WP3: Monitoring of forest-cover change and degradation
Context
Remote sensing has long been instrumental for mapping and monitoring forest cover changes and it was satellite imagery that highlighted widespread deforestation in the world's tropical regions (Pfaff, 1999 and Skole and Tucker, 1993). In contrast though, forest area is increasing in many developed nations due to combined effects of advances in agricultural productivity and increasing awareness regarding the environmental importance of forests (Lambin and Meyfroidt, 2010 and Meyfroidt and Lambin, 2011). However, information on forests and forest cover changes are not always publicly accessible and we still lack comprehensive knowledge of spatio-temporally explicit forest cover dynamics, especially across large areas and with sufficient spatial detail to resolve the full range of forest change processes.
Compositing algorithms were initially developed for wide-swath sensor data, where observations are very frequent, but no image is ever completely cloud-free, and reducing cloud contamination and other atmospheric effects is therefore essential (Cihlar et al., 1994 and Holben, 1986). For Landsat data, compositing offers comparable advantages, though. By selecting the best observation on a per-pixel basis, cloudy imagery (typically discarded within scene-based approaches) can be exploited for high quality observations and the 16-day repeat cycle can be overcome through utilization of the across track overlap between adjacent image acquisition paths, which is considerable at higher latitudes. A single, “global” classification/regression model can be trained and applied if composites have sufficient seasonal and radiometric consistency, making large area mapping and monitoring approaches with Landsat more practicable.
Main results
1. Forest dynamics based on Landsat compositing
Detailed knowledge of forest cover dynamics (Figure 1) is crucial for many applications from resource management to ecosystem service assessments. Landsat data provides the necessary spatial, temporal and spectral detail to map and analyze forest cover and forest change processes. With the opening of the Landsat archive, new opportunities arise to monitor forest dynamics on regional to continental scales. In this study we analyzed changes in forest types, forest disturbances, and forest recovery for the Carpathian ecoregion in Eastern Europe (Figure 1) . We generated a series of image composites at five year intervals between 1985 and 2010 and utilized a hybrid analysis strategy consisting of radiometric change classification, post-classification comparison and continuous index- and segment-based post-disturbance recovery assessment. For validation of the disturbance map we used a point-based accuracy assessment, and assessed the accuracy of our forest type maps using forest inventory data and statistically sampled ground truth data for 2010.
Figure 1: Total forest area and forest type by country for the years 1985 and 2010 in square kilometers (top), changes in the proportion of forest types between 1985 and 2010 for the seven countries, expressed as the percentage of the total country forest area in the study region (bottom).
Our Carpathian-wide disturbance map achieved an overall accuracy of 86% and the forest type maps up to 73% accuracy. While our results suggested a small net forest increase in the Carpathians, almost 20% of the forests experienced stand-replacing disturbances over the past 25 years. Forest recovery seemed to only partly counterbalance the widespread natural disturbances and clear-cutting activities. Disturbances were most widespread during the late 1980s and early 1990s, but some areas also exhibited extensive forest disturbances after 2000, especially in the Polish, Czech and Romanian Carpathians. Considerable shifts in forest composition occurred in the Carpathians, with disturbances increasingly affecting coniferous forests, and a relative decrease in coniferous and mixed forests. Both aspects are likely connected to an increased vulnerability of spruce plantations to pests and pathogens in the Carpathians. Overall, our results exemplify the highly dynamic nature of forest cover during times of socio-economic and institutional change, and highlight the value of the Landsat archive for monitoring these dynamics.
Additionnal information can be found in:
Griffiths, P., Kuemmerle, T., Baumann, M., Radeloff, V. C., Abrudan, I.V., Lieskovský, J., Muntenau, C., Ostapowicz, K., & Hostert, P. (2013). Forest disturbances, forestrecovery, and changes in forest types across the Carpathianecoregionfrom 1985 to 2010 based on Landsat image composites. Remote Sensing of Environment.
2. Using Landsat compositing to assess the effects of forest restitution in Post-Socialist Romania
The increasing availability of the Landsat image archive and the development of approaches to make full use of these data provide novel insights into the drivers and dynamics of land use systems change. Focusing on Romania, we asked how the drastic institutional and socio-economic transformation after the collapse of socialism in Eastern Europe affected forestry. We used an annual time series of Landsat images to investigate how three phases of forest restitution affected forest disturbances (due to both, natural events and forest management) (Figure 2). We employed the LandTrendr (Landsat-based detection of trends in disturbance and recovery) set of change detection algorithms to perform temporal segmentation and fitting of the Landsat time series, and derived annual disturbance maps (95.72% overall accuracy) along with recovery dynamics (Figure 2).
Figure 2: (A) Four details of the disturbance map, (B) imagery of one point in time close to the main disturbance events, (C) imagery of one point in time ca. five years later, (D) patch based percentage of recovered relative disturbance magnitude after five years (Imagery is shown as RGB = 453).
Our change map suggested that forest disturbances increased substantially since the collapse of socialism in 1989, with 75,000 ha of disturbed forest land (4.5% of the total studied forest area). Whereas the late socialist years were characterized by relatively low disturbance levels (12% of all detected disturbances), disturbances increased especially after each of the restitution laws were passed in 1991, 2000, and 2005 (34%, 21% and 32% respectively). Non-state ownership regimes (i.e. private owners vs. public property of local communities) and species composition of restituted forests were two important factors determining disturbance levels. The widespread disturbances we found also raise concerns about timber overexploitation in many areas of the Romanian Carpathians. Our study demonstrates the value of the temporal depth of the Landsat archive and highlights that trajectory-based change detection approaches can be highly beneficial for gaining insights on the effect of institutional shocks on land use patterns.
Additionnal information can be found in:
Griffiths, P., Kuemmerle, T., Kennedy, R.E., Abrudan, I.V., Knorn, J., & Hostert, P. (2012). Usingannual time-series of Landsat images to assess the effects of forest restitution in post-socialist Romania. RemoteSensing of Environment, 118, 199-214.
3. Forest cover changes in Bhutan at the national level
In progress
4. Long time series analysis for the evaluation of forest cover dynamics in Ecuador between 1960 and 2010
In progress