کامپیوترها در علوم زمین و محیط زیست ۲۰۲۱
Computers in Earth and Environmental Sciences 2021

1. Title of Book

2. Cover image

3. Title page

4. Table of Contents

5. Copyright

6. Dedication

7. Contributors

8. Acknowledgments

9. Chapter 1 Predicting dissolved oxygen concentration in river using new advanced machines learning: Long-short term memory (LSTM) deep learning

10. Chapter 2 Fractal analysis of valley sections in geological formations of arid areas

11. Chapter 3 A data-driven approach for estimating contaminants in natural water

12. Chapter 4 Application of analytical hierarchy process (AHP) in landslide susceptibility mapping for Qazvin province, N Iran

13. Chapter 5 Assessment of machine learning algorithms in land use classification

14. Chapter 6 Evaluation of land use change predictions using CA-Markov model and management scenarios

15. Chapter 7 Topographical features and soil erosion processes

16. Chapter 8 Mapping the NDVI and monitoring of its changes using Google Earth Engine and Sentinel-2 images

17. Chapter 9 Spatiotemporal urban sprawl and land resource assessment using Google Earth Engine platform in Lahore district, Pakistan

18. Chapter 10 Using OWA-AHP method to predict landslide-prone areas

19. Chapter 11 Multiscale drought hazard assessment in the Philippines

20. Chapter 12 Selection of the best pixel-based algorithm for land cover mapping in Zagros forests of Iran using Sentinel-2A data: A case study in Khuzestan province

21. Chapter 13 Identify the important driving forces on gully erosion, Chaharmahal and Bakhtiari province, Iran

22. Chapter 14 Analysis of social resilience of villagers in the face of drought using LPCIEA indicator case study: Downstream of Dorodzan dam

23. Chapter 15 Spatial and seasonal modeling of the land surface temperature using random forest

24. Chapter 16 Municipal landfill site selection and environmental impacts assessment using spatial multicriteria decision analysis: A case study

25. Chapter 17 Predictive habitat suitability models for Teucrium polium L. using boosted regression trees

26. Chapter 18 Ecoengineering practices for soil degradation protection of vulnerable hill slopes

27. Chapter 19 Soft computing applications in rainfall-induced landslide analysis and protection—Recent trends, techniques, and opportunities

28. Chapter 20 Remote sensing and machine learning techniques to monitor fluvial corridor evolution: The Aras River between Iran and Azerbaijan

29. Chapter 21 Studies on plant selection framework for soil bioengineering application

30. Chapter 22 IoT applications in landslide prediction and abatement—Trends, opportunities, and challenges

31. Chapter 23 Application of WEPP model for runoff and sediment yield simulation from ungauged watershed in Shivalik foot-hills

32. Chapter 24 Parameter estimation of a new four-parameter Muskingum flood routing model

33. Chapter 25 Predicting areas affected by forest fire based on a machine learning algorithm

34. Chapter 26 Pest-infected oak trees identify using remote sensing-based classification algorithms

35. Chapter 27 The COVID-19 crisis and its consequences for global warming and climate change

36. Chapter 28 Earthquake ionospheric and atmospheric anomalies from GNSS TEC and other satellites

37. Chapter 29 Landslide spatial modeling using a bivariate statistical method in Kermanshah Province, Iran

38. Chapter 30 Normalized difference vegetation index analysis of forest cover change detection in Paro Dzongkhag, Bhutan

39. Chapter 31 Rate of penetration prediction in drilling wells from the Hassi Messaoud oil field (SE Algeria): Use of artificial intelligence techniques and environmental implications

40. Chapter 32 Soil erodibility and its influential factors in the Middle East

41. Chapter 33 Non-carcinogenic health risk assessment of fluoride in groundwater of the River Yamuna flood plain, Delhi, India

42. Chapter 34 Digital soil mapping of organic carbon at two depths in loess hilly region of Northern Iran

43. Chapter 35 Hydrochemistry and geogenic pollution assessment of groundwater in Akşehir (Konya/Turkey) using GIS

44. Chapter 36 Comparison of the frequency ratio, index of entropy, and artificial neural networks methods for landslide susceptibility mapping: A case study in Pınarbaşı/Kastamonu (North of Turkey)

45. Chapter 37 Remote sensing technology for postdisaster building damage assessment

46. Chapter 38 Doing more with less: A comparative assessment between morphometric indices and machine learning models for automated gully pattern extraction (A case study: Dashtiari region, Sistan and Baluchestan Province)

47. Chapter 39 Identification of land subsidence prone areas and their mapping using machine learning algorithms

48. Chapter 40 Monitoring of spatiotemporal changes of soil salinity and alkalinity in eastern and central parts of Iran

49. Chapter 41 Kernel-based granulometry of textural pattern measures on satellite imageries for fine-grain sparse woodlands mapping

50. Chapter 42 Badland erosion mapping and effective factors on its occurrence using random forest model

51. Chapter 43 Application of machine learning algorithms in hydrology

52. Chapter 44 Digital soil mapping of soil bulk density in loess derived-soils with complex topography

53. Chapter 45 Landslide susceptibility mapping along the Thimphu-Phuentsholing highway using machine learning

54. Chapter 46 Drought assessment using the standardized precipitation index (SPI) in GIS environment in Greece

55. Chapter 47 COVID-19: An analysis on official reports in Iran and the world along with some comparisons to other hazards

56. Chapter 48 Multihazard risk analysis and governance across a provincial capital in northern Iran

57. Chapter 49 Distribution patterns in plants: Mapping and priorities for plant conservation

58. Chapter 50 Assessing agriculture land-use change using remote sensing data in the Gilan Province, Iran

59. Index