Automatic environmental quality assessment for mixed-land zones using lidar and intelligent techniques

Abstract

Human impact on the natural environment is an evident global fact. Natural, industrial and touristic areas coexist in a more than delicate balance. In Andalusia, in the south of Spain, the Regional Ministry for the Environment is responsible for the control and preservation of natural resources. This task bears a high cost in time and money. Remote sensing and the use of intelligent techniques are excellent tools to reduce such costs. This work explores the joint use of the lidar sensor, which provides a great quantity of information describing three dimensional space, and the application of intelligent techniques for rapid and efficient land use and land cover classification with the objective of differentiating urban land from natural ground close to protected areas of Huelva province. For this, seven types of land use and land cover have been studied for a riparian area next to the mouth of the rivers Tinto and Odiel, extracting 33 distinct features from the lidar point cloud. Subsequently, a supervised learning algorithm is applied to construct a model which, with a resolution of 4 m2, obtained relative precision between 71% and 100%and an average total precision of 85%.