Remote sensing for resources development and environmental management: Remote sensing for resources development and environmental management

Damen, M. C. J.

Bibliographic data

Multivolume work

Persistent identifier:: 856342815

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856342815

Language:: English

Additional Notes:: Volume 1-3 erschienen von 1986-1988

Editor:: Damen, M. C. J.

Document type:: Multivolume work

Volume

Persistent identifier:: 856343064

Title:: Remote sensing for resources development and environmental management

Sub title:: proceedings of the 7th international Symposium, Enschede, 25 - 29 August 1986

Scope:: XV, 547 Seiten

Year of publication:: 1986

Place of publication:: Rotterdam; Boston

Publisher of the original:: A. A. Balkema

Identifier (digital):: 856343064

Illustration:: Illustrationen, Diagramme

Signature of the source:: ZS 312(26,7,1)

Language:: English

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

Editor:: Damen, M. C. J.

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:: 3 Spectral signatures of objects. Chairman: G. Guyot, Liaison: N. J. J. Bunnik

Document type:: Multivolume work

Structure type:: Chapter

Chapter

Title:: An evaluation of different green vegetation indices for wheat yield forecasting. A. Giovacchini

Document type:: Multivolume work

Structure type:: Chapter

Symposium on Remote Sensing for Resources Development and Environmental Management / Enschede / August 1986 An evaluation of different green vegetation indices for wheat yield forecasting A.Giovacchini Aquater S.p.A., San Lorenzo in Campo, Pesaro, Italy ABSTRACT: In this study different spectral vegetation indices have been compared in order to select the more efficient index to forecast the final grain yield of the winter wheat. The study pointed out that at specific phenological stages, the maximum correlation between vegetation index values and the final grain yield can be obtained using indices belonging to different families. The maximum correlation value is yielded at the heading phase adopting vegetation indices based on the ratio concept. 1 INTRODUCTION Crop production forecasting, if carried out with a sufficient reliability, assumes great economic and strategic interest. Remote Sensing technology could contribute significantly to increase forecasting reliability both through a better estimation of the cultivated surface and by directly or indirectly measuring the biophysical parameters influencing the crop yield. Generally the relationships between crop and remote sensing data have been analyzed using different types of vegetation indices. These spectral vegetation indices derive from the combination of one more spectral bands referring to the visible and near-infrared parts of the electromagnetic. Extensive scientific literature exists on the relationships between biological crop characteri stics and vegetation index values. Some authors relate spectral vegetation indices to wheat dry- matter accumulation (Tucker. G.J. et al. 1981; Aasc.J.K. et al. 1981). A strong correlation between spectral vegetation index values and final grain yield of wheat and corn crops, has been proven for specific phenological stages (Tucker G.J. et al. 1980; Daughtry C.S.T. et al. 1984). Some authors have analyzed the possibility to estimate the leaf area index of crops by using different spectral vegetation indices (Goel. N.S. 1984; Badhwar C.D. 1984). This study describes the relationships between the final grain yield of the winter wheat and some vegetation indices at several phenological stages. The objective of this analysis is two fold: - to verify if a unique vegetation index can be used to forecast the final grain yield of the winter wheat; - to select the most appropriate vegetation index in relation to the different phenological stages of the crop. 2 2 MATERIAL AND METHODS The experiment was carried out taking into account 30 fields of durum wheat (cultivar Creso). The crop fields did not belong to a specific experimental design, but were part of an observational study carried out on field crops located in the Cesano Valley (Central Italy). During the growing season of the crops, seven measurement surveys were carried out from March to July. By using an Exotech radiometre (mod 100), spectral data was collected in the four bands of the MSS Landsat sensor. Each wheat field had been previously stratified on the basis of the vegetation cover density by using color aerialphotographs at 1:5.000 scale. Three radiometric measurements were carried out in each strata placing the instrument at 3 m above the ground. In order to collect more representative spectral data, the radiometer was moved four times in each plot to obtain data referring to sample units of 2x2 square meters. The radiometer was calibrated on a standard panel before collection of the spectral data. At the same time, the following data referring to biophysical plant characteristics was collected: plant height, humid and dry biomass, % of weeds, surficial soil 2 moisture, n° of stalks per m ,• vegetation condition, % of green vegetation cover. In addition, at harvest the grain yield of each wheat field was assessed. 3 RESULTS AND DISCUSSION For each measurement campaign spectral data was processed to calculate the vegetation indices reported on Tab. 1. For each vegetation index, the table reports the spectral bands used indicating the correspondent MSS Landsat bands. Both for each vegetation index and collection date, corresponding to a specific phenological stage, the coefficient of correlation between vegetation index values and final grain yield, were calculated. Tab. II shows these coefficients of correlation. As shown in Tab. II, all the vegetation indices yield the maximum correlation values at the heading stage. At this biophysical phase the indices based on the ratio concept yield the maximum correlation, as well as at the booting stage. At the first and second phenological stages considered in this study, the indices yielding the

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