Change detection with remote sensing : relating NOAA-AVHRR to environmental impact of agriculture in Europe

E. Addink

Research output: Thesisinternal PhD, WU

Abstract

<p>Agricultural production in the European Union sharply rose during the second half of the 20 <sup>th</SUP>century. As a side-effect environmental impact increased as well, and resulted in widespread environmental problems, which policymakers now seek to reduce. Therefore, up-to-date, standardised information on environmental impact of agriculture is required covering the entire area of the Union. NOAA-AVHRR images seem well suited to provide part of this information, because 1) one image covers a large area, 2) so significant time series are available, and 3) they contain two relevant spectral bands for vegetation and crop studies. The objective of this study is to develop a change detection method to locate changes in environmental impact using NOAA-AVHRR images.</p><p>The required spatial observation units were defined such that they match both agriculture and NOAA-AVHRR. For this purpose a method was developed to determine the correspondence in geometry between two polygon sets. It was shown that polygons formed by bio-physical variables match patterns in AVHRR images better than those formed by socio-economic variables. The selected units were obtained from the soil map.</p><p>Once the spatial units were defined, measures could be sought that characterise environmental impact in terms of land cover, so they might be observable in the AVHRR images. A suitable measure was found in change in agricultural area, which will result in changed environmental impact if other factors remain unchanged. For changes in agricultural intensity, which will lead to changed environmental impact as well, no suitable measures exist.</p><p>Finally, three different change detection methods were proposed to detect changes in agricultural area using NOAA-AVHRR images. The methods aim at enhancing the information regarding agricultural change while minimising classification inaccuracy, spatial misregistration and radiometric effects. None of these methods proved successful in locating regions with changes in agricultural areas. The conclusion is that NOAA-AVHRR images seem not suited to detect changes in European agriculture.</p><p>Besides these aspects related to a change detection method, methods to solve cloud contamination of NOAA-AVHRR images were studied. Clouds often reduce the useful area in AVHRR images. Seven procedures, including conventional and geostatistical methods, to replace small clouds by estimated land radiation values were compared. The estimates from the geostatistical methods led to the best estimates of reflection values from the landscape underlying the clouds.</p><p>Next, the suitability of near-future remote-sensing systems was assessed for detecting changes in environmental impact of agriculture. MERIS is a sensor mounted on ENVISAT, a European satellite that will be launched in November 2001. Its announced specifications make it seem a promising information source for land applications at the continental scale. To estimate the value of its 300m pixel a new method is proposed, which is referred to as the Stained Glass Procedure. This method relates pixel size to discernible detail, and predicts the level of detail detectable in another (here non-existing yet) image. According to the Stained-Glass Procedure, MERIS images will show twice as much detail as NOAA-AVHRR images, which is a significant improvement. Unfortunately, it will take quite some years before time series useful for change detection have been collected.</p>
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Wageningen University
Supervisors/Advisors
  • Molenaar, M., Promotor
  • de Jong, S.M., Promotor
  • Clevers, Jan, Promotor
Award date9 Nov 2001
Place of PublicationS.l.
Publisher
Print ISBNs9789058084163
Publication statusPublished - 2001

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Keywords

  • agricultural land
  • land evaluation
  • remote sensing
  • image processing
  • methodology

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