Two approaches to calculate TVDI in humid subtropical climate of southern Brazil

Abstract

Soybean crops occupy most areas in Rio Grande do Sul State and are highly dependent on rainfall since most of them are non-irrigated. Rainfall during the harvest period is often insufficient to meet the water demand, making water indicators an important tool for the crops.

Condições hídricas de lavoura de soja usando sensoriamento remoto terrestre

“…A necessidade de uso das imagens se dá pelo fato de ser necessário que na área em estudo ocorram condições hídricas extremas, em termos de umidade do solo, para os diferentes valores de IV, de forma a propiciar uma correta determinação dos limites secos e úmidos do triângulo evaporativo (Roerink et al, 2000;Kustas et al, 2004), o que não é possível somente com medidas de escala local. Foi utilizada a técnica de parametrização por múltiplas imagens, de acordo com Schirmbeck et al (2018a). Após parametrizado o TVDI foi estimado a partir dos dados de NDVI e T S medidos em escala local aplicando a equação proposta por Sandholt et al (2002):…”

Water monitoring of soybean crops using the TVDI obtained from surface radiometric sensors

“…Simultaneous T S and NDVI data allow obtaining the surface moisture index, known as the temperaturevegetation dryness index (TVDI) (Sandholt et al, 2002), which is based on the evaporative triangle concept and used in various studies to monitor surface water status (Wang et al, 2007;Holzman et al, 2014). Despite being widely used, most of the analyzes with this index were carried out in dry conditions, with few applications in humid subtropical conditions (Schirmbeck et al, 2017b(Schirmbeck et al, , 2018. When the TVDI is obtained from orbital images, the responsiveness of the index to variations in plant water status highlights some uncertainties related to issues of the temporal adequacy of data acquisition, such as satellite transit time or even number of revisits.…”

“…Radiometric issues can also lead to uncertainties, resulting from the spectral purity of the pixel, band position and width, and sensor degradation, among others. However, when the TVDI is obtained from radiometric sensors positioned on the surface, it is important to decide which methodology to adopt in order to determine the dry and wet limits of the evaporative triangle used to parameterize the index (Garcia et al, 2014;Schirmbeck et al, 2018). These limits define the possible conditions that may occur in a region and period of the year, relating the TVDI values at each moment to the set limits (Schirmbeck et al, 2018).…”

Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI); 21-year drought monitoring in Iran using satellite imagery within Google Earth Engine

“…a, b, a', and b' are the undetermined coefficients, related to the dry edge in the triangle. The parameters a and b were set equal to their average values used by (Schirmbeck et al, 2018). (Sandholt et al, 2002) MPDI…”