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Displaying 501 - 505 of 662Land cover in Upper Egypt assessed using regional and global land-cover products derived from MODIS imagery
Irrigation along the Nile River has resulted in dramatic changes in the biophysical environment of Upper Egypt. In this study we used a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m Normalized Difference Vegetation Index data and Landsat imagery to identify areas that changed from 2001 to 2008 as a result of irrigation and water-level fluctuations in the Nile River and nearby waterbodies.
comparative analysis of spatial indices and wavelet-based classification
Spatial indices measure the geometric arrangement of land use and land cover classes at various scales and are computationally adaptive with wavelet transform coefficients. Decision rules built on permutations of three spatial indices – energy, log energy and Shannon's diversity – are used to improve the accuracy of multi-resolution hierarchical wavelet-based classifications. Comparisons are made with classification results derived from other texture measures, as well as with classification results calculated from more conventional per-pixel techniques.
Farmers' perception of coconut mite damage and crop diversification alternatives in the coastal belt of Tanzania
This article analysed farmers' perceptions of the effects of coconut mite in their livelihood and assessed crop diversification as a copping strategy for reduced coconut production. A socio-economic model of farmers' decisions on intercropping as an indicator for overall crop diversity was developed. The study was conducted between November 2009 and March 2010 in five districts in Tanzania, which were selected on the basis of the coconut's economic importance, using structured questionnaires which were administered to 200 household heads.
Multi-scale object-based image analysis and feature selection of multi-sensor earth observation imagery using random forests
The random forest (RF) classifier is a relatively new machine learning algorithm that can handle data sets with large numbers and types of variables. Multi-scale object-based image analysis (MOBIA) can generate dozens, and sometimes hundreds, of variables used to classify earth observation (EO) imagery. In this study, a MOBIA approach is used to classify the land cover in an area undergoing intensive agricultural development. The information derived from the elevation data and imagery from two EO satellites are classified using the RF algorithm.
Regional spatial pattern of deep soil water content and its influencing factors
Plant root systems can utilize soil water to depths of 10 m or more. Spatial pattern data of deep soil water content (SWC) at the regional scale are scarce due to the labour and time constraints of field measurements. We measured gravimetric deep SWC (DSWC) at depths of 200, 300, 400, 500, 600, 800 and 1000 cm at 382 sites across the Loess Plateau, China. The coefficient of variation was high for soil water content (SWC) in the horizontal direction (48%), but was relatively small for SWC in the vertical direction (9%).