Abstract
Gullies are landforms with specific patterns of shape, topography, hydrology, vegetation, and soil characteristics. Remote sensing products (TanDEM-X, Sentinel-1, and Sentinel-2) serve as inputs into an iterative algorithm, initialized using a micro-mapping simulation as training data, to map gullies in the northwestern of Namibia. A Random Forest Classifier examines pixels with similar characteristics in a pool of unlabeled data, and gully objects are detected where high densities of gully pixels are enclosed by an alpha shape. Gully objects are used in subsequent iterations following a mechanism where the algorithm uses the most reliable pixels as gully training samples. The gully class continuously grows until an optimal scenario in terms of accuracy is achieved. Results are benchmarked with manually tagged gullies (initial gully labeled area 98%, with 60% in the gully class, Cohen Kappa >0.5, Matthews Correlation Coefficient >0.5, and receiver operating characteristic Area Under the Curve >0.89. Hence, our method outlines gullies keeping low false-positive rates while the classification quality has a good balance for the two classes (gully/no gully). Results show the most significant gully descriptors as the high temporal radar signal coherence (22.4%) and the low temporal variability in Normalized Difference Vegetation Index (21.8%). This research builds on previous studies to face the challenge of identifying and outlining gully-affected areas with a shortage of training data using global datasets, which are then transferable to other large (semi-) arid regions.
Highlights
S OIL health is a global concern affecting modern and traditional societies and is a fundamental aspect that sustains life on Earth [1], [2]
Considerable scientific effort has been directed in Namibia towards controlling [18] and understanding general land degradation [19], [20], in particular, that associated with gullies [21]–[23]
There are attempts to carry out inventories and distribution maps of gullies as well as land degradation by individual researchers [24], farmers associations [25], and the Ministry of Agriculture, Water and Rural development of Namibia [26], [27]
Summary
S OIL health is a global concern affecting modern and traditional societies and is a fundamental aspect that sustains life on Earth [1], [2]. Gullies are responsible for the loss of large masses of sediment from river catchments and agriculture plots [5] Given that they threaten important infrastructures such as settlements, roads, and cattle dams, these effects are considered more pronounced as compared to other soil erosion types [6]. There are attempts to carry out inventories and distribution maps of gullies as well as land degradation by individual researchers [24], farmers associations [25], and the Ministry of Agriculture, Water and Rural development of Namibia [26], [27]. A more global approach, is required to tackle the problem as a critical hazard affecting the entire nation In this sense, as highlighted by Poesen [5] for a global scale, research activities in Namibia should cover the development of standardized and reliable measuring techniques for gully identification and mapping at
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More From: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
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