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Displaying 401 - 405 of 661How Could Carbon Credits for Reducing Deforestation Compete with Returns from Palm Oil: A Proposal for a More Flexible REDD Valuation Tool
In order for carbon credits awarded for reducing emissions from deforestation and degradation of forests (REDD) to be effective, they need to be competitive with alternative land uses. In the case of Southeast Asia, oil palm cultivation is one of the most lucrative possible land uses. Existing mechanisms for awarding certified emission reductions (CERs) might not be adequately flexible to changing commodity prices or to meet the needs of landowners who heavily discount future returns from their land.
soil moisture assimilation scheme based on the microwave Land Emissivity Model and the Community Land Model
Applications of microwave remote-sensing data in land data assimilation are a topic of current interest and importance due to their high temporal and spatial resolution and availability. However, there have been few studies on land surface sub-grid scale heterogeneity and calculating microwave wetland surface emissivity when directly assimilating gridded Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) satellite brightness temperature (BT) data to estimate soil moisture.
Spatially adaptive smoothing parameter selection for Markov random field based sub-pixel mapping of remotely sensed images
Sub-pixel mapping is a process to provide the spatial distributions of land cover classes with finer spatial resolution than the size of a remotely sensed image pixel. Traditional Markov random field-based sub-pixel mapping (MRF_SPM) adopts a fixed smoothing parameter estimated based on the entire image to balance the spatial and spectral energies. However, the spectra of the remotely sensed pixels are always spatially variable.
super-resolution mapping method using local indicator variograms
Super-resolution mapping (SRM) is a recently developed research task in the field of remotely sensed information processing. It provides the ability to obtain land-cover maps at a finer scale using relatively low-resolution images. Existing algorithms based on indicator geostatistics and downscaling cokriging offer an SRM approach using spatial structure models derived from real data. In this article, a novel SRM method is developed based on a sequentially produced with local indicator variogram (SLIV) SRM model.
Mapping seasonal trends in vegetation using AVHRR-NDVI time series in the Yucatán Peninsula, Mexico
This research examines the spatio-temporal trends in Advanced Very High Resolution Radiometer (AVHRR) Global Inventory Modelling and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) time series to ascribe land use change and precipitation to observed changes in land cover from 1982 to 2007 in the Mexican Yucatán Peninsula, using seasonal trend analysis (STA).