Tuesday 27 June 2023

Pursue Your Passion for Remote Sensing with Lovely Professional University India

Are you fascinated by the world of remote sensing and eager to further your knowledge and expertise in this field? Look no further, as Lovely Professional University India (LPU India) is thrilled to announce the launch of its Master's program in Remote Sensing. This exciting opportunity is tailored for students like you who aspire to make a difference in the realm of spatial data analysis and environmental monitoring. Read on to discover how this program can help shape your future and pave the way for a successful career in remote sensing.

Why Choose LPU India?

LPU India, renowned for its academic excellence and holistic approach to education, has established itself as a leader in providing industry-relevant programs. With the launch of the Master's program in Remote Sensing, LPU continues its commitment to staying at the forefront of educational innovation and offering students the opportunity to excel in their chosen fields.

Unparalleled Faculty and Resources:

At LPU India, you will learn from a distinguished faculty comprising experienced professionals and renowned experts in the field of remote sensing. Their guidance and expertise will equip you with the necessary skills and knowledge to thrive in this rapidly evolving domain. Additionally, LPU India is equipped with state-of-the-art facilities, laboratories, and software resources, ensuring that you receive a comprehensive learning experience that blends theoretical concepts with practical applications.

Hands-on Training and Research Opportunities:

LPU India believes in learning by doing. Through hands-on training and practical sessions, you will have the opportunity to work with cutting-edge technologies and software used in remote sensing applications. The university also encourages research and innovation, providing you with a platform to contribute to the field through meaningful projects and collaborations.

Join LPU India's Master's Program in Remote Sensing:

If you are passionate about exploring the vast opportunities in remote sensing and wish to pursue a Master's degree in this exciting field, we invite you to take the first step. Fill out the attached Google form to express your interest and kick-start your journey towards a fulfilling career in remote sensing.

Rest assured that our dedicated admissions team will promptly reach out to you, providing further details and guidance throughout the application process. Stay tuned to our official website for updates and comprehensive information about the program.

Lovely Professional University India (LPU India) presents an incredible opportunity for aspiring remote sensing professionals to acquire the knowledge, skills, and industry exposure necessary to thrive in this dynamic field. With its prestigious ranking of 38 in the National Institutional Ranking Framework (NIRF) by the Government of India, LPU India stands as a testament to its commitment to excellence.

Don't miss out on this chance to pursue your passion for remote sensing and shape your future with LPU India. Fill out the Google form today and embark on an exciting educational journey that will set you on the path to success in the field of remote sensing.



Friday 27 January 2023

Crop yield estimation using remote sensing and GIS video tutorial

Crop yield estimation is a crucial aspect of agricultural management and planning. Accurate and timely yield estimates can help farmers make informed decisions about planting, fertilization, irrigation, and harvest timing. Remote sensing is a powerful tool that can be used to estimate crop yields with a high degree of accuracy. One of the most commonly used indices in remote sensing for crop yield estimation is the normalized difference vegetation index (NDVI). In this article, we will explore the use of NDVI in conjunction with regression equations to estimate crop yields using remote sensing.
NDVI is a commonly used index in remote sensing that measures the amount of vegetation cover in an area. NDVI is calculated by taking the difference between the near-infrared and red bands of a multispectral image and dividing that difference by the sum of the near-infrared and red bands. NDVI values range from -1 to 1, with higher values indicating more vegetation cover. NDVI is highly correlated with crop growth and yield, and it can be used to estimate crop yields with a high degree of accuracy.
Regression equations can be used to create a relationship between NDVI and crop yield. These equations can be used to estimate crop yields based on NDVI values, making it possible to estimate crop yields using remote sensing data. The regression equation can be developed by collecting data on NDVI and crop yield from a specific crop and area, and then using that data to create a mathematical equation that describes the relationship between NDVI and crop yield.
Remote sensing data can be used to estimate crop yields by collecting NDVI images of the crop and then applying the regression equation to the NDVI values. The resulting estimates of crop yield can be used to make informed decisions about planting, fertilization, irrigation, and harvest timing. Additionally, remote sensing can be used to estimate crop yields across a large area, making it possible to identify areas with the highest crop yields and target resources and attention accordingly.
In conclusion, NDVI is a commonly used index in remote sensing for crop yield estimation. Regression equations can be used to create a relationship between NDVI and crop yield, which can be used to estimate crop yields using remote sensing data. Remote sensing can be used to estimate crop yields across a large area, making it possible to identify areas with the highest crop yields and target resources and attention accordingly. Crop yield estimation, NDVI, remote sensing, regression equations, crop growth, agricultural management, planting, fertilization, irrigation, harvest timing, precision agriculture.


Highlights :

  1. Use Machine learning method for crop classification in ArcGIS, separate crops from natural vegetation

  2. The model was developed using the minimum observed data available online

  3. Crop NDVI separation

  4. Crop Yield model development

  5. Crop production calculation from GIS model data

  6. Identify the low and high-yield zones and area calculation

  7. Calculate the total production of the region

  8. Validation of developed model on another study area

  9. Validate production and yield of other areas using a developed model of another area

  10. Convert the model to the ArcGIS toolbox





Saturday 31 December 2022

Udemy GIS Coupon code for 2023

 ArcSWAT: Covers hydrological simulations and weather data preparation using R; use it for any research area, and scripts are available for download.

Link: https://www.udemy.com/course/running-arcswat-model-with-arcgis-for-any-study-area-gis/?couponCode=HAPPYNEWYEAR2023

SWAT CUP: The simulated flow may not always completely match the observed flow. In this scenario, we must establish hydrological parameters. SWATCUP handles it automatically and recommends the best match settings.

Link: https://www.udemy.com/course/swat-cup-calibration-validation-and-write-values-to-arcswat/?couponCode=HAPPYNEWYEAR2023

 

GROUNDWATER: This course covers the use of GIS for groundwater investigation using theoretical parameters. Create a live project from scratch.

Link: https://www.udemy.com/course/groundwater-potential-zones-using-gis-full-project-arcgis-tutorial/?couponCode=HAPPYNEWYEAR2023

 

LANDUSE LANDCOVER: Covers landuse classification of high-resolution data. You will learn how to correct error pixels such as urban and barren land, or agriculture and natural vegetation. It covers most classification methods, such as machine learning, supervised, unsupervised, and pixel-level recoding of challenging images.

Link: https://www.udemy.com/course/land-use-land-cover-classification-gis-erdas-arcgis-envi/?couponCode=HAPPYNEWYEAR2023

 

FUTURE LANDUSE: Remote sensing has impressive capabilities to generate future landuse classified image of  2090, even if it is not captured in the present; see machine learning in action. No coding is required.

Link: https://www.udemy.com/course/prediction-of-future-land-use-remote-sensing-and-gis-terrset/?couponCode=HAPPYNEWYEAR2023

 

BASIC GIS: This course covers more than a university lab class if you are new to GIS. This course will teach you about 3D, data analysis, and satellite image processing. 11hrs of hands-on videos of practicals.

Link: https://www.udemy.com/course/complete-basic-gis-tasks-arcgis-erdas-remote-sensing/?couponCode=HAPPYNEWYEAR2023

Tuesday 11 October 2022

Online GIS courses

Just click on links Discount applied.

Dear Research Scholars,

GIS courses updated with machine learning and R. Discount is applied on all links valid for 5 Days.

The ArcSWAT course is updated with more than 2 hr 26 minutes of video. Now it covers weather data management using R programming. It was experienced that weather data for swat was not available. So new section is added for data management.

Link: https://www.udemy.com/course/running-arcswat-model-with-arcgis-for-any-study-area-gis/?couponCode=SWATOFF90

 

Sometimes we found simulated flow does not perfectly match with observed flow. In this case, we need to set hydrological parameters. SWATCUP do it automatically and suggests the best fit values. That values are again written to SWAT to perfectly run and calibrated the swat model for a specific watershed. That also called sensitivity analysis.

Link: https://www.udemy.com/course/swat-cup-calibration-validation-and-write-values-to-arcswat/?couponCode=SWATCUP90OFF

 

If new to GIS, then this course covers more then a university lab class. Covers everything about remote sensing and GIS, including different ways of georeferencing, Mosiac, excel to GIS, hydrology, 3D views, adding data from servers,  and much more GIS  more than 11 hrs tutorial. Only 99% practical. Covering ArcGIS, Erdas, and some QGIS.

Link: https://www.udemy.com/course/complete-basic-gis-tasks-arcgis-erdas-remote-sensing/?couponCode=GISOFF90

 

This covers the application of GIS for groundwater exploration based on theoretical parameters linked with GIS. The same method will be used for drought or flood.

Link: https://www.udemy.com/course/groundwater-potential-zones-using-gis-full-project-arcgis-tutorial/?couponCode=GWDOFF90

 

Covers landuse classification, Landsat 8, managing of high-resolution data of Sentinal-2, Pixel editing of wrong classified pixels. Post correction of classified image, Number of methods covered, like machine learning-based classification and all other supervised and unsupervised methods.

Link: https://www.udemy.com/course/land-use-land-cover-classification-gis-erdas-arcgis-envi/?couponCode=LANDUSEOFF90

 

Use the output of landuse classification as input for terrset based on CA Markov model. Predict and generate a map of the future landuse of 2050 or 2090 by Machine learning.

Link: https://www.udemy.com/course/prediction-of-future-land-use-remote-sensing-and-gis-terrset/?couponCode=CAMARKOVOFF90

 

Thursday 15 July 2021

Udemy GIS course coupons

 

How to learn GIS at home, then these courses are for you. 

---

Course Name: ArcSWAT Model with ArcGIS - Run for any Study Area - GIS

Duration: 4hr 26min

Highlights: Watershed simulation, amount of sediment reach at the outlet, ET, PET, Water Yield, Groundwater Recharge estimates, Streamflow in m3/sec, Hending weather data, Cover zero to simulation graphs. Applicable for ArcGIS 10.1 to ArcGIS 10.7

Link:https://www.udemy.com/course/running-arcswat-model-with-arcgis-for-any-study-area-gis/?couponCode=LABATHOME


Course Name: SWAT CUP Calibration Validation and write values to ArcSWAT

Duration: 2hr 37min

Highlights: Multiple concepts of calibration and validation, Write calibrated parameter values to ArcSWAT.

Link: https://www.udemy.com/course/swat-cup-calibration-validation-and-write-values-to-arcswat/?couponCode=LABATHOME



Course Name: Land use Land cover classification GIS, ERDAS, ArcGIS, ENVI + Machine Learning in GIS

Duration: 6hr 22min

Highlights: A number of classification methods are covered including Machine learning. From data downloading to final results. Also covers pixel editing to improve LULC accuracy, Covers Accuracy assessment, Post modification and a number of basic and advanced tasks.  Applicable for Erdas 14 to Erdas 18. All versions of ArcGIS.

Link: https://www.udemy.com/course/land-use-land-cover-classification-gis-erdas-arcgis-envi/?couponCode=LABATHOME


Course Name: Future Land Use with GIS - TerrSet - CA Markov - ArcGIS

Duration: 4hr 4min

Highlights: How an urban are expand in future at which extended till the year 2030, 2060 or 2090. Based on past classification and factors affecting landuse incorporated in the software. Convert the theoretical concept of urban expension into relaity.  Generate Video simulation of Urban growthAlso, generate a map of the future landuse with the machine learning approach. No coding is required. TerrSet and ArcGIS software required.

Link: https://www.udemy.com/course/prediction-of-future-land-use-remote-sensing-and-gis-terrset/?couponCode=LABATHOME

Course Name: Complete Basic GIS Tasks - ArcGIS - Erdas - Remote Sensing

Duration: 11hr 7min

Highlights: If you are new to GIS then this 11 hrs course cover everything in GIS from data management to publication-ready maps. Rea;l life tasks are covered. Covers GIS, GPS, Excel,  Weather data handling, Advance scripts, Image mosaicking in the best way, image resolution increase, Processing of high-resolution free images of 10m, 30m resolution. 3D and much more. Applies to ArcGIS 10.1 to 10.8, Erdas 2014, 2015 and 2018.

Link: https://www.udemy.com/course/complete-basic-gis-tasks-arcgis-erdas-remote-sensing/?couponCode=LABATHOME

Friday 8 May 2020

Online GIS course 28 hrs



The combined duration of all GIS courses 28hr 25min. If you spend 1hr daily, you will be expert in GIS within 28 days.
Even you will be able to do a complete GIS Project within one Day if works continuously. All courses are designed in such a way that you will feel GIS is too comfortable. Even Larger simulation of Hydrology will be just like the word for you.
Basic of GIS and Remote Sensing: This course is scientifically designed you no need to put a load on your brain to understand typically task, Just by watching the video, you will understand an advance concept. Many of you demanded to make a course on Basic of GIS data. As we face problems in handling shapefiles and data handling, Mosaic of the satellite image, NDVI, Handling advance data, cutting study area. Increasing image resolution and even making research-ready layouts. So here is the course.
Duration 11hr 7min

Land use land cover classification in Depth Learn from scratch from data download to landuse change detection, How to improve images, How to classify bad pixels manually. Post landuse classification process, Accuracy assessment, you will also learn many of Basic GIS tools also. Supervised, Unsupervised and Combined method are covered. You will receive more accuracy in the combined method for even bad quality terrain.
Duration 5hr 13min

ArcSWAT Tutorial - Learn Watershed Simulation and working with weather data in GIS, In this course you will learn ungauged catchment water flow simulation in  Cubic Meter Per Second [m³/s] , groundwater recharge in watershed,  Sediment at outlet, Water yield, water quality, Curve number, Soils, Hydrological cycle parameters of watershed and many more advance output as you think. Duration 4hr 12min

Groundwater Potential Zones : In this course you will learn how to use landuse, DEM and Weather data. By generating stream density. Mosaic of DEM. How to run overlay analysis on multiple data set and many basic task of GIS like download  of weather data, convert to GIS. You will also learn ow to calculate water level fluctuation and generate map. You ca use same tutorial for Drought, site suitability or any other theme also, even this method applicable to Flood risk zones.
Duration 3hr 49min

Prediction of Future Landuse: In this course you will learn how to generate future landuse maps with GIS. How to use present data and simulate urban growth to future. How to validate predicted results. How to Modify image Matrix to get desire results. This method use, MLP and Machine learning based method. No single line code required. Only requirement is you must have well classified two satellite image with accuracy more than 80%, Rest of things covered in this course. Its so much easy then you think you just need Terrset and ArcGIS.
Duration 4hr 4min



Tuesday 14 April 2020

GIS course udemy Coupon - Complete Basic GIS Tasks - ArcGIS - Erdas - Remote Sensing

Complete GIS Course from scratch to Advance

This all course covers data processing in advance way and solving general GIS problems.
Discounted already applied to links.
All are discounted links.
In this course you will also learn
· Groundwater Potential Zones using.
· Site suitability
· This also covers Flood Zones
· Drought Zones
· Groundwater Fluctuation Maps.
· Like Using Excel Data in ArcGIS,
· Plotting Maps,
· Classify various type of Data.
· Handling CDF files etc.
· Working with excel data in ArcGIS
· Digital elevation model analysis
· Watershed



In this course you will learn
· How to generate future landuse maps using past landuse
· Power impacting landuse and use in Terrset
· Getting data ready for Future Prediction
· Running of CA Markov Model
· See power of Machine learning in Action


https://www.udemy.com/prediction-of-future-land-use-remote-sensing-and-gis-terrset/?couponCode=FUTURE_GIS_UDE

In this course you will learn
· Simulation of water flow in stream
· Daily Weather data including,
· Working with Temperature, rainfall, humidity, solar radiation
· Groundwater recharge.
· Making of Soil map of your study Area
· Extracting soil Properties
· DEM Mosiac
· Use of Landuse data in Model
· Soil Erosion at outlet


In this course you will learn
This course starts from Google Search to Final Results
· Covers basic of Image processing and data download
· Landuse land cover classification
· Supervised
· Unsupervised
· Combined classification
· Pixel Re-coding
· Correction Hill shade land feature
· Understanding satellite image and identifying features
· Accuracy Assessment
· Change Detection


In this course you will learn
This course starts from Georeferencing to Advance GIS - 11hrs
· Covers all basics of GIS 
· Understanding of Projection system
· Handling Raster and Vector data
· Basics of GIS digitization in depth
· Basics of all analysis
· All task of Image processing including mosaic 
· Working with 10 meter data
· Working with Survey data
· Weather data
· Using queries in GIS

· DEM - volume and 3D
· 3D animation in GIS
· Making publication ready maps.

Saturday 11 April 2020

GIS Basics Video Tutorial


The theory behind tools, how it works. Hands-on That tool. Practical. Mosaicking, satellite data, Digital Elevation Model, Most of the things covered that required for Mast of GIS students, PhD students and Civil Engineers, Irrigation and Hydrology Engineers. If you have missed your practical classes of GIS, then this course is for you. It covers the whole practical syllabus of GIS, even more than it. It also covers Error resolving is software, issue with Satellite data. Compared same task output on different software. This will enable you to do any real life project. Content are decide based on real life problems which my Engineer student faced in field. Sometimes satellite image not provide sharp resolution data then we take Help of Google Earth, How use that Data in GIS. Even how we can use our Good Android Phone to Survey up to 3 meter GPS accuracy by calibration its GPS. Later how we can use in GIS. Other than working with Data we need to represent in Best way. A best presentation of Data is considered to be Good work, so I have also covered how to make research ready GIS layouts. How we can improve satellite image improve resolution up to 15 meter and Processing of 10-meter satellite data. Getting Earthwork of Reservoir volume, converting to 3D. Mosaicking of Digital Elevation Model. Getting Drainage and watershed, stream order. Changing the projection of data. Advance labelling using scripts. Handling NetCDF data. Generation annual rainfall map and interpolation of Data. On Other side NDVI is covered. Cutting Study area for project and deleting bad data from satellite image and vector files using smart tricks covered. How to reference data without latitude longitude and make it usable. Even how to get street level data from online sources and convert to GIS format. Cutting shapes with shapes. Handling attributes and calculation on that. Data conversion between raster and vector of multiple type. Small mini project also shown how to use combination of tools to do one task. Even to find the right UTM Zone for your area. Also covers Excel data to GIS. Getting lat long, Making Grid, If you missed your GIS practical classes, then it is for you.
It does not matter which version of the software you have. Tool covered applicable to all version of ArcGIS 10.1 or 10.7 or above. Similarly Applicable to all versions of Erdas 2015 or 2018 and above.

Sunday 9 December 2018

Estimation of Groundwater Potential Zones using GIS and Remote Sensing

Estimation of Groundwater potential zone using GIS is and very easy work. Even Just basic knowledge of GIS is Required. You Just need to know to concept how it works and how to take that work from form GIS data. Groundwater Potential zone is just an estimate of possible location of water availability. But it does not tell the water depth. But if you want to know monitor changes in water depth in this case you need to work with actual data and plot that data in GIS. You can also calculate water level changes and location by using GIS if you have observation data. Groundwater Required few layers like Land Use, Rainfall, Soil, Drainage density,  DEM, Even number of layers is not limited you can use any number of layer as per information available, like Geomorphology also. This project is sometime given to Master of PhD students. But actually this is work of Just one day if you have good internet connection and ability to work Just 8 hrs continuous. Only write up will take time. So here is step by step Video tutorial is available for this project. It covers from data downloading to final results, Even the same tutorial covers Drought and Flood risk zone also, because it use same data.  High Quality GIS contents are not free, But too cheap also as 10$. If you learn GIS offline this will cost you thousand of dollars and at last you not have single video of course. You purely depend on you notebook. But if everything is available in video you can do it better, watch any step anytime rewind it. So All reading this post have access to this course using special link. Below this post. 
  • Successfully identify Groundwater Potential Zones
  • Also Drought prone Area analysis
  • Flood Risk map
  • Working with Rainfall Data
  • Generate Soil Map and identify Soil Properties
  • Delineate Watershed
  • Drainage Density and Drainage Maps
  • Mosaic of Digital Elevation Model
  • Area Calculation from Pixels
  • Data Interpolation
  • Adding Data from Excel to GIS Environment
  • Perform GIS data calculations
  • Tool used for Site suitability analysis
  • Working with CDF file and data Extraction, Map Generation, Calculation,
  • Data Reclassification
  • Generate Fluctuation maps to identify Good Aquifer.
  • Data Reproject
  • Calculation with Raster Data
  • Data management in GIS
Are there any course requirements or prerequisites?
  • Basic GIS
  • Must have Landuse image
  • You must have ArcGIS any Version
Who this course is for:
  • GIS Student
  • GIS Professionals
  • Professors
  • Scientists
  • Master Student of Remote Sensing and GIS
  • PhD Research Scholars
  • Groundwater Exploration Engineers
  • Irrigation Engineers
  • Water Resource Engineers
  • Students of WRDM
  • Govt. Policy Makers
  • Ministry of Earth Science

Groundwater Potential Zones using GIS




Wednesday 5 September 2018

CA Markov Method of Urban Growth using GIS Tutorial

CA Markov, People search lot of about CA Markov. But there is no proper GIS tutorial which Explain from Basic to run this model. If we know basic of GIS and data handling in Gis we will be easily able to run this Model. Its not a big deal. You just need ArcGIS and Terrset software to predict future land use and generate map for future. Think Few General points in Mind How it works. Lets think:
  1. New Urban area wll grow at boundary of older
  2. Some factor depends like distance between settelments
  3. Fistance from road
  4. Trend of change from Agriculture and forest each location
  5. Rate of Growth,
  6. Power of factor of change
And many More. You need only to model some layers and put in Machine learning model when the model trained put input to CA Markov model. This will predict future landuse map. If you found accuracy is not matching then Just change sampling rate and use hit and trail until it matches with actual land use if matched perfectly then Just o future and predict for year 205 and 2100.


See video of output. 



Tuesday 17 April 2018

ArcSWAT Tutorial

Landuse Tutorial

Sometime barren land has same appeared as urban area, Rivers are dry that appears as barren land. Even after final land use we think to add new class. But cannot add. Sometime forest in Hill shade area and appear black. Learn this all Everything how does with New Methods. More than Supervised classification and Get 90% Accuracy. Also learn how to do change detection. Like if urban area is increasing the how much area it takes from Agriculture or Forest, How Landuse is changing w.r.t Each class. Calculate are in Km, or Pixels. Lastly do accuracy report. Learn this everything. Only for LinkedIn offer who reading this post. This is already discounted link. Lear at your time. No time bound. Enrol now and watch more than 5 hrs step and your time.  You will also get valid certificate also.

ArcSWAT Tutorial

ArcSWAT is an watershed simulation model. Used for watershed, Water resource planning, Planning of Hydropower projects. It typical model to run with ArcGIS , Most of people facing error in SWAT Model. So, I have created a complete unofficial tutorial of SWAT model with ArcGIS. In this I covered Data download to final results. This include data preparation of SWAT model in Depth. Configuring swat model from scratch. I demonstrated using A live study area, from zero. I also covered custom data set for other countries to prepare for which no data is available, including preparation of soil maps. I covered to remove common error in weather data also. How to read output. How to manual configure inside SWAT model

Link to Tutorials

All tutorial covering GIS work from Data download to final results, you can use it as you like. No need to ask anyone to learn about land use. You also learn image processing and many tasks of GIS from zero, Discount already applied to this link for all who watching this page. This course Normally no one teach in depth, I decided to share deep knowledge which everyone can effort. You can watch it anytime after enrol, ask me questions. You will also get valid international corticate with digital id after complete of this tutorial.  if someone tech he charges you much money for this course. But I created all video and currently providing it only 700 Rs/ or 10$ only.  After enrol to this tutorial you will get all upcoming tutorial at same price. 

Discounted link to landuse course:
Discounted link to Watershed Simulation course with ArcSWAT GIS




Monday 16 April 2018

ArcSWAT and Landuse Best Tutorial Ever

ArcSWAT : Most of people facing error in SWAT Model. So, I have created a complete unofficial tutorial of SWAT model with ArcGIS. In this I covered Data download to final results. This include data preparation of SWAT model in Depth. Configuring swat model from scratch. I demonstrated using A live study area, from zero. I also covered custom data set for other countries to prepare for which no data is available, including preparation of soil maps. I covered to remove common error in weather data also. How to read output. How to manual configure inside SWAT model
Link:

Landuse: Sometime barren land has same appeared as urban area, Rivers are dry that appears as barren land. Even after final land use we think to add new class. But cannot add. Sometime forest in Hill shade area and appear black. Learn this all Everything how does with New Methods. More than Supervised classification and Get 90% Accuracy. Also learn how to do change detection. Like if urban area is increasing the how much area it takes from Agriculture or Forest, How Landuse is changing w.r.t Each class. Calculate are in Km, or Pixels. Lastly do accuracy report. Learn this everything. Only for LinkedIn offer who reading this post. This is already discounted link. Lear at your time. No time bound. Enrol now and watch more than 5 hrs step and your time.  You will also get valid certificate also.
Link:




Tuesday 9 January 2018

landuse landcover classification step by step in GIS

This is first landuse landcover course on udemy the most demanding topic in GIS, In this course I covered from data download to final results. I used ERDAS, ArcGIS and ENVI. I explained all possible methods of land use classification. More then landuse Pre Procession of images are covered after dowanload and after classification, how to correct error pixels are also covered, So after learning here you no need to ask anyone about lanudse classification. I explained theoretical concept also during processing of data. I have covered supervised, unsupevised, combined method, pixel correction methods etc. For in depth of all methods enroll in this course. 

Problem faced During classification:
Some of us faced problem during classification as:

  1. Urban area and barren land has same signature
  2. Dry river reflect same signature as urban area and barren land
  3. if you try to correct urban and get error in barren
  4. In Hilly area you cannot classify forest which is in the hill shade area. 
How to get rid of this all problems Join this course in link below. Don't miss this chance its already at 70% off link for all visitor of this site

This will cost you only 1280 Rs/-




Saturday 25 March 2017

Download High Resolution Satellite Images Free (10 meter)

Now Downloading of  High Resolution Satellite Images Free (10 meter). It is also available on Earth explorer. Watch the video Tutorial below. Also Subscribe our YouTube channel for more videos.


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Tuesday 10 January 2017

PC Configuration for Remote Sensing GIS - सुदूर संवेदन के लिए कंप्यूटर की कॉन्फ़िगरेशन

ये सारे तथ्य हमारे अपने अनुभव से हैं | अगर आप कोई कंप्यूटर लेने जा रहे हैं जिस पे GIS का काम हो तो एक बार निचे दी विडियो देख लें और यहाँ लिखा पड़ लें |

सॉफ्टवेर की साईट पे जो कंप्यूटर की कॉन्फ़िगरेशन दी होती है वो सिर्फ उस सॉफ्टवेर को इनस्टॉल करने के लिए दी होती हैं और ये लिखा होता है की ये कम ये कम इतना होना चाहिए | परन्तु जब आप उसे चलाते हैं तो उस से कहीं जयादा प्रोसेसिंग पॉवर की जरूरत पड़ती हैं |
GIS का काम करने के लिए हमारे अनुसार ये कॉन्फ़िगरेशन होनी चाहिए


  1. RAM 32 GB अथवा अधिक (DDR4 OR DDR5)
  2. इंटेल का xeon processor 4Ghz
  3. SSD (Non Rotating Hard disk) Solid State Drive



Saturday 7 January 2017

लैंडसैट 8 के डिजिटल नंबर को सतह के तापमान में बदलना

लैंडसैट 8 का प्रयोग करना 

ये जानकारी यहाँ भी उपलब्ध है (Source: https://landsat.usgs.gov/using-usgs-landsat-8-product)

लैंडसैट 8 में बैंड १० और ११ सतह का तापमान जानने के लिए प्रयोग  किये जाते हैं | जिसमे बैंड १० ताप तरंगो के कुछ पास के तरंग लम्बाई में है परन्तु बैंड ११ पूर्ण रूप से ताप को सेन्स करता है इस लिए बैंड ११ का प्रयोग करना की उचित समझा जाता है | परन्तु जब सॅटॅलाइट फोटो लेता है जो अदृश्य सूक्ष्म तरंग क्षेत्र  की हो वो  उसकी डिजिटल फिल्म में सीधे तरंग के (wavelength) तरंग लम्बाई के रूप में अंकित नहीं होती | क्योंकि डिजिटल फिल्म सिर्फ पूर्ण संख ही रिकॉर्ड कर सकती है दशमलव में नहीं , इस समस्या को हल करने के लिए उसे 16 बिट पे अंकित किया जाता है जिस से सब डाटा कुछ अधिक स्केल में अंकित होता है परन्तु सब रिकॉर्ड हो जाता है | इस अधिक डाटा को हम बाद में कम स्केल फैक्टर से प्रोसेस का के हम उसके मूल रूप में ला सकते हैं अथवा पूर्ण रूप से उस से वो प् सकते हैं जी के लिए वो बना है | परन्तु इस के लिए हमे डाटा को प्रोसेस करना होगा और गणित के मॉडल के द्वारा कैलकुलेशन (गणन्ना ) करनी होगी | इस तरह हमे सतह का तापमान मिल जायेगा | नासा हमे डाटा देता हैं परन्तु प्रोसेस उसे हमे करना होता है |  निचे वो सम्पूर्ण फार्मूला दिया है जिसके माध्यम से आप सतह का तापमान निकल सकते हैं | सतह का तापमान फसल , शहर की योजना और वाष्पीकरण की जानकारी के लिए महतवपूर्ण रहता है | ये सब की भी आप गन्ना कर सकते हैं | ये सारा कार्य आप एक एक से अधिक सॉफ्टवेर में कर सकते हैं परन्तु इस सब के लिए आपके कंप्यूटर की 8 GB, RAM हो i5 अथवा i7 प्रोसस्सेर हो और SSD हो तो अति उतम है , नहीं तो कंप्यूटर कुछ समय के लिए गरम हो जायेगा क्योंकि उसको कई अर्ब पिक्स्ले को प्रोसेस करना है | समस्त कार्य का फार्मूला निचे दिया गया है अथवा आप इस किताब को डाउनलोड कर के भी पड़ सकते हैं |


Conversion to TOA Radiance
OLI and TIRS band data can be converted to TOA spectral radiance using the radiance rescaling factors provided in the metadata file:
Lλ = MLQcal + AL 
where:              
Lλ          = TOA spectral radiance (Watts/( m2 * srad * μm))
ML         = Band-specific multiplicative rescaling factor from the metadata (RADIANCE_MULT_BAND_x, where x is the band number)
AL          = Band-specific additive rescaling factor from the metadata (RADIANCE_ADD_BAND_x, where x is the band number)
Qcal        = Quantized and calibrated standard product pixel values (DN)         

Conversion to TOA Reflectance
OLI band data can also be converted to TOA planetary reflectance using reflectance rescaling coefficients provided in the product metadata file (MTL file).  The following equation is used to convert DN values to TOA reflectance for OLI data as follows:
ρλ' = MρQcal + Aρ 
where:              
ρλ'          = TOA planetary reflectance, without correction for solar angle.  Note that ρλ' does not contain a correction for the sun angle.
Mρ         = Band-specific multiplicative rescaling factor from the metadata (REFLECTANCE_MULT_BAND_x, where x is the band number)
Aρ          = Band-specific additive rescaling factor from the metadata (REFLECTANCE_ADD_BAND_x, where x is the band number)
Qcal        = Quantized and calibrated standard product pixel values (DN)

TOA reflectance with a correction for the sun angle is then:
ρλ ρλ'=ρλ'
cos(θSZ)sin(θSE)
where:              
ρλ          = TOA planetary reflectance
θSE         = Local sun elevation angle. The scene center sun elevation angle in degrees is provided in the metadata (SUN_ELEVATION).
θSZ         = Local solar zenith angle;  θSZ = 90° - θSE
For more accurate reflectance calculations, per pixel solar angles could be used instead of the scene center solar angle, but per pixel solar zenith angles are not currently provided with the Landsat 8 products.

Conversion to At-Satellite Brightness Temperature
TIRS band data can be converted from spectral radiance to brightness temperature using the thermal constants provided in the metadata file:
T = K2
ln( K1 +1)
Lλ
where:              
T           = At-satellite brightness temperature (K)
Lλ          = TOA spectral radiance (Watts/( m2 * srad * μm))
K1          = Band-specific thermal conversion constant from the metadata (K1_CONSTANT_BAND_x, where x is the thermal band number)
K2          = Band-specific thermal conversion constant from the metadata (K2_CONSTANT_BAND_x, where x is the thermal band number)
अगर आप उपर लिखा सब प्रोसेस करंगे तो आपको इस तरह की आउटपुट मिलेगी | ये जयपुर शहर की सॅटॅलाइट इमेज को [रोसेस करने के बाद तापमान निकला गया है |  यदि हमसे संपर्क करना हो तो आप फेसबुक पे जा का इस पेज से हमे संदेश दे सकते हैं , आपको जवाब जरुर मिलेगा https://www.facebook.com/IndianRemoteSensing/   नए अपडेट के लिए इसे लाइक भी कर सकते हैं |