Mapping, Remote Sensing, and GIS
Simulating Forest Cover Changes of Bannerghatta National Park Based on a CA-Markov Model: A Remote Sensing ApproachBackgroundEstablishment of protected areas has been a primary response to deforestation and land-use change in tropical forests. However, few empirical evaluations have conducted a comparison of pre- and post-intervention landscapes. Open access copy available |
Deforestation and Reforestation of Latin America and the Caribbean (2001–2010)backgroundThis study examines contrasting forest cover change dynamics in Latin America and the Caribbean using MODIS satellite imagery. Many studies have documented deforestation, while others report forest recovery. This study seeks to analyze these trends on a large scale and connect them to environmental and population variables. Available with subscription or purchase |
Landscape Pattern Dynamics and Mechanisms during Vegetation Restoration: A Multiscale, Hierarchical Patch Dynamics ApproachBackgroundThis study examines patterns of restoration using permanent plots and remote sensing of a nature reserve from 1979 to the present using a multiscale, hierarchical patch dynamic framework. Research Goals & MethodsThis study attempts to document changes in time and space during the restoration of forests with the purpose of understanding its patterns and processes. Available with subscription or purchase |
Mangrove Ecosystem Recovery and Restoration from Oil Spill in the Niger Delta: The GIS PerspectiveBackgroundIn Nigeria, Mangrove's provide critical environmental and economic services, including maintaining water quality, serving as breeding grounds for important fish and crustacean, and as a source of food and materials. Yet, the country also has a history of oil spills that threaten these important ecosystems. In order to understand the effects of oil spills on mangroves, this study examines the land cover change of mangrove ecosystems in the Niger Delta between 1986 and 2008. Open access copy available |
Modelos espaciales aplicados al manejo de los recursos naturales: una propuesta en la sub-cuenca del Río Pilón, Nuevo León, México (Spacial modeling applied to natural resources management)Open access copy available |
Monitoring of Black Mangrove Restoration with Nursery-Reared Seedlings on an Arid Coastal LagoonbackgroundThis paper describes a reforestation experiment with black mangrove (Avicennia germinans) in an arid mangrove forest of Baja California Sur, Mexico. In arid mangrove systems, natural regeneration and small-scale reforestation are not adequate to restore mangrove forests, as they may be in the humid tropics. Thus, alternative nursery techniques for arid mangroves must be developed. Available with subscription or purchase |
Integration of Hyperion Satellite Data and A Household Social Survey to Characterize the Causes and Consequences of Reforestation Patterns in the Northern Ecuadorian AmazonbackgroundThis paper describes reforestation in the Northern Ecuadorian Amazon (NEA) using 2002 remotely sensed Hyperion images and 2001 Ikonos images. Open access copy available |
The Causes of the Reforestation in VietnambackgroundWood exploitation and agricultural expansion led to large-scale deforestation in Vietnam. Since the mid-1990s, forest cover in many areas has increased both in the form of natural regeneration and tree plantations. Policies such as the 1993 Land Law offered households rights to forestland and tree planting campaigns such as the Five Million Hectare Reforestation Programme made people responsible for owning and protecting forest land. Available with subscription or purchase |
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 |
