Applying Geospatial Technologies to Weed Mat Monitoring and Mapping: The Ythan Estuary, NE

Scotland

David R. Green & Stephen D. King

Centre for Marine and Coastal Zone Management University of Aberdeen, Scotland, UK

David R. Green & Stephen D. King

Centre for Marine and Coastal Zone Management University of Aberdeen, Scotland, UK

http://www.abdn.ac.uk/cmczm

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• Mapping of weedmats in the Ythan estuary has previously been undertaken by Raffaelli et al. - concluding that although fluctuating from year to year there appears to be a gradual trend towards an overall increase in the extent of weedmats over time.

• Using Raffaelli's work as a reference source the objectives of the current work were to: develop an up-to-date practical methodology using image processing and GIS (Geographic Information Systems) software to provide information about weedmat location and extent over time; and to provide quantitative estimates of weedmat coverage for comparison with earlier studies.

• Archival colour aerial photography for four years (1989, 1992, 1994 and 2000) was scanned into a computer. The application of image processing techniques resulted in a series of mosaiced images that were used as the basis for visual interpretation and mapping of the location and extent of weedmats for each year of photography.

• Input of the maps into a Geographical Information System (GIS) enabled the derivation of quantitative estimates of the areal coverage of macro-algal weedmats for each year and the creation a series of maps showing change.

This presentation examines the potential for using colour vertical aerial photography to map the spatial location, distribution, extent,

and changes over time in weedmat coverage found in the Ythan estuary, North East Scotland.

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• The Ythan estuary (57oN, 2oW) is the area of study. It lies approximately 20 km to the north of Aberdeen on the east coast of Scotland, and is tidal extending for approximately 8km in the general direction of Ellon.

• The estuary averages about 300m in width, and has an average depth at high water of 2.5m with tidal range of between less than a meter to 3m or more (Raffaelli, 1998, p. 138).

• According to Raffaelli (1999, p. 164) The low water channel is about 71 ha and there are 115 ha of mudflat and 70ha of mussel beds and sand.

• The Ythan drains a catchment of about 650 km2 of intense arable agricultural land. The study area chosen for this research is the entire intertidal zone for the estuary.

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• A significant visual feature of the Ythan estuary in NE Scotland in recent years has been the presence of benthic macro-algae (Enteromorpha, Ulva and Chaetomorpha) forming extensive 'green' 'mats' over the estuary's intertidal flats.

• One of the main reasons for the apparent observed increase in the areal extent of macro-algal weedmats is thought to be related to the amount of nitrogenous fertiliser applied to the Ythan catchment over time.

• Studies in the Ythan estuary have been undertaken to: (a) identify the location and distribution the weedmats (spanning a time period from the late 1940s to the present day), and (b) try to establish what is causing the weedmat.

• The primary reason for undertaking such studies is that the algal weedmats can have a dramatic impact on the invertebrates in the underlying sediment as well as on the shorebird populations.

Establish Background to ResearchObjectives and Aims

Study Area - Context and SettingEnvironmental Problem - DefinedInformation Required

Scene Model of Phinn et al. (1999)

Data AvailableSuitability for Task

i.e. algal weedmat monitoring

Data Processing

Manual Photo-interpretationDigitisingDigital Image Pre-ProcessingGIS layers

Analysis

Reports and Conclusions

Future Work

Report Preparation

Meeting 2

Meeting 1

Meeting 3

INPUT

OUTPUT

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Image Archive

Examine Panchromatic and Colour Aerial Photography

Select Aerial Photography

Scan Aerial Photography

Document Aerial Photography

Store Aerial Photography

Pre-Processing in DIP Geo-Correct OS Map data from Digimap

Mosaic & Colour Balance Aerial Photography

Digitise boundary of estuary at HWM in ArcView 3.2

Crop Mosaic to estuary boundary at HWM

Photo-Interpretation

Digitise weedmat units in ArcView 3.2

Output Maps from ArcView using Layout

GIS analysis for quantitative information e.g. areas

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• In order to study the location, distribution and areal extent of macro-algal weedmats, over time, a number of field survey- and aerial photo-interpretation-based studies have been undertaken to develop cost-effective methodologies for repeat environmental data acquisition.

• The methods developed and used are well documented in Raffaelli and Way (1996) and include:

the use of aerial photographs acquired from light aircraft flying at 1000-1500 feet

photo-interpretation using vertical photographs

the projection of colour photographic slide transparencies for manual tracing and area assessment with the aid of mm graph paper and a planimeter (see e.g. Raffaelli and Plomer, 1989).

• With developments in remote sensing (digital image processing) and GIS software and hardware technology the task of deriving spatial and temporal information on macro-algal weedmats has become far easier than was previously possible, allowing for rapid data capture, storage, handling and interpretation of remotely sensed photography and imagery in a computer environment.

• There is considerable potential to: (a) repeat and check the results from previous studies, (b) build up digital databases comprising geo-rectified and mosaiced aerial photography and vector map layers that can be used as a baseline for future monitoring and mapping exercises, and (c) derive quantitative information more quickly.

• Young et al. (2000, p. II-286) lend additional support for a 'remote sensing approach' to weedmat monitoring and mapping ….'The rapid development of benthic macroalgae on estuarine mudflats during the summer growing season makes difficult the accurate documentation of spatial and temporal distributions of such algae from ground surveys alone'.

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The overall objective of the current work is to devise a practical remote sensing-based methodology to extract spatial information (location and extent) about macro-algal weedmats in the Ythan estuary derived from multi-temporal archival aerial photography of varying different scales acquired from different sources.

More specifically:

• aerial photo-interpretation of archival aerial photography (panchromatic and colour) of varying scales and dates obtained from local sources to identify macro-algal weedmats

• data capture of selected archival aerial photography in the form of scanned raster digital datasets

• geo-correction of the scanned aerial photography in a digital image processing system (Erdas Imagine 8.4)

• stitching or mosaicing of the geo-corrected aerial photography (Erdas Imagine 8.4/PanaVue)

• multi-temporal mapping of the location and areal extent of macro-algal weedmats in the Ythan estuary, Aberdeenshire, Scotland (Erdas Imagine 8.4 and ESRI ArcView 3.2)

• comparisons between the information derived with other, earlier results using different methodologies to map from aerial photographs

• creation and documentation of a series of deliverables including digital aerial photographs, interpretations, analyses, maps, and other datasets

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mats • Typically Enteromorpha forms vast 'mats' that lie on the surface of estuarine mud-

and sand-flats. These mats can either be very fine coverings (thin) or several cms deep (thick).

• Although it is relatively easy to identify these extremes on aerial photographs densities of cover in-between are more difficult.

• The water retention characteristics of the species and also the presence of thin layers of water covering the algae have been found to lead to a reduction in the overall surface reflectance making identification on photography and imagery quite difficult

• Infrared reflectance is usually high, and on CIR photography the range of colours on the film varies from a dull blue/grey when saturated (with water) to deep red when present in thick healthy 'green' mats.

• Where found in free-floating mats, Enteromorpha may also be deposited on other vegetation types.

• In a recent study around Portsmouth, Baily et al. (2002) found that weedmats may form a crust of dead material on the upper surface, leading to similar reflectance characteristics to gravel deposits.

• Raffaelli et al. (1999, p. 108) note that: In situations like the Ythan estuary, Scotland, Chaetomorpha is much more intimately associated with the sediment than are Enteromorpha, Ulva, or Cladophora, with substantial amounts of biomass anchored firmly beneath the surface

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yA small number of vertical 35mm colour aerial photographs were taken in August 1994 using a model aircraft. These are for part of the Sleek of Tarty area only and do not cover the Ythan catchment. They are large scale, cover a small area and show macro-algal weedmats very clearly.

Data

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• The aerial photography selected, together with any additional data and information (where deemed appropriate), were transformed into a digital or computer compatible format.

• Conversion of the aerial photography from an analogue to digital format makes it directly compatible with digital OS map data and any other GIS layers available from other sources e.g. the sediment map from Raffaelli et al (1989) and Stapleton and Pethick (1996).

• Data capture of the analogue format aerial photographs (verticals) was carried out using a standard desktop scanner (Agfa Snapscan 1212). Scanning at a resolution (X and Y direction) of 150dpi (colour) the photography was captured and initially stored in a .TIF (F) format (Tagged Image File Format).

• Choice of the scanning resolution was primarily based upon generating a filesize for scanned photographs that was considered manageable (also bearing in mind the need to subsequently mosaic and geo-correct the images). Whilst the choice of a high scanning resolution retains more of the detail contained in the original document, a compromise usually has to be struck in practice between the relative gain in information content, and the final filesize, as well as considerations of filesize manageability for display, transmission and storage.

Dpi Zoom x 4 Details File size (photo)

75dpi x 4 zoomBlocky appearanceRough boundary definition of large shapes. Less good for small areas.

350K

150dpi x 4 zoomStill blocky but far less so than 75dpiAcceptable boundary definition. Good for small areas.

1.20Mb

300dpi x 4 zoomSmoother appearance than 150dpi but less difference between 150dpi and 300dpi than 75dpi and 150dpiBest boundary definition. Good for small areas

4.63Mb

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• Ideally all photography should be geo-corrected first to remove any inherent distortions if a map is to be the end product. The result will be a geometrically correct map (for each date) showing the macro-algal weedmat distribution which can then be used as a layer or coverage in ArcInfo/ArcView 3.2.

• Subsequently the digital raster aerial photographs were input to the Erdas Imagine 8.4 Digital Image Processing and GIS software system where they were: • Geo-referenced (Projection/Spheroid/ Datum : Transverse Mercator/Airy/OS GB 1936).

• Geo-referencing was achieved using digital OS vector map data tiles for the designated study area

• Geo-referenced and mosaiced imagery were also made available in the GeoTIFF format 'cropped' using an on-screen digitised boundary (ArcView 3.2 shape file) of the Ythan estuary catchment area

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osaic All of the images selected for study were geo-corrected using the Erdas Imagine 8.4 image

processing software referenced to OS digital map data using between 4 and 16 GCPs per image, a polynomial transformation (orders 1 and 2), and resampled using nearest neighbour. Where possible, the overall RMSE (Root Mean Square Error) was reduced to <1.

One objective of this work was to create a composite photographic image for the entire estuary for each date of photography available. To do this requires that each geo-corrected aerial photograph be stitched or mosaiced together. This was undertaken in Erdas Imagine 8.4 using the Mosaic option. Whilst some results were good, others resulted in relatively poor colour balancing between each photograph making up the mosaic. Subsequently, mosaicing was also tested in a software product PanaVue (http://www.panavue.com) with markedly improved colour balancing results.

Mosaic

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e• In order to conserve computer disk

storage requirements for the digital aerial imagery, and to speed up the display of the backdrop for the purposes of digitising, a digital vector map outline of the Ythan estuary high water mark (HWM) (captured as an ESRI .shp (Shape file format) via on-screen digitising using ArcView 3.2) was used to define an image 'cookie cutter' delimiting the boundary of the Ythan estuary study area.

• The filesizes of the resulting raster datasets were significantly reduced. However, in practice it was generally found that the full image mosaic provided more informational 'context' for interpretation.

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g• Default color balancing of the mosaiced image files completed in Erdas Imagine 8.4

was generally deemed to be satisfactory, although not all yielded good results due to the differences between individual images making up the mosaic (arising from the sun-sensor-ground angles, sensor view angle, and possibly small atmospheric changes or differences, the camera, and photographic processing).

• The mismatch in colour between one photograph and another is, for the most part, not a serious problem for mapping the weedmats, although in a few cases the resulting image colour balance would benefit from closer matching.

• Further investigation of this potential visual interpretation problem revealed the availability of some other mosaicing software (PanaVue from Canada) that helps to markedly improve the colour balancing between individual photographs and the resulting mosaic. PanaVue also allows manual positioning of the individual photographs making up the mosaic.

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• Each cropped mosaic image of the Ythan estuary was input to the ArcView 3.2 GIS software package in Imagine (.IMG) format. Units of macro-algal weedmatting were mapped using the online interactive digitising tools.

• Consistency in the interpretation (drawing boundaries and identifying the category) is important, hence the work was carried out by a single individual to: (a) digitise, and (b) interpret.

• The minimum mappable unit (mmu) is often used as the basis for determining a 'cut-off' point or threshold for deciding which map units to digitise and which not to digitize.

• To some extent the choice of unit to map also depends upon:

• original photographic scale• quality of the aerial photography/mosaic• degradation of the photographic image e.g. due to scanning/screen display• image contrast and sharpness between the feature of interest and the

background or surrounding area/surface (sometimes difficult towards the edges of aerial photographs)

• Image magnification• Interactive zooming (in and out of an image)• eyesight of the interpreter• experience of the interpreter• quality of the display/original (electronic colour versus reflective colour)• Some assistance in the interpretation exercise can also be offered through: (a)

reference to contextual information and (b) an examination of the hardcopy aerial photographs

Dense weed mat

Less Dense

weed mat

Weed mat/ sand

Weed mat units

Small weed mat

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Weed mat Weed mat Sparse wed mat

Weed mat

Sand

Mud/ Sand

Mussel Beds

An Example Photo-interpretation Key

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• In general, weedmats appear to be a distinct 'emerald green' colour in contrast to the 'pale brown/greybrown' colour of the 'sand/mud' background. Some, however, appear 'brownish' in colour in the digital imagery and visual checks had to be made with the original photographic prints.

• The general location of the weedmats in each mosaic also seem to correspond to the 'habitat conditions' e.g. sheltered marine environments, middle to low intertidal zone, calm, protected harbours etc.

• Overall the weedmats do appear to show a strong visual contrast with the bottom sediments (sand and mud). Only where they overlap darker bottom sediments e.g. mussel beds/sea weed does it pose difficulty in accurately delineating weedmat units (e.g. where they overlap). Some help is, however, provided by examining a sediment map for the area by Stapleton and Pethick (1996).

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on In order to narrow down the

decision-making process (weedmat/not weedmat) contextual information (e.g. text sources, maps etc.) can be added into the mapped layers when digitising the weedmat boundaries.

For example, a bottom sediment or substrate map showing sand, mud, mussel beds and other known 'habitat' factors.

South Quay 1992

South Quay 2000

South Quay Erdas Imagine 8.4 Swipe Tool (left

half=1992; right half = 2000)

South QuayErdas Imagine 8.4 Blend Tool (pale

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IS'On-screen' digitising of features on aerial photography can be undertaken directly onto a single or mosaiced image backdrop displayed in Arc/Info, ArcView 3.2 or Erdas Imagine 8.4.

Accompanying each digitised map layer in ArcView 3.2 is an attribute table comprising the attributes of the feature type e.g. polygon/area, and an ID number for each algal weedmat unit (polygon) digitised, together with any other information associated with the polygon.

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s• Originally it was anticipated that the weedmat maps derived by

Raffaelli et al. for the Ythan estuary would all be made available for this work. Using the display and overlay functionality of a GIS it would be possible to undertake the following:

• check the quantitative areal measurements of weedmat coverage for the Ythan estuary as obtained by Raffaelli et al. and as shown on the accompanying maps and histograms

• overlay weedmat maps for the same year obtained from different sources (Raffaelli et al.; Green and King) to compare and contrast both the interpretations and the quantitative estimates of weedmat cover

• Unfortunately only one map for 1986 was available. It was a very generalised paper hardcopy black and white map, and had been derived from oblique colour photographic slide transparencies of the Ythan estuary.

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s • the maps sourced from Raffaelli are of a very small format, generalised and appear to be the result of work by several different interpreters

• comparison of the temporal maps through use of overlay techniques reveals that they are indeed quite generalised and moreover they do not entirely co-register or have the same locational reference points

• other sources of error may have arisen in the derivation of the original maps e.g. different interpreters, different scales of photography. It is more than likely that all the maps contain errors, but it is difficult to assess this quantitatively or to be able to report it easily

• inspection of the additional reports by Raffaelli et al. (1988, 1989, 1996) reveals some useful information about the areal extent of weed mats as measured on aerial photography taken at different points during the season.

• Raffelli and Plomer (1989, p.1) also indicate that the 1989 survey was carried out two weeks later than in previous years resulting in the weed mat being past its peak.

• the fact that the survey of 1986 was mapped from 50 colour transparencies via projection onto paper (Raffaelli and Nicol, 1988) suggests some possible sources of inaccuracy as far as the mapping and weedmat area estimates are concerned.

An alternative approach, therefore, was to consider some of the weedmat maps made by Raffaelli et al. for the South Quay area at Newburgh (other areas are also shown in Raffaelli and Way, 1996). Although these were similarly rather generalised maps they provided one way of 'comparing and contrasting' interpretations and quantitative data. There are, however, some limitations to this approach that must be considered when interpreting the results.

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• spatial location of the weedmats is often similar for each year

• there are definite differences in areal weedmat coverage from year to year (as might be expected)

• comparisons between the different interpretations available show that strong similarities exist but that differences do arise possibly due to the interpreter's choice of the minimum mappable unit (mmu), the accuracy of the rectified imagery being used to map from, the weedmat units which are identified and drawn around (greater or lesser detail), and the details of the boundaries drawn (see Green and Hartley, 2000). This suggests that quantitative measurements of the areal weedmat coverage - in terms of how many metres squared were present at each date - may be larger or smaller than they really are at any one time, or alternatively may be less than they really are due to the time of year that the photography was acquired and the interpretation.

However, bearing these limitations in mind it is possible to locate four ground control points on each map that appear to be the 'same' and to geo-correct each of the maps, sufficient to facilitate overlay with the geo-corrected aerial photographs and mosaics, as well as with the maps for each date. This allows some comparisons to be made between different years and potentially forms a basis within the GIS for showing change over time that can then be mapped as a 'change' map (using different colours and shadings) for each year, or to be animated.

Reference to the photographic interpretations of the weedmats does reveal, however, that:

GIS

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tThe input of geo-referenced datasets to ArcView 3.2 makes it possible to undertake somesimple GIS analyses to:

• show the spatial distribution and pattern of algal weedmats over time (overlay analysis)• show the changes in the areal distribution of the weedmats between e.g. time 1 and

time 2 (T1-T2 - a simple form of change detection or differencing)• estimate the total areal coverage of weedmats in metres squared for each date• estimate the percentage change over time

•Photomosaic and Vector Overlay•Weedmat Coverage Maps for each year•Composite Weedmat Coverage Maps•Classes of Weedmat Coverage for each year

An ArcView extension, XTools, was downloaded and installed to select polygons in a theme or coverage that has geographic co-ordinates and to derive e.g. area measurements in metres squared, acres or hectares for each polygon.

It is also possible to make use of the Swipe, Blend and Fade tools in the Erdas Imagine 8.4 Viewer to provide a visual basis for observing changes in weedmat distribution, pattern and coverage over time.

A number of different maps using the View, Layout options can be derived for the Ythan estuary from the environmental map and image databases created.

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1989 122,005 292,933

1992 333,917 508,047

1994 220,887 370,620

2000 616,195 NA

Date % weedmat coverage of

estuary

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1992 13.2

1994 8.7

2000 24.3

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sPhoto-interpretation experience suggests that if aerial photography were to be flown again, for repeat monitoring and mapping of weedmats ideally it is:

It is suggested that if more aerial photography is to be acquired in the future for an extension of this work that:

• best to acquire either high quality large scale vertical colour aerial photographs at a scale of 1:3,000-1:5,000, or high quality large scale vertical colour infrared (CIR) aerial photographs at a scale of 1:3,000-1:5,000 in a 9"x9" format preferably with fiducial marks and a GPS (note: other examples of work on the use of remote sensing for weedmats have made use of scales of 1:7,200, 1:8,000, 1:10,000, 1:12,000 and 1:16,666)

In both cases the high spatial resolution of the photography enables an interpreter to:

(a) both see and locate the algal weed-mats because of the high contrast between the 'vegetation' and the substrate (mudflats, sandflats)

and

(b) map the boundaries of the identified units with better accuracy

• For comparisons with previous aerial photographically derived data and information that it is acquired at approximately the same time as in previous overflights using the same camera setup and film at the same scale

• Some aerial overflights are also made for other times during the season to try to ascertain whether or not there is an optimum period for aerial photographic acquisition to assist in the identification and mapping process. The optimum overflights could (within reason: bearing in mind aircraft/pilot availability, prevailing weather conditions, cloud cover, etc.) be established by examining the previous aerial photography acquired and other information sources and graphs such as provided by Raffaelli et al. (1999, p. 108).

Reco

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ons Macro-Algae From To Peak

Enteromorpha spA May November May-June

Enteromorpha spB May November July-September

Chaetomorpha linum

Mid-May November July/August

Ulva lactuca Late May Mid-October September

• Colour infrared (CIR) and/or multispectral aerial photography is considered in the future for such studies, the former offering the opportunity to maximise the identification and separability of the macro-algal communities from the substrate. Young et al. (1999) also suggest the use of colour negative film.

• Other sources of remotely sensed imagery are considered as alternatives to aerial photography that potentially offer a similar (or better spatial resolution) and better spectral resolution

• It would be highly appropriate to gather some field or ground-based data and information coincident with the aerial photography to assist in characterising the photographic appearance of the macro-algal weedmats for different localities and densities (see for example work by Young et al. (1998))

Future Studies are now underway to examine the problem of weed mat monitoring and mapping in the YthanFu

ture

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s• As part of this current work due account has also been taken of the long-term requirements

of the Ythan Project

• The catalogue of datasets used for this project provides a useful reference and record for any future work and for any further comparisons between digital datasets

• The digital datasets generated also form a useful resource and baseline database for the Ythan estuary, which could eventually form the basis for a GIS for the Ythan

• Subsequently the map datasets could also be utilised within an online mapserver e.g. ArcIMS to provide a means for provision of public access to environmental information about the Ythan estuary and its surrounds

• This work has also provided a basis upon which it is now possible to compare and contrast the work already undertaken by Raffaelli et al. on the Ythan by: creating new weedmat map interpretations for comparison with the original maps and aerial photographs; and for digital capture of the Raffaelli et al. datasets for integrated analysis and comparison with new interpretations

• Compatibility of the geo-corrected photographic datasets (single and mosaiced) with other digital GIS datasets (e.g. SNH and other data) will also be useful for future GIS analyses

• The practical methodology developed here will also be useful for any subsequent comparisons with information derived from other remotely sensed image sources e.g. CASI, ATM and LIDAR. Additionally, the information derived can also be analysed within a GIS. LIDAR data, for example, offers the opportunity to acquire digital height data and to derive a Digital Elevation Model (DEM).

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s• This may subsequently be useful for image display, interpretation and classification,

particularly if a 3-D terrain model with imagery draped over the top has value for visualisation purposes in the public domain.

• Assuming that one of the long-term goals of this work is to generate information about weedmat coverage and extent over time, it may be appropriate to consider the need to develop a similar or compatible methodology for mapping weedmats from different sources of remotely sensed data/imagery that may be compared with the work done here and by Raffaelli et al. This will be particularly important to consider if any observations are to be made about spatial pattern and distribution over time as well as for quantitative change detection.

• Based upon the information provided in the documentation available, analysis of CASI imagery and LIDAR data may also be used in future studies to determine the role that they (remote sensing and heighting data respectively) can play in monitoring, identifying, and mapping macro-algal weedmats. CASI imagery, for example, offers finer multi-spectral resolution than aerial photography that may be of help in the identification of the macro-algal weedmats. Similarly with Airborne Thematic Mapper (ATM) which has successfully been used by NERC for macro-algal weedmat monitoring and mapping in the south of England.

• The application of digital image processing of aerial photography is not straightforward and classification of the weedmats versus the surroundings is not always successful and repeatable. This is a view similar to that of Young et al. (1999, p.1176) who observed that 'the use of digital image processing techniques alone to classify…. was problematic'….. because macroalgae, for example, share the spectral characteristics of other classes in the visual portion of the electromagnetic spectrum. Alternative approaches might be to utilise Definien's ECognition software that incorporates contextual information into the spectral classification. A solution proposed by Young et al. (1999, p. 1176) is 'to use these techniques as a first step in the classification process, followed by a visual examination of the imagery, and to edit the results in a traditional approach to photointerpretation'.

Refe

rence

s

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Thank YouDavid R. Green & Stephen D.King

Centre for Marine and Coastal Zone ManagementDepartment of Geography and Environment

School of Resources, Environment and SocietyUniversity of Aberdeen, Elphinstone Road

Aberdeen, AB24 3UF, Scotland, UK

Tel. +44 (0)1224 272324Fax. +44 (0)1224 272331

Email. d.r.green@abdn.ac.uk / s.d.king@abdn.ac.ukInternet. http://www.abdn.ac.uk/cmczm

In conclusion, the combination of digital data capture, conversion and input capabilities, digital image processing and GIS technology offers considerable potential for integrating archival map and image datasets, as well as providing the potential to create a baseline GIS-based system as the basis for future multi-temporal monitoring and mapping of environmental change of macro-algal weedmats in the Ythan.