Studying Olive Trees Age دراسة عمر أشجار الزيتون
| dc.contributor.author | ميسره عوده | |
| dc.contributor.author | رؤى بري | |
| dc.contributor.author | حيدر دياب | |
| dc.date.accessioned | 2025-01-26T10:44:18Z | |
| dc.date.available | 2025-01-26T10:44:18Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | The age and spatial distribution of olive trees play a crucial role in resource management, environmental monitoring, and agricultural productivity. Remote sensing techniques, such as the Normalized Difference Vegetation Index (NDVI), drones, and LIDAR technology, provide valuable insights into these factors. Understanding the age and distribution of olive trees aids farmers and land managers in optimizing resource allocation, improving yield estimation, and planning future planting efforts. Moreover, remote sensing helps monitor environmental changes, detect early signs of pest infestations or diseases, and assess the impact of climate change on agricultural landscapes. These techniques also support government agencies and policymakers in formulating effective agricultural policies and promoting sustainable farming practices. Utilizing remote sensing for olive tree analysis enhances cultivation practices, ensures food security, and contributes to environmental conservation. The study employs drones to capture aerial images and LIDAR technology for comprehensive surveys, comparing results to determine olive tree age and estimate productivity. This non-invasive approach offers an efficient method for farmers and researchers to manage olive groves and make informed decisions, ultimately improving agricultural efficiency and sustainability. | |
| dc.identifier.uri | https://hdl.handle.net/20.500.11888/19842 | |
| dc.language.iso | en | |
| dc.supervisor | يوسف دعمه | |
| dc.supervisor | سامر مياله | |
| dc.title | Studying Olive Trees Age دراسة عمر أشجار الزيتون |