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Abstract
Terraces, which are typical artificial landforms found around world, are of great importance for agricultural production and soil and water conservation. However, due to the lack of maintenance, terrace damages often occur and affect the local flow process, which will influence soil erosion. Automatic high-accuracy mapping of terrace damages is the basis of monitoring and related studies. Researchers have achieved artificial terrace damage mapping mainly via manual field investigation, but an automatic method is still lacking. In this study, given the success of high-resolution unmanned aerial vehicle (UAV) photogrammetry and object-based image analysis (OBIA) for image processing tasks, an integrated framework based on OBIA and UAV photogrammetry is proposed for terrace damage mapping. The Pujiawa terrace in the Loess Plateau of China was selected as the study area. Firstly, the segmentation process was optimised by considering the spectral features and the terrains and corresponding textures obtained from high-resolution images and digital surface models. The feature selection was implemented via correlation analysis, and the optimised segmentation parameter was achieved using the estimation of scale parameter algorithm. Then, a supervised k-nearest neighbourhood classifier was used to identify the terrace damages in the segmented objects, and additional geometric features at the object level were considered for classification. The comparison with the ground truth, as delineated by the image and field survey, showed that proposed classification can be adequately performed. The F-measures of extraction on three terrace damages were 92.07% (terrace sinkhole), 81.95% (ridge sinkhole), and 85.17% (collapse), and the Kappa coefficient was 85.34%. Finally, the potential application and spatial distribution of the terrace damages in this study were determined. We believe that this work can provide a credible framework for mapping terrace damages in the Loess Plateau of China.
Highlights
The objective of this study is to propose an object-based image analysis (OBIA) workflow for the automatic extraction of terrace damages in the Loess Plateau of China
The original was segmented into objects by Multiple resolution segmentation (MRS) using the selected feature combination the optimal
Our study indicated that the occurrence of terrace damages is related to the morphological characteristics of terraces, including the height of the steps, the width of the field surface, and the number of steps
Summary
Terraces, which are represented by a series of successively receding flat surfaces along contour lines on slopes [1], are typical artificial landforms in hilly and mountainous areas [2]. Terracing can increase arable land and agricultural production [3,4] and contribute to soil and water conservation [5,6] by changing the local topography of slopes and their corresponding water flow process [7] and soil properties [8]. The artificially terraced landscapes that have been developed widely around the world [2,9] can enhance biodiversity and landscape diversity [10,11] and provide aesthetic, cultural, and tourism landscape value [12,13,14].
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