications we will be discussing in the coming lectures related to further remote sensing applications when we discuss the decision support system or the numerical modeling. Thank you.