NEON: the first continental-scale ecological observatory with airborne remote sensing of vegetation canopy biochemistry and structure

2009 ◽  
Author(s):  
Brian R. Johnson ◽  
Thomas U. Kampe ◽  
Michele A. Kuester ◽  
Michael Keller
Keyword(s):  
Remote Sensing ◽  
Vegetation Canopy ◽  
Airborne Remote Sensing ◽  
Continental Scale

Characterizing Vegetation Canopy Structure Using Airborne Remote Sensing Data

2017 ◽  
Vol 55 (2) ◽  
pp. 1160-1178 ◽  
Author(s):  
Debsunder Dutta ◽  
Kunxuan Wang ◽  
Esther Lee ◽  
Allison Goodwell ◽  
Dong Kook Woo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Canopy Structure ◽  
Remote Sensing Data ◽  
Vegetation Canopy ◽  
Airborne Remote Sensing ◽  
Sensing Data

scholarly journals Extensive Evaluation of a Continental-Scale High-Resolution Hydrological Model Using Remote Sensing and Ground-Based Observations

2021 ◽  
Vol 13 (7) ◽  
pp. 1247
Author(s):  
Bowen Zhu ◽  
Xianhong Xie ◽  
Chuiyu Lu ◽  
Tianjie Lei ◽  
Yibing Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hydrological Modeling ◽  
Infiltration Capacity ◽  
Modeling Framework ◽  
Large Domain ◽  
Continental Scale ◽  
Extensive Evaluation ◽  
Mean Differences ◽  
Fine Resolution

Extreme hydrologic events are getting more frequent under a changing climate, and a reliable hydrological modeling framework is important to understand their mechanism. However, existing hydrological modeling frameworks are mostly constrained to a relatively coarse resolution, unrealistic input information, and insufficient evaluations, especially for the large domain, and they are, therefore, unable to address and reconstruct many of the water-related issues (e.g., flooding and drought). In this study, a 0.0625-degree (~6 km) resolution variable infiltration capacity (VIC) model developed for China from 1970 to 2016 was extensively evaluated against remote sensing and ground-based observations. A unique feature in this modeling framework is the incorporation of new remotely sensed vegetation and soil parameter dataset. To our knowledge, this constitutes the first application of VIC with such a long-term and fine resolution over a large domain, and more importantly, with a holistic system-evaluation leveraging the best available earth data. The evaluations using in-situ observations of streamflow, evapotranspiration (ET), and soil moisture (SM) indicate a great improvement. The simulations are also consistent with satellite remote sensing products of ET and SM, because the mean differences between the VIC ET and the remote sensing ET range from −2 to 2 mm/day, and the differences for SM of the top thin layer range from −2 to 3 mm. Therefore, this continental-scale hydrological modeling framework is reliable and accurate, which can be used for various applications including extreme hydrological event detections.

scholarly journals Airborne remote sensing applications to coastal wave research

1998 ◽  
Vol 103 (C9) ◽  
pp. 18791-18800 ◽  
Author(s):  
Paul A. Hwang ◽  
Edward J. Walsh ◽  
William B. Krabill ◽  
Robert N. Swift ◽  
Serdar S. Manizade ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Airborne Remote Sensing ◽  
Sensing Applications ◽  
Wave Research ◽  
Remote Sensing Applications

scholarly journals Extrinsic Parameters Calibration Method of Cameras with Non-Overlapping Fields of View in Airborne Remote Sensing

2018 ◽  
Vol 10 (8) ◽  
pp. 1298 ◽  
Author(s):  
Lei Yin ◽  
Xiangjun Wang ◽  
Yubo Ni ◽  
Kai Zhou ◽  
Jilong Zhang
Keyword(s):  
Remote Sensing ◽  
Camera Calibration ◽  
Calibration Method ◽  
Optimization Method ◽  
Airborne Remote Sensing ◽  
Camera System ◽  
Translation Error ◽  
Camera Systems ◽  
Calibration Methods ◽  
Extrinsic Parameters

Multi-camera systems are widely used in the fields of airborne remote sensing and unmanned aerial vehicle imaging. The measurement precision of these systems depends on the accuracy of the extrinsic parameters. Therefore, it is important to accurately calibrate the extrinsic parameters between the onboard cameras. Unlike conventional multi-camera calibration methods with a common field of view (FOV), multi-camera calibration without overlapping FOVs has certain difficulties. In this paper, we propose a calibration method for a multi-camera system without common FOVs, which is used on aero photogrammetry. First, the extrinsic parameters of any two cameras in a multi-camera system is calibrated, and the extrinsic matrix is optimized by the re-projection error. Then, the extrinsic parameters of each camera are unified to the system reference coordinate system by using the global optimization method. A simulation experiment and a physical verification experiment are designed for the theoretical arithmetic. The experimental results show that this method is operable. The rotation error angle of the camera’s extrinsic parameters is less than 0.001rad and the translation error is less than 0.08 mm.

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