Design of intelligent agricultural landscape planning and ecological balance control system based on remote sensing images

With the modernization of agricultural production and the acceleration of urbanization, agricultural landscape planning and ecological balance control have become important issues in promoting sustainable development. Traditional agricultural production methods have problems such as resource waste, environmental pollution, and ecological damage. This article aimed to achieve scientific planning and management of agricultural landscapes, and promote the efficiency of agricultural production, rational utilization of resources, and protection of the ecological environment, thereby promoting sustainable agricultural development. This study first focused on denoising and feature extraction of agricultural remote sensing data images, using remote sensing technology to obtain agricultural landscape information. After that, artificial intelligence was adopted to achieve intelligent agricultural landscape planning, with the goal of maintaining ecological balance and promoting efficient, eco-friendly, and sustainable agricultural production. This study took the landscape of a certain city as an example to test the processing effect of remote sensing images, and it was proved that the effect was good. We tested the performance of an intelligent agricultural landscape planning and ecological balance control system based on remote sensing images. According to the experimental results, it can be concluded that the resource utilization efficiency of farmland A monitored by the intelligent agricultural landscape planning system using remote sensing image technology was 82%, while the traditional one was only 60%. This indicated that the collection effect of remote sensing image technology was much better than that of traditional technology. This article comprehensively and timely monitored and evaluated farmland through remote sensing image technology, including crop growth status, soil moisture, nutritional status, etc. The system can provide precise planting and management suggestions for farmers based on this information, and help them optimize farmland layout, crop selection, and irrigation management, thereby improving the production efficiency of farmland and crop yield.