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Displaying 136 - 140 of 661new locally-adaptive classification method LAGMA for large-scale land cover mapping using remote-sensing data
A new locally-adaptive image classification method LAGMA (Locally-Adaptive Global Mapping Algorithm) has been developed to meet requirements of land cover mapping over large areas using remote-sensing data. The LAGMA involves the grid-based supervised image classification using classes’ features estimated locally in classified pixels’ surrounding from spatially distributed reference data.
Considerations for Monitoring and Evaluating Forest Restoration
The methods and approaches selected in a restoration project depend on the degree of ecosystem degradation and on future land use plans. Programs of monitoring and evaluation must therefore compare restoration progress and effectiveness relative to untreated conditions and to target conditions, particularly with respect to the attributes and functions essential to land use objectives. It is usually not feasible to directly monitor all important forest attributes and functions, so a few indicators must be selected.
Assessing the impact of land cover map resolution and geolocation accuracy on evapotranspiration simulations by a land surface model
The land surface models used in numerical weather forecasts and hydrological applications rely on the accuracy of land cover maps available from satellite remote sensing to simulate the energy and water balance at the surface of the Earth. While the impact of classification accuracy on land surface simulations has already been reported, little attention has been paid on the consequences of land cover map uncertainty driven by geolocation accuracy.
Environmental Risk Assessment of Dams by Using Multi-Criteria Decision-Making Methods: A Case Study of the Polrood Dam, Guilan Province, Iran
A dam's construction always imposes some risks to the environment. In this article, the environmental risks of the Polrood dam, located in a northern province of Iran, during its construction phase, were identified, ranked, and evaluated. The risk factors were initially identified by Delphi questionnaire and then rated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Subsequently, the Analytical Hierarchy Process (AHP) was applied to classify the risk factors into four major categories, and Expert Choice software was used to weight them.
Linking Farmers’ Knowledge, Farming Strategies, and Consequent Cultivation Patterns into the Identification of Healthy Agroecosystem Characteristics at Local Scales
In order to identify sustainable management solutions for small-scale farmer agroecosystems, a better understanding of these dynamic forest–farmland systems, existing farming and forestry strategies, and farmer perspectives is important. We examined the relationship between agricultural land use patterns and farmers’ practices and identified existing and potential characteristics of healthy agroecosystems at local scale in the context of village communities in Zanzibar, Tanzania.