Aerial photo interpretation for change detection of treeline ecotones in the Swedish mountains
Year: 2008
Type: report
Abstract: It is expected that the ongoing climate change will have a strong influence on the Earth’s \nvegetation and cause the advancement of treelines towards the poles and up to higher \nelevations. In the Swedish mountains, changes in the positions of alpine treelines have \nalready been reported, and major changes due to changing climate are predicted for the near \nfuture. Remote sensing techniques have considerable potential to improve the monitoring of \nspatially complex treeline ecotones, which are likely to show site dependent responses to \nchanging climate. Aerial photos provide the longest temporal record of remote sensing data \nfor studying the historical treeline changes. High spatial resolution and the possibility of \ninterpreting photos in three-dimensions are the main strengths of aerial photos. The National \nInventory of Landscapes in Sweden (NILS) is a nationwide environmental monitoring \nprogram, which provides sampling infrastructure for monitoring treelines over the Swedish \nmountains using high spatial resolution remote sensing data. \n \nThe aim of this project was to study the feasibility of visual interpretation of aerial photos for \nmonitoring changes in treeline ecotones (transition zones between closed forest and treeless \nalpine vegetation). More specifically, our aim was to compare possible methods for change \ndetection using recent and historical aerial photos, and to demonstrate a method that is \napplicable to the Swedish mountains using the NILS sampling infrastructure. We also wanted \nto evaluate how the technical properties of the aerial photos, particularly the photo scale, \naffect the change detection. The results were used for evaluating the potential and costs for a \nmore comprehensive change detection study including a greater number of NILS squares. \n \nWe compared interpretation methods in three 5×5 km NILS squares and studied in total six \n5×5 km NILS squares for changes. Colour infrared aerial photos from two points in time \n(1975–1980 and 2002–2004) were used. The evaluation of the technical properties of aerial \nphotos is important as the recent photos have been taken from a height of 4600 m (photo \nscale approximately 1:30,000) and the historical photos from 9200 m (1:60,000). The \ndifference in photo scale could introduce significant errors to the change detection. Therefore \nthe effect of photo scale was studied in two experiments in a separate study site, which had \nbeen photographed within a few days from both flying heights. \n \nWe assessed three visual interpretation methods: complete cover mapping (polygon \ninterpretation), sample plot method and transect method. To avoid recording false changes \nand to minimize the effect of different photo scales, we interpreted the recent and historical \nphotos at the same time using scanned photos and digital photogrammetric workstations. The \nfirst method, polygon interpretation, was tested by comparing the current NILS \ninterpretations for the central 1×1 km square within the 5×5 km NILS squares with the \nhistorical photos, and updating polygon borders and attributes if changes were observed. In \nthe second method the vegetation variables were interpreted for circular sample plots (20 m \nradius). We used digital land cover data and GIS techniques for defining a buffer zone \nbetween the forest and the treeless alpine areas in order to focus the interpretation efforts on \nthe treeline ecotone. The distance between the systematically sampled plots was 250 m within \nthe treeline buffer. In the third method the variables were interpreted along subjectively \nselected transects across the altitudinal treeline transitions. Transects were also used for \ninterpreting individual trees within the treeline, of which some were measured in the field. \n \nBased on the analyses we can recommend the sample plot method for interpreting tree cover \nchanges within 5×5 km NILS squares. The main advantage with the method is that it can be applied to any NILS square overlapping the treeline ecotone, and that the sampling can be \ndone objectively. A treeline buffer zone based on digital land cover data provides one \npossible method for pre-stratification. Delineation of polygon borders is not needed and small \nsized sample plots are easier to interpret concerning vegetation changes than larger polygons. \nThis is particularly the case when changes are small. The polygon interpretation using change \ncontrol mapping can also be a cost-effective method for change detection within the 1×1 km \nsquares. The greatest advantage is that in addition to tree cover changes, it can provide \ninformation on the spatial patterns (landscape structure). However, the small changes in the \nborders are subjective and difficult to interpret. The transect method can also provide \ncharacterization of treelines, particularly in relation to elevation, but the selection of transects \nwithin NILS squares can be difficult. Furthermore, the result cannot be generalised to larger \nareas similar to the method based on probability sampling. \n \nWe conclude that only tree cover changes can be interpreted with sufficient accuracy, \nbecause of the relatively small scale historical photos. Larger scale photos and more \nextensive field control would be necessary to interpret changes in small trees and shrubs. The \nexperiments with photo scale show that the greatest source of uncertainty is related to the \ndifferent photo scale of the recent and historical photos. The comparison of two independent \ninterpretations made at different scales would lead to detection of substantial false changes, \nparticularly if interpretations would be made by different interpreters. However, we think that \nconcurrent comparison of digital aerial photos from two points in time provides meaningful \nchange detection for tree cover although some errors due to scale effects should be expected. \n \nThe interpretation of six NILS squares by the sample plot method suggests that tree cover has \nincreased within the treeline ecotone in three of the squares. The results demonstrate the \npotential of visual interpretation of aerial photos for treeline change detection. The \ninformation on tree cover changes could supplement field based monitoring of treeline \nelevations. Therefore, we consider that there is potential for a more comprehensive study to \nexamine tree cover changes in a greater number of NILS squares in the Swedish mountains. \nThen, however, more emphasis should be given to the panchromatic black and white photos \nfrom the 1960s, which have been taken from approximately the same flying height (4600 m) \nas the most recent CIR photos. We estimate that a large scale study, involving the \ninterpretation of approximately 50–60 NILS squares for three points in time would require a \nbudget of about 1 million SEK. Airborne laser scanning and larger scale aerial photos are \npotential data sources for monitoring future changes in treeline ecotones. \n \n
Language: English
Topic: Tree-ring climate responses
Subfield: Atmospheric Science
Field: Earth and Planetary Sciences
Domain: Physical Sciences
SDGs: Life on land, Climate action
Open Access status: green
OpenAlex ID: W1541393629