《定量遥感英文版》：深入探讨土地表面遥感理论与应用

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"《定量遥感英文版》是一本专注于定量土地表面遥感领域的专业书籍，由Shunlin Liang编著，作为Wiley系列遥感出版物的一部分。这本书深入探讨了定量遥感理论与应用，重点关注光学遥感技术在土地表面监测中的实际操作。首先，书中的理论部分涵盖了Asrar的《光学遥感的原理与技术》和Haykin、Lewis、Raney和Rossiter的《遥感海冰和冰山》等，介绍了电磁波在各种环境条件下的传播特性，如Crane所写的通过雨的电磁波传播，以及Elachi的合成孔径雷达系统和信号处理技术。这些内容为理解遥感数据的获取和解读提供了基础。接着，书中讨论了适应性雷达探测和估计技术，如Hord的《遥感：方法与应用》，这包括如何在复杂环境中提高雷达信号的处理能力，以便更准确地识别和解析地面信息。Janssen的《微波遥感大气探测》则聚焦于大气层对微波辐射的影响，这是理解地球表面对电磁波响应的关键。对于多光谱遥感中的信号理论方法，Landgrebe的著作提供了深入剖析，而Maffett则探讨了用于统计描述雷达横截面的专题。Steinberg和Subbaram的《微波成像技术》详细介绍了如何利用微波数据进行高分辨率的地表图像重建。Szekielda的章节则涉及卫星监测地球的最新技术和案例研究。最后，Tsang、Kong和Shin的《微波遥感理论》以及Tsang、Kong和Ding的合作作品，进一步深化了对微波遥感技术的理解，包括其理论基础和实际应用前景。《定量遥感英文版》是一本全面而深入的资源，它不仅涵盖了遥感的基本原理，还展示了其在实际环境中的广泛实践，对于从事土地表面遥感、气象学、海洋学、地理信息系统等领域研究的专业人士具有极高的参考价值。"

xiv

CONTENTS

13.4

Carbon Cycle Studies

13.4.1

Background

13.4.2

“Bottom-up” Approach

13.4.3

Case Demonstrations

13.5

Land-Atmosphere Interaction

13.6

Summary

References

APPENDIX

CD-ROM

Content

Data Directory

Software Directory

504

506

509

51 2

51 5

525

Index

528

Preface

Remote sensing has entered a new era in the twenty-first century with a

series

operating satellites from the NASA Earth Observing System (EOS)

program, other international programs, and commercial programs. Since

November 2000 the first civilian spaceborne hyperspectral sensor, Hyperion,

has observed land surfaces on the NASA Earth Observer-1 (EO-1) platform.

The first hyperspatial commercial satellite, IKONOS, produces global im-

agery at the spatial resolutions of

m (panchromatic band) and

(multispectral bands) operationally. An increasing number

people are

processing and analyzing vast amounts of optical remotely sensed observa-

tions for monitoring land surface processes and other applications on both

local and global scales.

One basic characteristic of optical remote sensing in the twenty-first

century is the extensive use

quantitative algorithms for estimating Earth

surface variables. New sensors have much higher measurement precision with

new technology and are far better calibrated. Empirical statistical models are

being replaced by physically based models developed mostly since the early

1980s.

the NASA Earth Vision by 2020, environmental prediction is the

primary goal. The reliable prediction relies on the physical dynamic models

of land surface processes whose variables must be quantitatively estimated

from Earth observing data.

This book emphasizes both the basic principles of optical remote sensing

(0.4-14

pm) and practical algorithms for estimating land surface variables

quantitatively from remotely 5ensed observations. It presents the current

physical understanding of remote sensing as a system with a focus on

radiative transfer modeling of the atmosphere, canopy, soil, and snow, and

also the state-of-the-art quantitative algorithms for sensor calibration, atmos-

pheric and topographic correction, estimation

a variety of biophysical

variables (e.g., leaf area index, fraction of photosynthetically active radiation

absorbed by vegetation) and geophysical variables (e.g., broadband albedo,

emissivity, and skin temperature), and four-dimensional data assimilation.

This book evolved from the lecture notes for a graduate-level remote

sensing course that

offered at the University

Maryland, but it can serve

as a valuable reference book for advanced undergraduates and professionals

XVi

PREFACE

who are involved in remotely sensed data in different scientific disciplines.

This book does not assume a special mathematical background beyond a

good working knowledge of statistics, calculus, and linear algebra on an under-

graduate level. Although some detailed formulas are given in certain sections

as important references, the derivations of these formulas are not provided.

aid the rcader, each chapter starts with a brief overview of its content and

concludes with a summary containing

overview of open research issues

and pointers to relevant references. Extensive verbal “explanations” of what

is bcing addressed in the corresponding formulas are also given.

This book should be studied in sequential order, but readers who are

interested primarily

practical algorithms might follow the shorter sequence

of Chapters

and

5-13.

Book

chapters are conceptually organized into two

parts-Chapters 2--4 and 5-12-plus an introductory chapter (Chapter

and a final chapter (Chapter

13)

on applications. Chapter

introduces some

basic concepts and presents an overview of an optical remote sensing model-

ing systcm that links surface environmental variables to remotely sensed data.

Major components of the systems are outlined as a background

the

following chapters. Chapter

describes many different examples demon-

strating how quantitative remote sensing techniques can be used to address

scientific issues and solve practical societal problems.

Quantitative cstimation of land surface variables relies greatly on physical

understanding of the remotely sensed data and their relation to these

variables. In Chapters 2-4,

summarize major physical modeling methods

atmosphere, vegetation canopy, soil, and snow media in the reflective spec-

trum with an emphasis

radiative transfer modeling. Radiative transfer

modeling in the thermal infrared spectrum in conjunction with the estimation

of land surface skin temperature is discussed in Chapter

10.

Chapter 2 introduces the basic principles of radiative transfer theory and

its connections with atmospheric properties with numerical and approximate

solutions to the atmospheric radiative transfer equation. Chapter

presents

three types of canopy reflectance models: radiative transfer models, geomet-

ric

optical

models, and computer simulation models. In

rudiatiue

transfer

modeling,

different leaf models are also introduced, different methods for

solving one-dimensional

canopy radiative transfer equation are pre-

sented, and methods for handling spatial heterogeneity of the canopy field

are outlined.

geometric

optical

modeling,

major models are outlined.

simply but widely mentioned Li-Strahler model is presented in greater

detail. In

computer

sinzulutiorz

models,

the basic principles of both Monte

Carlo ray tracing and radiosity modeling methods are presented. Chapter 4

presents the modeling methods for soil and snow media. The emphasis is on

radiative transfer modeling, but geometric optical modeling methods are also

outlined.

Chapters

present the practical algorithms for estimating land surface

variables from optical remotely sensed data. It starts with sensor calibration

and ends with product validation. Chapter

discusses the need for sensor

PREFACE

XVii

radiometric calibration and various postlaunch vicarious calibration methods.

The calibration coefficients for land remote sensing satellite thematic map-

ping (Landsat TM) and National Oceanic and Atmospheric Administration

advanced very high-resolution radiometer (NOAA AVHRR) data are pro-

vided for easy reference. Chapter

presents the basic principles and practical

methods of atmospheric correction that convert top-of-atmosphere (TOA)

radiance to surface reflectance. It focuses mainly on estimating aerosol

optical properties from single-viewing remotely sensed data, but multiangle

imaging spectroradiometric

(MISR)

aerosol estimation methods representing

multiangular remote sensing and those for estimating total column water

vapor content of the atmosphere are also discussed. Chapter

discusses

various topographic correction algorithms that remove the disturbance caused

by the variable land surface topography. The current status of digital eleva-

tion model (DEM) data is also evaluated. Chapter

presents various meth-

ods for estimating land surface variables, such

leaf area index, fraction

the photosynthetically active radiation (FAPAR) absorbed by vegetation

canopies, the fraction of vegetation coverage, and biochemical concentra-

tions. Statistical algorithms (based mainly

vegetation indices from multi-

spectral and hyperspectral remotely sensed data) and physical inversion

methods (based mainly on process models introduced in the first few chap-

ters of the book) are presented.

Chapters

and 10 discuss various methods for estimating land surface

radiation budget components, such

broadband albedo, broadband emissiv-

ity, and skin temperature.

calculating broadband albedo, we focus mainly

the conversion algorithms from narrowband to broadband. In estimating

skin temperature, split-window algorithms

as well

other temperature and

emissivity separation algorithms are presented. Chapter

presents four-di-

mensional data assimilation algorithms and applications. This

a quantita-

tive, objective method for inferring the state of the dynamic system from

heterogeneous, irregularly distributed, and temporally inconsistent observa-

tional data with differing accuracies. One unique feature is the ability to

estimate environmental variables that are not related to any remotely sensed

radiometric quantities. The basic principles and the typical algorithms are

introduced, and the applications to hydrology and crop growth are demon-

strated. Chapter

discusses the validation of the estimated land surface

variables and various methods of spatial scaling. Since land surface variables

drive various models related to land surface processes, the accuracy of the

remotely sensed products will largely affect the model outputs and the final

conclusions. The validation rationale, NASA

EOS

validation programs, and

some validation methodologies are presented. Because of its importance in

remote sensing besides validation, spatial scaling is presented separately. The

emphasis is on downscaling methods, including linear unmixing, generating

continuous fields, decomposition of normalized difference vegetative index

(NDVI) temporal profiles, multiresolution data fusion, and statistical down-

scaling global

(or

general) circulation model

(GCM)

outputs.

XViii

PREFACE

This book builds on many journal papers and books cited in the references

at the end of each chapter, which is at best representative but by no means

exhaustive. Many references are made in the text to websites that serve as

references and as sources of complimentary information. As most users of

the Internet know, uniform resource locators (URLs) are often changed,

while some are even dropped and removed. We have strived

make these

current as possible, but as time progresses some will disappear or otherwise

be altered without our knowledge.

This book cites more than

1300

references. Some useful computer pro-

gram codes and valuable datasets are also included in the CD-ROM for easy

reference.

ACKNOWLEDGMENTS

Many people substantially contributed to this book, both directly and indi-

rectly. First and foremost,

am greatly indebted to Professors Alan Strahler

at Boston University and John Townshend at the University of Maryland for

their consistent encouragement and guidance. Parts

the

book

were written

during my sabbatical leave while visiting the Center for Remote Sensing and

Geographic Information Science, Beijing Normal University (BNU), China;

the Earth Ohervation Research Center, National Space Development Agency

of Japan (NASDA); CSIRO Land and Water at Canberra, Australia; and

USDA Beltsville Agricultural Research Service (BARC), Maryland. I greatly

appreciate all the support from Professors Xiaowen Li, Qijiang Zhu, and

Jindi Wang at BNU; Dr. Tamotsu Igarashi at NASDA; Dr. Tim McVicar at

CSIRO; and Drs. Craig Daughtry and Charlie Walthall at BARC. I’d like to

thank Drs. Mat Disney, Philip Lewis, and David Jupp for their kindly

providing me with some of the illustrations used in this book, and my

co-authors of the journal papers that largely build this book. I am indebted to

my students who made great contributions to this book, particularly Chad

Shuey, Hongliang Fang, and Lynn Thorp for their help in preparing the

manuscript.

gratefully acknowledge the assistance of George Telecki (Edi-

tor), Rosalyn Farkas (Production Editor), and other staff at Wiley. I would

also like to acknowledge the research funding support from several agencies,

particularly from NASA through its Terrestrial Ecology,

EOS,

EO-1

and

other programs. Finally,

would like to express my most heartfelt thanks to

my lovely wife, Jie, for her endless support and encouragement. Without her

sacrifice,

his project would never come to the end.

SHUNLIN

LIANG

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