Data Mining Using NDVI Time Series Applied to Change Detection

Land-Cover Change Detection Using Multi-Temporal MODIS NDVI Data

Monitoring the locations and distributions of land-cover change is important for establishing links between policy decisions, regulatory actions and resulting land-use activities. Past activities including two-date change detection efforts using Landsat data have tended to be performance limited for applications in biologically complex systems. This study explored the use of 250 m multi-tempora...

Urban Wetland Change Detection Using Time-Series Remote Sensing Data

Wetland, as one of the weakest ecosystems in the world, is deteriorating rapidly in many regions. Longfeng wetland is the biggest urban wetland in China, located in the inner of Daqing city, Heilongjiang Province. It is divided into two areas by Wolong road, the east is provincial natural reserve and the west is unprotected. This paper describes a remote sensing change detection approach used t...

Change Detection in Time Series Data Using Wavelet Footprints

Detecting changes in time series data is an important data analysis task with application in various scientific domains. In this paper, we propose a novel approach to address the problem of change detection in time series data, which can find both the amplitude and degree of changes. Our approach is based on wavelet footprints proposed originally by the signal processing community for signal co...

Change Point Detection in Time Series Data Using Support Vectors

Change Point Detection in time series data is of interest in various research areas including data mining, pattern recognition, statistics, etc. Even though there are several e®ective methods in the literature for detecting changes in mean, and an increase in variance, there are none for decrease in variance. E®ective detection of decreased variance has been reported as future work in earlier p...

Monitoring Agricultural Biomass Using NDVI Time Series