Application of spectral indices and spectral transformation methods for assessment of winter wheat state and functioning

Daniela Avetisyan; Roumen Nedkov; Denitsa Borisova; Galya Cvetanova

doi:10.1117/12.2538117

21 October 2019 Application of spectral indices and spectral transformation methods for assessment of winter wheat state and functioning

Daniela Avetisyan, Roumen Nedkov, Denitsa Borisova, Galya Cvetanova

Author Affiliations +

Proceedings Volume 11149, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI; 1114929 (2019) https://doi.org/10.1117/12.2538117
Event: SPIE Remote Sensing, 2019, Strasbourg, France

Abstract

As a commercial activity, agriculture is aimed primarily at production and relies on the availability of natural resources. The development of commercial activities has brought new environmental pressures on the natural capital stock. Technological progress and the desire to maximize returns and minimize costs have produced a marked intensification in agriculture over the last 40 years. Intensification can lead to degradation of soil, water and air. Water scarcity and related with it droughts have now emerged as a major challenge – and climate change is expected to make matters worse. In the last decades, Bulgarian agricultural sector is also negatively impacted by climate changes and water scarcity. Vegetation growing is limited by water scarcity and it is necessary to figure out the vegetation dynamic changes and responses to climate change to estimate the quality of ecosystems and maintain optimal ecosystem functioning. Water status can be effectively monitored by utilizing spectral indices and spectral transformation methods. Vegetation, water stress, and soil moisture indices are important to assess the crop state and its response of changing environmental conditions and to determine irrigation scheduling. The spectral transformation methods are very effective for interpretation and analysis of phenomena and processes related to the dynamics of change of the main components of the Earth surface. In the study Tasselled Cap model and obtained from its application Normalized Difference Greenness Index (NDGI) and Normalized Difference Wetness Index (NDWnI) will be applied. Microwave and optical satellite data, acquired by the sensors Sentinel 1 and Sentinel 2 of the European Space Agency Program for Earth Observation “Copernicus”, as well as climate data will be used.

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Daniela Avetisyan, Roumen Nedkov, Denitsa Borisova, and Galya Cvetanova "Application of spectral indices and spectral transformation methods for assessment of winter wheat state and functioning", Proc. SPIE 11149, Remote Sensing for Agriculture, Ecosystems, and Hydrology XXI, 1114929 (21 October 2019); https://doi.org/10.1117/12.2538117

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