Page 82 - รายงานการประยุกต์ใช้ฐานข้อมูลการสำรวจระยะไกลจากซอฟต์แวร์รหัสเปิดและคลาวด์คอมพิวติงเพื่องานพัฒนาที่ดิน Utilization of Remote Sensing Database derived from Open-source software and Cloud computing platform for Land Development

ห้องสมุดกรมพัฒนาที่ดิน

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Hird, J.N., E. R. DeLancey, G. J. McDermid, and J. Kariyeva. 2017. Google Earth Engine,
Open-Access Satellite Data, and Machine Learning in Support of Large-
Area Probabilistic Wetland Mapping. Remote Sensing. 9, no. 12: 1315.
Available Source: https://doi.org/10.3390/rs9121315, February 2023, 09.

Htitiou, A., A. Boudhar, Y. Lebrini, R. Hadria, H Lionboui, L. Elmansouri, B. Tychon, T. Benabdelouahab.

2019. The Performance of Random Forest Classification Based on Phenological Metrics
Derived from Sentinel-2 and Landsat 8 to Map Crop Cover in an Irrigated Semi-arid
Region. Remote Sensing in Earth Systems Sciences. Available souse:
https://doi.org/10.1007/s41976-019-00023-9, April 10, 2022.

Horning, N., P. T. McPhearson, and O. C. Wallace. n.d. An Introduction to Remote Sensing.

https://www.academia.edu/12190786/An_Introduction_to_Remote_Sensing

Huth, Juliane, C. Kuenzer, T. Wehrmann, S. Gebhardt, V. Q. Tuan, and S. Dech. 2012.
Land Cover and Land Use Classification with TWOPAC: towards
Automated Processing for Pixel- and Object-Based Image Classification.

Remote Sens. 4 (9) p. 2530-255. https://doi.org/ 10.3390/rs4092530
Indian Agricultural Statistics Research Institute. 2014. Lesson 12 Image Classification.

Available Source: http://ecoursesonline.iasri.res.in/mod/page/view.php?id=2065,
December 2022, 10.

Jensen, J.R. 2000. Remote Sensing of Environment: An Earth Resource Perspective
Second edition. Pearson Education, Inc. Upper Saddle River, NJ, USA. 592p.

Khan, M. A. and F. UrRehman. 2012. Free and Open Source Software: Evolution,

Benefits and Characteristics. International Journal of Emerging Trends &
Technology in Computer Science (IJETTCS) Volume 1, Issue 3. Available Source:
09.https://www.researchgate.net/ publication/2560883, February 2023, 15

Kulo, Nedim. 2018. Benefits of the Remote Sensing Data Integration. Department of
Geodesy and Geoinformatics, Faculty of Civil Engineering University of Sarajevo,

Sarajevo, BOSNIA AND HERZEGOVINA.
https://www.researchgate.net/publication/329443299

Liaghat, S. and S.K. Balasundram, 2010. A Review: The Role of Remote Sensing in
Precision Agriculture. Am. J. Agric. Biol. Sci. 5, 50-55.