The aim of this study is to estimate surface soil moisture at a spatial resolution of 500 m and a temporal resolution of at least 6 days, by combining remote sensing data from Sentinel-1 and optical data from Sentinel...
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The aim of this study is to estimate surface soil moisture at a spatial resolution of 500 m and a temporal resolution of at least 6 days, by combining remote sensing data from Sentinel-1 and optical data from Sentinel-2 and MODIS (Moderate-Resolution Imaging Spectroradiometer). The proposed methodology is based on the changedetection technique, applied to a series of measurements over a three-year period (2015 to 2018). The algorithm described here as "Soil Moisture Estimations from the Synergy of Sentinel-1 and optical sensors (SMES)" proposes different options, allowing information from vegetation densities and seasonal conditions to be taken into account. The output from this algorithm is a moisture index ranging between 0 and 1, with 0 corresponding to the driest soils and 1 to the wettest soils. This methodology has been tested at different test sites (South of France, Central Tunisia, Western Benin and Southwestern Niger), characterized by a wide range of different climatic conditions. The resulting surface soil moisture estimations are compared with in situ measurements and already existing satellite-derived soil moisture ASCAT (Advanced SCATterometer) products. They are found to be well correlated, for the African regions in particular (RMSE below 6 vol.%). This outcome indicates that the proposed algorithm can be used with confidence to estimate the surface soil moisture of a wide range of climatically different sites.
SMAPVEX12 is a pre-launch field campaign for evaluating and testing the soil moisture retrievals retrieved from the SMAP project. During this experiment, airborne microwave observations from PALS radiometer and radar:...
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ISBN:
(纸本)9781628413274
SMAPVEX12 is a pre-launch field campaign for evaluating and testing the soil moisture retrievals retrieved from the SMAP project. During this experiment, airborne microwave observations from PALS radiometer and radar: brightness temperature and radar backscatter, as well as ground measurements were acquired. In this study, the remote sensing soil moisture was retrieved from SMAPVEX12 PALS radiometer L-band ( 6GHz) brightness temperature at high altitude flight. The PALS soil moisture was then aggregated and compared with PALS radar backscatter coefficient to generate high spatial resolution microwave soil moisture in change. The R-2 values of PALS soil moisture retrieval validation range from 0.407-0.881, indicating good accuracy of soil moisture retrieval. The R2 values of comparison between aggregated PALS Delta theta and PALS Delta sigma range from 0.492-0.805, while the downscaled Delta theta validation range from 0.128-0.383.
Forest disturbances such as harvesting, wildfire and insect infestation are critical ecosystem processes affecting the carbon cycle. Because carbon dynamics are related to time since disturbance, forest stand age that...
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Forest disturbances such as harvesting, wildfire and insect infestation are critical ecosystem processes affecting the carbon cycle. Because carbon dynamics are related to time since disturbance, forest stand age that can be used as a surrogate for major clear-cut/fire disturbance information has recently been recognized as an important input to forest carbon cycle models for improving prediction accuracy. In this study, forest disturbances in the USA for the period of similar to 1990-2000 were mapped using 400+ pairs of re-sampled Landsat TM/ETM scenes in 500m resolution, which were provided by the Landsat Ecosystem Disturbance Adaptive Processing System project. The detected disturbances were then separated into two five-year age groups, facilitated by Forest Inventory and Analysis (FIA) data, which was used to calculate the area of forest regeneration for each county in the USA. In this study, a disturbance index (DI) was defined as the ratio of the short wave infrared (SWIR, band 5) to near-infrared (NIR, band 4) reflectance. Forest disturbances were identified through the Normalized Difference of Disturbance Index (NDDI) between circa 2000 and 1990, where a positive NDDI means disturbance and a negative NDDI means regrowth. Axis rotation was performed on the plot between DIs of the two matched Landsat scenes in order to reduce any difference of DIs caused by non-disturbance factors. The threshold of NDDI for each TM/ETM pair was determined by analysis of FIA data. Minor disturbances affecting small areas may be omitted due to the coarse resolution of the aggregated Landsat data, but the major stand-clearing disturbances (clear-cut harvest, fire) are captured. The spatial distribution of the detected disturbed areas was validated by Monitoring Trends in Burn Severity fire data in four States of the western USA (Washington, Oregon, Idaho, and California). Results indicate omission errors of 66.9%. An important application of this remote sensing-based disturbance
We formulate the problem of microcalcification detection in digital mammograms as a statistical changedetection problem in the local properties of the image. First, we represent mammograms by two-dimensional autoregr...
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ISBN:
(纸本)9781424471379
We formulate the problem of microcalcification detection in digital mammograms as a statistical changedetection problem in the local properties of the image. First, we represent mammograms by two-dimensional autoregressive moving-average (2D ARMA) fields;thus uniquely characterizing the images by their reduced dimensionality 2D ARMA feature vectors. Texture changes in mammograms are then modeled as an additive change in the mean parameter of the PDF associated with the 2D ARMA feature vector sequence that describes the image. A generalized likelihood ratio test is used to detect theses changes and estimate the exact time (or space) where they occur. Our simulation results on the Digital Database for Screening Mammography hosted by the University of South Florida show that the decision functions of cancerous images present high peaks at the microcalcification locations, whereas they exhibit a uniform behavior for healthy mammograms. The proposed algorithm achieves a sensitivity and specificity of 96.9% and 97.8%, respectively.
In recent decades vandal acts and graffiti drawing problem have increased and have required a lot of public funding. To face this problem the communal administrations have invested in automatic video surveillance syst...
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ISBN:
(纸本)0780393856
In recent decades vandal acts and graffiti drawing problem have increased and have required a lot of public funding. To face this problem the communal administrations have invested in automatic video surveillance systems. To deal with this problem through image processing techniques, this paper presents a method for graffiti detection based on change detection algorithm and motion vector. The aim of this system is to detect the graffiti painting act while people tire going to draw, identify them and distinguish the drawer.
Remote Sensing provides the only practical means to monitor changes over large areas. This paper describes the development of a generic algorithm designed to map the temporal occurrence and spatial extent of areas exh...
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ISBN:
(纸本)0780387422
Remote Sensing provides the only practical means to monitor changes over large areas. This paper describes the development of a generic algorithm designed to map the temporal occurrence and spatial extent of areas exhibiting sudden change. The algorithm is demonstrated here applied to the problem of mapping fire affected areas. The research further develops the work of [1], which implemented a bi-directional reflectance (BRDF) model-based change detection algorithm to map the approximate day and location of burning, using daily 500m MODIS surface reflectance data. An original algorithm assumption is that the surface state remains static prior to the changes of interest. This is problematic in file presence of underlying change (for example, due to vegetation phenology) especially when there are missing and/or cloudy data. In an attempt to deal with this issue, an additional kernel has been added to the BRDF model in the form of a cubic function of time. In addition, a step function kernel has been introduced in order to more robustly detect step-like changes. These modifications and preliminary results over southern Africa using daily MODIS land surface reflectance data are presented.
[1] A methodology to infer skin soil moisture from time series of passive microwave imagery is presented. Based on temporal changes in the microwave polarization difference temperature, it yields a quantitative moistu...
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[1] A methodology to infer skin soil moisture from time series of passive microwave imagery is presented. Based on temporal changes in the microwave polarization difference temperature, it yields a quantitative moisture estimate as a fraction of field capacity. Based on a processing technique that separates low-frequency components caused by vegetation changes from fast precipitation-induced changes, its main feature is the complete independence of ground-based data. The method solely employs information contained in the microwave signal itself. When applied on Special Sensor Microwave/Imager imagery over the European continent, it is found that the methodology is only applicable to areas with sparse vegetation cover, where the fractional error (with respect to field capacity) is estimated to range from 16 to 28%. Finally, comparison of calculated moisture time series with observed precipitation shows a fair agreement.
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