Protected areas (PA), especially montane forests, have been identified as an essential tool for conserving biodiversity and as key sources of ecosystem services, which include Net Primary Productivity (NPP), carbon sequestration, habitat and shelter for endemic and endangered species, and clean water.  However, forests are threatened constantly by human impacts like forest fires, air pollution, clearing for agricultural uses, and illegal cutting. Despite those benefits, conservationists are far from able to assist all those natural wonders under threat due to the lack of funding for research and other related conservation projects. Therefore, one of the six key landscapes identified for conservation in the Albertine Rift known as montane forest Nyungwe National Park (NNP) located in Rwanda, its forest degradation and its canopy daily net primary productivity and carbon sequestered were assessed and evaluated using remote sensing and ArcGIS techniques combined with a light use efficiency model.

To carry out this study, freely available dry season Landsat Thematic Mapper (TM) images were downloaded from the U.S. Geological Survey Global Visualization Viewer along with Rwanda Digital Elevation Model (DEM). Landsat TM images data were processed through radiometric correction, dark object subtraction, then masked and geo-referenced to NNP. Based on ground knowledge and features such as wetlands and infrastructure e.g., roads and buildings, Regions Of Interest (ROI) were used for training data for supervised maximum likelihood classification where all spectral bands in each satellite image were used, then classified into three land cover types using Envi 4.7 image processing software. Through raster calculator ArcGIS 10.1 tool, the most commonly used vegetation indices, Normalized Difference Vegetation Index (NDVI) and its time series change detection analysis from 1986 to 2010 were performed, but also resampling and surface analysis techniques were executed on DEM.

The land cover classes, as revealed by the processed satellite images, showed that 92.4% of forestland has undergone degradation from 1986 to 2010. The highest forestland downsizing rate of 4.5% was observed between 1986 and 1994. The entire park has lost up to 40% of its daily NPP and carbon sequestration capacity between 1986 and 2010. The study also revealed that the degradation was evenly distributed across the entire area of the park, which negatively affects endemics and endangered species of this park through lack of alternative habitat once one habitat becomes less suitable. Thus, the present study suggests further investigation of climatic variables, conditions, and anthropogenic threats, which may impact interpretations of the sources of this forest coverage degradation. The results of this study show that cost and time effective biodiversity information technology research tools, namely remote sensing and GIS, can effectively and accurately document time series forest degradation with associated factors and also assist in assessing the ecosystem services.