Proceedings of the Symposium on Global and Environmental Monitoring: Proceedings of the Symposium on Global and Environmental Monitoring

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Persistent identifier:: 856665355

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts ; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856665355

Language:: English

Document type:: Multivolume work

Volume

Persistent identifier:: 856669164

Title:: Proceedings of the Symposium on Global and Environmental Monitoring

Sub title:: techniques and impacts; September 17 - 21, 1990, Victoria Conference Centre, Victoria, British Columbia, Canada

Scope:: XIV, 912 Seiten

Year of publication:: 1990

Place of publication:: Victoria, BC

Publisher of the original:: [Verlag nicht ermittelbar]

Identifier (digital):: 856669164

Illustration:: Illustrationen, Diagramme, Karten

Signature of the source:: ZS 312(28,7,1)

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Editor:: International Society for Photogrammetry and Remote Sensing, Commission of Photographic and Remote Sensing Data

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Volume

Collection:: Earth sciences

Chapter

Title:: [WP-3 FOREST INVENTORY APPLICATIONS]

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: APPLICATION OF THE WEIGHTED DIFFERENCE VEGETATION INDEX TO SATELLITE DATA. Dr. J. G. P. W. Clevers

Document type:: Multivolume work

Structure type:: Chapter

APPLICATION OF THE WEIGHTED DIFFERENCE VEGETATION INDEX TO SATELLITE DATA Dr. J.G.P.W. Clevers, Remote Sensing Researcher in Agriculture, Dept, of Landsurveying and Remote Sensing, Wageningen Agricultural University, P.O. Box 339, 6700 AH Wageningen, the Netherlands ABSTRACT The application of the weighted (near-infrared - red) difference vegetation index (WDVI) to satellite data is evaluated. It was described earlier (Clevers 1988a, 1989) that the WDVI, based on reflectance factors, can be used for estimating green leaf area index (LM). This WDVI offered a good correction for soil background (soil moisture) in estimating the LAI of e.g. cereals. With satellites, digital numbers instead of reflectance factors are obtained. A procedure for applying the WDVI to satellite data is described: (1) offset correction, (2) calculating the slope of the soil line and (3) calculating the WDVI for satellite data (WDVI sat ). The WDVI sat is a two-dimensional analogue of the Kauth-Thomas Greenness. The results of an analysis of a TM scene of the Flevoland agricultural area in the Netherlands, recorded 22 August 1984, shows little difference between images of the WDVI (based on TM bands 3 and 4) and the Kauth-Thomas Greenness. A training set yielded a linear correlation coefficient of 0.997 between WDVI and Greenness. Application of the WDVI concept induces a considerable simplification of data analysis. Atmosheric correction is indispensable for a multitemporal analysis of optical satellite data. The above procedure is extended in order to derive the WDVI in a multitemporal analysis based on surface information only (e.g. water, bare soil and urban areas). KEY WORDS: Weighted Difference Vegetation Index, Satellite data, Greenness. 1. INTRODUCTION Application of remote sensing techniques has the potential to provide information about agricultural crops quantitatively, instantaneously and, above all, non- destructively. During the past decades knowledge about remote sensing techniques and their application to fields such as agriculture has improved considerably. Bunnik (1978) demonstrated the possibilities of applying remote sensing in agriculture, particularly with regard to crop charac teristics such as soil cover and leaf area index (LAI). LAI is defined as the total one-sided green leaf area per unit soil area and it is regarded as a very important plant characteristic because photosynthesis takes place in the green plant parts. The LAI is also a main driving variable in many crop growth models, designed for yield prediction (Penning de Vries & Laar, 1982). Crop growth models describe the relation between physio logical processes in plants and environmental factors such as solar radiation, temperature and water and nutrient availability. Estimates of crop growth often are inaccurate for sub-optimal growing conditions. Remote sensing may yield information about the actual status of a crop (e.g., in terms of LAI), resulting in an improvement of crop growth modelling. At the beginning of the growing season, soil reflectance influences the relation between measured infrared reflectance and LAI. At low soil cover, soil reflectance contributes strongly to the composite canopy-soil reflectance in the different spectral bands. Soil moisture content is not constant during the growing season and differences in soil moisture content greatly influence soil reflectance. At the end of the growing season, annual agricultural plants will show signs of senescence. Leaves turn from green to yellow. This phenomenon starts when the LAI is at its maximum value. In cereals all the leaves have appeared by that moment and the ears are about to appear. Subsequently, both LAI and photosynthetic activity decrease, because only the green parts will be photosynthe- tically active. During this stage it is important to gain an impression of the speed of senescence and to estimate LAI. Yellow leaves will also influence the relation between measured infrared reflectance and (green) LAI. If a multitemporal analysis of remote sensing data is required, a correction has to be made for background when ascertaining the relation between infrared reflectance factors and LAI. First of all, attention will be focussed on correction for soil background (Clevers 1988a, 1989). Clevers (1990) has

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