This project aims to automate tree counting and forest land diversion assessment through satellite image combined with advanced computing techniques. The treatment of forest resources needs accurate monitoring because growing environmental challenges such as deforestation, biodiversity loss, and climate change require it for sustainable land management. The research uses satellite imagery along with machine learning and deep learning tools, specifically convolutional neural networks (CNNs), to precisely detect and count trees across expansive territories. The study demonstrates how satellite analytics technologies will enhance forestry applications with their capabilities for better tree enumeration at higher efficiency and greater accuracy.