- Email: [email protected]
Deterioration of forests in the Sudety Mountains, Poland, detected on satellite images
Environmental Pollution, Vol. 98, No. 3, pp. 375±379, 1997 # 1997 Elsevier Science Ltd. All rights reserved Printed in Great Britain PII: S0269-7491(97)00146-2 0269-7491/97 $17.00+0.00
DETERIORATION OF FORESTS IN THE SUDETY MOUNTAINS, POLAND, DETECTED ON SATELLITE IMAGES Zbigniew Bochenek, Andrzej Ciolkosz and Maria Iracka Institute of Geodesy and Cartography, Remote Sensing and Spatial Information CentreÐOPOLIS, u1. Jasna 2/4, 00-950 Warsaw, Poland
Abstract Dierent methods of classi®cation of satellite images were analyzed in order to derive information on the state of forests heavily aected by air pollution in southwestern Poland. Detailed information about type and quality of stands, derived from ®eld inventories and aerial color infrared photographs, was used for assessing the accuracy of classi®cation of satellite data. Using Landsat Thematic Mapper images, the characteristics of health conditions, structure of stands, three levels of damage and various phenomena could be determined that indicate forest decline. Comparison of the classi®ed images with forest maps revealed class correspondence between satellite data and those derived from forest maps. Major changes were detected between 1976 and 1990. # 1997 Elsevier Science Ltd. All rights reserved
dead and dying trees based on changes in crown color. By determining the percentage of dead and dying trees in a given stand, ®ve categories of damage to pine forest were recognized and a number of maps were published on the state of forest health in dierent regions of Poland (Ciolkosz et al., 1987). Damage in some forests has become so extensive that it was decided to use satellite images in the investigation of the problem, including Landsat Multiple Spectral Scanner and Thematic Mapper and SPOT images, as well as Cosmos space photographs. After several attempts it turned out that the Landsat TM images have been the best source of information for this type of investigation. This paper discusses the use of satellite images to classify air pollution damage to forests in southwestern Poland.
Keywords: Remote sensing, satellite images, forests, damage, pollution.
MATERIALS AND METHODS Study area The study site covers the western part of the Sudety Mountains, in the Karkonosze and Izerskie Ranges, containing a large forest complex of spruce (Picea abies). The Sudety Mountains, located on the borders of Poland, Germany, and the Czech Republic, were chosen as a test site because forests at this region in Poland are seriously damaged (Ciolkosz and Zawila-Niedzwiecki, 1990). Forest degradation is caused by a concentration of brown coal open-pit mines and electric power stations emitting a large volume of pollutants into the atmosphere. The damage is so severe that the region has been considered an ecological disaster called the ``Black Triangle''.
INTRODUCTION Air pollution in Europe increases as a function of prevailing wind direction from southwest to northeast. This explains why pollution originating in southern and western Europe accumulates in Poland. Poland itself contributes signi®cantly to total air pollution, adding high amounts of pollutants from fuel and power industries, means of transport, and from fossil fuel-heated homes. The majority of Polish forests were contained within the zones of slight and moderate impact of SO2 (yearly average concentration 20±60 g mÿ3) with slight and moderate damage to trees. Quite large areas of forest also occur within the zones of severe damage (yearly SO2 average concentration higher than 60 gÿ3). Methods applied by foresters to determine forest damage have been based on analysis of the morphological changes in needles and tree growth. In the 1980s the Remote Sensing and Spatial Information Centre (OPOLIS) in Poland applied remote sensing to determine the extent of damage to pine and spruce stands. In the beginning of the project, color infrared aerial photographs were used to detect damage to pine stands caused by air pollution. It was possible to distinguish
Satellite image systems The ®rst stage of the study examined the usefulness of high-resolution satellite images for classifying health conditions of forests, species composition, and other forest phenomena (clear-cuts, open canopy closure, etc.). In order to ful®l this task, Landsat TM data collected in July 1984 and in August 1990, as well as MSS images collected in May 1976, were selected. The analysis was done with the use of the ERDAS image processing system. This system enables interactive analysis of satellite images, i.e. radiometric and geometric correction, 375
376
Z. Bochenek et al.
location of training areas on satellite images, determination of spectral signatures, and data classi®cation. Field works and aerial photographs In order to determine relationships between ®eld characteristics of stands and their signatures on satellite images, ®eld evaluation of spruce stands was done at a preliminary stage of the study by using more than 500 ground sites. Field appraisal was performed on the basis of methods prepared by the Forestry Research Institute (Zawila-Niedzwiecki, 1994). Each ground site covered a homogeneous appraisal unit (1±10 ha), which was characterized through direct measurements and observations. The following information was collected in the ®eld: . Description of terrain conditions (type, relief, slope, aspect, type of cover and degree of coverage by rocks, stones, debris); . description of stand (structure, layer, species composition, age, form of mixing, closure, average breast-diameter, mean height, height of crown base, number of trees per unit area, including dying and dead trees); . evaluation of damage of stand (defoliation (Df), discoloration (Dc), quality of trees described by vigor of tree crown (Dm)). Defoliation and discoloration was evaluated in accordance with International Cooperation Program on Assessment and Monitoring Pollution Eects on Forests (ICP) recommendations, while quality of trees was assessed on the basis of the state of assimilatory apparatus, height increments, and vigor of trees. The numerous relations were studied between stand/ terrain characteristics and spatial signatures of stands, derived from Landsat TM satellite images, which included elevation/aspect information. The following conclusions were drawn from these studies (ZawilaNiedzwiecki, 1994): . Tree height and the height of tree crown base were lower while the elevation increased; trees of lower quality (moderately and heavily damaged stands) were more closely correlated with elevation than less damaged trees. . Spectral response in Landsat TM bands and some indices of quality of stands (Df, Dc, Dm) were signi®cantly correlated. The strongest relations were found for defoliation and quality index (vigor of trees), while discoloration was less correlated. Usually the relations are de®ned through multiple regression, which involved use of two to four spectral TM bands (most commonly visible near infrared and middle infrared bands). . Open canopy closure decreased the relationships between ground parameters and spectral signatures of stands. Hence, if relationships are diminished regionally, then this information was considered in the supervised classi®cation. Aerial color infrared photographs were the second source of reference information on stand characteristics.
These photographs were taken for large areas of the Karkonosze±Izerskie Range test area in 1984 by using Kodak Aerochrome Infrared ®lm. Detailed stereoscopic interpretation of the photographs resulted in classi®cation of four levels of damage of spruce stands, hardwoods and mixed stands, as well as various phenomena accompanying forest decline such as: (1) openings, (2) windbreaks and windfalls, (3) loose canopy closure, (4) aorestations, and (5) regenerations. The aerial photographs signi®cantly improved the analysis of satellite data. They made possible the determination of the spatial extent of the dierent factors characterized in the ®eld for the classi®cation of Landsat satellite images. Karkonosze±Izerskie Ranges test area Aerial color infrared photographs taken in July 1984 were the supplementary source of information on the state of forests within the study area. A map of forest health prepared from these photographs was used as a the reference for making appropriate selection of training and test areas and for supervised classi®cation of satellite data. The classi®cation was done by using Polish and foreign experience in the ®eld of analyzing forest areas on satellite images (Horler and Ahern, 1986; Rock et al., 1986; Williams and Nelson, 1986; Kadro, 1988; Zawila-Niedzwiecki, 1994). As a result of classi®cations, three maps of the test area were prepared on the basis of the 1984 TM image, 1990 TM image, and 1976 MSS image. After thorough analysis of TM data nine forest categories were distinguished: 1. 2. 3. 4. 5. 6. 7. 8. 9.
Healthy/slightly impaired spruce stands. Moderately impaired spruce stands. Heavily impaired spruce stands. Clear-cuts. Openings. Vegetated openings. Deciduous stands. Mixed stands. Dwarf mountain pine.
Classi®cation images based on 1990 satellite data reveals serious destruction of the forests at the western part of the study area. Extensive areas were totally deforested in this region. Three levels of deforestation were presented in the classi®cation image (Fig. 1): . Clear-cutsÐdeforestations with bare soil, i.e. the areas where dead trees were recently removed; . openingsÐdeforestations with some decayed trees and sparse vegetation; . vegetated openingsÐold deforestations already covered with grass, shrubs, and regeneration. Deforestations also cover large areas outside of Poland (in the Czech Republic), bright patches on the map (Fig. 1). For other forest classes, quite healthy and slightly damaged forests cover only small valley areas. Dying
Deterioration of forests in the Sudety Mountains, Poland and dead stands can be still be seen on the classi®cation image, but these areas will also be deforested in the near future. Distinct strati®cation of the study area can be observed in the eastern region as a larger contribution of slightly and moderately impaired stands, and in the western region as heavily deforested. In order to assess the dynamics of forest destruction, the 1976 Landsat MSS image was analyzed. Despite the coarser resolution of that image compared to TM imagery, three levels of damage to spruce stands were discriminated, as well as openings and non-coniferous categories (Fig. 2). Then comparing 1976 and 1990 classi®cation images (Figs 1 and 2) the extent and character of forest changes in this region may be presented. DISCUSSION OF RESULTS Comprehensive analysis of Landsat TM satellite images for 1976 and 1990 shows that spectral dierentiation of spruce stands in the Sudety Mountain region permits discrimination of three classes of forest quality. Class 1 includes healthy and slightly impaired stands, with a 30% loss of needles. Initial phases of spruce damage
377
cannot be separated from healthy stands with the use satellite data. Hence, training ®elds de®ning stands with loss of needles 0±30% should be treated as representative of one forest category. Accuracy of discriminating the succeeding classes of spruce damage (> 30%) is dependent on local conditions: canopy closure, soil cover, understorey vegetation, etc. For instance, if stands with open canopy closure contain openings with vegetation cover, the spectral signature for these stands changes towards a better class of quality. Generally, it is possible to distinguish heavily impaired stands with a 30±60% loss of needles, as well as dying and dead stands that have lost more than 60% of needles. Young coniferous stands were delineated well on satellite images from 1984. This class includes mainly spruce stands (and partly pine stands) at the age of 7±25 years, covering 9% of the Karkonosze and Izerskie Ranges test area. The other classes, which were marginally discerned on satellite images, i.e. grasslands and aorestations, were well-discriminated. Because aorestation areas cover about 7% of the total classi®ed area, this class signi®cantly characterized structure of the forest areas.
Fig. 1. Forest quality in the western Sudety Mountains in 1990.
378
Z. Bochenek et al.
The main forest categories were classi®ed with high accuracy, exceeding 80%. Although complex natural phenomena exist in the region we believe, that the analysis of both structure and health conditions of forest at the Sudety Mountains was accurate. Comparative analysis of two classi®ed images, Karkonosze and Izerskie Ranges, in 1984 and 1990 enabled an evaluation of qualitative changes in the forest. The primary changes were as follows (Zawila-Niedzwiecki, (1994):
determined from satellite data and stand characteristics shown in forest maps. Thus, the characteristics of stands, obtained from classi®cation of Landsat TM images, are suitable for large-area descriptions of health conditions and structure of stands in this region. Comparative analysis of 1976 and 1990 classi®cations enabled evaluation of the extent of deforestation within a 14-year period, as well as assessment of the changes of other forest categories. The following conclusions were drawn from this analysis:
. Increase in the area comprising moderately impaired spruce stands by 30%; . decrease in the area of dying and dead trees from 15 to 5%; . increase in the area of openings and clear-cuts from 8 to 15%, most notably in 1990.
. The area of healthy/slightly impaired stands was two times larger in 1976 than in 1990; . there was 2.5% more moderately impaired stands in 1990; . heavily impaired stands covered 5.5% less area in 1990; . the most signi®cant dierence was found for deforestations, covering 3.5 times more area in 1990 than in 1976.
The comparison of the classi®ed image with forest maps revealed good consistency between the classes
Fig. 2. Forest status in the western Sudety Mountains in 1976 (prior to the air pollution-related extensive damage of forest stands).
Deterioration of forests in the Sudety Mountains, Poland
379
Table 1. Comparison of the area of forest classes in the western Sudety Forest category
Area (ha) MSS 1976
Healthy/slightly impaired spruce stands Moderately impaired spruce stands Heavily impaired spruce stands Mixed stands Deciduous stands Vegetated openings Openings Clear-cuts
The deforestation category is spectrally homogeneous on the 1976 MSS classi®cation image, but it is dierentiated on 1990 TM image. Hence, we decided to distinguish three classes within this category characterized by various vegetation cover. Classi®cations from 1976 and 1990 were also compared in detail (Table 1). An analysis of forest quality with the use of Landsat satellite data has also been done for the eastern Sudety, for the Sowie and Stolowe Ranges. In this region heavy and moderate forest damage occurred only on relatively small areas, showing that these forests are less degraded than in western Sudety. Hence, the analysis was concentrated on dierentiating coniferous and deciduous stands, located on various forest sites. In summary, this research conducted at two test areas demonstrated the usefulness of Landsat TM satellite images for large-area classi®cation of forests. They also permitted an appraisal of the health conditions and structure of stands, enabling the evaluation of degradation processes that occurred between 1976 and 1990.
18 529 10 380 9938 8636 2497
(32.6%) (18.3%) (17.5%) (15.2%) (4.4%)
4894 (8.8%)
TM 1990 9919 11 792 6831 10 104 435 5528 6752 4434
(17.5%) (20.8%) (12.0%) (17.8%) (0.8%) (9.7%) (11.9%) (7.8%)
REFERENCES Ciolkosz, A., Iracka, M. and Zawila-Niedzwiecki, T. (1987) Monitoring of forest decline in Poland by remote sensing. In Proceedings of the Seminar on Remote Sensing and Forest Pollutants, 11±12 March 1987, International Institute for Applied System Analysis, EA-S715 Laxenburg, Austria. Ciolkosz, A. and Zawila-Niedzwiecki, T. (1990) Remotely sensed data and limitation of forest productivity in Poland. Nature and Resources 26(1), 41±44. Horler, D. N. H. and Ahern, F. J. (1986) Forestry information content of Thematic Mapper data. International Journal of Remote Sensing 7(3), 405±428. Kadro, A. (1988) Use of Landsat TM data for forest damage inventory. ESA Publishing, The Netherlands. Rock, B. N., Vogelmann, J. E., Williams, D. L., Vogelmann, A. F. and Hozhizaki, T. (1986) Remote detection of forest damage. Bioscience 36, 439±445. Williams, D. L. and Nelson, R. F. (1986) Use of remotely sensed data for assessing forest conditions in Eastern United States. IEEE Transactions on Geoscience and Remote Sensing 24, 1. Zawila-Niedzwiecki, T. (1994) Evaluation of forest state in threatened ecosystems with the use of satellite images and GIS (in Polish). In Proceedings of the Institute of Geodesy and Cartography, Warsaw, Poland. Vol. XLI, No. 90, 7±78.
DETERIORATION OF FORESTS IN THE SUDETY MOUNTAINS, POLAND, DETECTED ON SATELLITE IMAGES Zbigniew Bochenek, Andrzej Ciolkosz and Maria Iracka Institute of Geodesy and Cartography, Remote Sensing and Spatial Information CentreÐOPOLIS, u1. Jasna 2/4, 00-950 Warsaw, Poland
Abstract Dierent methods of classi®cation of satellite images were analyzed in order to derive information on the state of forests heavily aected by air pollution in southwestern Poland. Detailed information about type and quality of stands, derived from ®eld inventories and aerial color infrared photographs, was used for assessing the accuracy of classi®cation of satellite data. Using Landsat Thematic Mapper images, the characteristics of health conditions, structure of stands, three levels of damage and various phenomena could be determined that indicate forest decline. Comparison of the classi®ed images with forest maps revealed class correspondence between satellite data and those derived from forest maps. Major changes were detected between 1976 and 1990. # 1997 Elsevier Science Ltd. All rights reserved
dead and dying trees based on changes in crown color. By determining the percentage of dead and dying trees in a given stand, ®ve categories of damage to pine forest were recognized and a number of maps were published on the state of forest health in dierent regions of Poland (Ciolkosz et al., 1987). Damage in some forests has become so extensive that it was decided to use satellite images in the investigation of the problem, including Landsat Multiple Spectral Scanner and Thematic Mapper and SPOT images, as well as Cosmos space photographs. After several attempts it turned out that the Landsat TM images have been the best source of information for this type of investigation. This paper discusses the use of satellite images to classify air pollution damage to forests in southwestern Poland.
Keywords: Remote sensing, satellite images, forests, damage, pollution.
MATERIALS AND METHODS Study area The study site covers the western part of the Sudety Mountains, in the Karkonosze and Izerskie Ranges, containing a large forest complex of spruce (Picea abies). The Sudety Mountains, located on the borders of Poland, Germany, and the Czech Republic, were chosen as a test site because forests at this region in Poland are seriously damaged (Ciolkosz and Zawila-Niedzwiecki, 1990). Forest degradation is caused by a concentration of brown coal open-pit mines and electric power stations emitting a large volume of pollutants into the atmosphere. The damage is so severe that the region has been considered an ecological disaster called the ``Black Triangle''.
INTRODUCTION Air pollution in Europe increases as a function of prevailing wind direction from southwest to northeast. This explains why pollution originating in southern and western Europe accumulates in Poland. Poland itself contributes signi®cantly to total air pollution, adding high amounts of pollutants from fuel and power industries, means of transport, and from fossil fuel-heated homes. The majority of Polish forests were contained within the zones of slight and moderate impact of SO2 (yearly average concentration 20±60 g mÿ3) with slight and moderate damage to trees. Quite large areas of forest also occur within the zones of severe damage (yearly SO2 average concentration higher than 60 gÿ3). Methods applied by foresters to determine forest damage have been based on analysis of the morphological changes in needles and tree growth. In the 1980s the Remote Sensing and Spatial Information Centre (OPOLIS) in Poland applied remote sensing to determine the extent of damage to pine and spruce stands. In the beginning of the project, color infrared aerial photographs were used to detect damage to pine stands caused by air pollution. It was possible to distinguish
Satellite image systems The ®rst stage of the study examined the usefulness of high-resolution satellite images for classifying health conditions of forests, species composition, and other forest phenomena (clear-cuts, open canopy closure, etc.). In order to ful®l this task, Landsat TM data collected in July 1984 and in August 1990, as well as MSS images collected in May 1976, were selected. The analysis was done with the use of the ERDAS image processing system. This system enables interactive analysis of satellite images, i.e. radiometric and geometric correction, 375
376
Z. Bochenek et al.
location of training areas on satellite images, determination of spectral signatures, and data classi®cation. Field works and aerial photographs In order to determine relationships between ®eld characteristics of stands and their signatures on satellite images, ®eld evaluation of spruce stands was done at a preliminary stage of the study by using more than 500 ground sites. Field appraisal was performed on the basis of methods prepared by the Forestry Research Institute (Zawila-Niedzwiecki, 1994). Each ground site covered a homogeneous appraisal unit (1±10 ha), which was characterized through direct measurements and observations. The following information was collected in the ®eld: . Description of terrain conditions (type, relief, slope, aspect, type of cover and degree of coverage by rocks, stones, debris); . description of stand (structure, layer, species composition, age, form of mixing, closure, average breast-diameter, mean height, height of crown base, number of trees per unit area, including dying and dead trees); . evaluation of damage of stand (defoliation (Df), discoloration (Dc), quality of trees described by vigor of tree crown (Dm)). Defoliation and discoloration was evaluated in accordance with International Cooperation Program on Assessment and Monitoring Pollution Eects on Forests (ICP) recommendations, while quality of trees was assessed on the basis of the state of assimilatory apparatus, height increments, and vigor of trees. The numerous relations were studied between stand/ terrain characteristics and spatial signatures of stands, derived from Landsat TM satellite images, which included elevation/aspect information. The following conclusions were drawn from these studies (ZawilaNiedzwiecki, 1994): . Tree height and the height of tree crown base were lower while the elevation increased; trees of lower quality (moderately and heavily damaged stands) were more closely correlated with elevation than less damaged trees. . Spectral response in Landsat TM bands and some indices of quality of stands (Df, Dc, Dm) were signi®cantly correlated. The strongest relations were found for defoliation and quality index (vigor of trees), while discoloration was less correlated. Usually the relations are de®ned through multiple regression, which involved use of two to four spectral TM bands (most commonly visible near infrared and middle infrared bands). . Open canopy closure decreased the relationships between ground parameters and spectral signatures of stands. Hence, if relationships are diminished regionally, then this information was considered in the supervised classi®cation. Aerial color infrared photographs were the second source of reference information on stand characteristics.
These photographs were taken for large areas of the Karkonosze±Izerskie Range test area in 1984 by using Kodak Aerochrome Infrared ®lm. Detailed stereoscopic interpretation of the photographs resulted in classi®cation of four levels of damage of spruce stands, hardwoods and mixed stands, as well as various phenomena accompanying forest decline such as: (1) openings, (2) windbreaks and windfalls, (3) loose canopy closure, (4) aorestations, and (5) regenerations. The aerial photographs signi®cantly improved the analysis of satellite data. They made possible the determination of the spatial extent of the dierent factors characterized in the ®eld for the classi®cation of Landsat satellite images. Karkonosze±Izerskie Ranges test area Aerial color infrared photographs taken in July 1984 were the supplementary source of information on the state of forests within the study area. A map of forest health prepared from these photographs was used as a the reference for making appropriate selection of training and test areas and for supervised classi®cation of satellite data. The classi®cation was done by using Polish and foreign experience in the ®eld of analyzing forest areas on satellite images (Horler and Ahern, 1986; Rock et al., 1986; Williams and Nelson, 1986; Kadro, 1988; Zawila-Niedzwiecki, 1994). As a result of classi®cations, three maps of the test area were prepared on the basis of the 1984 TM image, 1990 TM image, and 1976 MSS image. After thorough analysis of TM data nine forest categories were distinguished: 1. 2. 3. 4. 5. 6. 7. 8. 9.
Healthy/slightly impaired spruce stands. Moderately impaired spruce stands. Heavily impaired spruce stands. Clear-cuts. Openings. Vegetated openings. Deciduous stands. Mixed stands. Dwarf mountain pine.
Classi®cation images based on 1990 satellite data reveals serious destruction of the forests at the western part of the study area. Extensive areas were totally deforested in this region. Three levels of deforestation were presented in the classi®cation image (Fig. 1): . Clear-cutsÐdeforestations with bare soil, i.e. the areas where dead trees were recently removed; . openingsÐdeforestations with some decayed trees and sparse vegetation; . vegetated openingsÐold deforestations already covered with grass, shrubs, and regeneration. Deforestations also cover large areas outside of Poland (in the Czech Republic), bright patches on the map (Fig. 1). For other forest classes, quite healthy and slightly damaged forests cover only small valley areas. Dying
Deterioration of forests in the Sudety Mountains, Poland and dead stands can be still be seen on the classi®cation image, but these areas will also be deforested in the near future. Distinct strati®cation of the study area can be observed in the eastern region as a larger contribution of slightly and moderately impaired stands, and in the western region as heavily deforested. In order to assess the dynamics of forest destruction, the 1976 Landsat MSS image was analyzed. Despite the coarser resolution of that image compared to TM imagery, three levels of damage to spruce stands were discriminated, as well as openings and non-coniferous categories (Fig. 2). Then comparing 1976 and 1990 classi®cation images (Figs 1 and 2) the extent and character of forest changes in this region may be presented. DISCUSSION OF RESULTS Comprehensive analysis of Landsat TM satellite images for 1976 and 1990 shows that spectral dierentiation of spruce stands in the Sudety Mountain region permits discrimination of three classes of forest quality. Class 1 includes healthy and slightly impaired stands, with a 30% loss of needles. Initial phases of spruce damage
377
cannot be separated from healthy stands with the use satellite data. Hence, training ®elds de®ning stands with loss of needles 0±30% should be treated as representative of one forest category. Accuracy of discriminating the succeeding classes of spruce damage (> 30%) is dependent on local conditions: canopy closure, soil cover, understorey vegetation, etc. For instance, if stands with open canopy closure contain openings with vegetation cover, the spectral signature for these stands changes towards a better class of quality. Generally, it is possible to distinguish heavily impaired stands with a 30±60% loss of needles, as well as dying and dead stands that have lost more than 60% of needles. Young coniferous stands were delineated well on satellite images from 1984. This class includes mainly spruce stands (and partly pine stands) at the age of 7±25 years, covering 9% of the Karkonosze and Izerskie Ranges test area. The other classes, which were marginally discerned on satellite images, i.e. grasslands and aorestations, were well-discriminated. Because aorestation areas cover about 7% of the total classi®ed area, this class signi®cantly characterized structure of the forest areas.
Fig. 1. Forest quality in the western Sudety Mountains in 1990.
378
Z. Bochenek et al.
The main forest categories were classi®ed with high accuracy, exceeding 80%. Although complex natural phenomena exist in the region we believe, that the analysis of both structure and health conditions of forest at the Sudety Mountains was accurate. Comparative analysis of two classi®ed images, Karkonosze and Izerskie Ranges, in 1984 and 1990 enabled an evaluation of qualitative changes in the forest. The primary changes were as follows (Zawila-Niedzwiecki, (1994):
determined from satellite data and stand characteristics shown in forest maps. Thus, the characteristics of stands, obtained from classi®cation of Landsat TM images, are suitable for large-area descriptions of health conditions and structure of stands in this region. Comparative analysis of 1976 and 1990 classi®cations enabled evaluation of the extent of deforestation within a 14-year period, as well as assessment of the changes of other forest categories. The following conclusions were drawn from this analysis:
. Increase in the area comprising moderately impaired spruce stands by 30%; . decrease in the area of dying and dead trees from 15 to 5%; . increase in the area of openings and clear-cuts from 8 to 15%, most notably in 1990.
. The area of healthy/slightly impaired stands was two times larger in 1976 than in 1990; . there was 2.5% more moderately impaired stands in 1990; . heavily impaired stands covered 5.5% less area in 1990; . the most signi®cant dierence was found for deforestations, covering 3.5 times more area in 1990 than in 1976.
The comparison of the classi®ed image with forest maps revealed good consistency between the classes
Fig. 2. Forest status in the western Sudety Mountains in 1976 (prior to the air pollution-related extensive damage of forest stands).
Deterioration of forests in the Sudety Mountains, Poland
379
Table 1. Comparison of the area of forest classes in the western Sudety Forest category
Area (ha) MSS 1976
Healthy/slightly impaired spruce stands Moderately impaired spruce stands Heavily impaired spruce stands Mixed stands Deciduous stands Vegetated openings Openings Clear-cuts
The deforestation category is spectrally homogeneous on the 1976 MSS classi®cation image, but it is dierentiated on 1990 TM image. Hence, we decided to distinguish three classes within this category characterized by various vegetation cover. Classi®cations from 1976 and 1990 were also compared in detail (Table 1). An analysis of forest quality with the use of Landsat satellite data has also been done for the eastern Sudety, for the Sowie and Stolowe Ranges. In this region heavy and moderate forest damage occurred only on relatively small areas, showing that these forests are less degraded than in western Sudety. Hence, the analysis was concentrated on dierentiating coniferous and deciduous stands, located on various forest sites. In summary, this research conducted at two test areas demonstrated the usefulness of Landsat TM satellite images for large-area classi®cation of forests. They also permitted an appraisal of the health conditions and structure of stands, enabling the evaluation of degradation processes that occurred between 1976 and 1990.
18 529 10 380 9938 8636 2497
(32.6%) (18.3%) (17.5%) (15.2%) (4.4%)
4894 (8.8%)
TM 1990 9919 11 792 6831 10 104 435 5528 6752 4434
(17.5%) (20.8%) (12.0%) (17.8%) (0.8%) (9.7%) (11.9%) (7.8%)
REFERENCES Ciolkosz, A., Iracka, M. and Zawila-Niedzwiecki, T. (1987) Monitoring of forest decline in Poland by remote sensing. In Proceedings of the Seminar on Remote Sensing and Forest Pollutants, 11±12 March 1987, International Institute for Applied System Analysis, EA-S715 Laxenburg, Austria. Ciolkosz, A. and Zawila-Niedzwiecki, T. (1990) Remotely sensed data and limitation of forest productivity in Poland. Nature and Resources 26(1), 41±44. Horler, D. N. H. and Ahern, F. J. (1986) Forestry information content of Thematic Mapper data. International Journal of Remote Sensing 7(3), 405±428. Kadro, A. (1988) Use of Landsat TM data for forest damage inventory. ESA Publishing, The Netherlands. Rock, B. N., Vogelmann, J. E., Williams, D. L., Vogelmann, A. F. and Hozhizaki, T. (1986) Remote detection of forest damage. Bioscience 36, 439±445. Williams, D. L. and Nelson, R. F. (1986) Use of remotely sensed data for assessing forest conditions in Eastern United States. IEEE Transactions on Geoscience and Remote Sensing 24, 1. Zawila-Niedzwiecki, T. (1994) Evaluation of forest state in threatened ecosystems with the use of satellite images and GIS (in Polish). In Proceedings of the Institute of Geodesy and Cartography, Warsaw, Poland. Vol. XLI, No. 90, 7±78.