**5. Remotely sensed data as a support for the map creation**

Several digital and analogical sources of data can be used to produce thematic maps both in the stage before the preparation of the map and in the successive stages.

Aerial photo interpretation is a well-established working tool in Earth Science research; DEMs and satellite images, on the contrary, are considered as new tools with an enormous potential, not yet fully explored. In the following paragraphs the different data are described according to their use in this work.

The Use of Remote Sensed Data and GIS to Produce

(dendritic, rectangular, parallel and so on).

a Digital Geomorphological Map of a Test Area in Central Italy 107

association are characteristics to be taken into account. *Site* is the relationship of a feature to the environment (elevation, slope, surface cover). *Situation* observes the mutual spatial relationship of the features. *Association* refers to the possibility that, when particular geomorphological processes or landforms are recorded is quite obvious to find associated features. Other important characteristics are diagnostic for geomorphogical interpretation: *tone* or colour is the brightness or the shade of gray or the colour of the detected element and depends on the amount of light that it reflects, constituting a sort of spectral signature of anthropogenic and natural objects in the area. Also, a transition between two different tones is relevant to detect a variation in some physical processes and useful to locate landform limits. *Texture* can be defined as the arrangement of tone or colour structured in a well recognizable pattern and depends strongly on the scale of the photos. When features are too small on an image to be identified, their repetition can be a clear evidence of a specific feature. So, the smoothness (uniform and homogeneous texture) or the roughness (coarse and heterogeneous texture) of an image can identify a particular vegetation cover (e.g. tree as rough, grass as smooth). *Pattern*, or the spatial arrangement of a landform, is the last characteristic used in geomorphology, particularly useful in drainage network recognition

In the study area aerial photo interpretation was one of the first activity carried out, joined with field survey and bibliographical research. In this project analogical photos in black and

The use of black and white in this case is preferred because it allows to better highlight tones and textural variations on the images. At first it is useful to observe photos on a small scale (1:33000) for an overview of the area. Features due to tectonic and structural control like faults, ridge alignments, structural scarps, discontinuity along slopes are best identified in this scale. Also the river drainage pattern, any anomaly along river tracks and large landslide phenomena are well evident at this scale. In the study area these photos highlight the morphological units linked with the different bedrocks. The calcareous anticline of the Subasio Mountain shows distinctive characteristics (high slope values, low rates of drainage density), significantly different from the rest of the area, where the presence of rock types with an high clay abundance, strongly influences the morphological arrangement (i.e. high value of drainage density and medium and low slope values, high index of landslides, fluvial erosion with badlands and fluvial scarps). Photos analysed at a larger scale (1:10000) are more useful for identifying and drawing landforms. The accuracy is detailed enough for mapping the different morphological elements of a landslide (e.g. crown, main and minor scarps, the displaced material, the accumulation and so on). The choice to use two distinct years of acquisition of the images (1997 and 2004) ensure the multitemporal analysis of the area assigning a relative age to some deposits and landforms (active, inactive). The work is divided into a first phase of identification and drawing of landforms directly on aerial photo

white were used at a scale of 1:33000 (year 1977) and 1:10000 (year 2004).

(Figure 6) and subsequent transposition of vector data in a GIS environment.

**5.2 DEMs and satellite images: A new perspective to view the landscape** 

associated with the themes contain alphanumeric data in unlimited quantities.

The resulting geomorphologic map has several advantages. The final document is upgradable and easily editable. The organization of data into layers lets the user to select, for viewing and printing operations, one or more layers simultaneously. The attribute tables

### **5.1 The aerial photo interpretation: A traditional technique for landform detection**

The main goal in reading an aerial photo in the Earth Science applications is to identify and understand the physical landforms on the terrestrial surface and, in some cases, underground morphologies. Aerial photos can be in an analogical or in a digital format. Both of them are acquired by an aerial platform using a camera slipped into a mount located at the bottom of the aircraft. Analogical and digital cameras are quite similar. Analogical images, taken on a photographic film, can be in natural or black and white colours and show the topographic surface as a series of overlapping photos for a large percentage of the detected area. Digital images are taken on a strip with a linear scanner in black and white, colour (RGB format) or infrared. The most important difference is the storage device where the digital camera system uses a charge-coupled device (CCD) that can strongly vary in capacity and resolution, affecting the quality of the images. Both data sets have advantages. Digital images can have a better resolution and filter only few bands of the electromagnetic spectrum allowing the use on specific research fields. In addition they are subjected to editing and post-processing, for example to sharpen the edges of the objects represented on the image. On the contrary analogical films are more nuanced and show a better colour rendering. Moreover, in the analogical data, the images show a much more natural aspect giving the opportunity to better visualize and identify natural features on the surface.

In both cases aerial photos show a "bird's – eye" view of the Earth surface and, unlike the topographic maps that are a selective representation of reality, omitting a large number of natural features, aerial photos provide an objective idea of the arrangement of the spatial pattern.

The limits of this technique are related to the presence of clouds or haze in the atmosphere and snow on the Earth surface covering the topographic pattern. Moreover, distortion effects have to be corrected for an optimal use of the data sets.

Aerial photos are used in a wide group of applications: engineering, logistic and planning, mineral exploration, geoarchaeology, mining and resource extraction, land use and landcover analysis and so on.

In geomorphology air photos interpretation is an irreplaceable tool to detect landforms allowing to identify the type of bedrock and the main morphological processes acting in the study area and the palaeogeographic reconstruction of particular morphological situations (past river captures or the infilling of ancient lacustrine depressions). Some large landforms are more evident on the aerial photos than on the field due to the landform location or the topography arrangement.

Therefore, the aerial photo interpretation is a fundamental method in every geomorphological mapping process.

Moreover, the possibility to observe images taken in different periods of time, and with diverse scales, permits to monitor the landscape evolution (multitemporal and multi-scalar observation). Examples include the evolution of a landslide, the health status of vegetation, the rate of retreat of a cliff, the changes affecting a river drainage network.

The first elements of interpretation in geomorphology are the *size* of the objects identified and their *shape*. Also the spatial arrangement is very important, so site, situation and

The main goal in reading an aerial photo in the Earth Science applications is to identify and understand the physical landforms on the terrestrial surface and, in some cases, underground morphologies. Aerial photos can be in an analogical or in a digital format. Both of them are acquired by an aerial platform using a camera slipped into a mount located at the bottom of the aircraft. Analogical and digital cameras are quite similar. Analogical images, taken on a photographic film, can be in natural or black and white colours and show the topographic surface as a series of overlapping photos for a large percentage of the detected area. Digital images are taken on a strip with a linear scanner in black and white, colour (RGB format) or infrared. The most important difference is the storage device where the digital camera system uses a charge-coupled device (CCD) that can strongly vary in capacity and resolution, affecting the quality of the images. Both data sets have advantages. Digital images can have a better resolution and filter only few bands of the electromagnetic spectrum allowing the use on specific research fields. In addition they are subjected to editing and post-processing, for example to sharpen the edges of the objects represented on the image. On the contrary analogical films are more nuanced and show a better colour rendering. Moreover, in the analogical data, the images show a much more natural aspect giving the opportunity to better visualize and identify natural features on the surface.

In both cases aerial photos show a "bird's – eye" view of the Earth surface and, unlike the topographic maps that are a selective representation of reality, omitting a large number of natural features, aerial photos provide an objective idea of the arrangement of the spatial

The limits of this technique are related to the presence of clouds or haze in the atmosphere and snow on the Earth surface covering the topographic pattern. Moreover, distortion

Aerial photos are used in a wide group of applications: engineering, logistic and planning, mineral exploration, geoarchaeology, mining and resource extraction, land use and

In geomorphology air photos interpretation is an irreplaceable tool to detect landforms allowing to identify the type of bedrock and the main morphological processes acting in the study area and the palaeogeographic reconstruction of particular morphological situations (past river captures or the infilling of ancient lacustrine depressions). Some large landforms are more evident on the aerial photos than on the field due to the landform location or the

Therefore, the aerial photo interpretation is a fundamental method in every

Moreover, the possibility to observe images taken in different periods of time, and with diverse scales, permits to monitor the landscape evolution (multitemporal and multi-scalar observation). Examples include the evolution of a landslide, the health status of vegetation,

The first elements of interpretation in geomorphology are the *size* of the objects identified and their *shape*. Also the spatial arrangement is very important, so site, situation and

the rate of retreat of a cliff, the changes affecting a river drainage network.

effects have to be corrected for an optimal use of the data sets.

pattern.

landcover analysis and so on.

topography arrangement.

geomorphological mapping process.

**5.1 The aerial photo interpretation: A traditional technique for landform detection** 

association are characteristics to be taken into account. *Site* is the relationship of a feature to the environment (elevation, slope, surface cover). *Situation* observes the mutual spatial relationship of the features. *Association* refers to the possibility that, when particular geomorphological processes or landforms are recorded is quite obvious to find associated features. Other important characteristics are diagnostic for geomorphogical interpretation: *tone* or colour is the brightness or the shade of gray or the colour of the detected element and depends on the amount of light that it reflects, constituting a sort of spectral signature of anthropogenic and natural objects in the area. Also, a transition between two different tones is relevant to detect a variation in some physical processes and useful to locate landform limits. *Texture* can be defined as the arrangement of tone or colour structured in a well recognizable pattern and depends strongly on the scale of the photos. When features are too small on an image to be identified, their repetition can be a clear evidence of a specific feature. So, the smoothness (uniform and homogeneous texture) or the roughness (coarse and heterogeneous texture) of an image can identify a particular vegetation cover (e.g. tree as rough, grass as smooth). *Pattern*, or the spatial arrangement of a landform, is the last characteristic used in geomorphology, particularly useful in drainage network recognition (dendritic, rectangular, parallel and so on).

In the study area aerial photo interpretation was one of the first activity carried out, joined with field survey and bibliographical research. In this project analogical photos in black and white were used at a scale of 1:33000 (year 1977) and 1:10000 (year 2004).

The use of black and white in this case is preferred because it allows to better highlight tones and textural variations on the images. At first it is useful to observe photos on a small scale (1:33000) for an overview of the area. Features due to tectonic and structural control like faults, ridge alignments, structural scarps, discontinuity along slopes are best identified in this scale. Also the river drainage pattern, any anomaly along river tracks and large landslide phenomena are well evident at this scale. In the study area these photos highlight the morphological units linked with the different bedrocks. The calcareous anticline of the Subasio Mountain shows distinctive characteristics (high slope values, low rates of drainage density), significantly different from the rest of the area, where the presence of rock types with an high clay abundance, strongly influences the morphological arrangement (i.e. high value of drainage density and medium and low slope values, high index of landslides, fluvial erosion with badlands and fluvial scarps). Photos analysed at a larger scale (1:10000) are more useful for identifying and drawing landforms. The accuracy is detailed enough for mapping the different morphological elements of a landslide (e.g. crown, main and minor scarps, the displaced material, the accumulation and so on). The choice to use two distinct years of acquisition of the images (1997 and 2004) ensure the multitemporal analysis of the area assigning a relative age to some deposits and landforms (active, inactive). The work is divided into a first phase of identification and drawing of landforms directly on aerial photo (Figure 6) and subsequent transposition of vector data in a GIS environment.

#### **5.2 DEMs and satellite images: A new perspective to view the landscape**

The resulting geomorphologic map has several advantages. The final document is upgradable and easily editable. The organization of data into layers lets the user to select, for viewing and printing operations, one or more layers simultaneously. The attribute tables associated with the themes contain alphanumeric data in unlimited quantities.

The Use of Remote Sensed Data and GIS to Produce

The four slope classes are: 1) 0°-13°, 2) 13°-20°, 3) 20°-27°, 4) 27°-48°.

distribution of the phenomena is always significant.

(active), 7) Debris (inactive), 8) Fluvial lacustrine deposits.

Fig. 7. Hillshade (on the left) and slope (on the right) grids derived from SRTM DEM.

a) Falls, b) Slides, c) Flows, d) Complex landslides. 1) Eluvial and colluvial deposits, 2) Alluvial deposits, 3) Calcareous Complex, 4) Terrigenous Complex (1), 5) Terrigenous Complex (2), 6) Debris

Fig. 8. Diagrams showing the spatial distribution of landslides on several lithotypes.

Geomorphological processes are strictly related to topographic trends and the spatial

a Digital Geomorphological Map of a Test Area in Central Italy 109

1) Peak, 2) Saddle, 3) Ridge, 4) Scarp, 5) River valley with a "V" shape, 6) Doline, 7) Structural surface, 8) Calcareous Morphological Unit, 9) Marly Morphological Unit.

Fig. 6. Aerial photo of the Subasio Mountain and the surrounding area with some examples of features identified and drawn on the photo (b/w, scale 1:33000, year 1977).

However, at this point of the project, the paper is simply a digital geomorphological map. The subsequent implementation of satellite data is an added value and offers the possibility to obtain additional useful spatial information for different types of applications.

The topographic model used in this project is the Shuttle Radar Topography Mission DEM elaborated for Italy with an horizontal resolution of about 90mx90m (Taramelli & Barbour, 2006).

Several topographic attributes including an hillshade, to better visualize the topographic surface and slope and aspect grids are derived (Figure 7).

1) Peak, 2) Saddle, 3) Ridge, 4) Scarp, 5) River valley with a "V" shape, 6) Doline, 7) Structural surface,

Fig. 6. Aerial photo of the Subasio Mountain and the surrounding area with some examples

However, at this point of the project, the paper is simply a digital geomorphological map. The subsequent implementation of satellite data is an added value and offers the possibility

The topographic model used in this project is the Shuttle Radar Topography Mission DEM elaborated for Italy with an horizontal resolution of about 90mx90m (Taramelli & Barbour, 2006). Several topographic attributes including an hillshade, to better visualize the topographic

of features identified and drawn on the photo (b/w, scale 1:33000, year 1977).

to obtain additional useful spatial information for different types of applications.

8) Calcareous Morphological Unit, 9) Marly Morphological Unit.

surface and slope and aspect grids are derived (Figure 7).

The four slope classes are: 1) 0°-13°, 2) 13°-20°, 3) 20°-27°, 4) 27°-48°.

Fig. 7. Hillshade (on the left) and slope (on the right) grids derived from SRTM DEM.

Geomorphological processes are strictly related to topographic trends and the spatial distribution of the phenomena is always significant.

a) Falls, b) Slides, c) Flows, d) Complex landslides. 1) Eluvial and colluvial deposits, 2) Alluvial deposits, 3) Calcareous Complex, 4) Terrigenous Complex (1), 5) Terrigenous Complex (2), 6) Debris (active), 7) Debris (inactive), 8) Fluvial lacustrine deposits.

Fig. 8. Diagrams showing the spatial distribution of landslides on several lithotypes.

The Use of Remote Sensed Data and GIS to Produce

a Digital Geomorphological Map of a Test Area in Central Italy 111

Fig. 9. A still image of the virtual flight on the park with the geomorphogical map overlapping an ASTER image (view from SW). The RGB combination is the 742. The 3D

view is assured by the SRTM DEM height values.

Spatial analysis tools can calculate the statistical distribution of the landforms, starting from the topographic grids (Melelli & Taramelli, 2010; Taramelli & Melelli, 2009). In Figure 8 a statistical distribution of the different types of landslide is shown.

To better understand to what extent the topographic parameter influences the spatial distribution of a geomorphological process a quantitative analysis is required. Therefore, the digital map, with the addition of a DEM, becomes an interactive document for further applications.

Remotely sensed data also offer further enhancements to geomorphological mapping and landscape comprehension. A different perspective view of the area, together with the overlapping of different types of data in a 3D view, is an appealing idea for a different use of geomorphological mapping, in particular for a non-specialized audience. Due to the aforementioned difficulties in interpreting the geomorphological symbolism, a backdrop layer resulting from remotely sensed images can aid in the comprehension of the landforms. The perspective view, joined with virtual flights through the area, increase even more the visualization of the landscape. The user can observe any landform in a perspective view and, with a virtual cloche, can fly near and above the feature. So it is possible to intuitively distinguish the main scarp or the convexity on a slope corresponding to the accumulation of a landslide. The transparency tool can make simultaneously visible the alignment of a fault system on the geomorphological map and the corresponding geomorphological features (scarps or triangular facets) on the underlying DEM or satellite image. In the same way a badland drawn on a map is better evident with an image overlaid, where the dense network of valleys engravings on a slope with the absence of vegetation and the grey light colours of the clay bedrock are shown.

The use of remotely sensed images can improve this kind of perception. It is well known that particular RGB arrangements can highlight different natural aspects on the ground: 432 for vegetation, 741 for the moisture content in the soil coverage and so on. So the manipulation of a remotely sensed image under the digital geomorphological map with a 3D perspective view due to the DEM addition, is the best possible analysis of a geomorphological map.

In this example, the Arcscene ESRI Tool was used to obtain a 3D view of the park and a virtual flight on the area. In order to achieve a more realistic view an ASTER image (Advanced Spaceborne Thermal Emission and Reflection Radiometer) is overlapped (Abrams, 1999; Yamaguchi et al., 1998). ASTER is an imaging instrument flying on the Terra satellite (http://asterweb.jpl.nasa.gov/index.asp). The satellite was launched in December 1999 as part of NASA's Earth Observing System (EOS). The data are in 14 bands (from the visible to the thermal infrared wavelengths) and offer high-resolution characteristics. Thanks to the swath width of the sensor, each ASTER image takes an area of 60 x 60 km (Figure 9).

All the data described above can be represented in the final double-sided printing layout of the map showing how interactive this kind of document can be (Figures 10 and 11). Figure 10 represents the first side of the map with the Figure 11 on the back.

In the final layout, the part dedicated to the geomorphogical data and the section for the grids and satellite images have the same importance. So the remote sensing information is added to make the final product in keeping with the rest of the maps, becoming a source of information for the knowledge of the territory.

Spatial analysis tools can calculate the statistical distribution of the landforms, starting from the topographic grids (Melelli & Taramelli, 2010; Taramelli & Melelli, 2009). In Figure 8 a

To better understand to what extent the topographic parameter influences the spatial distribution of a geomorphological process a quantitative analysis is required. Therefore, the digital map, with the addition of a DEM, becomes an interactive document for further

Remotely sensed data also offer further enhancements to geomorphological mapping and landscape comprehension. A different perspective view of the area, together with the overlapping of different types of data in a 3D view, is an appealing idea for a different use of geomorphological mapping, in particular for a non-specialized audience. Due to the aforementioned difficulties in interpreting the geomorphological symbolism, a backdrop layer resulting from remotely sensed images can aid in the comprehension of the landforms. The perspective view, joined with virtual flights through the area, increase even more the visualization of the landscape. The user can observe any landform in a perspective view and, with a virtual cloche, can fly near and above the feature. So it is possible to intuitively distinguish the main scarp or the convexity on a slope corresponding to the accumulation of a landslide. The transparency tool can make simultaneously visible the alignment of a fault system on the geomorphological map and the corresponding geomorphological features (scarps or triangular facets) on the underlying DEM or satellite image. In the same way a badland drawn on a map is better evident with an image overlaid, where the dense network of valleys engravings on a slope with the absence of vegetation and the grey light

The use of remotely sensed images can improve this kind of perception. It is well known that particular RGB arrangements can highlight different natural aspects on the ground: 432 for vegetation, 741 for the moisture content in the soil coverage and so on. So the manipulation of a remotely sensed image under the digital geomorphological map with a 3D perspective view due to the DEM addition, is the best possible analysis of a

In this example, the Arcscene ESRI Tool was used to obtain a 3D view of the park and a virtual flight on the area. In order to achieve a more realistic view an ASTER image (Advanced Spaceborne Thermal Emission and Reflection Radiometer) is overlapped (Abrams, 1999; Yamaguchi et al., 1998). ASTER is an imaging instrument flying on the Terra satellite (http://asterweb.jpl.nasa.gov/index.asp). The satellite was launched in December 1999 as part of NASA's Earth Observing System (EOS). The data are in 14 bands (from the visible to the thermal infrared wavelengths) and offer high-resolution characteristics. Thanks to the swath

All the data described above can be represented in the final double-sided printing layout of the map showing how interactive this kind of document can be (Figures 10 and 11). Figure

In the final layout, the part dedicated to the geomorphogical data and the section for the grids and satellite images have the same importance. So the remote sensing information is added to make the final product in keeping with the rest of the maps, becoming a source of

width of the sensor, each ASTER image takes an area of 60 x 60 km (Figure 9).

10 represents the first side of the map with the Figure 11 on the back.

information for the knowledge of the territory.

statistical distribution of the different types of landslide is shown.

applications.

colours of the clay bedrock are shown.

geomorphological map.

Fig. 9. A still image of the virtual flight on the park with the geomorphogical map overlapping an ASTER image (view from SW). The RGB combination is the 742. The 3D view is assured by the SRTM DEM height values.

The Use of Remote Sensed Data and GIS to Produce

a Digital Geomorphological Map of a Test Area in Central Italy 113

Fig. 11. The final layout of the geomorphological map (back side) including the remotely

sensed data.

Fig. 10. The final layout of the geomorphological map (front side) with the geomorphological map, a geological sketch, some significant photos and the scheme of the transition from the analogical product to the digital one.

Fig. 10. The final layout of the geomorphological map (front side) with the

transition from the analogical product to the digital one.

geomorphological map, a geological sketch, some significant photos and the scheme of the

Fig. 11. The final layout of the geomorphological map (back side) including the remotely sensed data.

The Use of Remote Sensed Data and GIS to Produce

Chichester, 1-434.

Vol. 5, No. 2, pp. 227-245.

Vol. 101–102, pp. 156–167.

33, pp. 179-185.

Vol. 5, pp. 3–30.

Canada.

341–350.

inHenglandReuter, pp.65–85.

*International*, Vol. 122, pp. 837–857.

*Geographica Helvetica*, Vol. 62, pp. 140–147.

*Españoles*, Vol. 45, pp. 79–98.

*Telerilevamento*, Vol. 36, pp. 3-15.

Istituto Poligrafico e Zecca dello Stato, Roma, 1994.

Chichester, UK. doi: 10.1002/9780470666517.fmatter.

a Digital Geomorphological Map of a Test Area in Central Italy 115

Gray, M. (2004) - *Geodiversity valuing and conserving abiotic nature*. John Wiley & Sons Ltd,

Gustavsson, M., Kolstrup, E. & Seijmonsbergen A.C. (2006). A new symbol-and-GIS based

Lillesand, T.M., Kiefe, R.W. & Chipman, J.W. (2011). Front Matter. In: *Computer Processing of* 

Malinverno, A. & Ryan, W.B.F. (1986). Extension in the Tyrrhenian Sea and shortening in the

Mayer, L., Menichetti, M., Nesci, O. & Savelli D. (2003). Morphotectonic approach to the

Melelli, L. & Floris, M. (2003). A new Geodiversity Index as a quantitative indicator of

Melelli, L. & Taramelli, A. (2010) – Criteria for the elaboration of susceptibility maps for

Moore, I.D., Grayson, R.B. & Ladson, A.R. (1991) Digital terrain modeling: a review of

Nelson, A., Reuter, H.I. & Gessler, P. (2009). DEM Production Methods and Sources. Ch.3

Peucker, T.K., Fowler, R.J., Little, J.J. & Mark, D.M. (1977). Digital representation of Three –

Pike, R.J. (1988). The geometric signature: Quantifying landslide-terrain types from digital

Sambridge, M., Braun, J., & McQueen, H. (1995). Geophysical parameterization and

Schmidt, J. & Andrew, R. (2005). Multi-scale landform characterization. *Area*, Vol. 37, pp.

Serrano, E. & Ruiz-Flaño, P. (2007a). Geodiversidad: concepto, evaluación y aplicación

Serrano, E. & Ruiz-Flaño, P. (2007b) - Geodiversity: a theoretical and applied concept.

Taramelli, A. & Barbour, J. (2006). A new DEM of Italy using SRTM data. *Rivista Italiana* 

elevation models. *Mathematical Geology*, Vol. 20, No. 5, pp. 491-511.

*Geophysical research abstracts*, Vol. 13, EGU General Assembly, 2011.

Guida al rilevamento. Servizio Geologico Nazionale. *Quaderni serie III*, Vol. 4,

detailed geomorphological mapping system: Renewal of a scientific discipline for understanding landscape development. *Geomorphology*, Vol. 77, No. 1-2, pp. 90-111.

*Remotely-Sensed Images: An Introduction*, Fourth Edition, John Wiley & Sons, Ltd,

Apennines as result of arc migration driven by sinking of the lithosphere. *Tectonics*,

drainage analysis in the North Marche region, central Italy. *Quaternary International*,

abiotic parameters to improve landscape conservation: an Italian case study.

DGSD phenomena in central Italy. *Geografia Fisica e Dinamica del Quaternario*, Vol.

hydrological, geomorphological, and biological applications. *Hydrological Processes*,

Dimensional Surfaces by Triangulated Irregular networks (TIN). Tech. Rept. 10, ONR Contract N00014-75-C-0886, Dept. of Geogr., Simon Fraser U., Burnaby, B.C.

interpolation of irregular data using natural neighbors. *Geophysical Journal* 

territorial. El caso de Tiermes Caracena (Soria). *Boletín de la Asociación de Geógrafos* 
