PHOTOGRAMMETRIC ENGINEERING
& REMOTE SENSING
J
ournal
S
taff
Publisher
Dr. Michael Hauck
Editor
Russell G. Congalton
Technical Editor
Michael S. Renslow
Assistant Editor
Jie Shan
Assistant Director — Publications
Rae Kelley
Electronic Publications Manager/Graphic Artist
Matthew Austin
Photogrammetric Engineering & Remote Sensing
is the official journal
of the American Society for Photogrammetry and Remote Sensing. It is
devoted to the exchange of ideas and information about the applications of
photogrammetry, remote sensing, and geographic information systems. The
technical activities of the Society are conducted through the following Technical
Divisions: Geographic Information Systems, Photogrammetric Applications,
Lidar, Primary Data Acquisition, Professional Practice, and Remote Sensing
Applications. Additional information on the functioning of the Technical
Divisions and the Society can be found in the Yearbook issue of
PE&RS
.
Correspondence relating to all business and editorial matters pertaining to
this and other Society publications should be directed to the American Society
for Photogrammetry and Remote Sensing, 5410 Grosvenor Lane, Suite 210,
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PE&RS.
PE&RS
(ISSN0099-1112) is published monthly by the American
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COPYRIGHT 2014
. Copyright by the American Society for Photogrammetry
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LETTER FROM ANATOLY A.
GITELSON, TECHNION—ISRAEL
INSTITUTE OF TECHNOLOGY
Dear Readers,
Application of remotely sensed data into
agriculturaldecisionsisnotanewconcept.
Over the past 30 years there have been
several demonstrated accomplishments
that used remotely sensed data for field-
and regional-scale assessments. This
special issue “Hyperspectral Remote
Sensing of Vegetation and Agricultural
Crops” presents the current status and
understanding of how hyperspectral
remote sensing can be used for
classifying, modelling, mapping, and
monitoring crop status. Among problems
of crop monitoring discussed in the issue,
the most important one, in my view, is
finding specific spectral bands where
crop reflectance is maximally sensitive
to the biophysical characteristics of
interest (e.g., green LAI, yield, vegetation
fraction and fraction of absorbed
photosynthetically active radiation)
and minimally affected by other factors
(sun elevation, soil background, crop
bidirectional reflectance factor, among
others). To address these problems,
hyperspectral data are essential.
Properly processed and interpreted,
hyperspectral data make it possible
to develop physically-based models to
quantify cropbiophysical andbiochemical
properties. This issue includes papers in
different areas supporting science of crop
monitoring, specifically, development of
(1) vegetation indices to estimate crop
biophysical characteristics; (2) technics
for reduction of data dimensionality; (3)
spectral libraries of vegetation; and (4)
automatedmethods of hyperspectral data
analysis. The issue documents numerous
practical applications of hyperspectral
remote sensing for crop monitoring from
local to global scales. It provides broad
coverage of the research and applications
of high spectral resolutionmeasurements
for vegetation mapping, monitoring and
analysis and surely will increase the
research communities’ understanding of
how to use hyperspectral data for crop
monitoring.
Anatoly A. Gitelson
Technion - Israel Institute of Technology
696
August 2014
PHOTOGRAMMETRIC ENGINEERING & REMOTE SENSING
