64-LQP-ARJCS 20241230000000 Lumina Quest Publishing m.arslansohail@gmail.com Lumina Quest Publishing Advanced Research Journal of Computer Science Adv. Res. J. Comput. Sci. 3134-884X 10.66590/arjcs https://lquestpub.com/archives.php?journal=advanced-research-journal-of-computer-science 12 30 2024 12 30 2024 1 1 10.66590/arjcs20240101 https://lquestpub.com/articles-list.php?journal=advanced-research-journal-of-computer-science&volume=1&issue=1 Crop Density Estimation using Unmanned Aerial Vehicle Images Rida Afzal As we know well that the economy of our country is based upon agriculture. It is a basic source to get food. As the population of our country has increased, so our basic need is to fulfill the food requirements. So, I used different modern methods to identify the crop density. In this research I tried to replace the old methods with modern techniques which are more efficient and cost effective. RGB images were used with higher resolution camera in order to identify the green pixels of the plants. If density of crop is higher, then crop growth and its health would also be increased. The components of crop rows will identify by extracting them. Functioning of crop was very important in order to identify the different features like water, yield and requirement of fertilizers along with susceptibility towards pathogens. Wheat is the most common crop which is cultivated along whole world having different ranges. The population density of plants is very important in competition among different plants along weeds and their effective usage on the availability of sources like water, light and nutrients. With this technique, I was able to collect visual plants into a field on a specific area in order to collect the sample. The use of NDVI (Normalized Difference Vegetation Index) agriculture and different drone sensors were the basic indicator of health for the plants. Live green plants can absorb a large amount of solar radiation and it could be used as the primary source of energy in the basic process of photosynthesis. 12 30 2024 12 30 2024 1 8 10.66590/arjcs2024010101 https://lquestpub.com/article/10.66590/arjcs2024010101