The agricultural sector in the Jordan Valley plays an important role in the economic system and that the region is essentially Jordan's food basket. The adoption of sustainable agricultural practices is widely recognized as essential to ensure agricultural sustainability. This study analyzed factors influencing citrus farmer's adoption of sustainable agricultural practices (SAPs) in the Northern Ghor of Jordan valley. The study used a quantitative approach. Simple random sampling was adopted to select 115 farmers in the study area. A multiple regression analysis was applied to identify factors influencing the sustainability of citrus farming practices. The study found that the largest proportion 44.4% of the citrus farmers had a fairly high adoption rate of SAPs while 13.0% of ones had high adoption of SAPs. In addition, the study revealed that age of farmer, Farm experience, primary education, and tertiary education were factors that affected farmers SAPs adoption. Policy recommendations are proposed to enhance the implementation of sustainable agriculture practices by the citrus farmers in the Northern Ghor of Jordan valley.
Representing the Earth’s physical features onto a flat surface is a critical and challenging issue for geodesists to build topographic mappings at field scale in various applications. Artificial satellite positioning data are currently defined on a global geocentric frame, while terrestrial geodetic networks are determined on a local ellipsoid. Hence, coordinate transformations in three-dimensional space are required for data fusion involving different coordinate systems utilizing common points in two sets of coordinates. On the other hand, small companies in many developing countries have some data conversion difficulties due to the need for high-cost software and qualified persons. A low-cost automated tool is helpful in achieving this task and ensuring quality and positional accuracy. In this investigation, the problem was undertaken by establishing a software tool in the Microsoft Visual Studio environment for map-matching with global coordinates based on similarity transformations and a conformal polynomial approach. The tool’s performance was evaluated through a numerical example to assign transformation parameters and derive coordinates of checkpoints from the prediction surface.
The adoption of sustainable agricultural practices is widely recognized as essential to ensure agricultural sustainability. This study analyzed factors influencing citrus farmers adoption of sustainable agricultural practices (SAPs) in the Northern Ghor of Jordan valley. The study used a quantitative approach. Simple random sampling was adopted to select 115 farmers in the study area. The study found that the largest proportion 44.4% of the citrus farmers had a fairly high adoption rate of SAPs while 13.0% of ones had high adoption of SAPs. In addition, the study revealed that age was the significant variable that positively influences farmers SAPs adoption, while experience, primary education, and tertiary education have a negative influence on the adoption of SAPs. The study recommends that special attention be given to older farmers to exploit their skills and receptive to implementing SAPs, encourage and guide farmers toward implementing sustainable agriculture techniques and suitable inputs by providing premium and incentive payments to them, and take deterrent penalties against farmers who using inappropriate and harmful applications, or who do not use appropriate applications.
This paper investigates multi-temporal land surface temperature (LST) for large ungauged areas of Ma’an Governorate, Jordan, based on changes in normalized difference vegetation index (NDVI) using remotely sensed data. Five mosaic images were taken for both the 1990 and 2018 years by Landsat 5 (TM) and Landsat 8 (OLI) (path/row, 174/36- 174/37). These were used as the basic data source, where most of Ma’an Governorate has no meteorological stations. The five-mosaic images for both Landsat 5 and Landsat 8-OLI were taken in September. LST and NDVI maps have been generated to determine the changes in LTS during the monitoring period. The results showed that the minimum value of LST increased by 4°C, and the mean surface temperature increased nearly by 2°C between 1990 and 2018. The average LST has been rising at a rate of 0.071°C/y.
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