This book discusses the detrimental consequences of climate-related land changes over a 40-year period between 1981 and 2020, and focuses on how climate warming is deteriorating the agricultural system due to excessive heat, lack of moisture and more intensive and widespread droughts leading to a reduction of agricultural production. Most of the existing literature on the unfavourable consequences of global warming for land are based on a relatively short period of weather station data, covering local land areas with limited networks and monitoring parameters. These concerns have led to the use of satellite data, whose measurements are controlled by such vegetation characteristics as chlorophyll, carotenoids, moisture contents in the plants and temperature inside the vegetation community. Therefore, the discussion of this book is completely based on high-resolution global land surface measurements by the sensors on the National Oceanic and Atmospheric Administration’s (NOAA) operational afternoon polar-orbiting satellites.
The book also focuses on understanding climate change impacts on land changes where humans are living, and combines biophysically-grounded methods and the 40-year data to develop models for monitoring large-scale Earth warming impacts on land and for timely prediction of climate consequences for humans. These 40-year trends in land characteristics will help to better inform the assessment of potential changes in the future and how to reach human sustainability. The book will of interest to scientists using satellite remote sensing to track climate change impacts on land over time, as well as students and researchers in climatology and environmental sustainability.
Author(s): Felix Kogan
Publisher: Springer
Year: 2023
Language: English
Pages: 462
City: Cham
Contents
Chapter 1: Why This Book?
1.1 Land Changes Due to Global Warming
1.2 Living on Warmer Land
1.3 The Goals of the Book
1.4 Book Composition
1.5 Short Summary
References
Chapter 2: Global Warming Impacts on Earth Systems
2.1 Introduction
2.2 Global Temperature and Anomalies for Climate Studies
2.2.1 Development and Accuracy of the Global TA Time Series and UN-Based IPCC Activities
Land, Ocean, and Global Temperature Records
Land Temperature
Ocean: Sea Surface Temperature from Buys
Ocean: SST from Ships
Ocean: Combine SST from Buys and Ships
Global Mean Temperature, Temperature Climatology, and Temperature Anomaly
Multiyear Global Mean Temperature Anomaly Time Series
Basic Assumption Used for the Development of Temperature Anomaly’s Time Series
Preliminary Evaluation
2.2.2 Land, Ocean, and Global Temperature Anomalies from NOAA
Development of Erroneous TA Trend, Using Non-corrected Ships’ SST T Measurements
2.3 IPCC Program: Global Warming and Impacts on Earth
2.3.1 Global Warming and IPCC-Based Earth/Land Changes
Global Temperature
Sea Ice
Arctic
Antarctic
Glaciers and Permafrost
Snow
Sea Level
Ocean
Land
Ecosystems
Greenhouse Gases
Extreme Events
Food Security
2.4 Conclusion
References
Chapter 3: The IPCC Reports on Global Warming and Land Changes
3.1 Introduction
3.2 Climate Warming and Land Changes from the IPCC Reports
3.2.1 Land Changes
3.2.2 Temperature
3.2.3 Land Degradation and Desertification
3.2.4 Food Security
3.2.5 General IPCC Statements and Brief Comments
3.2.6 The Statements
3.3 Evaluation of the IPCC Statements
3.4 Summary
References
Chapter 4: NOAA Operational Environmental Satellites for Earth Monitoring
4.1 Introduction
4.2 NOAA Operational Polar-Orbiting Environmental Satellites (POES)
4.2.1 AVHRR Sensor
4.2.2 AVHRR Data for Vegetation Monitoring
4.2.3 Initial Algorithm for Data Collection
4.2.4 Normalized Difference Vegetation Index and Brightness Temperature
4.2.5 Removing Noise from NDVI and BT
Removing Long-Term Noise
Removing Short-Term Noise
4.2.6 VIIRS Data for Vegetation Monitoring
4.2.7 Continuity of NOAA/AVHRR, S-NPP/VIIRS, and NOAA-20/VIIRS Data Records
4.3 Conclusion
References
Chapter 5: New Remote Sensing Vegetation Health Technology
5.1 Introduction
5.2 What Is Vegetation Health?
5.3 Theoretical Base of Vegetation Health Method
5.3.1 Biophysical Considerations
5.3.2 Basic Laws for Extracting Weather Component from NDVI and BT
5.4 Renewed Vegetation Health Algorithm
5.5 Vegetation Health at Work
5.6 Validation
5.7 Conclusion
References
Chapter 6: Causes of Climate Warming
6.1 Introduction
6.2 Global Warming and Major Earth Changes
6.3 What Is Controlling Global Warming?
6.3.1 Climate System
6.3.2 CO2 and Global Warming
Activities to Reduce CO2
Other Environmental Sources of Global Warming
Prove That CO2 Is Controlling Global Temperature
6.3.3 CO2–TA Match: New Analysis
6.4 New Ideas About the Causes of Global Warming
6.4.1 Warming Due to Ozone Depletion
6.4.2 Earth Climate and Milankovitch Cycle
6.4.3 Milankovitch-Based Precession Cycle
6.5 Summary
References
Chapter 7: Land Cover Changes from Intensive Climate Warming
7.1 Introduction
7.1.1 General Statements
7.1.2 NOAA Satellites, Used for This Analysis
7.2 Land Cover Temperature
7.2.1 Global-Regional Land Cover Temperature (SMT)
World
Hemispheres
Countries
Countries Producing 10–21% of Global Cereals
Countries Producing 3–4% of Global Cereals
Countries Producing Around 2% of Global Cereals
Several Other Countries
7.3 Land Cover Greenness
7.3.1 World and Hemispheres
7.3.2 China, the USA, and India
7.3.3 Brazil, Indonesia, Russia
7.3.4 Argentina, Ukraine, France, Canada
7.3.5 Other Countries
7.4 Summary
References
Chapter 8: Global Warming Crop Yield and Food Security
8.1 Introduction
8.2 Modeling Principles
8.2.1 Yield Time Series
8.2.2 Vegetation Health Indices
8.2.3 Yield-Vegetation Health Models
8.3 Yield-Vegetation Health Models
8.3.1 Global Grain and Food Security
8.3.2 Corn in China
8.3.3 Winter Wheat, Corn, and Sorghum in the USA
8.3.4 Winter Wheat in Ukraine
8.3.5 Corn in Argentina
8.3.6 Wheat in Australia
8.3.7 Rice in Bangladesh
8.3.8 Cereals in Russia
8.3.9 Spring Wheat in Kazakhstan
8.3.10 Corn in Zimbabwe
8.3.11 Other Countries and Crops
8.3.12 VH-crop Modeling for Food Security: Concluding Remarks
8.4 Short Summary
References
Chapter 9: Remote Sensing Malaria During Global Warming
9.1 Introduction
9.2 Modeling Principles
9.2.1 Malaria’s Multiyear Time Series
9.2.2 VHI Applied to Malaria
9.3 Malaria-VH Models
9.3.1 Southeast Asia
Bangladesh
Large Area
Correlation and Regression Analysis
Midsize Area
Correlation and Regression Analysis
Model Validation
Small Area
Data
Correlation and Regression Analysis
Model Validation
Summary
India
Tripura State, India
Environment
Data
Matching Malaria and VH Data
Correlation Regression Analysis
Orissa State, India
Data
Malaria Time Series Analysis
Correlation and Regression Analysis
South Korea
9.3.2 Africa
Swaziland
Tanzania
Malaria Risk Index (MRI)
9.3.3 South America
9.4 Summary
References
Chapter 10: Malaria Performance Trend During 1981–2020 Global Warming
10.1 Introduction
10.2 Earth Climate Warming and Consequences
10.3 Strong Global Warming During 2015–2018
10.4 Global and Continental Malaria Activities, Assessed from 1981 to 2018 Satellite-Based Moisture-Thermal Characteristics
10.4.1 Malaria Activities Assessed Form Vegetation Greenness and Temperature
10.4.2 Vegetation Health Indices as the Indicators of Malaria activities
10.4.3 High Malaria (HM) and Low Malaria (LM), Assessed from Vegetation Health Indices
10.4.4 Percent Global Malaria Area with HM and LM from the 1981–2018 Moisture-Thermal Index (VHI)
10.4.5 Percent Global Malaria Area with HM and LM from the 1981–2018 Moisture (VCI) and Thermal (TCI) Indices
10.4.6 Percent Continental (South America, Africa and Southeast Asia) Malaria Area with HM and LM from 1981 to 2018 Thermal (TCI) and Moisture (VCI) Conditions During Climate Warming
10.5 Percent Malaria Endemic Area with HM and LM (Assessed from 1981 to 2019 Moisture (VCI) and Thermal (TCI) Vegetation Condition) in the Most Malaria-Affected Countries During 1981–2019 Global Warming
10.5.1 Brazil and Colombia (South America (SA))
10.6 Conclusion
References
Chapter 11: Remote Sensing Drought Watch and Food Security
11.1 Introduction
11.2 Drought as Natural Disaster
11.3 What Is Drought?
11.3.1 Drought Features
11.3.2 Measuring Drought
11.3.3 Drought Types
11.4 Drought Detection and Monitoring Methods
11.4.1 Meteorological Methods
11.4.2 Soil Moisture Methods
11.4.3 Satellite-Derived Methods
11.5 Vegetation Health-Based Droughts: Past to Present
11.6 Droughts at 0.5 and 1 km2 Resolution from NOAA/VIIRS
11.7 Devastating Droughts in 2017 and 2018
11.8 Drought, Food Insecurity, and Hunger in Africa
11.9 Unusual 2021 Droughts
11.10 Conclusions
References
Chapter 12: Has Drought Intensified During 1981–2021 Global Warming?
12.1 Introduction
12.2 Global Warming and Droughts
12.3 How to Measure Drought from NOAA/POES?
12.4 41-Year (1981–2021) Drought Dynamics
12.4.1 Thermal Vegetations Stress and Drought Dynamics During 1981–2021 Global Warming
World and Hemispheres
Countries
12.4.2 Dynamics of Moisture Vegetation Stress During 1981–2021 Global Warming
12.5 Conclusion
References
Chapter 13: Summary
Index
