Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

Memorial of the President and Fellows of Harvard College to the General Court for the enlargement of their power to hold real estate. Copy, [1797 July 15]

Four folio-sized leaves containing a handwritten copy of a petition to the Massachusetts General Court from the Harvard Corporation requesting the College's amount of tax exempt real estate be enlarged.

The Impact of a Substance Abuse Treatment for Offenders in Relation to the Time Spent in Treatment

The objective of this research is to evaluate the outcomes of a treatment for addicts. 123 subjects were tested before treatment and at 5, 8 and 11 months follow-up periods with a French version of the Addiction Severity Index (ASI). Exposure to treatment was based on the number of clients’ contact-hours with a therapist. The sample was divided into three groups according to the number of hours spent in treatment. The data was analysed using MANOVA on the seven scales of the ASI for the three groups and the four time periods. Results showed that all groups improved significantly but that this improvement was not related to the number of hours spent in treatment.