Abstract
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.
Highlights
Accurate mapping and classification of landscape elements including different land covers and ecosystems is key for land planning, natural resources management and biodiversity conservation [1,2,3]
The method proposed here allowed the automatic mapping of the four study areas at high spatial resolution
The algorithm developed this study allows identification and delineation different types of landscape features and land uses at the local level including forest/tree/woody vegetation types of landscape features and land uses at the local level including forest/tree/woody vegetation patches of of small size
Summary
Accurate mapping and classification of landscape elements including different land covers (crops, pastures, forest areas, etc.) and ecosystems is key for land planning, natural resources management and biodiversity conservation [1,2,3]. In this sense, over the last few decades, a wide range of products and methodologies related to landscape mapping have been released (e.g., [2,4,5,6,7]). High spatial resolution images (i.e., pixel sizes smaller than 1–2 m [11]) allow for the delineation of small or very narrow features or patches. Small-sized forest patches, isolated trees, and non-forest woody formations are relevant elements of traditional landscapes of Europe [12]
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