Francisco Darío Maldonado

Change detection technique based on the radiometric rotation controlled by no-change axis, applied on a semi-arid landscape

We demonstrate a new digital technique for change detection that integrates field survey data in a methodology. The field survey was specifically designed to control the operation of this new technique for change detection. The Radiometric Rotation Controlled by No‐change Axis (RCNA) technique was applied with spectral bands in the visible spectral range without atmospheric correction. The 190.37 km2 study area is located in the centre of the semi‐arid region of northeast Brazil. This region is occupied by a natural shrub vegetation and low arboreal type steppe. This is known locally as ‘caatinga’, and in this area the predominant use is grazing by cattle and goat. Two TM/Landsat images in digital format of the dry seasons of 1984 and 1996 were used together with two ETM+ /Landsat images for the dry seasons of 1999 and 2001. Three change maps were generated, all with accuracy index values of around 0.70, which is acceptable for areas with complex patterns like semi‐arid lands. In conclusion, there is no need to apply atmospheric correction methods to a pair of multi‐temporal images to obtain an acceptable accuracy of change detection in semi‐arid regions. Although this technique can combine images from different sensors, this requires that both have similar spectral ranges.

Radiometric rotation technique to monitor degradation and regeneration features in Brazilian semi-arid region

The objective is to present a technique on “Radiometric rotation controlled by a no-change axis (RCEN)”, using a multi-temporal comparison between ETM+/LANDSAT-7 and CCD/CBERS-2 images. The area under study is located in the central of Brazilian semi-arid region, whose landscape is dominated by steppe savanna (caatinga). The result of RCEN technique is an change detection-image, whose continuous image (floating-point) was transformed into a thematic image through the procedure of slicing and labelling. This allowed the spectral discrimination in five thematic classes: two related to degradation, two referring to regeneration and one of no-change. A map of changes 2001/2004 was generated, illustrating the distribution of these thematic categories mentioned at the caatinga zone , which is under a strong impact due to agriculture activities for subsistence, besides pastureland for goats in the community fields.

Multi-temporal analysis of radiometric changes in satellite images of forest edges to infer selective-logging areas in the Amazon forest

Radiometric changes observed in multi-temporal optical satellite images have an important role in efforts to characterize selective-logging areas. The aim of this study was to analyze the multi-temporal behavior of spectral-mixture responses in satellite images in simulated selective-logging areas in the Amazon forest, considering red/near-infrared spectral relationships. Forest edges were used to infer the selective-logging infrastructure using differently oriented edges in the transition between forest and deforested areas in satellite images. TM/Landsat-5 images acquired at three dates with different solar-illumination geometries were used in this analysis. The method assumed that the radiometric responses between forest with selective-logging effects and forest edges in contact with recent clear-cuts are related. The spatial frequency attributes of red/near infrared bands for edge areas were analyzed. Analysis of dispersion diagrams showed two groups of pixels that represent selective-logging areas. The attributes for size and radiometric distance representing these two groups were related to solar-elevation angle. The results suggest that detection of timber exploitation areas is limited because of the complexity of the selective-logging radiometric response. Thus, the accuracy of detecting selective logging can be influenced by the solar-elevation angle at the time of image acquisition. We conclude that images with lower solar-elevation angles are less reliable for delineation of selecting logging.

Characterization and monitoring of semi-arid landscape in the Maule region from satellite data

The objective of this research is to apply the Radiometric Rotation Controlled by No-change Axis (RCNA) technique on Landsat TM images, 2004 and 2008, covering the coastal dry land of the Region of Maule, Chile, in order to obtain the spatial distribution of changes and degradation in the forest landscape. The RCNA procedure allows the use of images without atmospheric calibrations, whose empirical method for the label was based on field observations. The Kappa Index for the change thematic image was 0.74, showing that the recovery and loss of vegetation were 17 and 5%, respectively. SRTM (Shuttle Radar Topography Mission) data were used to derive slope angle, where the major proportion of no-change surface occurs in areas of high and low slope. In the category of recovery of vegetation, the major proportion takes place in the 10-50% slope class. On the other hand, the loss vegetation is uniformly distributed through the whole gradient of the slope angle.

Change detection in the semi-arid landscape using radiometric rotation applied to remote sensing data

The main task is to apply in the semi arid landscape of Maule region (Chile), the multi-temporal change detection algorithm ¿RCNA multi-spectral¿, using TM/Landsat images (2004 and 2008). The RCNA is based in angular parameters; those angles are calculated in function of the axis formed by the straight line of regression of those points labeled in the field survey as no-change. The image for detection was transformed from a continuous (floating-point) to thematic image, through a slicing and labeling process. Hence it is possible to discriminate: two classes related to degradation, two referring to regeneration and one of no-change. In the timeframe studied 4.6% of area under study presents degradation patterns, derived from the complete removal of the matorral type, followed by changes of land use. We found out that the application of multi-spectral RCNA technique in semi-arid landscape is sufficiently robust and the complex radiometric correction is not necessary.