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Full-Text Articles in Plant Sciences
An Accurate Vegetation And Non-Vegetation Differentiation Approach Based On Land Cover Classification, Chiman Kwan, David Gribben, Bulent Ayhan, Jiang Li, Sergio Bernabe, Antonio Plaza
An Accurate Vegetation And Non-Vegetation Differentiation Approach Based On Land Cover Classification, Chiman Kwan, David Gribben, Bulent Ayhan, Jiang Li, Sergio Bernabe, Antonio Plaza
Electrical & Computer Engineering Faculty Publications
Accurate vegetation detection is important for many applications, such as crop yield estimation, landcover land use monitoring, urban growth monitoring, drought monitoring, etc. Popular conventional approaches to vegetation detection incorporate the normalized difference vegetation index (NDVI), which uses the red and near infrared (NIR) bands, and enhanced vegetation index (EVI), which uses red, NIR, and the blue bands. Although NDVI and EVI are efficient, their accuracies still have room for further improvement. In this paper, we propose a new approach to vegetation detection based on land cover classification. That is, we first perform an accurate classification of 15 or more …
Long-Term Ndvi And Recent Vegetation Cover Profiles Of Major Offshore Island Nesting Sites Of Sea Turtles In Saudi Waters Of The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Hesham El-Askary, Ace Vincent B. Flandez, Joshua J. Dagoy, Joselito Francis A. Alcaria, Abdullajid U. Basali, Khaled A. Al-Abdulkader, Ronald A. Loughland, Mohamed A. Qurban
Long-Term Ndvi And Recent Vegetation Cover Profiles Of Major Offshore Island Nesting Sites Of Sea Turtles In Saudi Waters Of The Northern Arabian Gulf, Rommel H. Maneja, Jeffrey D. Miller, Wenzhao Li, Hesham El-Askary, Ace Vincent B. Flandez, Joshua J. Dagoy, Joselito Francis A. Alcaria, Abdullajid U. Basali, Khaled A. Al-Abdulkader, Ronald A. Loughland, Mohamed A. Qurban
Mathematics, Physics, and Computer Science Faculty Articles and Research
Vegetation is an important ecological component of offshore islands in the Arabian Gulf (AG), which maintains long-term resilience of these islands. This is achieved by influencing sediment retention and moisture acquisition via condensation during periods of high humidity and by providing a variety of microhabitats for island fauna. The resilience of offshore islands’ ecosystems in the Saudi waters is important because they host the largest number of nesting hawksbill and green turtles in the AG. This study defines the characteristics and the long-term trends in vegetation cover of the offshore islands used by sea turtles as nesting grounds in the …
Vegetation Detection Using Deep Learning And Conventional Methods, Bulent Ayhan, Chiman Kwan, Bence Budavari, Liyun Kwan, Yan Lu, Daniel Perez, Jiang Li, Dimitrios Skarlatos, Marinos Vlachos
Vegetation Detection Using Deep Learning And Conventional Methods, Bulent Ayhan, Chiman Kwan, Bence Budavari, Liyun Kwan, Yan Lu, Daniel Perez, Jiang Li, Dimitrios Skarlatos, Marinos Vlachos
Electrical & Computer Engineering Faculty Publications
Land cover classification with the focus on chlorophyll-rich vegetation detection plays an important role in urban growth monitoring and planning, autonomous navigation, drone mapping, biodiversity conservation, etc. Conventional approaches usually apply the normalized difference vegetation index (NDVI) for vegetation detection. In this paper, we investigate the performance of deep learning and conventional methods for vegetation detection. Two deep learning methods, DeepLabV3+ and our customized convolutional neural network (CNN) were evaluated with respect to their detection performance when training and testing datasets originated from different geographical sites with different image resolutions. A novel object-based vegetation detection approach, which utilizes NDVI, computer …
Using An Active-Optical Sensor To Develop An Optimal Ndvi Dynamic Model For High-Yield Rice Production (Yangtze, China), Xiaojun Liu, Richard B. Ferguson, Hengbiao Zheng, Qiang Cao, Yongchao Tian, Weixing Cao, Yan Zhu
Using An Active-Optical Sensor To Develop An Optimal Ndvi Dynamic Model For High-Yield Rice Production (Yangtze, China), Xiaojun Liu, Richard B. Ferguson, Hengbiao Zheng, Qiang Cao, Yongchao Tian, Weixing Cao, Yan Zhu
Department of Agronomy and Horticulture: Faculty Publications
The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model …