Jun 2012, Volume 6 Issue 2
    

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  • RESEARCH ARTICLE
    Lev SPIVAK, Irina VITKOVSKAYA, Madina BATYRBAYEVA, Alexey TEREKHOV

    Sigificant dependence from climate and anthropogenic influences characterize ecological systems of Kazakhstan. As result of the geographical location of the republic and ecological situation vegetative degradation sites exist throughout the territory of Kazakhstan. The major process of desertification takes place in the arid and semi-arid areas. To allocate spots of stable degradation of vegetation, the transition zone was first identified. Productivity of vegetation in transfer zone is slightly dependent on climate conditions. Multi-year digital maps of vegetation index were generated with NOAA satellite images. According to the result, the territory of the republic was zoned by means of vegetation productivity criterion. All the arable lands in Kazakhstan are in the risky agriculture zone. Estimation of the productivity of agricultural lands is highly important in the context of risky agriculture, where natural factors, such as wind and water erosion, can significantly change land quality in a relatively short time period. We used an integrated vegetation index to indicate land degradation measures to assess the inter-annual features in the response of vegetation to variations in climate conditions from low-resolution satellite data for all of Kazakhstan. This analysis allowed a better understanding of the spatial and temporal variations of land degradation in the country.

  • RESEARCH ARTICLE
    Svetlana M. KOCHUBEY, Taras A. KAZANTSEV

    This paper focuses on the advantages of derivative vegetation indices over simple reflectance-based indices that are traditionally used for remote sensing of vegetation. The idea of using reflectance derivatives instead of simple reflectance spectra was proposed several decades ago. Despite this, it has not been widely used in monitoring systems because the derivatives lack reliable parameters. In addition, most satellite monitoring systems are not equipped with hyperspectral sensors, which are considered necessary for operating with the reflectance derivatives. Here, we present original data indicating that the chlorophyll-related derivative index D725/D702 we derived can be accurately estimated from a reflectance spectrum of 10 nm resolution that would be suitable for most satellite-based sensors. Furthermore, the index is not sensitive to soil reflectance and can therefore be used for testing of open crops. Presence of blanc reflectance is also unnecessary. Preliminary results of index testing are presented. Perspectives on using this and other derivative indices are discussed.