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Marcelo Rodrigues Barbosa Júnior, Danilo Tedesco, Vinicius dos Santos Carreira, Antonio Alves Pinto, Bruno Rafael de Almeida Moreira, Luciano Shozo Shiratsuchi, Cristiano Zerbato and Rouverson Pereira da Silva
Remote sensing can provide useful imagery data to monitor sugarcane in the field, whether for precision management or high-throughput phenotyping (HTP). However, research and technological development into aerial remote sensing for distinguishing cultiva...
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Banteamlak Kase Abebe, Fasikaw Atanaw Zimale, Kidia Kessie Gelaye, Temesgen Gashaw, Endalkachew Goshe Dagnaw and Anwar Assefa Adem
In most developing countries, biophysical data are scarce, which hinders evidence-based watershed planning and management. To use the scarce data for resource development applications, special techniques are required. Thus, the primary goal of this study...
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Venkataramana Sridhar, Syed Azhar Ali and David J. Sample
The Mekong River Basin is one of the world?s major transboundary basins. The hydrology, agriculture, ecology, and other watershed functions are constantly changing as a result of a variety of human activities carried out inside and by neighboring countri...
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Deyong Hu, Manqing Liu, Yufei Di, Chen Yu and Yichen Wang
Urban 3D surface reflectance is a critical parameter for the modeling of surface biophysical processes. It is of great significance to enhance the accuracy of reflectance in urban areas. Based on the urban solar radiative transfer (USRT) model, this stud...
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Ruiting Zhai, Chuanrong Zhang, Weidong Li, Xiang Zhang and Xueke Li
Understanding the driving forces of land use/cover change (LUCC) is a requisite to mitigate and manage effects and consequences of LUCC. This study aims to analyze drivers of LUCC in New England, USA. It combines meta-study, GIS, and machine learning to ...
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Huihui Mao, Jihua Meng, Fujiang Ji, Qiankun Zhang and Huiting Fang
Leaf area index (LAI) is a crucial crop biophysical parameter that has been widely used in a variety of fields. Five state-of-the-art machine learning regression algorithms (MLRAs), namely, artificial neural network (ANN), support vector regression (SVR)...
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Pengfei Xue, David J Schwab, Xing Zhou, Chenfu Huang, Ryan Kibler and Xinyu Ye
Current numerical methods for simulating biophysical processes in aquatic environments are typically constructed in a grid-based Eulerian framework or as an individual-based model in a particle-based Lagrangian framework. Often, the biogeochemical proces...
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Amy L. Steimke, Bangshuai Han, Jodi S. Brandt and Alejandro N. Flores
Hydrologic scientists and water resource managers often focus on different facets of flow regimes in changing climates. The objective of this work is to examine potential hydrological changes in the Upper Boise River Basin, Idaho, USA in the context of b...
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Kevin Thellmann, Sergey Blagodatsky, Inga Häuser, Hongxi Liu, Jue Wang, Folkard Asch, Georg Cadisch and Marc Cotter
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Meng Xia and Long Jiang
To provide insightful information on water quality management, it is crucial to improve the understanding of the complex biogeochemical cycles of Chesapeake Bay (CB), so a three-dimensional unstructured grid-based water quality model (ICM based on the fi...
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