Konstantinos Perakis

Vegetation Indices: Advances Made in Biomass Estimation and Vegetation Monitoring in the Last 30 Years

Abstract During the last 30 years Vegetation Indices (VI) have been extensively used for tracing and monitoring vegetation conditions, such as health, growth levels, production, water and nutrients stress, etc. In this paper the characteristics of over 20 VIs based on the VNIR spectrum are described in order to provide the reader with adequate material to form a picture of their nature and purpose. It is not, though, a review article due to the fact that a huge volume of work exists all over the world and a simple lining up of the related papers would not contribute to an understanding of the usefulness of VIs. A limited number of review work is included, together with research results from various operational and research applications of VI for wheat damage assessment in Northern Greece.

Assessment of crop damage using space remote sensing and GIS

This paper reports on a new Earth Observation (EO) research field concerning the potential use of space remote sensing for the assessment of crop damage at the field level. Digital field (cadastral) maps were used in order to overcome the problem of poor field boundary distinction (due to the current spatial resolution, small field size, a hilly landscape and the homogeneity of the area cover) and to estimate damage at field level. The relationship between crop damage estimations made by field observations and Normalized Difference Vegetation Index (NDVI) data was studied. By transforming the cadastral (field) map into a GRID format containing cells of one metre square (ArcView, Spatial Analyst), it was possible to determine the number of cells overlaying pixels or part of pixels only within the field area and the corresponding mean NDVI value. Various techniques, including Supervised Classification and Regression Models, were applied in order to study the correlation between NDVI values and those estimated by Hellenic Organization of Agricultural Insurance (HOAI) experts. The results appear to be very promising and the HOAI has decided to continue the research using the next generation high-resolution satellites.

Efficient segmentation of urban areas by the VIBI

Urban populations are expanding rapidly and so are cities. Remote sensing offers a convenient means of monitoring this expansion as it covers a period of 40 years in the case of the LANDSAT satellite. In some parts of the globe, this is probably the only viable means of monitoring due to the lack of other types of data. In order to monitor expansion, first, urban land has to be separated from other land-cover types. Although this can be done by standard classification processes, it is much more efficient to establish an urban index (UI) analogous to the widely used normalized difference vegetation index (NDVI) for vegetation. Existing efforts to establish such a UI are reviewed and compared in a common context. Following this, a novel, more efficient UI is introduced. The calculation of the new index is straightforward, based on combining the NDVI with the normalized difference built-up index. The results are promising as the index can efficiently segment urban areas, even in the presence of excessive bare land. The proposed method is evaluated on two test sites selected in different LANDSAT scenes. The new index is valid only for sensors with the same bands as those of LANDSAT.

Statistical evaluation of PCDD/F emission data during solid waste combustion by fuzzy clustering techniques.

An advanced statistical analysis technique using the fuzzy clustering method was employed in this work, for the evaluation of PCDD/F emissions during solid waste combustion. In addition, this technique was applied for the assessment of the effect of an inhibitor (urea) on the toxic compound releases and on the various isomer distributions. Municipal solid wastes were combusted in a lab-scale reactor and the toxic gas emissions were measured at the unit outlet. Combustion tests of urea-fuel mixtures were classified in the same group, indicating that urea affected the formation mechanisms of toxic gases. Combustion tests of single fuel were not included in the same group. Furthermore, urea ability to modify the gas emissions pathways was not affected by the method of its addition to the fuel.

Relationships between remote sensing spectral indices and crops discrimination

Abstract Multitemporal and multispectral SPOT data were used for calculation of three spectral indices, (1) Radiometric means, (2) Vegetation Index (NDVI), (3) Brightness Index. The sequence reflectance, absorption, reflectance in bands 1,2 and 3 respectively, is common for all the studied crops and months (June and July). The highest differences in reflectance values are observed in July and especially in band 3 which proved very sensitive to chlorophyll development. Pearson correlation coefficients show that combination of band I and 2 or band I and 3 supply more thematic information than band 1 and 2. Discriminant Analysis shows that for sugarebeets, radiometric values and brightness index(BI) present the same classification accuracy. On the other hand Vegetation Index (NDVI) is sufficient for cotton and harvested alfalfa, while the classification accuracy of the other crops ranges between the Radiometric Values and Brightness Index. Pairwise squared generalized distances show that radiometric values a...

Geospatial predictive modelling of the Neolithic archaeological sites of Magnesia in Greece

Abstract Sources of heterogeneous geospatial data such as the elevation, the slope, the aspect, the water network and the current settlements related to the known Neolithic archaeological sites of Magnesia, are used in an attempt to confirm the existence and allow for the prediction of other archaeological sites using predictive modelling theory. Predictive modelling allows the update of the problem solving strategy as soon as new data layers are available. The Dempster–Shafer Theory also commonly referred to as evidential reasoning (ER) is used to compose probability maps of areas of archaeological interest from physiographical and historical data. The advantage of this theory is that the ignorance is quantified and used to compose the probability maps named as belief, plausibility and belief interval for the archaeological sites. The final digital probability maps show that the Neolithic archaeological sites can be detected in the prefecture of Magnesia. This research study forms a methodological tool for the prediction of new archaeological sites in other areas of archaeological interest according to the physiographical and historical characteristics of the archaeological period being examined. It also contributes to the digital earth modelling and archaeological site protection, one of the most critical and challenging global initiatives.

Qualitative and Spatial Comparative Study of Satellite Images Classified by Supervised and Fuzzy Logic Based Classification Algorithms: A case study in Kilkis prefecture, Central Macedonia, Greece

Abstract In a first stage a SPOT image of the survey area was classified for land use/land cover classification, using the Maximum Likelihood Algorithm (MLC). However, due to the spatial uncertainty which exist mainly between the borders of the spectral categories, as they defined by MLC, in a second stage a supervised classification based on fuzzy classifiers was applied. A sigmoid function defines the degree that every pixel belongs in each category and differentiates the results of the classification in comparison with those of the classical Boolean logic. The results of the fuzzy classification leads to the construction of another land use/land cover map. For reasons of comparison between the two methods, the results of each classified category in both methods was converted to an integer binary image. As qualitative index of agreement between the two methods, the Kappa index of agreement and for each category was used. The results are evaluated with field work.