Planning the mission of an Earth remote sensing spacecraft based on open source data

2019 ◽  
Author(s):  
M.P. Zapletin ◽  
A.T. Zhakypov
Keyword(s):  
Remote Sensing ◽  
Programming Languages ◽  
Web Application ◽  
Region Of Interest ◽  
Earth Remote Sensing ◽  
Non Profit ◽  
Open Source Data ◽  
Source Data ◽  
Remote Sensing Satellite ◽  
Computational Part

The paper introduces a non-profit program designed to improve the efficiency in the study of the Earth’s surface. The program is designed to build the orbit of an Earth remote sensing satellite, to evaluate the plan and the possibilities of surveying a region of interest on the Earth's surface. Using this program, the user can visualize the orbit of any available commercial Earth remote sensing satellite in the required period of time, evaluate and plan a survey of the certain area by a specific spacecraft. The computational part of the program is based on the SGP4 model, which uses publicly available TLE data for Earth remote sensing satellites, on spherical trigonometry formulas and heuristic methods of computational shortcut. The program is implemented as a web application in the programming languages JavaScript and PHP using the Bootstrap, JQuery and Cesium libraries.

On optimization of attitude control programs for earth remote sensing satellite

2014 ◽  
Vol 5 (2) ◽  
pp. 90-97 ◽  
Author(s):  
Yu. N. Gorelov ◽  
L. V. Kurganskaya ◽  
A. I. Manturov ◽  
A. V. Sollogub ◽  
V. E. Yurin
Keyword(s):  
Remote Sensing ◽  
Attitude Control ◽  
Earth Remote Sensing ◽  
Control Programs ◽  
Remote Sensing Satellite

scholarly journals One-Class Classification of Natural Vegetation Using Remote Sensing: A Review

2021 ◽  
Vol 13 (10) ◽  
pp. 1892
Author(s):  
Sébastien Rapinel ◽  
Laurence Hubert-Moy
Keyword(s):  
Remote Sensing ◽  
Natural Vegetation ◽  
Open Source Data ◽  
Source Data ◽  
Good Classification ◽  
Long Term Monitoring ◽  
One Class Classification ◽  
Term Monitoring

Advances in remote sensing (RS) technology in recent years have increased the interest in including RS data into one-class classifiers (OCCs). However, this integration is complex given the interdisciplinary issues involved. In this context, this review highlights the advances and current challenges in integrating RS data into OCCs to map vegetation classes. A systematic review was performed for the period 2013–2020. A total of 136 articles were analyzed based on 11 topics and 30 attributes that address the ecological issues, properties of RS data, and the tools and parameters used to classify natural vegetation. The results highlight several advances in the use of RS data in OCCs: (i) mapping of potential and actual vegetation areas, (ii) long-term monitoring of vegetation classes, (iii) generation of multiple ecological variables, (iv) availability of open-source data, (v) reduction in plotting effort, and (vi) quantification of over-detection. Recommendations related to interdisciplinary issues were also suggested: (i) increasing the visibility and use of available RS variables, (ii) following good classification practices, (iii) bridging the gap between spatial resolution and site extent, and (iv) classifying plant communities.

Cameras for the EROS Earth remote sensing satellite constellation

1999 ◽  
Author(s):  
Jeremy M. Topaz ◽  
Ilan Porat ◽  
Avigdor Blasberger ◽  
David Stavitsky ◽  
Dov Freiman
Keyword(s):  
Remote Sensing ◽  
Earth Remote Sensing ◽  
Satellite Constellation ◽  
Remote Sensing Satellite

GIS, Remote Sensing, and Landscape Archaeology

2017 ◽  
Author(s):  
Sarah H. Parcak
Keyword(s):  
Remote Sensing ◽  
Satellite Remote Sensing ◽  
Ethical Issues ◽  
Landscape Archaeology ◽  
Archaeological Site ◽  
Light Detection And Ranging ◽  
Future Prospects ◽  
Gis And Remote Sensing ◽  
Open Source Data ◽  
Source Data

This chapter examines a number of current practices relating to the use of geographic information systems (GIS) and remote sensing, including developments in LiDAR (Light Detection and Ranging) in landscape archaeology. It explains landscape archaeology and what it encompasses; whether remote sensing and GIS are a formal part of landscape archaeology; whether GIS and remote sensing are the same or completely different subfields; and whether remote sensing covers both satellite and ground-based remote sensing. Also discussed are challenges faced by archaeologists with regards to the application of landscape archaeology. The article also considers the applications of ground-based remote sensing, GIS, photogrammetry, satellite remote sensing, and LiDAR in landscape archaeology; ethical issues in landscape archaeology; the problem of archaeological site looting; the use of open source data; and citizen science approaches to landscape archaeology. Finally, it reflects on the future prospects for landscape archaeology.

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