Land cover classification, crop detection and its area and yield estimation using remote sensing
Pakistan is an agricultural state but we don't have any proper management for the record of agriculture production. There are many challenges to the government of Pakistan in yield estimations, our government still use primitive techniques in the analysis of crop yields. So in this project, by using
2025-06-28 16:33:57 - Adil Khan
Land cover classification, crop detection and its area and yield estimation using remote sensing
Project Area of Specialization Artificial IntelligenceProject SummaryPakistan is an agricultural state but we don't have any proper management for the record of agriculture production. There are many challenges to the government of Pakistan in yield estimations, our government still use primitive techniques in the analysis of crop yields. So in this project, by using remote sensing we will estimate the production of the crops by using machine learning algorithms. And in the end, an accurate statistics report will be generated.
Also there is no official platform that connect a vegetable buyer to order or connect with sellers/farmers. So we will develop a platform (web app and mobile app) that will give details information about crops to buyers. So users can easily order through there.
Project Objectives? A ground survey using the geo-survey application to collect data of different crops including vegetables.
?Collection of satellite imagery that we have done in the survey.
?Preprocessing on satellite imagery.
?Use processed and refined images to train a classifier that will give us accurate statistic report.
?Area estimation will be done with the help of our classifier.
?Statistics Report.
?Publishing a research paper.
?Developing a web app that will give details information about crops using our updated map.
Project Implementation MethodThe project team will do surveys in different regions to collect data of different crops. Data collection will be done with the mobile app "Geo Survey "develop by NCBC. Then will download that data and do different pre-processing step to ready the data for training the classifier. Then testing phase will state. After that, we can easily estimate the production of different crops. Besides this when we get the statics of crops we will develop a web and mobile app that gives the information of the vegetables and fruits. And their quantity and quality in that region. So that buyer can easily order what he/she wants.
Benefits of the Project?Proper management through remote sensing and satellite imagery.
?Estimation through remote sensing using machine learning.
?A complete statistical report for government that will give details of the crop.
?The government can easily predict which item should be export more.
?In the future which item can cultivate more or less can easily predict through analytics report.
?A platform that gives complete information to buyers about the quality and quantity of vegetables or fruits in a specific area.
?A marketplace in form of web app for buying and selling of vegetables and fruits.
?Dealers will look for fresh vegetables and fruits in big quantity to order them from our web application.
Technical Details of Final DeliverableResearch paper and market place in web/mobile app for buyers and sellers
Final Deliverable of the Project Software SystemCore Industry AgricultureOther Industries Education , Food Core Technology Artificial Intelligence(AI)Other Technologies Big DataSustainable Development Goals Decent Work and Economic GrowthRequired Resources| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Total in (Rs) | 80000 | |||
| Tablet device | Equipment | 2 | 15000 | 30000 |
| Garmin gps device | Equipment | 1 | 40000 | 40000 |
| Survey cost | Miscellaneous | 1 | 10000 | 10000 |