The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This article presents a methodology to improve the flood classification results of an automatic Sentinel-1 Flood Service (S-1FS) in arid areas, where reliable SAR-based water detection is usually not possible. Statistical information of Sentinel-1 (S-1) backscatter time series data were used to remove water look-alikes related to sand surfaces which generally lead to significant overestimations of...
We propose to use the temporal coherence of a time series to extract using Vertex Component Analysis (VCA) the suitable set of endmembers for each scene. The reconstruction error computed on the two previous scenes for each date is used to constrain the selection of the set of endmembers produced by VCA. Snow cover estimation is considered as application. We tested different approaches for abundance...
In this research, we proposed the Synchro Water Index (SWI) to detect widespread inundation extent in a transboundary river basin using the time-series Moderate Resolution Imaging Spectrometer (MODIS) data, a major contributor to progress in international flood monitoring. After removing clouds using the White-object Index (WoI), the multi-temporal processing coupled with in-situ water level data...
In this paper, we present a nearest neighbor based hierarchical change detection methodology for analyzing multi-temporal remote sensing imagery. A key contribution of this work is to define change as hierarchical rather than boolean. Based on this definition of change pattern, we developed a novel time series similarity based change detection framework for identifying inter-annual changes by exploiting...
In this study, we compare the classification performance of time series with single polarized SAR data, optical data and fused optical and SAR data through the Gram-Schmidt transform. Different machine learning algorithms for crop classification were applied. Specifically Gradient Boosting Trees (GBT) yielded good results as they are known to perform well with imbalanced feature labels and datasets...
The launch of Sentinel-1 constellation raise a new era for InSAR applications and time series analysis. The wide coverage, fine temporal and spatial resolution, precise control of orbits and the free distribution policy bring more new chances than ever to earth observations applications. In this experiment we use Sentinel-1A data that covers a period of one year and a half (from November 2014 to June...
This paper presents the Hybrid Analysis for Synthetic Aperture Radar (HASAR) framework for time series change detection (TSCD). The HASAR framework utilizes spatiotemporal observations to identify abrupt changes in SAR data stacks. Full resolution is used and no filtering processes are involved. Moreover, no thresholds or prior knowledge of the changes are required. The HASAR framework includes two...
Change detection (CD) between a pair of images is a popular problem in remote sensing. Despite a large amount of data is acquired every day by remote sensing satellites, standard CD methods usually consider only the two target images between which we desire to detect changes. The aim of this work is to present a novel framework in which the bi-temporal CD is redefined by evaluating the consistency...
Normalized Difference Vegetation Index (NDVI) time series is used to study different land cover dynamics such as change, compare vegetation dynamics between years and analyze intra-annual components. A nonlinear cosine model of the NDVI time series with a constant frequency is used to account for the time-varying nature of the land cover parameters due to seasonality or change. The Extended Kalman...
Landslides occur frequently and it is very meaningful to monitor them in disaster researches. Extracting the landslide from the high resolution satellite with fewer false changes is an important problem to be solved for remote sensing change detection research. In high spatial resolution and multi-temporal remote sensing images, landslides show significant differences with the background in both temporal...
Discriminating human-induced vegetation change is essential for sustainable managements of arid and semi-arid ecosystems. Residual Trends method (RESTREND), an effective quantitative method, has been widely used to discriminate human-induced vegetation changes in specific arid and semi-arid ecosystems. However, how to define homogeneous spatial neighborhood to determine reference pixel for estimating...
Disturbance and regrowth are vital processes in determining the roles of forest ecosystem in carbon and biogeochemical cycles. The vegetation change tracker (VCT) algorithm derives the spectral disturbance magnitude based on the time series observations. While these spectral disturbance magnitudes are indicative of physical changes in tree cover or biomass, their quantitative relationships have yet...
The well-being of the environment is one of the major factors that contributes to sustainability. Sustainable human settlements require local governance to plan, implement, develop, and manage human settlements expansions. This is important as the number anthropogenic activities is directly correlated to the increase in human population within a geographical region. Regional mapping of land cover...
Medium resolution remote sensing data such as Landsat imagery and its analysis are heavily affected by the mixed pixel problem especially in regions of heterogeneous, spatially dispersed land cover such as peri-urban environments. However, this data is often the only available temporally consistent data source for multi-temporal applications that cover time periods prior to 2000. For this reason,...
Temporal sequences of images called Satellite Image Time Series (SITS) allow land cover monitoring and classification by affording a large amount of images. Many approaches attempt to exploit this multi-temporal data in order to extract relevant information such as classification-based techniques. In this paper we compare low and high levels classification-based approaches that aim to reveal the SITS...
An effective monitoring and analysis of ecosystems requires developing new tools and knowledge. In this paper, we propose an approach for detecting land-cover changes using satellite Image Time Series. This approach represents each image by spectral indices and then extracts local features of these representations. Next, a clustering technique (e.g., k-means) is applied to the extracted features,...
The vast amount of data acquired by current high resolution Earth observation satellites implies some technical challenges to be faced. Google Earth Engine (GEE) platform provides a framework for the development of algorithms and products built over this data in an easy and scalable manner. In this paper, we take advantage of the GEE platform capabilities to exploit the wealth of information in the...
The absolute in situ calibration of the altimeter missions could insure the regular and long-term control of the altimeter sea surface height (SSH) time series with independent measurements[1]. At present there are mainly four absolute calibration sites over the world, which have been providing absolute biases for multiple satellite altimeters from the T/P mission (1992–2005) to the Jason-3 mission...
SMAP project is working on a new and enhanced high-resolution (3km and 1km) soil moisture product. This product will combine SMAP radiometer data and Sentinel-1A and -1B data, and it will use the heritage SMAP active-passive approach. However, modifications in the SMAP active-passive algorithm are done to accommodate the Sentinel-1A and -1B C-band SAR data. Tests of the SMAP and Sentinel active-passive...
A temporal change of lights from islands on the South China Sea was monitored by the Day/Night Band (DNB) of the visible infrared imaging radiometer (VIIRS) on the Suomi-NPP from 2014 to 2016. As the DNB data could be contaminated by the lunar lights reflected by clouds for half of each month, the DNB data around the new moon period were used to focus on detecting lights from the surface. DNB mean...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.