Steffen Kuntz
      Abteilung Luftbildmessung und Fernerkundung, Universitat Freiburg,
                   Werderring 6, D-79098 Freiburg, Germany
                               Christoph Kleinn
            Abteilung Forstliche Biometrie, Universitat Freiburg,
                   Werderring 6, D-79098 Freiburg, Germany

ABSTRACT:  At the beginning of 1990, two hurricanes caused the largest storm
damages ever known in the forests of Middle Europe with a total of about 73
million cubic meters of broken wood.  The survey of the damage situation was
mainly done by field survey and frequently in conjunction with aerial
photography utilizing local experience.  At the same time, a pilot project was
carried out to investigate the possibilites of using satellite remote sensing,
Landsat TM (Thematic Mapper), to assess the area of storm damages.  Some
results of this study are given here.  Due to the heterogeneity of the storm
damage area class and the properties of Landsat TM with respect to spatial and
spectral resolution and due to organizational aspects, there are still many
problems that inhibit a standard application of this technique at present.

                          STUDY AREA AND OBJECTIVES

   At the beginning of 1990, two hurricances caused the largest storm damages
ever known in the forests of Middle Europe.  The forest services had to solve
problems of a magnitude not known until then.  In the western states of
Germany the damage was about 73 million cubic meters of broken wood, which is
almost twice as much as the regular annual allowable cut under a regime of
sustainable yield.  The damages were not spread evenly over the entire region
but were concentrated in only some areas, depending on topography, stand
structure and other local factors.

   It was one of the most important issues for the forest administration to
get a timely overview of the situation, i.e., of the extent and distribution
of the damages.  Obtaining reliable information was necessary to plan and
organize the logging and wood market activities.  Two different levels of
information are required then:  for forest policy considerations overall
statistics may be sufficient, but for the planning of the processing
activities spatial information is required.   Figure 1 shows the storm damage
pattern in a window of the study region.  The study region has a size of about
25 x 25 km and is located in the northern Black Forest.  One sees that the
damaged areas have considerable variation in size and spread more or less over
the entire area, while the overall percentage of damaged areas in the entire
region is relatively small, less than 1% in this case.  The variable of
damaged area, therefore, can be regarded as a 'rare event' - at least from the
sampling point of view.  Sampling procedures for area assessment are critical
under these circumstances as highly fragmented areas with a low percent have
relatively large sampling errors and therefore require considerable efforts to
obtain satisfactory results (Kleinn, 1990).  On the other hand, maps are
required for planning activities that can hardly be produced by sampling

   Remote sensing can provide large area information in a short time and give
a complete coverage of the region of interest that can in many cases be used
to produce maps.  Most states in Germany used aerial photographs for an
operational storm damage assessment.  In conjunction with these activities,
interviews and field survey activities were evaluated using local knowledge of
the foresters.  The general demand of the state forest service was to obtain
an overview of the situation within 3 weeks period to be able to adjust
management planning.

   Another idea was to utilize satellite imagery which is available at even
lower cost for large areas.  No experience in the state forest service was
available on the application of Landsat TM for storm damage assessment.
Therefore the government of the state of Baden-Wurttemberg supported a pilot
study to test the possibilites and to find out the limitations of this
technique.  The objectives of this study thus are strongly oriented towards an
operational use of satellite imagery for storm damage area assessment.

   'Storm damage area' is a wide land cover category covering the transition
between few single broken trees per hectare and completely broken stands.  To
get an operational definition for satellite remote sensing of what is to be
considered 'storm damage area', in this study a storm damage area was defined
as one which is completely or almost completely broken, which means that
the crown cover is less than 40%.  As in the study area only closed forests
exist, reduction of crown coverage means either human logging activities or
any catastrophic event.

                            MATERIALS AND METHODS

   The study area is situated in the northern Black Forest.  It corresponds to
one map sheet of the topographic map at 1:50,000 scale and has an extent of
about 25 x 25 km (map sheet L7316, Wildbad).  It was known previously that
this area was affected severely by the two hurricanes.  Earlier studies
(Rahlmann, 1991) showed that mainly due to the heterogeneity of the storm
damage area class only a multitemporal approach allows reliable identification
of storm damage areas.  Three Landsat 5 TM images, dated July 1987, March 1990
and July 1990, were available for the study.

   No automatic classification procedure was adopted, as Fritz (1991) showed
that due to the limited geometric and radiometric resolution and again due to
the heterogeneity of the storm damage area class an automatic classification
cannot be operational.  Even within storm damage areas, the variation of the
pixel values is considerable and it seems that 7 spectral bands are not
sufficient to properly recognize the target areas by standard automatic
classification procedures.  The areas were therefore delineated visually at
the monitor; which of course requires well trained staff.  The data processing
and map producing procedure consisted of several steps as listed in the
following.  The map production used, as sources of information, the multi-
temporal Landsat TM images and some known damage areas that served as training

#1  Geometrical correction and transformation to the geodetic coordinate
    system (Gauss-Kruger).

#2  Selection of optimal combination of spectral bands to represent damage
    areas in the image processor (some known damage areas were used as
    training areas for this purpose).

#3  Contrast stretching and edge enhancement for optimization of image

#4  Visual delineation of storm damaged areas.

#5  Map production from satellite image interpretation and ancillary
    information (layers of the digitized topographic map, available from
    the state geodetic survey).

   This procedure was adopted for the entire Landsat scene within a 4 weeks
period after having received the satellite images, and produced a complete
coverage of the inventory region.  The most time consuming jobs are the
correction procedures in step 1 and the final map production in step 5.  The
delineation of the storm affected areas itself in the 25 x 25 km window (study
area) took the experienced interpreter about two work days.  These time
figures, however, are experiences from the study region only.  Identification
and delineation depends very much on the local situation.


   Map accuracy with respect to the target information is one of the most
important aspects in map production.  The accuracy assessment of products
that have been created with non-statistical techniques can only be carried out
knowing the true data.  To obtain the truth about the storm damaged areas, 64
orthophotos of scale 1:10,000 of the study region dating from summer 1990 were
used to delineate the storm damaged areas.  The damages were very well visible
in these images.  There were 241 areas found and digitized, with area sizes
between 0.1 ha and 66.5 ha.  Several field checks and checks with local
foresters, refering to size and location of the damage areas, determined that
there were only negligible deviations between the aerial photography
delineation and the field situation.  The map window shown in  Figure 1  is
based on the orthophotos, and the corresponding distribution of area sizes is
given in  Figure 2.  It can be seen that the major part of the storm damaged
areas have small extent.  With respect to this situation, one has to keep in
mind that the spatial resolution of Landsat is about 30 x 30 meters and
therefore recognition of very small areas poses technical problems.

   Table 1 compares the total number of areas and total area for the
evaluation of the satellite imagery and the aerial photography.  The number of
areas is very close, but the size of the damaged areas is overestimated by
about 20% through the satellite image interpretation, though in the satellite
image the small areas delineated in the orthophotos can not be identified.
The overestimation can partly be explained by the properties of the sensors.
There is a high percentage of mixed pixels, as they generally occur in highly
fragmented area structures; and as the damaged areas normally appear markedly
lighter than the surrounding closed forests, the mixed pixels tend to be
classified as damaged area (Kuntz, 1991).

Table 1.  Summary of results of the interpretation of aerial photographs
          and the satellite imagery.

Method             Number of damaged areas       Size of damaged areas
------             -----------------------       ---------------------

Satellite                    243                         580 ha

Airphotos                    241                         483 ha

   There are several categories of undamaged areas wrongly classified as
damaged, such as rocks and less dense old stands with mostly high quality
timber (Table 2).  Of the damaged stands, 81% were identified and classified
correctly (390 ha) in the satellite image.

Table 2.  List of categories interpreted in the satellite imagery, number of
          areas and (in parentheses) the corresponding size of the areas.

Recognized as      243            Not recognized      54
damaged areas                     damaged areas       (29 ha)
Damaged areas      187 (390 ha)

Rocks on ground      6 (  5 ha)

Low stocked areas   13 ( 16 ha)

Road intersections   8 (  6 ha)

Very young stands   17 ( 23 ha)

Low stocked         12 ( 14 ha)
old stands

                          DISCUSSION AND CONCLUSIONS

   There are several problems that generally exist with the application of
remote sensing surveys after catastrophes:

- The situation after the catastrophe changes very fast, especially in regions
  with intensively managed forests.  The goal of the forest services is here
  to process the broken wood as fast as possible, and it can happen that a
  remotely sensed survey after perhaps two months will give a highly biased
  figure relative to the true extent of the catastrophe.

- When there are several catastrophic events in the same area, possibly with
  different causes like snow damage and storm damage, it can be very difficult
  to make a proper distinction if no additional information is available.

- With respect to satellite remote sensing, the availability of the images
  may be a bottleneck.  It is not guaranteed that suitable imagery will be
  available in the time immediately after a catastrophe.  Cloud cover is a
  severe problem as storms normally are connected with a cloud covered sky.

- A general restriction to the use of Landsat TM is that the overflight is at
  9:30 hrs Central European Time. Because of the shadow problem, the
  application of these data in mountainous areas is limited to the summertime.
  However, storm damages occur mostly in winter in Central Europe.

- In the study area there is a pattern of storm damaged areas with a large
  number of small areas.  The geometrical resolution of Landsat TM of 30 x 30
  meters means that only areas of about 1 hectare and larger can be clearly
  recognized.  As many of the damaged areas in the study are smaller than
  1 hectare, application of Landsat imagery is marginal.

- Also critical is the misinterpretation of old hardwood stands, forest roads,
  and rocky ground as damaged.  The spectral reflectance of areas where the
  ground is visible through the canopy layer is similar to that of damaged
  areas.  This problem can only be solved by processing additional information
  as could reside in geographic information systems.

   As a general conclusion, it can be stated that, at present, it is not
possible to fully make use of the advantages of satellite imagery in the
context of storm damage assessments under the situation in the study area.

                               LITERATURE CITED

Fritz, R.  1991.  Digitale Waldkarte und Kartierung der Sturmschaden 1990
   mit Landsat-TM Daten fur das Forstamt Bebenhausen.  Unpublished thesis,
   Forestry Faculty, University of Freiburg, Germany.

Kleinn, C.  1990.  Estimating the areas of irregular-shaped objects by dot
   counts.  In:  Proceedings of the International IUFRO S.4.02 and S.6.04
   Symposium on Forest Inventories in Europe with Special Reference to
   Statistical Methods, May 14-16, 1990, Birmensdorf, Switzerland.

Kuntz, S.  1991.  Anwendung von Satellitenbildern zur Erfassung und
   Kartierung von Sturmschaden.  In:  Oesten, G., S. Kuntz und C. P. Gross,
   Eds.  Fernerkundung in der Forstwirtschaft - Stand und Entwicklungen.
   Wichmann-Verlag, Karlsruhe, Germany.

Kuntz, S. & C. Zimmermann.  1993.  Erfassung von Sturmschaden im nordlichen
   Schwarzwald mit Satellitendaten.  AFJZ, accepted, in press.

Rahlmann, H.  1991.  Visuelle Interpretation van Sturmschaden anhand von
   Landsat-TM Daten am Beispiel des Schonbuchs der Forstdirektion Tubingen.
   Unpublished thesis, Forestry Faculty, University of Freiburg, Germany.

Zimmermann, C.  1992.  Kartierung von Sturmschaden im mittleren Schwarzwald
   mit Landsat-TM Daten.  Unpublished thesis, Forestry Faculty, University
   of Freiburg, Germany.