دانلود کتاب Concepts and Applications of Remote Sensing in Forestry

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Preface
Contents
Editor and Contributors
Part I: Introduction
Remote Sensing for Forest Inventory and Resource Assessment
1 Introduction
2 Inventory and Sampling Design
3 Tree Crop Inventory and Assessments
4 Developments in Remote Sensing Technologies
5 Forestry Applications of Remote Sensing in Developing Countries
6 Relationship Between Forest Parameters and Remote Sensing Data
7 Summary
References
Part II: Overview of Remote Sensing
Multiple Sensors and Platforms for Biophysical and Biochemical Characterisations of Various Ecosystem Types of Tropical Forest...
1 Introduction
2 Remote Sensing as Tool for Forest Mapping and Inventory
3 Remote Sensing for Biomass Carbon Assessment
4 Remote Sensing forTree Species Recognition
5 Remote Sensing for Forest Structure
6 Limitation and Advancement in Remote Sensing
7 Opportunity
8 Conclusion
References
A Review on the Use of LiDAR Remote Sensing for Forest Landscape Restoration
1 Introduction
2 Forest Landscape Restoration
2.1 Definition
2.2 Principles of Forest Landscape Restoration
2.2.1 Focus on Landscape
2.2.2 Preservation and Enhancing Natural Ecosystems Within Landscapes
2.2.3 Work Collaboratively with the Stakeholders and Participate in Government
2.2.4 Adapt to the Local Environment Through a Variety of Methods
2.2.5 Restore Multiple Functions for Multiple Benefits
2.2.6 Manage Adaptively for Long-Term Resilience
3 Understanding Forest Types
3.1 Primary Forest
3.2 Secondary Forest
3.3 Restored Forest
4 Light Detection and Ranging (LiDAR)
4.1 An Overview of LiDAR
5 LiDAR in Monitoring the Effectiveness of Forest Restoration
6 LiDAR in Quantifying Structural Attributes
6.1 Tree Dimensions
6.2 Aboveground Biomass
6.3 Deadwood
6.4 Canopy Structure and Layering
6.5 Vegetation Cover
6.6 Tree Species Composition
6.7 Structural Complexity
References
Assessment and Modelling of Forest Biomass and Carbon Stock and Sequestration Using Various Remote Sensing Sensor Systems
1 Introduction
2 Remote Sensing and AGB/Carbon Stock Assessment
3 Key Literatures of Remote Sensing Applications in Forest AGB and Carbon Stock Estimation
3.1 Very High-Resolution Satellite (VHRS) Image Applications
3.2 Airborne Laser Scanner (ALS) Applications
3.3 Terrestrial Laser Scanner (TLS) Applications
3.4 Synthetic Aperture Radar (SAR) Applications
3.5 Unmanned Aerial Vehicle (UAV) Applications
4 Conclusions
References
Part III: Modelling and Monitoring
Spatial Modeling of Transport and Resources Accessibility for Protecting Forest Ecosystems Against Forest Fires
1 Introduction
2 The Optimum Ground Access Route to Forest Fires
3 Accessible Forest Lands by Firefighting Teams and Their Optimal Locations
4 Forest Roads as Effective Infrastructures for Fire Protection
5 Conclusion
References
Assessment of Forest Aboveground Biomass Estimation from SuperView-1 Satellite Image Using Machine Learning Approaches
1 Introduction
2 Study Area
3 Research Methodology
4 Forest Inventory, SuperView-1 Satellite Image, and LiDAR Data
5 Georeferencing and Orthorectification
6 Segmentation and Classification Process of Tropical Forest
7 Tree Classification
8 Shadow Masking and Building Classification
9 Morphology
10 Accuracy Assessment of Segmentation Output
11 Allometric Equation for AGB and Carbon Stock Estimation
12 Artificial Neural Network (ANN) and Random Forest (RF)
13 Regression Model Evaluation
14 Results and Analysis
14.1 Description of Statistical Values of Dependent and Independent Variables
14.2 Analysis of Statistical Value and Accuracy Assessment of OBIA Output
14.3 The Accuracy Assessment for Estimating Forest Aboveground Biomass Using an Artificial Neural Network (ANN) and Random For...
14.4 Plot the Graph and Evaluation Model of ANN and RF Algorithms
15 Conclusion
References
Potential Tree Species Distribution Modelling Using MaxEnt Model for Resource Partitioning in Azad Jammu and Kashmir (AJK), Pa...
1 Introduction
2 Study Area
3 Materials and Methods
3.1 Data Preparation and Processing
3.2 MaxEnt Model Calibration and Evaluation
3.3 Tree Species Diversity Maps
4 Results
4.1 Selected Independent Variables for MaxEnt Modelling
4.2 Model Calibration and Evaluation
4.3 Tree Species Distribution Maps
4.4 Tree Species Diversity Maps
5 Discussion
6 Conclusion
References
Application of Remote Sensing Vegetation Indices for Forest Cover Assessments
1 Introduction
2 Spectral Reflectance of Vegetation
3 Vegetation Index
3.1 Ratio Vegetation Index
3.2 Normalized Difference Vegetation Index
3.3 Green Normalized Difference Vegetation Index
3.4 Soil-Adjusted Vegetation Index
4 Use of Vegetation Indices for Forest Cover Assessments
5 Use of Vegetation Indices for Forest Type Classification
6 Recommendation Before Using Vegetation Index for Forest Assessment
7 Conclusion
References
Rainforest Assessment in Brunei Darussalam Through Application of Remote Sensing
1 Introduction
2 Physical Characteristic of Case Study Area
3 Data and Methodology
4 Results and Discussion
4.1 The Status of the Tropical Rainforest in Brunei Darussalam
4.2 The Management of Rainforest
4.3 Monitoring and Changing Pattern of Rainforest
5 Conclusions
References
Part IV: Remote Sensing of Agricultural Tree Crops
Rubber Trees and Biomass Estimation Using Remote Sensing Technology
1 Introduction
2 Biomass at a Glance
3 Carbon Sequestration
4 Application of Remote Sensing for Rubber
5 Vegetation Indices for Biomass Calculation
6 Rubber Tree Biomass as a Carbon Sink
7 Remote Sensing for Biomass Estimation
8 Optical Remote Sensing for Biomass Estimation
9 Radar Remote Sensing for Biomass Estimation
10 LiDAR Remote Sensing for Biomass Estimation
11 The Allometric Equation for Biomass Estimations
12 Remote Sensing for Rubber Trees Above-Ground Biomass (AGB)
13 Conclusion
References
The Use of Landsat TM Imagery for the Application of Rubber Tree Area and Stand Volume Predictive Models in Rubber Plantations...
1 Introduction
2 Materials and Methods
2.1 Satellite Image Acquisition and Reference Data
2.2 Image Pre-processing
2.3 Application of the Predictive Rubber Area and Stand Volume Models
2.4 Supervised Image Classification
2.5 Accuracy Assessment of the Land Use/Cover Classification
3 Results and Discussion
3.1 Rubber Area Model Application
3.2 Rubber Tree Stand Volume Model Application
3.3 Land Use/Cover Classification
3.4 Rubber Tree Stand Volume Classification
3.5 Signature Separability Between Rubber Volume Classes
3.6 Rubber Volume Classification Accuracy
4 Conclusions
References
Using Historical Disturbance Identified with LandTrendr in Google Earth Engine for Land Cover Mapping of Oil Palm Landscapes
1 Introduction
2 Background to Remote Sensing Methods for Mapping Oil Palm in Insular Southeast Asia
3 Methods
3.1 Study Area
3.2 Overview of Methods
3.3 Image Preparation
3.4 Land Cover Classification Scheme
3.5 Ground Truth Data for Calibration and Accuracy Assessment
3.6 LandTrendr Historical Disturbance Mapping
3.6.1 Sliding Rule
3.6.2 Calibration Points
3.6.3 LandTrendr Parameters
3.6.4 Magnitude Threshold
3.6.5 Accuracy Estimation
3.7 Supervised Random Forest Classification of Land Cover for 2019
3.8 Validation
4 Results
4.1 Optimal Parameters
4.2 Land Cover Maps
4.3 Accuracy Assessment
4.4 LandTrendr
5 Discussion
5.1 Overview
5.2 Parameterization
5.3 Mapping
5.4 Limitations and Future Research
6 Conclusion
References
Part V: Remote Sensing of Mangrove Ecosystems
Geospatial Technology: Unlocking the Management and Monitoring in Malaysian Mangrove Forests
1 Introduction
2 Mangrove Forests in Malaysia
3 Mangrove and Geospatial Technology
3.1 Methodology
3.2 Finding and Discussion
4 Concluding Remarks
References
Effect of Tidal Regime, Relative Sea Level and Wind Intensity on Changes of Mangrove Area Using Remote Sensing Approach
1 Introduction
2 Study Area
3 Environmental Parameters
4 Tidal Regime
5 Wind Intensity
6 Relative Sea Level
7 Methods and Techniques
7.1 Supervised Classification (Maximum Likelihood)
7.2 Correlation Analysis
7.3 Relationship of Mangrove Area Changes and Environmental Parameter
8 Results
8.1 Changes of Mangrove Boundary Area Quantification
8.2 Analyses of the Relationship Determination Between Mangrove Area with Tidal Regime, Wind Intensity and Relative Sea Level
8.3 Correlation Analysis
8.4 Vulnerable Map Establishment
8.4.1 Chendering
8.4.2 Kuala Perlis
9 Perspectives and Conclusion
References
Spatiotemporal Distribution of Mangrove at Kuala Sepetang Forest Reserve, Malaysia, Using Remotely Sensed Data
1 Introduction
2 Materials and Method
2.1 Study Area
2.2 Data Processing
2.3 Calibration and Validation Data
2.4 Land Use Land Cover Classification
2.5 Normalized Difference Vegetation Index (NDVI)
3 Results and Discussion
4 Conclusion
References
Part VI: Remote Sensing of Urban Forestry
Determination of the Effect of Urban Forests and Other Green Areas on Surface Temperature in Antalya
1 Introduction
2 Materials and Methods
2.1 Study Area
2.2 Method
3 Results
4 Discussions
5 Conclusions
References
Conceptualising the Citizen-Driven Urban Forest Framework to Improve Local Climate Condition: Geospatial Data Fusion and Numer...
1 Introduction
1.1 Trees Outside Forest
2 Geospatial for Environmental Urban Solution
3 Numerical Simulation for Urban Climate
4 Benefits and Uses of Urban Forests and Trees
5 Urban Biodiversity
6 Local Climate Change Impacts
7 Urban Forest Policy and Planning
7.1 Key Elements of Urban Forest Policies and Planning
7.2 Implementation and Measuring Success of Urban Forest Policy and Planning
7.3 Issues and Challenges
8 Urban Forestry: Innovative Solutions and Future Potential
9 Remote Sensing and GIS Data Fusion for Urban Forest Management and Research
10 Community-Based Approach of Urban Forest
11 The ``Coming of Age´´ of Urban Forestry: The Citizen-Driven of Urban Forest (CDUF)
12 Conclusion/Summary
References
Part VII: Remote Sensing of Forest Engineering and Restoration
State of the Art on Airborne LiDAR Applications in the Field of Forest Engineering
1 Introduction
2 Basic Principles of LiDAR Technology
3 Forest Road Design and Road Construction
4 Forest Transportation and Forest Operations
5 Logging Impact Assessment
6 Conclusion
References
Restoration of Damaged Forest and Roles of Remote Sensing
1 Introduction
2 Remote Sensing Application in Forestry
3 Trends in Remote Sensing Techniques for Forest Monitoring
4 Approaches for Ecological Restoration
5 Conceptual Approach
6 Policy Approach
7 Technical Approach
8 Roles of Remote Sensing for Forest Restoration
9 Conclusion
References
Recent Advances in UAV-Based Structure-from-Motion Photogrammetry for Aboveground Biomass and Carbon Storage Estimations in Fo...
1 Introduction
2 A Very Brief Historical UAV Technology
3 UAV Photogrammetry in Forestry
4 UAV-SfM Photogrammetry Use in Forestry
5 UAV-SfM Studies in Aboveground Biomass and Carbon Estimation
6 Conclusion
References
Part VIII: Hyperspectral and Multi Source Remote Sensing
Hyperspectral Identification of Selected Dipterocarp Montane at the Species Level
1 Introduction
2 General Introduction of Tropical Rainforests
3 Introduction on Dipterocarp Species
4 Hyperspectral Remote Sensing of Forest
5 Study Area
6 Biodiversity Profile and Biophysical of Selected Dipterocarp Species in Semangkok Forest
7 Methodology
7.1 Random Sampling and Selection of Dipterocarp Species
7.2 Biophysical Information
7.3 Mapping of the Study Area
7.4 Spectral Reflectance of Selected Dipterocarp Species
8 Spectral Analysis of Dipterocarp Species
8.1 Derivative Analysis
8.2 Ratio of Derivative Peak
9 Results and Discussion
9.1 Statistical Analysis and Significance Tests
9.2 ANOVA on First Derivative Spectra of Four Dipterocarp Species
10 Discussion and Conclusion
References
Tree Biophysical Parameter Retrieval from Multi-source Remote Sensing Data Fusion
1 Introduction
2 Genus of Shorea
3 Extracting Tree Biophysical Parameters Using Remote Sensing Data Sets
4 High-Resolution Remote Sensing Images
5 Extracting Tree Parameters from Airborne LiDAR
6 Synergism of Satellite Images and LiDAR Data in Forestry
7 Object-Based Image Analysis (OBIA) for Shorea Classification
8 Multi-resolution Image Segmentation
9 Classification of Forest Structure
10 Spectral Range for Shorea Tree
11 Spectral Signature for Selected Tree Species
12 Distribution Map of Shorea Trees
13 Vertical Accuracy for LiDAR Data
14 Conclusion
References
Index