Tuesday, June 27, 2023

Admission for Masters in Remote Sensing at LPU

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, January 27, 2023

Crop yield estimation using remote sensing and GIS 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 and geographic information systems (GIS) are powerful tools 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).  we will explore the use of NDVI in conjunction with remote sensing and GIS to estimate crop yields.
Remote sensing is the process of collecting and analyzing data about the earth's surface using sensors mounted on aircraft or satellites. These sensors can detect and measure various characteristics of the earth's surface, such as temperature, humidity, and vegetation cover. 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.
GIS is a collection of software and data that can be used to analyze, visualize, and manage geographic data. GIS can be used to analyze remote sensing data, such as NDVI images, to estimate crop yields.By developing a regression model on NDVI and crop yield. GIS can also be used to create maps that show crop yields across an entire region, making it easier to identify areas that may need additional resources or attention.
ArcGIS is a popular GIS software that can be used to analyze remote sensing data and estimate crop yields. It can be used to process NDVI images and create maps that show crop yields across an entire region. The software also has a wide range of tools that can be used to analyze and manipulate spatial data, making it an ideal tool for crop yield estimation.
Model development required a number of tools and logic to use together.  



Tutorial 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, December 31, 2022

GIS Udemy Tutorial Coupon codes 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