Research Interests:
Research Interests:
Research Interests:
Research Interests:
Engineering, Geography, Decision Making, Fuzzy Logic, Decision Analysis, and 14 moreTime Use, Pure Mathematics, Entropy, Information Processing, Uncertainty, Variance, Case Study, Membership Function, Fuzzy System, Fuzzy Set, Fuzzy Sets and Systems, Condition Factor, Fuzzy Membership Function, and Entropie
Research Interests:
DAWSON ET AL. 573 alder had poplar heights comparable with those ob-tained from optimal rates of ammonium nitrate fertil-ization. The greatest growth of hybrid poplar occurred where alder comprised 66% of the mix and where alder rows were... more
DAWSON ET AL. 573 alder had poplar heights comparable with those ob-tained from optimal rates of ammonium nitrate fertil-ization. The greatest growth of hybrid poplar occurred where alder comprised 66% of the mix and where alder rows were directly adjacent to poplar ...
Research Interests:
This chapter provides a review of the statistical and modelling disciplines, their techniques and potential contribution to sustainable forest management,(SFM). The main topics covered are: Mensuration and models for sustainable forest... more
This chapter provides a review of the statistical and modelling disciplines, their techniques and potential contribution to sustainable forest management,(SFM). The main topics covered are: Mensuration and models for sustainable forest management,(SFM) Inventory and monitoring for forest sustainability: criteria and indicators Models of tropical forests for the conservation of biodiversity Integrating information and models across spatial and temporal scales for
Research Interests:
Research Interests:
Abstract Land use maps are widely used in modeling land use change, urban sprawl, and for other landscape related studies. A misclassification confusion matrix for land use maps is usually provided as a measure of their quality and... more
Abstract Land use maps are widely used in modeling land use change, urban sprawl, and for other landscape related studies. A misclassification confusion matrix for land use maps is usually provided as a measure of their quality and uncertainty. However, this very ...
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Research Interests:
Soil, Environmental Management, Forecasting, Environmental Monitoring, Multidisciplinary, and 16 moreParameter estimation, Soil Erosion, Nonlinear Regression, Regression Analysis, Poaceae, Spatial Distribution, Uncertainty analysis, Theoretical Models, Ecosystem, Human Activity, Conservation of Natural Resources, Vegetation Mapping, Reference Values, Off Road Vehicle, Environmental, and Motor vehicles act
Research Interests:
Research Interests:
Research Interests:
ABSTRACT When a ground and vegetation cover factor related to soil erosion is mapped with the aid of remotely sensed data, a cost-efficient sample design to collect ground data and to obtain an accurate map is required. However, the... more
ABSTRACT When a ground and vegetation cover factor related to soil erosion is mapped with the aid of remotely sensed data, a cost-efficient sample design to collect ground data and to obtain an accurate map is required. However, the supports used to collect ground data are often smaller than the desirable pixels used for mapping, which leads to complexity in developing procedures for sample design and mapping. For these purposes, a sampling and mapping method was developed by integrating stratification and an up-scaling method in geostatistics — block cokriging with Landsat Thematic Mapper imagery. This method is based on spatial correlation and stratified sampling. It scales up not only the ground sample data but also the uncertainties associated with the data aggregation from smaller supports to larger pixels or blocks. This method uses the advantages of both stratification and block cokriging variance-based sample design, which leads to sample designs with variable grid spacing, and thus significantly increases the unit cost-efficiency of sample data in sampling and mapping. This outcome was verified by the results of this study.