Remote Sensing Land Surface Changes: The 1981-2020 Intensive Global Warming

463 Pages·2023·34.177 MB·English

by  Felix Kogan

Felix Kogan
Remote Sensing
Land Surface
Changes
The 1981-2020 Intensive
Global Warming
Remote Sensing Land Surface Changes
Felix Kogan
Remote Sensing Land
Surface Changes
The 1981-2020 Intensive Global Warming
Felix Kogan
National Oceanic and Atmospheric Administration
Rockville, MD, USA
ISBN 978-3-030-96809-0 ISBN 978-3-030-96810-6 (eBook)
https://doi.org/10.1007/978-3-030-96810-6
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Contents
1 Why This Book? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Land Changes Due to Global Warming . . . . . . . . . . . . . . . . . . . . . . 1
1.2 Living on Warmer Land . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3 The Goals of the Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
1.4 Book Composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
1.5 Short Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
2 Global Warming Impacts on Earth Systems . . . . . . . . . . . . . . . . . . . . 21
2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.2 Global Temperature and Anomalies for Climate Studies . . . . . . . . . 25
2.2.1 Development and Accuracy of the Global TA Time
Series and UN-Based IPCC Activities . . . . . . . . . . . . . . . . . 26
2.2.2 Land, Ocean, and Global Temperature Anomalies
from NOAA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2.3 IPCC Program: Global Warming and Impacts on Earth . . . . . . . . . 44
2.3.1 Global Warming and IPCC-Based Earth/Land Changes . . . 47
2.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 61
3 The IPCC Reports on Global Warming and Land Changes . . . . . . . 67
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.2 Climate Warming and Land Changes from the IPCC Reports . . . . 69
3.2.1 Land Changes. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69
3.2.2 Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
3.2.3 Land Degradation and Desertification . . . . . . . . . . . . . . . . . 70
3.2.4 Food Security . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72
3.2.5 General IPCC Statements and Brief Comments . . . . . . . . . 73
3.2.6 The Statements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
3.3 Evaluation of the IPCC Statements . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 78
v
vi Contents
4 NOAA Operational Environmental Satellites for Earth
Monitoring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.2 NOAA Operational Polar-Orbiting Environmental Satellites
(POES) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
4.2.1 AVHRR Sensor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
4.2.2 AVHRR Data for Vegetation Monitoring . . . . . . . . . . . . . . . 84
4.2.3 Initial Algorithm for Data Collection . . . . . . . . . . . . . . . . . . 85
4.2.4 Normalized Difference Vegetation Index and Brightness
Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
4.2.5 Removing Noise from NDVI and BT . . . . . . . . . . . . . . . . . 91
4.2.6 VIIRS Data for Vegetation Monitoring . . . . . . . . . . . . . . . . 106
4.2.7 Continuity of NOAA/AVHRR, S-NPP/VIIRS,
and NOAA-20/VIIRS Data Records . . . . . . . . . . . . . . . . . . 110
4.3 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 115
5 New Remote Sensing Vegetation Health Technology . . . . . . . . . . . . . . 121
5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121
5.2 What Is Vegetation Health? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122
5.3 Theoretical Base of Vegetation Health Method . . . . . . . . . . . . . . . . 123
5.3.1 Biophysical Considerations . . . . . . . . . . . . . . . . . . . . . . . . . 124
5.3.2 Basic Laws for Extracting Weather Component
from NDVI and BT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
5.4 Renewed Vegetation Health Algorithm . . . . . . . . . . . . . . . . . . . . . . 126
5.5 Vegetation Health at Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
5.6 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 137
5.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
6 Causes of Climate Warming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
6.2 Global Warming and Major Earth Changes . . . . . . . . . . . . . . . . . . . 151
6.3 What Is Controlling Global Warming? . . . . . . . . . . . . . . . . . . . . . . 154
6.3.1 Climate System . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
6.3.2 CO and Global Warming . . . . . . . . . . . . . . . . . . . . . . . . . . 155
2
6.3.3 CO–TA Match: New Analysis . . . . . . . . . . . . . . . . . . . . . . 159
2
6.4 New Ideas About the Causes of Global Warming . . . . . . . . . . . . . . 163
6.4.1 Warming Due to Ozone Depletion . . . . . . . . . . . . . . . . . . . . 163
6.4.2 Earth Climate and Milankovitch Cycle . . . . . . . . . . . . . . . . 166
6.4.3 Milankovitch-Based Precession Cycle . . . . . . . . . . . . . . . . 168
6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Contents vii
7 Land Cover Changes from Intensive Climate Warming . . . . . . . . . . . 181
7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
7.1.1 General Statements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 181
7.1.2 NOAA Satellites, Used for This Analysis . . . . . . . . . . . . . . 182
7.2 Land Cover Temperature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 184
7.2.1 Global-Regional Land Cover Temperature (SMT) . . . . . . . 185
7.3 Land Cover Greenness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
7.3.1 World and Hemispheres . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202
7.3.2 China, the USA, and India . . . . . . . . . . . . . . . . . . . . . . . . . . 203
7.3.3 Brazil, Indonesia, Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . 204
7.3.4 Argentina, Ukraine, France, Canada . . . . . . . . . . . . . . . . . . 205
7.3.5 Other Countries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
7.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 209
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211
8 Global Warming Crop Yield and Food Security . . . . . . . . . . . . . . . . . 217
8.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 217
8.2 Modeling Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
8.2.1 Yield Time Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
8.2.2 Vegetation Health Indices . . . . . . . . . . . . . . . . . . . . . . . . . . 220
8.2.3 Yield-Vegetation Health Models . . . . . . . . . . . . . . . . . . . . . 221
8.3 Yield-Vegetation Health Models . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
8.3.1 Global Grain and Food Security . . . . . . . . . . . . . . . . . . . . . 223
8.3.2 Corn in China . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
8.3.3 Winter Wheat, Corn, and Sorghum in the USA . . . . . . . . . . 227
8.3.4 Winter Wheat in Ukraine . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
8.3.5 Corn in Argentina . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
8.3.6 Wheat in Australia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
8.3.7 Rice in Bangladesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
8.3.8 Cereals in Russia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 248
8.3.9 Spring Wheat in Kazakhstan . . . . . . . . . . . . . . . . . . . . . . . . 254
8.3.10 Corn in Zimbabwe . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258
8.3.11 Other Countries and Crops. . . . . . . . . . . . . . . . . . . . . . . . . . 262
8.3.12 VH-crop Modeling for Food Security: Concluding
Remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
8.4 Short Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 271
9 Remote Sensing Malaria During Global Warming . . . . . . . . . . . . . . . 277
9.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
9.2 Modeling Principles . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
9.2.1 Malaria’s Multiyear Time Series . . . . . . . . . . . . . . . . . . . . . 280
9.2.2 VHI Applied to Malaria . . . . . . . . . . . . . . . . . . . . . . . . . . . . 282
viii Contents
9.3 Malaria-VH Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284
9.3.1 Southeast Asia . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284
9.3.2 Africa . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
9.3.3 South America . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325
9.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328
10 Malaria Performance Trend During 1981–2020 Global Warming . . . 333
10.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
10.2 Earth Climate Warming and Consequences . . . . . . . . . . . . . . . . . . 335
10.3 Strong Global Warming During 2015–2018 . . . . . . . . . . . . . . . . . 337
10.4 Global and Continental Malaria Activities, Assessed
from 1981 to 2018 Satellite-Based Moisture-Thermal
Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 339
10.4.1 Malaria Activities Assessed Form Vegetation
Greenness and Temperature . . . . . . . . . . . . . . . . . . . . . . 340
10.4.2 Vegetation Health Indices as the Indicators
of Malaria activities . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344
10.4.3 High Malaria (HM) and Low Malaria (LM),
Assessed from Vegetation Health Indices . . . . . . . . . . . . 345
10.4.4 Percent Global Malaria Area with HM and LM
from the 1981–2018 Moisture-Thermal Index (VHI) . . 345
10.4.5 Percent Global Malaria Area with HM and LM
from the 1981–2018 Moisture (VCI) and Thermal (TCI)
Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346
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 . . . . . . . . . . . . . . . 348
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 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353
10.5.1 Brazil and Colombia (South America (SA)) . . . . . . . . . 354
10.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
11 Remote Sensing Drought Watch and Food Security . . . . . . . . . . . . . . 373
11.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373
11.2 Drought as Natural Disaster . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 374
11.3 What Is Drought? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 375
11.3.1 Drought Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377
11.3.2 Measuring Drought . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377
11.3.3 Drought Types . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 378
Contents ix
11.4 Drought Detection and Monitoring Methods . . . . . . . . . . . . . . . . . 379
11.4.1 Meteorological Methods . . . . . . . . . . . . . . . . . . . . . . . . . 379
11.4.2 Soil Moisture Methods . . . . . . . . . . . . . . . . . . . . . . . . . . 381
11.4.3 Satellite-Derived Methods . . . . . . . . . . . . . . . . . . . . . . . 382
11.5 Vegetation Health-Based Droughts: Past to Present . . . . . . . . . . . 390
11.6 Droughts at 0.5 and 1 km2 Resolution from NOAA/VIIRS . . . . . . 405
11.7 Devastating Droughts in 2017 and 2018 . . . . . . . . . . . . . . . . . . . . 412
11.8 Drought, Food Insecurity, and Hunger in Africa . . . . . . . . . . . . . . 414
11.9 Unusual 2021 Droughts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
11.10 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 418
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 419
12 Has Drought Intensified During 1981–2021 Global Warming? . . . . . 425
12.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425
12.2 Global Warming and Droughts . . . . . . . . . . . . . . . . . . . . . . . . . . . 427
12.3 How to Measure Drought from NOAA/POES? . . . . . . . . . . . . . . . 429
12.4 41-Year (1981–2021) Drought Dynamics . . . . . . . . . . . . . . . . . . . 430
12.4.1 Thermal Vegetations Stress and Drought Dynamics
During 1981–2021 Global Warming . . . . . . . . . . . . . . . 431
12.4.2 Dynamics of Moisture Vegetation Stress During
1981–2021 Global Warming . . . . . . . . . . . . . . . . . . . . . . 444
12.5 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445
References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 446
13 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 449
Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453
Chapter 1
Why This Book?
1.1 Land Changes Due to Global Warming
This Book is studying numerical land changes due to an intensive global warming.
The recent climate warming has affected the entire earth. Why the major focus of
the Book is on land? Land is the only earth system supporting people’s living. Land
area is not big, occupying 148.3 million km2 or 29% of the total earth surface
(510.1 million km2). Although the land is 2.4 times smaller than ocean, nearly 80%
of Earth’s species live on land and 5% are living in land’s freshwater (IGBP 2020).
The rest 15% species are remaining in the ocean. The most important land’s goals
are supporting living 7.8 billion people. Considering the size of land (excluding two
Poles) and assuming uniform population distribution, each land’s 1 km2 contains 50
people. Meanwhile, people are distributed not uniformly. Nearly two-thirds of the
world’s population lives in Asia, with nearly 2.7 billion in the two countries, China
and India.
Supporting currently the living of 7.8 billion earth population, and having rela-
tively limited land’s resources, any deviations of land conditions from the estab-
lished over many years might produce negative impacts on land resources and
population living. Such strong deviations of the conditions have been currently cre-
ated by the global warming, which is affecting the entire earth and especially land.
Earth climate has been warming up since the mid-eighteenth century (IPCC 2007,
2014, 2018a, b, 2019a, b, c, d, e, f, g, h). This process has intensified, from the
late- 1970s, and by the turn of the twentieth century, global temperature anomaly
(TA) increased by nearly 0.9 °C (over the preindustrial time (1850–1900) (IPCC
2007, 2014, 2019b).
Such a strong increase in global temperature anomaly (TA) has been leading to
quite unusual changes in Earth and specifically land environmental, economic, and
social events (IPCC 2014, 2019d).
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2022 1
F. Kogan, Remote Sensing Land Surface Changes,
https://doi.org/10.1007/978-3-030-96810-6_1