Automatic Delineation of Forest Patches in Highly Fragmented Landscapes Using Coloured Point Clouds

Forests

JoséV. Roces-Díaz¹  Carlos Cabo¹  Cristina Santín¹  Celestino Ordoñez²  Covadonga Prendes³ 

[1] Department of Geography, College of Science, Swansea University, Wallace Building, Singleton Park, Swansea SA2 8PP, Wales, UK;Department of Mining Exploitation and Prospecting, University of Oviedo, 33003 Oviedo, Spain;Forest and Wood Technology Research Centre Foundation (CETEMAS), Pumarabule s/n, 33936 Carbayín, Asturias, Spain;

关键词: forest mapping;    non-forest woody vegetation;    lidar;    ndvi;    high-resolution imagery;   

DOI  :  10.3390/f11020198

来源: DOAJ

【 摘 要 】

Accurate mapping of landscape features is key for natural resources management and planning. For this purpose, the use of high-resolution remote sensing data has become widespread and is increasingly freely available. However, mapping some target features, such as small forest patches, is still a challenge. Standard, easily replicable, and automatic methodologies to delineate such features are still missing. A common alternative to automated methods is manual delineation, but this is often too time and resource intensive. We developed a simple and automatic method from freely available aerial light detection and ranging (LiDAR) and aerial ortho-images that provide accurate land use mapping and overcome some of the aforementioned limitations. The input for the algorithm is a coloured point cloud, where multispectral information from the ortho-images is associated to each LiDAR point. From this, four-class segmentation and mapping were performed based on vegetation indices and the ground-elevation of the points. We tested the method in four areas in the north-western Iberian Peninsula and compared the results with existent cartography. The completeness and correctness of our algorithm ranging between 78% and 99% in most cases, and it allows for the delineation of very small patches that were previously underrepresented in the reference cartography.

【 授权许可】

Unknown