Monitoring
Importance of Input Classification to Graph Automata Simulations of Forest Cover Change in the Peruvian AmazonBackgroundIn an area of Peru difficult for remote sensing imaging of deforestation and regeneration, the authors evaluate landcover and detect changes in landuse using novel data simulation techniques. Research goals & MethodsThe authors aim to compensate for remote assessments of deforestation or reforestation that may be strongly dependent on the seasonality of input images. To do this, they ran graph automata simulations while varying forest cover inputs to model land cover change. Open access copy available |
Soil organic matter dynamics during 80 years of reforestation of tropical pasturesBackgroundLand disturbance affects soil physical and chemical properties. Some properties may be recovered over long periods of reforestation. Mosaic-pattern landscapes with shifting usages over time, common in the mountainous tropics, can reveal dynamic soil properties. This study reports on changes in soil carbon over 80 years of secondary forest growth on abandoned pasture over a chronosequence in Puerto Rico. Open access copy available |
