The stream length‐gradient index (SL) shows the variation in stream power along river reaches. This index is very sensitive to changes in channel slope, thus allowing the evaluation of recent tectonic activity and/or rock resistance. Nevertheless, the comparison of SL values from rivers of different length is biased due to the manner in which the index is formulated, thus making correlations of SL anomalies along different rivers difficult. Therefore, when undertaking a comparison of SL values of rivers of different lengths, a normalization factor must be used. The graded river gradient (K) has already been used in some studies to normalize the SL index. In this work, we explore the relationships between the graded river gradient (K), the SL index and the stream power, proposing the use of a re‐named SLk index, which enables the comparison of variable‐length rivers, as well as the drawing of SLk anomaly maps. We present here a GIS‐based procedure to generate SLk maps and to identify SLk anomalies. In order to verify the advantages of this methodology, we compared an SLk map of the NE border of the Granada basin with both simple river profile–knickpoint identification and with an SL map. The results show that the SLk map supplies good results with defined anomalies and suitably reflects the main tectonic and lithological features of the study area. Copyright © 2008 John Wiley & Sons, Ltd.

This paper deals with the application of Unmanned Aerial Vehicles (UAV) techniques and high resolution photogrammetry to study the evolution of a landslide affecting olive groves. The last decade has seen an extensive use of UAV, a technology in clear progression in many environmental applications like landslide research. The methodology starts with the execution of UAV flights to acquire very high resolution images, which are oriented and georeferenced by means of aerial triangulation, bundle block adjustment and Structure from Motion (SfM) techniques, using ground control points (GCPs) as well as points transferred between flights. After Digital Surface Models (DSMs) and orthophotographs were obtained, both differential models and displacements at DSM check points between campaigns were calculated. Vertical and horizontal displacements in the range of a few decimeters to several meters were respectively measured. Finally, as the landslide occurred in an olive grove which presents a regular pattern, a semi-automatic approach to identifying and determining horizontal displacements between olive tree centroids was also developed. In conclusion, the study shows that landslide monitoring can be carried out with the required accuracy—in the order of 0.10 to 0.15 m—by means of the combination of non-invasive techniques such as UAV, photogrammetry and geographic information system (GIS).