PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
May 2017
335
BOOK
REVIEW
Remote Sensing of the Terrestrial Water
Cycle
Venkataraman Lakshmi
American Geophysical Union and Wiley 2014, 576 pp, photos,
index. Hardback $206, ISBN-13: 978-1118872031, ISBN-10:
1118872037.
Reviewed by:
Melissa J. Rura Ph.D. Contributing
Editor,
Photogrammetric Engineering & Remote
Sensing
(
PE&RS
).
This collection from the American Geophysical Union
(AGU) brings together research and researchers from across
disciplines and the world to examine the how satellite data
is used to expand our knowledge about the terrestrial water
cycle and quantify its spatial and temporal variations. This
particular text comes directly from the AGU Chapman
Conference on Remote Sensing of the Terrestrial Water Cycle
held in February 2012.
This book is one Monograph (206) in the Geophysical
Monograph Series published by Wiley in cooperation with the
AGU. In particular, the book is divided into seven sections
all of which relate directly to the terrestrial water cycle.
Each individual chapter within each section is independent
research contributed by different researchers that are grouped
together by topic that do not necessarily and generally do not
build upon each more comparable in the world of fiction to
short stories than a novel and should be read as such.
Section 1 addresses the remote sensing of precipitation with
two literature reviews, the first on Rain / no rain classification
(RNC) algorithms based on passive microwave sensors and the
second review is on the Climate Prediction Center Morphing
(CMORPH) techniques including the development and future
directions. An application chapter considers work to improve
the measure of precipitation in mountainous regions through
research using Global Satellite Mapping (GSMap) algorithm
and Tropical Rainfall Measuring Mission (TRMM) microwave
imager (TMI). Finally, there is a discussion of quantitative
precipitation estimates (QPEs) for error characterization and
quantification in terms of the TRMM and Global Precipitation
Measurement Mission (GPM).
Section 2 addresses the remote sensing of evapotranspiration
(ET) with two case-studies. The first case-study uses the
3Temp. model to ET based on Moderate Resolution Imaging
Spectroradiometer (MODIS) data. It tests this method
regionally, also looking for spatial and temporal trends within
the Jinghe River Basin in the southern part of the Loess Plateau
in China. The second case-study centered in the Lower-Colorado
River Basin in a region of interest in southern California looked
at ET using a Remotely Sensed Energy Balance (RSEB) model
to investigate effects on the invasive Tamarisk species.
Section 3 addresses surface water remote sensing. The first
chapter is a case study looking at the Central Congo Basin’s
Terrestrial Water Storage (TWS) changes using multiple
satellite measures including, among others, the Gravity
Recovery And Climate Change Experiment (GRACE) mission
data. Chapter 10, Downstream Hydraulic Geometry (DHG)
estimates are derived for the entire Yukon River Basin using
software designed to measure river widths through algorithms
applied to imagery data in conjunction with Digital Elevation
Model (DEM) discharge estimates. The final chapter in this
section is a report from the Jet Propulsion Lab on ongoing
Surface Water Ocean Topography (SWOT) research. This
particular study repurposed of the Terminal Descent Sensor
(TDS) from the Mars Science Laboratory, which is a 35.75
GHz Dopplar Radar. This repurposed Ka- band radar was
deployed in bridge based river observations and preceded
KaSPAR airborne radar.
Section 4 addresses remote sensing of snow and the sensors
best suited for its detection. The first chapter is a literature
review of snow cover depletion in hydrologic applications and the
change in remotely sensed data, its uses, and how it has changed
the understanding of, especially snow extent measures. Next, a
chapter discussing snow cover observations using the Visible /
Photogrammetric Engineering & Remote Sensing
Vol. 83, No. 5, May 2017, pp. 335–336.
0099-1112/17/335–336
© 2017 American Society for Photogrammetry
and Remote Sensing
doi: 10.14358/PERS.83.5.335
