detection and analysis of soil erodibility patterns using...

The Hydrology^Geoworphology Interface: Rainfall, Floods, Sedimentation, Land Use (Proceedings of the Jerusalem Conference, May 1999). IAHS Publ. no. 261, 2000. 127

Detection and analysis of soil erodibility patterns using air photographs of the Avisur Highlands, Israel

MAXIM SIIOSHANY Remote Sensing & GIS Laboratory, Geography Department, Bar-Ilan University, Ramat Can 52900, Israel e-mail: [email protected]

Abstract Quantitative use of historical black and white air photographs is presented for the study of soil erosion in semiarid regions. The methodology developed is based on known relationships between the brightness values in certain portions of the photographs, and the soil properties of organic matter content and aggregates size of corresponding soil patches. The image processing techniques applied include geometric corrections, mutual calibration of brightness values and multi-date classification. Results provide a better understanding of the general erosion trends and an insight into patterns of source-sink processes. Key words ecosystem recovery; GIS; Mediterranean ecosystems; patch dynamics; remote sensing; soil erodibility; source-sink processes

INTRODUCTION

Soil and vegetation losses are the most fundamental characteristics of desertification processes (Perez-Trejo, 1994). According to Yassoglou (1996), "... a land would be considered desertified, when its soil cannot supply sufficient water for the production of biomass that has some value for mankind". This perspective stresses that desertification must be considered within an holistic framework of human activity and vegetation and soil changes (Thornes, 1990). The intensity and extent of land degradation has attracted much attention in global change studies (Bolle, 1996) and the Mediterranean region (Hill et al, 1996). The contribution of a remote sensing top-down approach for investigating desertification, in addition to the traditional bottom-up approach based on fieldwork, is discussed by Imeson (1996). Important examples of relevant remote sensing studies are the works of De Jong (1994), who assessed the applicability of vegetation variables for monitoring soil erosion, and Pickup & Chewings (1988) who developed a soil stability index. Relationships between vegetation parameters and soil types along transition zones between arid and Mediterranean environments were investigated in Israel by Shoshany et al. (1995) using remote sensing techniques. Areas of severe erosion were detected in the Judean Mountains from multi-date Landsat TM images. A review of satellite remote sensing indicators for land degradation was presented by Bolle (1996) and included, for example, soil multi-spectral reflectance, vegetation indices, albedo, and surface energy fluxes. Anticipated advances using radar images were also mentioned. In his conclusions, Bolle stressed the need for extending the remote sensing techniques from a sequential static mode to a more dynamic approach.

Existing satellite remote sensing data may be characterized by either a highly dynamic rate of data acquisition with low resolution (Meteosat and NOAA AVHRR

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128 Maxim Shoshany

data, for example) or by moderate resolution data (between 10 m and 80 m length of elementary image units), which is limited in providing repeated coverage. The spatio-temporal fragmentation, heterogeneity and dynamics of Mediterranean environments (Di Castri & Mooney, 1973) are the source for two typical problems in the application of satellite remote sensing to soil erosion mapping. First, its low spectral and spatial resolution presents difficulties in linking it to field measurements (due to the mixing of signals). Second, the availability of historical satellite data is limited, in the earliest case to 1972 for Landsat MSS images. Due to the slow rates of soil loss processes, research of soil erosion changes requires a much longer historical perspective. Black and white airphotographs are almost the only data source for investigating erosion processes on a regional scale over the last 50 to 70 years. Another important advantage is due to the spatial detail provided by these photographs which permits direct linkage to field studies.

However, there are severe limitations on the availability of photographs taken at the "right" season with adequate quality. Furthermore, their use is problematic for reasons which have not yet gained considerable attention, partly since most use was based on visual interpretation rather than from measurements based on image processing methods. Major sources of difficulties in utilizing airphotographs are, for example, the fact that many of these photographs are stored as hardcopy over many years under conditions that affect their quality, the effects of scanning procedures, and the infonnation content due to their panchromatic spectral integration.

This study aims at developing a methodology based on image processing techniques for assessing soil erosion from historical airphotographs and implementing these techniques in an area (Fig. 1) within the semiarid zone of Israel. There are very few studies in that field, in general, and in Israel, in particular. In this respect, it is important to mention the study of Seginer (1966) on measuring gully extension, and a more recent work by Rozin & Schick (1996) on monitoring stream channel response to land use changes using historical airphotographs. However, monitoring soil erosion requires further processing of the photographs to improve, for example, their relative brightness accuracy. The application developed here is similar in many ways to the studies of historical shoreline erosion processes along the Israeli coast using air photographs (Shoshany et al, 1996; Shoshany & Degani, 1992).

Indicators for soil erosion

Soil erosion is commonly assessed with regard to rainfall (average annual and storm frequencies), soil erodibility, slope length, slope gradient and land use (Kirkby, 1999; Wischmeier & Smith, 1978), while soil erodibility representing the "resistance to sediment detachment and transport" (Kirkby, 1999) is determined by physical, chemical and biological soil properties. Among these properties, soil aggregates size and organic matter content are commonly regarded as having direct relationships with soil stability. Lavee et al. (1998) studied the spatial variability of soil properties along a climatic gradient between the Judean Mountains and the Judean Desert. They found that aggregates size and organic matter content are correlated to climatic conditions in general and are highly responsive to abrupt precipitation changes between 340 mm year"1 and 280 mm year"' across the transition zone from the Mediterranean to semiarid environments. This study is directly relevant since it assessed the empirical

Detection and analysis of erodibility patterns using air photographs of the Avisur Highlands, Israel 129

F ig . 1 Ramat Avisur site locat ion map.

relationships between soil stability and soil properties in an area with environmental conditions similar to those investigated here.

Several studies have indicated that a decrease in organic matter content and soil particle size increases the reflectance in the visible and the NJJR (Near Infra Red) spectral range. Stoner & Baumgardner (1981) claimed that the reflectance sensitivity to organic matter content is high in the visible range. Relationships between aggregates size and spectral reflectance of soils have been investigated by both Bowers & Hanks (1965) and Hunt & Salisbury (1976) who found that the integrated reflectance in the visible and the NIR ranges is sensitive to aggregates size. Reflectance measurements of

130 Maxim Shoshany

soils in agricultural lands near Rehovot (about 20 km north of our test site), and near Ma'agan Michael in Northern Israel by Ben-Dov (1987) verified these relationships in four different soil types at various statistical significance levels. Attempts to predict these properties from a single-date aerial photograph were only partly successful.

Black and white aerial photographs are characterized by high sensitivity to the integrated reflectance in the visible range. This work thus assumes, according to the studies discussed above, that multi-temporal changes in soil brightness (as derived from black and white photographs) are indicative of soil erodibility. This assumption is restricted to areas of relatively smooth micro-topography that are represented by low spatial brightness heterogeneity or, alternatively, to areas which did not change in their roughness. The use of a combination of multi-temporal aerial photographs for classifying types of soil erodibility will be demonstrated in this paper.

METHOD

A survey of available air photographs and the selection of a suitable set for brightness change processing always involves some level of compromise (with respect to the expected information content). This is because the photographs' acquisition was not designed to meet the requirements (frequency, dates, and scale for example) of the erosion-monitoring scheme, but rather almost arbitrary criteria. In principle, a sufficient number of photographs are required according to the expected rates and the spatio-temporal extent of the soil erosion processes under consideration. Ideally these photographs should have the same sun illumination direction (same date of year) at the end of the summer to minimize as much as possible the effect of green or dry vegetation cover. They should also be of almost the same scale and flight direction. In reality, all these requirements are rarely met and due attention must be given to limitations set by the available photographs on the expected results.

The photographs that were found for this study represent three dates from the same month (September 1956, 1976 and 1990). Following conversion of the photographs into digital format, processing was carried out in three stages: (a) geometric corrections to allow geographic integration of the photographs into a unified database; (b) radiometric calibration of the photographs to enable measurement of changes in the soil brightness; and (c) multi-temporal analyses and classification of brightness changes through time. These stages are described below.

Geometric correction involves the treatment of two problems: the displacement of photographs' objects due to the combination of topographic relief and viewing direction (off-nadir viewing angle) effects, and the lack of existing details in historical photographs to allow their direct geo-referencing. The first problem has satisfactory solutions using commercial photogrammetric packages and thus will not be treated here. However, attention must be given to ensuring that the orthorectification process will not corrupt the brightness information contained in the photographs. The second problem was treated in an earlier study of historic shoreline changes by Shoshany & Degani (1992) and Shoshany et al. (1996). The approach developed is based on the selection of a reference photograph with the maximal number of common points (detectable objects) within both early and late photographs. This reference photograph


is corrected geometrically relative to existing maps or using GPS measurements of detectable objects. The other photographs are then corrected relative to the reference photograph according to the identification of common points. This procedure ensures maximum overlap between corresponding objects in the different photographs.

Radiometric calibration involves the calibration of brightness values and local correction according to the sun incidence angle. The first task is carried out by selecting fiat horizontal objects with extreme high brightness (bare chalk patches) and low brightness (shadowed vegetation) that appear in all of the overlapping photographs. The brightness at each pixel (elementary image unit) of a photograph is then calibrated according to the following equation:

BiJ = a{B*u-c) (1)

where B*tj is the old brightness value at pixel location ij and the coefficients of this equation (a and c) are derived by regression according to the corresponding values retrieved from the black and white objects. Since the photographs of 1976 and 1995 were found to be of similar brightness, the calibration constants were calculated only between these two dates and the 1956 photographs (a = 1.099 and c = 23).

The next stage of correction for the local sun angle of incidence is carried out according to:

• Bcij = B,j/cosQ (2)

where:

cosO = cos9„ cos9z + sin0„ sin9z cos<j)z cos<j>„ + sin9z sin<j)z sin9„ sin<j)„ (3)

where 9Z and <j>z are the solar zenith and azimuth angles, 9„ and (J),, are the zenith and azimuth angles of the normal to the surface (determined from a Digital Elevation Model of the region with spatial resolution of 50 m, Fig. 4). This correction assumes isotropic reflection that might be permissible in cases of high sun elevation angle in hilly terrain (Shoshany, 1992, 1993). Areas of high local angle of incidence such as formed at steep north facing slopes should be excluded from the soil erosion analysis due to the unknown BRDF (Bidirectional Reflectance Distribution Function) of these soils.

Multi-temporal analysis and classification of brightness values was carried out using the ISODATA (Iterative Self Organizing Data Analysis) unsupervised classification technique (PCI, 1996). This technique determines areas of characteristic patterns of temporal brightness change by clustering pixels of similar multi-date values. The number of clusters and an upper limit of the brightness variation permitted at each cluster are required as input parameters by the software. The selection of these parameters is frequently done on the basis of empirical assessment of results obtained with different values as inputs to the program.

Study area

The Ramat Avisur site (Fig. 1) extends over more than 4 Ion2 of the Judean Lowland (hilly terrain) in the west and the western margins of the Judean Mountains. The site's

132 Maxim Shoshany

boundaries were defined according to the overlapping areas between the air photographs of the different dates. This area represents a subhumid phyto-geographical zone along a north-south rainfall gradient with an annual average of 400 mm year"1. The dominant rock formation is mostly chalk with patches of calcrete and the dominant soil is brown rendzina (Haploxerolls). Vegetation in this area varies from shrublands and garigue (dominated by Quercus calliprinos and Phillyrea latifolia), through dwarf shrubs (dominated by Sarcopoterium spinosium), to open areas with diverse grasslands vegetation (dominated by Gramineae). The spatial patterns represent a wide range of transitional stages, with areas of high homogeneity of mainly tall shrubs and grasslands with various compositions of the three vegetation formations.

This diversity of patterns is a result of a long history of human activity (since the Late Bronze period, approximately 5500 years ago). Land use in this area is composed of croplands in the valleys and rangelands with controlled grazing pressures (Svoray et al, 1996; Pervolotski et al, 1992). The study area is characterized by a wide range of "regeneration and degradation patterns" (Naveh & Kutiel, 1990) of patches representing various soil-vegetation relationships that permit a generalization of the methods to wider areas of transition between Mediterranean and arid regions. The processing of brightness changes was limited to the footslopes and to areas of fluvial transformation that represent much higher rates of erosion compared to those observed on the slopes (Nir & Klein, 1974).

RESULTS

Figure 2 represents a combination of the photographs from the three dates (1956, 1976 and 1990). Visual assessment of differences reveal, for example: - vegetation patches that did not change between 1956 and 1990 (low brightness on

all three dates). - rock patches that did not change between 1956 and 1990 (high brightness on all

three dates). - vegetation patches that were expanded in the first time phase—between 1956 and

1976 (high brightness due to soil/rock cover in 1956 but low brightness due to vegetation cover in 1976 and 1990).

- degradation of vegetation patches and soil erosion (low brightness due to vegetation cover in 1956 and high brightness due to soil/rock cover in 1976 and 1990).

As a generalization, the landscape changes identified are characterized by increased vegetation cover over the last 50 years; and are expressed by an overall decreasing brightness. A quantitative description of the processes is given by the histograms of brightness values for the three dates (Fig. 3). According to these histograms, the landscape became more heterogeneous (the standard deviation increased from 45 in 1956, to 58 in 1976, and to 68 in 1990). In 1956, the histogram had an almost symmetrical normal shape; in 1976, it had changed into a bi-modal shape representing the dichotomy between bare and vegetated surfaces. In 1990, the histogram represents the dominance of the vegetation cover by its asymmetric form.

Brightness changes observed for the soil patches included in the investigated area ranged between 100 and 255 (in digital counts), corresponding to soil reflectance


Fig . 2 Airphotographs of the Rama t Avisur site: 1956, 1976 and 1990.

changes between 20% and 50%. These changes are assumed here to result mainly from soil deposition (decreased brightness) and soil depletion/erosion that exposed bedrock and rock fragments (increased brightness). Analysis of the soil changes pattern will be conducted here within the framework of the source-sink model developed by Pickup (1985). This model describes the process by "development of erosion cell mosaics" between source cells undertaking severe erosion, through cells of both deposition and erosion with decreasing proportions of erosion rates to a sink of dominant deposition. A source area in this work is characterized by relatively high brightness values and/or increasing brightness, indicating soil depletion (increase in bedrock or rock fragments) and/or change in the soil properties: organic matter depletion or decrease in aggregates size. A sink area, on the other hand, is characterized by relatively low brightness values and/or decreasing brightness, indicating an increase in the proportion of the soil relative to the bedrock and rock fragments and/or change in the soil properties: organic matter accumulation or increase in aggregates size.

This work is done at two scales: (a) at the generalized scale of the Ramat Avisur area, and (b) at a local site scale of a few hectares. At the Ramat Avisur area scale it is possible to suggest the location of the main source and sink areas on the basis of both the classification of brightness data and the topographic structure of the region (Fig. 4).

134 Maxim Shoshany

1956

1976

1990

60 90 120 150 180

Image Brightness Values Fig. 3 His tograms of the brightness distribution for the three dates.

Average brightness values for the source area at the top of the Avisur Highland increased from 110 in 1956, to 134 in 1976, to 180 in 1990. At the same time, brightness values in the sink area formed by the low relief at the junction of the streams draining the highland to the west decreased from 130 in 1956 to 115 in 1990, with an intermediate increase to a value of 162 in 1976. Identification of a regional transition pattern from the source to sink areas is difficult at this scale of observation, suggesting that the process is undertaken through a more complex pattern of local changes.

The detailed mapping area (presented in Figs 5 and 2 and located in Fig. 1) was chosen to represent a stream (wadi) that connects the main source and sink areas without the disturbance of a road within it. Figure 5 is the result of the multi-date brightness change classifications for the detailed mapping area into 20 classes with a standard deviation of less than eight brightness values (within a range of almost 200) in each of them. A visual assessment of both the aiiphotograph sequence (Fig. 2) in comparison to the multi-date classification,' illustrates the additive value provided by such classification to a visual interpretation of the raw brightness data. Figure 6 is a graphic description of six classes representing the variation in bare soil patches along the main stream of the wadi connecting the main source and sink areas. Assessment of these graphs suggests that the brightness has changed significantly in various directions and that it is difficult to differentiate visually between these classes in a single date photograph. This is a result of the clustering of at least four classes in a relatively limited range of brightness values that is too small to allow detection of differences between the classes by the human eye. They are differentiated by the ISODATA technique due to their very different configuration of multi-date change.

i3M> iii-i -.1

1 a n o i i n ••

F i g . 4 A Digital Elevat ion Mode l (DEM) of the region (*marks the locat ion of the detailed mapping area which appears in Fig. 5).

C l a s s 1 C l a s s 6 C l a s s 4

C l a s s 5 C l a s s 3 Fig . 5 M a p of mult i-date classification of br ightness changes in the detailed mapping area us ing the I S O D A T A technique (20 classes).

136 Maxim Shoshany

Source-sink relations between the classes were analysed by looking at the brightness deviation in two phases (Fig. 7) between 1976 and 1956 (y axis) and between 1976 and 1990 (x axis). Assessment of the diagram indicates that the classes represent a wide variation of source and sink functioning. The processes at each of the classes can be described as follows: - class 1 represents a source in the first phase and a slight depletion at the second; - class 2 represents continuous erodibility increase between 1956 and 1990; - class 3 represents an area of depleted soil (expanding exposure of bare rock); - class 4 represents a sink at the first phase and a source at the second; - class 5 represents a continuous increase in soil deposition; - class 6 represents a source at the first phase and a sink at the second. Analysis of the spatial pattern of these classes indicates that classes 2 and 3 in Fig. 5 represent the main transportation areas from the slopes and the major source area to the major sink area. Classes 1 and 4 represent the lateral extension of the erosion zone at the second phase, while class 6 represents the opposite phenomenon, i.e. a lateral decrease of the erosion belt in the second phase. Areas that, isolated from the channel due to their closure by dwarf shrubs at their boundary, show a continuous brightness decrease from a relatively high level in 1956, are represented by class 5. Integration of the presented indicators for soil erodibility, together with a detailed survey of height differences, may permit the construction of a model describing the flows between the different patches. This task, however, is beyond the scope of the present paper.

Another way of looking at the relationships between brightness changes and erosional activity is by assessing the total brightness differences. It is then possible to suggest that classes 1, 2 and 5 represent areas of relative "stability" with total brightness changes less than 30. Classes 3, 4 and 6 represent high brightness fluctuations that indicate instability and dynamic changes. Accordingly, the main transportation areas close to the channel and patches close to the north-facing slope are relatively stable (classes 1, 2 and 5), while the foot-slopes on the south-facing slope side are characterized by a dynamic change (classes 3, 4 and 6). These differences highlight the effect of slope aspect differences in the relative vegetation cover on soil erosion


- i s o -

Source to sink

c l a s s 6

c l a s s

100

50 class 1

3 #

00 -50 c l a s s 5

Sink Functioning

-50

-100

-450-

1976 -1956 Source Functioning

' c l a s s 2 1990 - 1976 50

£ c l a s s 4

Sink to Source

100

F i g . 7 A scatter d iagram of brightness differences in the six mult i -date classes as determined for two phases : be tween 1956 and 1976, and be tween 1976 and 1990.

activity. Visual assessment of the opposite slope units indicates distinctive patterns of vegetation-soil relationships. In view of the results obtained for the footslope areas, it is obvious that a better understanding of the erosional activity requires treatment of the soil contribution from the upper to the lower slope units. However, such assessment is more complicated due to the heterogeneity and complexity of the patterns.

SUMMARY AND CONCLUSIONS

A methodology was presented for monitoring and detecting changes in soil erodibility using multi-date airphotographs based on mutual calibration of brightness values and their classification according to temporal changes. Results permit better understanding of general erosion trends and an insight into the patterns of source-sink processes. The information content from the multi-date classification is relevant not only for soil erosion studies but also for ecological research with regard to vegetation patch dynamics. Further development of this work will involve its extension in three linked directions: - calibration of brightness changes to actual soil loss intensities; - assessment of grazing intensities on both soil erosion and vegetation patterns

within the framework of GIS, using dynamic modelling techniques such as Cellular Automata;

- expanding this type of erosion study into wider areas along climatic gradients.

138 Maxim Shoshany

Acknowledgements Financial support was provided within the framework of the MEDALUS III research program. PCI Canada provided us with the software tools needed to carry out such work. I thank my students Yafit Cohen and Orly Haimi for their help in processing the data.

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