Applications of remote sensing in the areas of crop identification, range management, forest management and soil mapping are summarized

Baldwin, R.

English

NASA Technical Reports Server

I. Agriculture
Richard Baldwin0
N76-17614
INTRODUCTION
The United States has always been able to meet its
demands for food, fiber, and timber. There was always
more land to cultivate; fertilizers and other agricultural
chemicals have increased the food producing capacity of
land already under cultivation; hybrids and new plant
strains grow faster, produce more, or are hardier; and
cheap energy has replaced horsepower to operate
mechanized farm equipment, which has replaced much
manpower. !
For the future, one important new tool is remote
sensing. It has potential applications in four areas: crop
reporting, range management, forest management, and
soils surveys.
APPLICATIONS
Users and potential users include persons who are
oriented to applications research, .those who are
implementing remotely sensed data into their
operations, and government or managerial people who
require various levels of information for their
decisionmaking. Several levels of information that can be
extracted from remotely sensed data and a number of
applications for the information have been identified.
Much of this information can be acquired at a relatively
low cost per acre.
Crop Reporting
Several papers reported the ability to identify crops
and to inventory acreages, as well as to spot areas of
plant damage (by weather, insects, or disease), using
processing techniques on Landsat data.
In one test area composed of small grains (95 percent
wheat), sod, and fallow land, remote-sensing techniques
identified the small grains with 9,8 to 99 percent
accuracy, sod with 96 to 97 percent accuracy, and
fallow land with 91 percent accuracy. This success
encourages a broader use of Landsat data (when
combined with information on soils, weather, and
previous crop yields) to supplement nationwide or
perhaps even worldwide estimates of crop production. A
need exists for such information on a worldwide basis to
improve the orderly marketing of feed and grain supplies
and to provide early warning signals for distress so that
corrective action can be taken in various parts of the
world.
For that purpose, a large area crop inventory
experiment (LACIE) has been undertaken jointly by the
U.S. Department of Agriculture (USDA), the National
Oceanic and Atmospheric Administration (NOAA), and
the National Aeronautics and Space Administration. The
LACIE effort is concentrated on the application of
remote-sensing technology to locate, identify, and
measure wheat acreage. (Wheat was chosen as the
experimental crop because of its importance in human
nutrition and international trade.) The experiment will
combine crop area measurements obtained from Landsat
data and meteorological information from NOAA
satellites and ground stations, designed to relate weather
to yield assessment and, ultimately, to production
forecasts. The USDA will study incorporation of the
experimentally derived production estimates into its
crop reports. If the activity is successful and the results
prove useful, the application will be extended
geographically and, ultimately, to other crops.
In another potential worldwide application, Landsat
data have been used in field trials for mapping natural
vegetation at a scale of 1:1 000 000. The United Nations
Educational, Scientific, and Cultural Organization has
established a uniform classification system that can be
used more or less directly with Landsat-generated maps
because of the small scale. The theory is that natural
vegetation is the best clue to the cultivated crops an area
will optimally support.
Cargill, Incorporated, Minneapolis, Minnesota.
https://ntrs.nasa.gov/search.jsp?R=19760010526 2020-03-22T16:14:16+00:00Z
Range Management
Techniques for estimating and predicting the available
forage for range animal consumption were demonstrated
in several major rangeland areas. The sandhills region in
Nebraska is a unique area for using Landsat data in
estimating vegetative biomass for managing this 20 000
square statute miles (52 000 square kilometers) of
rangeland. The uniform soils of this area minimize the
variances in radiance caused by soils variability.
Correlation coefficients of 0.9 for radiances to biomass
were achieved using band 5 of the multispectral scanner
and automatic data processing methods. The ability to
monitor annual grasslands was demonstrated in the
intermountain region of California. By use of Landsat
data, the investigator was able to correlate plant growth
stages and forage production with climatic and other
environmental factors. Image characteristics and spectral
reflectance data were then related to forage production,
range condition, range site, and changing growth
conditions.
Landsat data appear to be adequate to determine,
with a high degree of confidence, the available forage in
selected rangelands. This information could be of great
value to range management agencies (such as the Bureau
of Land Management, the Forest Service, or regional
groups) in determining how many animal units can be
put on a specific piece of rangeland and when to take
them off. For this use, the data are needed promptly
(within 5 to 10 days after collection) and frequently (at
9-day intervals). An operational system needs to be
devised and implemented to test this demonstrated
technology for cost effectiveness and feasibility for
full-scale ongoing operations.
Forest Management
Forest lands, both public and privately owned, also
cover large areas, and efficient management is essential
to capture their greatest productive capacity. Speakers
discussing forest-related applications demonstrated
various ways of converting data from Landsat and
high-altitude sensors to useful information.
One speaker showed how the data were used to
update maps of clear-cut forest areas, to map cutting
rates, and to better manage forest areas. A representative
of a large paper and timber company described how, on
a limited budget, his company was developing simple
techniques to help determine the location, type,
quantity, and quality of available timber supplies.
Another speaker demonstrated how Landsat data can be
used to classify timber with as high as 95 percent
accuracy for types of trees and as high as 80 percent
accuracy in defining the conditions of the forest stand.
Landsat data were converted to information depicting
the available fuel for sustaining fires in the Santa Monica
Mountains in southern California. Here, 1.25 million
acres were mapped for a cost of less than 3 cents per
acre. This information was used as input to an
operational model, which aids in reducing and
controlling forest fires and in preserving the forest.
The results of a study of gypsy moth infestation
demonstrated that Landsat data can be used to
discriminate between defoliated and healthy vegetation
in Pennsylvania and that digital processing methods can
be used to map the extent and degree of defoliation.
Soils Surveys
Soils mapping, from a broad synoptic view down to
the soil association level, was demonstrated in the papers
presented. Soils mapping was used to help satisfy state
tax legislation in South Dakota. Soils association maps
keyed to productive capacities and land values were
developed for the state. Cost for producing such
low-intensity surveys was approximately 2 cents per
hectare.
At the Purdue University Laboratory for Applications
of Remote Sensing, digital data were analyzed to
identify a specific soil association that had not been
detected in previous soil surveys. This soil association
was a continuity of a narrow, meandering strip of prairie
soil in an area of predominantly timber soils. It is
believed to be a buried valley of the glacial age.
These examples demonstrate that first-echelon soil
mapping can be done from satellite data at a very low
cost per unit area. Of course, supporting classes of soils
must be mapped in the conventional manner.
Skylab data were used to delineate possible avenues
of travel of citrus pests between Mexico and the United
States. Also identified through Skylab S190B data were
various crops and frost damage.
A speaker described how his company used remotely
sensed data to manage various crops, especially cotton,
in an effort to get an early determination of plant stress,
disease, weed or insect infestation, and faulty irrigation.
With such information on a timely basis, corrective
action can be taken soon enough to actually improve the
yields. It was stressed that such applications, to be
useful, must be cost effective and very timely.
CONCLUSIONS
The workshop participants generally agreed that the
technology exists to extract useful information, but
several problems must be overcome before an
operational system can be implemented. First, one must
remember that remotely sensed data do not provide a
total information base but are complementary to
existing systems. One of the biggest tasks ahead is to
design the optimum information mix for each user need.
Second, the data should be supplied to a user in a format
and quantity for his particular needs and parameters,
rather than being supplied in bulk and excessive to his
needs. Furthermore, costs to the user must be realistic.
The timeliness of data is probably the most critical
problem inhibiting the implementation of an operational
system. Those dynamic applications requiring data
within 9 days of acquisition cannot be functional at this
time. By contrast, applications requiring data seasonally
or annually can be implemented immediately.
It appears that organizations which acquire and
supply data must work in conjunction with those who
extract information and those who use it to identify the
best information, format, analysis system, and time
frame for each potential application.
Interest is high in generating useful information from
remote-sensing data for all four areas of agriculture. The
technology does exist and it can be a valuable tool in
producing and distributing food, fiber, and timber to a
growing population.


Agriculture

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