1,721,190 research outputs found
Performance indicators for the statistical evaluation of digital image classifications
No full textA statistical procedure is proposed to evaluate the algorithms for the numerical classification of images. The approach is based on the derivation of performance indicators from measurements of signature separability and thresholding analysis. Although these measurements are not new in image processing techniques, they are used in this study in an original way for the comparison of outputs resulting from different classification criteria. The theoretical description of the method suggested is followed by its practical application to a case-study for mapping crop coefficients in an irrigation district
Thermal infrared observations of heterogeneous soil-vegetation systems
No full textRemote SensingAerospace Engineerin
Spectral indicators of photosynthesis. The impact of anisotropy of reflectance and heterogeneity of vegetation
No full textRemote sensing and simulation modelling for on-demand irrigation systems management
No full textThis paper describes a procedure for monitoring and improving the performance of on-demand irrigation networks, based on the integration of remote sensing techniques and simulation modelling of water flow in each component of the system. In order to adequately reproduce the actual operation of an on-demand irrigation system, the physical characteristics of the irrigation systems (crop, soil and distribution network) are linked to the farmers' irrigation criteria and preferences. The development of this procedure, which is currently being implemented in a district in South Italy, is of great support to improving the management and monitoring of irrigation systems
Adapting numerical models and remote sensing applications to the needs of irrigation agencies and farmers
No full text
Reconstruction of gap-free time series satellite observations of land surface temperature to model spectral soil thermal admittance
No full textThe soil thermal properties (soil thermal conductivity, soil heat capacity and soil diffusivity) are the main parameters in the applications that need quantitative information on soil heat transfer. Conventionally, these properties are either measured in situ or estimated by semi-empirical models using the fractions of soil constituents. The use of such methods over large and heterogeneous areas, however, is often costly, timeconsuming and sometimes impractical. This thesis proposes and evaluates a new approach to estimate the soil thermal properties by inverse modelling of Spectral Soil Thermal Admittance (SSTA) which is determined using the time series satellite observations of Land Surface Temperature (LST) and soil heat flux (G0) over the entire Qinghai-Tibet Plateau (QTP) from 2008 to 2010. To calculate the soil thermal admittance, the amplitudes of G0 and LST at significant frequencies are required which needs consistent, continuous and long time series. The hourly FY-2C LST time series used in this study were often contaminated by missing data (gaps) and outliers. The HANTS algorithm and M-SSA were used to fill the gaps and remove the outliers in the LST time series. Then, the gap-filled hourly LST was used to identify the most significant periodic components over a three-year data. The amplitude of soil heat flux and LST were estimated at significant frequencies and then the soil thermal admittance at each frequency was determined over the study area. The SSTA, which is the variation of STA against frequency, contains information about the soil thermal properties of different soil layers. An inversion model was used to estimate soil thermal properties of different soil layers (assuming three-layer soil) over the Q-TP.Geoscience and Remote SensingCivil Engineering and Geoscience
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