Pixel‐oriented land use classification in energy balance modelling

Abstract

Mass and energy transfer between soil-vegetation and the atmosphere is the\ud process that allows to maintain an adequate energy and water balance in the\ud earth-atmosphere system. However, the evaluation of the energy balance\ud components, such as the net radiation and sensible and latent heat fluxes, is\ud characterized by significant uncertainties related both to the dynamic nature of\ud heat transfer processes and surfaces heterogeneity. Therefore, a detailed land use\ud classification and an accurate evaluation of vegetation spatial distribution are\ud required for an accurate estimation of these variables. For this purpose, in the\ud present paper, a pixel-oriented supervised classification was applied to obtain\ud land use maps of the Basilicata region, in Southern Italy, by processing three\ud Landsat TM and ETM+ satellite images. An accuracy analysis based on the\ud overall accuracy index and the agreement Khat of Cohen coefficient showed a\ud good performance of the applied classification methodology and a good quality of\ud the obtained maps. Subsequently, these maps were used in the application of a\ud Simplified Two-Source Energy Balance (STSEB) model for estimating the actual\ud evapotranspiration at a regional scale. The comparison between the simulations\ud made by applying the STSEB model and the measurements of evapotranspiration\ud at a lysimetric station located in the study area showed the applicability and\ud validity of the proposed methodology

Daily Evapotranspiration Estimation at the Field Scale: Using the Modified SEBS Model and HJ-1 Data in a Desert-Oasis Area, Northwestern China

“…These approaches can be broadly grouped into four categories: (1) empirical and semi-empirical methods [7,8]; (2) surface energy balance models (SEB) (e.g., the surface energy balance algorithm for land (SEBAL), the surface energy balance system (SEBS) and mapping ET with internalized calibration (METRIC), the two-source energy balance model (TSEB), and the simplified two-source energy balance model (STSEB) [9][10][11][12][13][14]; (3) vegetation index approaches (e.g., vegetation index combined with the Penman-Monteith (PM) method and the Priestley-Taylor (PT) method) [15,16]; (4) data assimilation combined with land surface models and observations [17,18]. RS-based models have been developed and applied over a wide range of spatial scales from local to global, performing consistently with ground measurements by the relative error of 10-30% for daily ET and 5% for seasonal and annual ET [19][20][21][22][23].…”

Variability of Temperature and Its Impact on Reference Evapotranspiration: The Test Case of the Apulia Region (Southern Italy)

“…Several methods for the estimation of potential evapotranspiration are available in the literature, based on radiation or temperatures. Tegos et al (2015) presented a parametric method which implements spatially varying parameters calibrated on the basis of potential evapotranspiration data [18][19][20][21][22][23][24]. Recently, landscape planning has been related to climate change; in particular, the knowledge of variables, especially temperatures and evapotranspiration, plays an important role in urban and rural planning policies [25][26][27][28][29].…”

Mapping Evapotranspiration Coefficients in a Temperate Maritime Climate Using the METRIC Model and Landsat TM

“…The results finally showed a clear improvement (difference mean value = 0.004, std = 0.06) as might have been expected. Interestingly, the evaluation of the energy balance components, such as the net radiation and the sensible and latent heat fluxes, is characterized by significant uncertainties related to surfaces heterogeneity [68]. Therefore, a new pixel oriented parameterization would be required for IW surfaces [69].…”