scholarly journals Airborne Position and Orientation System for Aerial Remote Sensing

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Jianli Li ◽  
Jiancheng Fang ◽  
Zhaoxing Lu ◽  
Lijian Bai
Keyword(s):  
Remote Sensing ◽  
Time Synchronization ◽  
Imaging System ◽  
Estimation Method ◽  
Vital Role ◽  
Error Modeling ◽  
Initial Alignment ◽  
Reference Information ◽  
Orientation System ◽  
Aerial Remote Sensing

The airborne Position Orientation System (POS) can accurately measure space-time reference information and plays a vital role in aerial remote sensing system. It may be applied in a direct georeference system for optical camera and a motion imaging system for Synthetic Aperture Radar (SAR), which further advances efficiency and quality of imaging sensors. In this paper, the operation principle and components of airborne POS are introduced. Some key technologies of airborne POS are summarized. They include the error calibration and compensation, initial alignment, lever arm error modeling, time synchronization, and integrated estimation method. A high precision airborne POS has been developed and applied to a variety of aerial remote sensing systems.

scholarly journals Research on the Gravity Disturbance Compensation Terminal for High-Precision Position and Orientation System

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4932
Author(s):  
Zhuangsheng Zhu ◽  
Hao Tan ◽  
Yue Jia ◽  
Qifei Xu
Keyword(s):  
Remote Sensing ◽  
Real Time ◽  
High Precision ◽  
Gravity Data ◽  
Flight Test ◽  
Disturbance Compensation ◽  
Gravity Disturbance ◽  
Orientation System ◽  
Aerial Remote Sensing ◽  
Position And Orientation

The Position and Orientation System (POS) is the core device of high-resolution aerial remote sensing systems, which can obtain the real-time object position and collect target attitude information. The goal of exceeding 0.015°/0.003° of its real-time heading/attitude measurement accuracy is unlikely to be achieved without gravity disturbance compensation. In this paper, a high-precision gravity data architecture for gravity disturbance compensation technology is proposed, and a gravity database with accuracy better than 1 mGal is constructed in the test area. Based on the “Block-Time Variation” Markov Model (B-TV-MM), a gravity disturbance compensation device is developed. The gravity disturbance compensation technology is applied to POS products for the first time, and is applied in the field of aerial remote sensing. Flight test results show that the heading accuracy and attitude accuracy of POS products are improved by at least 6% and 16%, respectively. The device can be used for the gravity disturbance compensation of various inertial technology products.

Machine learning-based crop recognition from aerial remote sensing imagery

2021 ◽  
Vol 15 (1) ◽  
pp. 54-69
Author(s):  
Yanqin Tian ◽  
Chenghai Yang ◽  
Wenjiang Huang ◽  
Jia Tang ◽  
Xingrong Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Remote Sensing ◽  
Remote Sensing Imagery ◽  
Aerial Remote Sensing

scholarly journals Multi-Scene Building Height Estimation Method Based on Shadow in High Resolution Imagery

2021 ◽  
Vol 13 (15) ◽  
pp. 2862
Author(s):  
Yakun Xie ◽  
Dejun Feng ◽  
Sifan Xiong ◽  
Jun Zhu ◽  
Yangge Liu
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Estimation Method ◽  
Absolute Error ◽  
Large Error ◽  
Estimation Methods ◽  
Height Estimation ◽  
Building Height ◽  
Remote Sensing Imagery ◽  
High Resolution Imagery

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m-3.76 m, which can achieve high-precision estimation of building height.

scholarly journals Precise Estimation of NDVI with a Simple NIR Sensitive RGB Camera and Machine Learning Methods for Corn Plants

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3208 ◽  
Author(s):  
Liangju Wang ◽  
Yunhong Duan ◽  
Libo Zhang ◽  
Tanzeel U. Rehman ◽  
Dongdong Ma ◽  
...  
Keyword(s):  
Machine Learning ◽  
Professional Training ◽  
Imaging System ◽  
Estimation Method ◽  
Machine Learning Algorithms ◽  
Plant Phenotyping ◽  
Band Pass Filter ◽  
Pass Filter ◽  
Corn Plants ◽  
Hyperspectral Camera

The normalized difference vegetation index (NDVI) is widely used in remote sensing to monitor plant growth and chlorophyll levels. Usually, a multispectral camera (MSC) or hyperspectral camera (HSC) is required to obtain the near-infrared (NIR) and red bands for calculating NDVI. However, these cameras are expensive, heavy, difficult to geo-reference, and require professional training in imaging and data processing. On the other hand, the RGBN camera (NIR sensitive RGB camera, simply modified from standard RGB cameras by removing the NIR rejection filter) have also been explored to measure NDVI, but the results did not exactly match the NDVI from the MSC or HSC solutions. This study demonstrates an improved NDVI estimation method with an RGBN camera-based imaging system (Ncam) and machine learning algorithms. The Ncam consisted of an RGBN camera, a filter, and a microcontroller with a total cost of only $70 ~ 85. This new NDVI estimation solution was compared with a high-end hyperspectral camera in an experiment with corn plants under different nitrogen and water treatments. The results showed that the Ncam with two-band-pass filter achieved high performance (R2 = 0.96, RMSE = 0.0079) at estimating NDVI with the machine learning model. Additional tests showed that besides NDVI, this low-cost Ncam was also capable of predicting corn plant nitrogen contents precisely. Thus, Ncam is a potential option for MSC and HSC in plant phenotyping projects.

LAI Retrieval Based on PROSPECT-SAILH Model from Multi-Angular Data of WiDAS Imaging System

2012 ◽  
Vol 518-523 ◽  
pp. 5697-5703
Author(s):  
Zhao Yan Liu ◽  
Ling Ling Ma ◽  
Ling Li Tang ◽  
Yong Gang Qian
Keyword(s):  
Remote Sensing ◽  
Imaging System ◽  
Remote Sensing Data ◽  
Canopy Reflectance ◽  
Area Index ◽  
Sensing Data ◽  
Spectral Bands ◽  
Sensing Technology ◽  
Leaf Optical Properties ◽  
Angular Data

The aim of this study is to assess the capability of estimating Leaf Area Index (LAI) from high spatial resolution multi-angular Vis-NIR remote sensing data of WiDAS (Wide-Angle Infrared Dual-mode Line/Area Array Scanner) imaging system by inverting the coupled radiative transfer models PROSPECT-SAILH. Based on simulations from SAILH canopy reflectance model and PROSPECT leaf optical properties model, a Look-up Table (LUT) which describes the relationship between multi-angular canopy reflectance and LAI has been produced. Then the LAI can be retrieved from LUT by directly matching canopy reflectance of six view directions and four spectral bands with LAI. The inversion results are validated by field data, and by comparing the retrieval results of single-angular remote sensing data with multi-angular remote sensing data, we can found that the view angle takes the obvious impact on the LAI retrieval of single-angular data and that high accurate LAI can be obtained from the high resolution multi-angular remote sensing technology.

Generating population census data through aerial remote sensing

1994 ◽  
Vol 22 (3) ◽  
pp. 131-138 ◽  
Author(s):  
R. C. S. Taragi ◽  
K. S. Bisht ◽  
B. S. Sokhi
Keyword(s):  
Remote Sensing ◽  
Census Data ◽  
Population Census ◽  
Aerial Remote Sensing
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