Climate Impacts on Sustainable Natural Resource Management

382 Pages·2021·40.473 MB·English

by  Pavan Kumar (editor), Ram Kumar Singh (editor), Manoj Kumar (editor), Meenu Rani (editor), Pardeep Sharma (editor)

Climate Impacts on Sustainable Natural Resource Management

Climate Impacts on Sustainable Natural
Resource Management
Edited by
Pavan Kumar
College of Horticulture and Forestry
Rani Lakshmi Bai Central Agricultural University
Gwalior Road, Jhansi- 284003, Jhansi, India
Ram Kumar Singh
Hexagon Geospatial
Gurgaon, India
Manoj Kumar
GIS Centre
Forest Research Institute, PO: New Forest
Dehradun -­­248006,­Uttarakhand,­India
Meenu Rani
Department of Geography
Kumaun University
Nainital-2­63001,­Uttarakhand,­India
Pardeep Sharma
Department of Geography,
Government­College­for­Women,­Hisar-­125001,­Haryana,­India
This edition first published 2022
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Library of Congress Cataloging- in- Publication Data
Names: Kumar, Pavan (Professor of forestry); Singh, Ram Kumar; Kumar, Manoj; Rani, Meenu; Sharma, Pardeep editors.
Title: Climate impacts on sustainable natural resource management / edited
by Pavan Kumar, Ram Kumar Singh, Manoj Kumar, Meenu Rani, Pardeep
Sharma.
Description: Hoboken, NJ : John Wiley & Sons, Ltd, 2022. | Includes
bibliographical references and index.
Identifiers: LCCN 2021038152 (print) | LCCN 2021038153 (ebook) | ISBN
9781119793373 (cloth) | ISBN 9781119793380 (adobe pdf) | ISBN
9781119793397 (epub)
Subjects: LCSH: Natural resources–Management–Case studies. | Renewable
natural resources–Case studies. | Climatic changes–Case studies.
Classification: LCC HC85 .C56 2022 (print) | LCC HC85 (ebook) | DDC
333.7–dc23
LC record available at https://lccn.loc.gov/2021038152
LC ebook record available at https://lccn.loc.gov/2021038153
Cover Design: Wiley
Cover Images: © Josephine Julian/Shutterstock, Ratnakorn Piyasirisorost/Getty, japatino/Getty, Patrick Orton/Getty
Set in 9.5/12.5pt STIXTwoText by Straive, Pondicherry, India
10 9 8 7 6 5 4 3 2 1
ffirs.indd 4 11-02-2021 12:53:26
v
Contents
About the Editors xiii
List of Contributors xv
Foreword xxi
Preface xxii
Section I Sustainable Natural Resource Management 1
1 Impact of Local REDD+ Intervention on Greenhouse Gas Emissions in East
Kalimantan Province, Indonesia 3
Kiswanto, Martiwi Diah Setiawati, and Satoshi Tsuyuki
1.1 Introduction 3
1.1.1 Tropical Deforestation 3
1.1.2 REDD+ 3
1.1.3 REDD+ in Indonesia 4
1.2 Materials and Methods 5
1.2.1 Spatial Dataset 5
1.2.2 Carbon Stock in Each Land Cover Class 5
1.2.3 Change in Carbon Stock and CO Emission 7
2
1.2.4 Historical Baselines and Future Trajectories 7
1.3 Results 8
1.3.1 Annual GHG Emissions 8
1.3.2 Historical Baselines and Future Trajectories 9
1.4 Discussion 10
1.5 Conclusions 12
Acknowledgement 12
Author Contribution 12
List of Appendix 13
References 14
2 Role of Geospatial Technologies in Natural Resource Management 19
Abhishek K. Kala and Manoj Kumar
2.1 Introduction 19
2.2 Applications of Geospatial Technology in Natural Resource Management 20
vi Contents
2.2.1 Forest Management 20
2.2.2 Water Resource Management 21
2.2.3 Water Quality Monitoring 22
2.2.4 Agriculture 23
2.2.5 Combating Desertification 25
2.2.6 Biodiversity Management 25
2.3 LiDAR Technology 26
2.4 Artificial Intelligence and Remote Sensing 26
2.5 Machine Learning Tools for Natural Resource Management 27
2.6 Applications of Unmanned Aerial Systems in Natural Resource
Management 28
2.7 Google Earth Engine as a Platform for Environmental Monitoring and NRM 29
2.8 Conclusion 29
References 30
3 Estimation of Snow Cover Area Using Microwave SAR Dataset 35
Shafiyoddin B. Sayyad and Mudassar A. Shaikh
3.1 Introduction 35
3.2 Classification Technique 36
3.2.1 Unsupervised Classification 36
3.2.1.1 H A Alpha Unsupervised Classification 36
3.2.1.2 Wishart H A Alpha Unsupervised Classification 37
3.2.2 Supervised Classification 37
3.2.2.1 Wishart Supervised Classification 38
3.2.2.2 Support Vector Machine (SVM) Supervised Classification 38
3.3 Statistical Parameters 39
3.3.1 Mean 39
3.3.2 Standard Deviation 40
3.3.3 Coefficient Variance 40
3.3.4 Equivalence Number of Looks (ENL) 40
3.4 Error and Accuracy Assessment 40
3.4.1 Confusion Matrix 41
3.4.2 Commission Error 41
3.4.3 Omission Error 42
3.5 Study Area 42
3.6 Methodology 43
3.7 Result and Discussion 44
3.8 Conclusion and Future Perspective 52
References 52
Section II Determinants of Forest Productivity 57
4 Forest Cover Change Detection Across Recent Three Decades in Persian Oak
Forests Using Convolutional Neural Network 59
Alireza Sharifi, Shilan Felegari, Aqil Tariq, and Saima Siddiqui
4.1 Introduction 59
4.2 Materials and Methods 61
Contents vii
4.2.1 Study Area 61
4.2.2 Dataset 61
4.2.3 Image Pre- processing 64
4.2.4 Image Classification 64
4.3 Results and Discussion 65
4.4 Conclusion and Future Prospects 68
References 69
5 The Interlinked Mechanisms of Productivity for Developing Process- Based
Forest Growth Models 74
Keshav Tyagi, Manoj Kumar, Sweta Nisha Phukon, Abhishek Ranjan, Pavan Kumar,
and Ram Kumar Singh
5.1 Introduction 74
5.2 Productivity: Definition and Associated Components 76
5.3 Various Processes and Components Driving Forest Productivity 77
5.3.1 Photosynthesis 78
5.3.2 Light Interception 79
5.3.3 Stomatal Conductance 79
5.3.4 Leaf Area Index 79
5.3.5 Gas- Exchange 80
5.3.6 Plant Respiration 80
5.3.7 Hydrology 81
5.3.8 Nitrogen Cycle 81
5.3.9 Litterfall 81
5.4 Different Approaches to Productivity Assessment 82
5.5 Evolution of Process- Based Models 83
5.6 Conclusion 84
References 84
6 Allometric Equations for the Estimation of Biomass and Carbon in the
S ub- tropical Pine Forests of India 89
Harshi Jain, Keshav Tyagi, Akshay Paygude, Pavan Kumar, Ram Kumar Singh, and
Manoj Kumar
6.1 Introduction 89
6.1.1 Species of Pine in India and its Associates 91
6.1.2 Uses of Chirpine 91
6.2 Chir Pine – a Boon or Bane? 92
6.3 Forest Carbon and Forest Biomass 93
6.4 Composition of Forest Biomass 94
6.4.1 Indian Forest Biomass and Carbon Estimates 94
6.4.2 Importance of Forest Biomass Estimation 95
6.5 Allometric Equations for Biomass Estimation 96
6.5.1 How Are Allometric Equations Developed? 96
6.6 Biomass and Carbon Stock Estimation in Chir Pine Forests of India Using
Allometric Equations 97
6.7 Conclusion 101
References 102
viii Contents
Section III Agriculture and Climate Change 109
7 Characterization of Stress- Prone Areas for Dissemination of Suitable Rice
Varieties and their Adoption in Eastern India: An Integrated Approach toward
Food Security 111
Sk Mosharaf Hossain, Devi Dayal Sinha, and Swati Nayak
7.1 Introduction 111
7.1.1 Characterization of Stress- Prone (Flood and Drought) Areas in Eastern India:
Geo- Spatial Based Studies (Submergence and Drought) 112
7.1.2 Eastern India (Submergence Study – Assam) 114
7.1.3 Eastern India (Drought Study – Uttar Pradesh) 115
7.1.4 Rice- Growing Environments in India and Constraints 116
7.1.5 Abiotic Stress in the Context of Rice Production 117
7.2 Materials and Method (for Submergence- prone: Assam) 118
7.3 Results and Discussion 120
7.4 Conclusions 127
References 128
8 Farmers’ Perspective and Adaptation Efforts to Tackle the Impacts
of Climate Change 132
Shivani Mehta and Shridhar Samant
8.1 Introduction 132
8.2 Methodology 135
8.3 Results and Analysis 137
8.3.1 Trends in Rainfall Patterns 137
8.3.1.1 Trends in Annual Rainfall 137
8.3.1.2 Trends in Rainy Days 140
8.3.1.3 Trends in Actual and Normal (Expected) Rainfall for Every Month 144
8.3.2 Impact of Climate Change on Farmers 148
8.3.2.1 Demographic Profile of the Respondents 148
8.3.2.2 Livelihood 148
8.3.2.3 Pests and Diseases 149
8.4 Understanding the Farmer’s Perception of Climate Change 149
8.5 Adaptation Efforts 150
8.6 Conclusion 151
References 152
Section IV Water Resource Management and Riverine Health 157
9 Multicriteria Drought Severity Analysis in Monaragala District Sri Lanka
by Utilizing Remote Sensing and GIS 159
K.U.J. Sandamali, K.A.M. Chathuranga, B.A.S.C. Kumara, and D.K.D.A. Ranaweera
9.1 Introduction 159
9.2 Methodology 162
9.2.1 Study Area 162