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Content-based querying allows efficient retrieval of images based on the information they contain, rather than acquisition date or geographical extent. We extend the potential of a content-based image retrieval (CBIR) system based on Self- Organizing Maps (SOMs), to the analysis of remote sensing data. A database was artificially created by splitting each satellite image to be analyzed into small...
A phenomenon is defined as any state or process known through the senses rather than by intuition or reasoning, and thus is an observable event, especially something special or unusual. A geophysical phenomenon in the context of geoscience data can be characterized as a spatial region which is significantly different from the rest of the image; having higher/lower than average background intensity...
Presently Earth observation (EO) satellites acquire huge volumes of high resolution images very much over-passing the capacity of the users to access the information content of the acquired data. Thus, in addition to the existing methods for EO data and information extraction, new methods and tools are needed to explore and help to discover the information hidden in large EO image repositories. This...
Geospatial content-based image retrieval (CBIR) systems can be used to query for visually similar images by identifying similar patterns between a query image and those in the database. When several different classes of features are used, some queries require that each class should be given a different degree of weight; to this end, CBIR indexes are built for each class of features. This paper proposes...
For decades, the task to precisely calibrate the satellite microwave radiometer is challenging. The evaluation of the absolute calibration of the TMI brightness temperatures is an extremely formidable task due to the difficulty in obtaining an accurate standard with which to compare the TMI. The proposed research will investigate the Amazon rain forest area as a distributed target for the Satellite...
There are many satellites in orbit using total power microwave radiometers with external calibration targets. Pre- launch and on-orbit calibrations have been developed and applied to ensure accurate measurements over decades. But because of different designs as well as instrument aging effects, subsequent calibration is necessary to improve or maintain measurement accuracy. In-orbit inter-satellite...
The objective of this study is to investigate the relationship between a wide range of spectral chlorophyll indices and chlorophyll content of wheat crop using laboratory measurements. The measurements included the GER-3700 spectroradiometric data, leaf chlorophyll content using the SPAD-502 meter, and leaf chlorophyll content estimated from chemical laboratory analysis. The SPAD-502 readings were...
Selective application of herbicide in agricultural cropping systems provides both economic and environmental benefits. Implementation of this technology requires knowledge of the location and density of weed species within a crop. In this study, two image classification techniques (neural networks and maximum likelihood) are compared for accuracy in weed/crop species discrimination. In the summer...
In precision agriculture, crop nitrogen status could be estimated based on the measurement of leaf chlorophyll content at specific stages of crop development. Over the last decade, several spectral chlorophyll indices have been developed to estimate chlorophyll content both at the leaf and the canopy level using hyperspectral remote sensing data and considering different crop types. For an accurate...
The optical properties of the Amazon waters are controlled by the so called optically active substances which can be represented by the load of suspended and dissolved substances in water, and phytoplankton. The water composition undergoes intense variations along the year, as a response to the seasonal exchange of water between the Amazon River and its floodplain. The present study evaluates the...
We present here a solution to thermal volcano monitoring, based on the synergetic merge of up to four multispectral payloads and the use of adhoc developed computing routines "MyVOL" and "MyMOD". The latter, are based on auto-adaptive, automated processes involving high-resolution SWIR-TIR and low-resolution MIR-TIR radiances. Both routines were tested on large and dense eruptive...
Feature extraction is often applied for dimensionality reduction in hyperspectral data classification problems to mitigate the Hughes phenomenon. Some studies had proven that nonparametric weighted feature extraction (NWFE) is a powerful tool to extract well-described features for classification. NWFE concentrates only on the separability of spectral data, however, in many remotely sensed images,...
Natural and crop vegetation phenologic data become indispensable when creating thematically and geographically detailed maps through satellite images classification. Several date acquisition is necessary to achieve this cartography. However, the presence of clouds, shadows, snow, etc, is usual when many different dates are used and that fact implies an important loss in classifiable surface. This...
The present paper presents an application of non- parametric statistical tests for the analysis of time series of remotely sensed data, acquired by different sensors of the same series. A set of points, extracted from the NOAA AVHRR GAC pathfinder dataset, which covers the period 1981-2001, was used as test dataset. Two tests, the Kruskal-Wallis and the Friedman test, have been used to address two...
Remote sensing imagery has relatively low spatial resolution. Since different materials/objects may be present in the area covered by a pixel, the pixel reflectance can be considered as the linear mixture of reflectance of these materials/objects (i.e., endmembers). Thus in remote sensing image processing we deal with mixed pixels instead of pure pixels as in traditional digital image processing....
Ecological and hydrological cycles play a key role in global climate dynamics. Remote sensing data are important in climate studies as they provide a global coverage of important hydrological variables at a variety of spatial and temporal scales. In this paper we study the long term relationships between NDVI derived from AVHRR and microwave brightness temperature from SSM/I sensor for different climate...
All remote sensing of the Earth's surface in the solar wavelengths is impacted by the bidirectional reflectance distribution function (BRDF): all Earth surfaces scatter light anisotropically. The BRDF describes the angular distribution of scattered light and is thus what most remote sensing instruments sample. The BRDF is dependent on the structural as well as the optical characteristics of surfaces...
The metabolism and phenology of Amazon rainforests significantly influence global dynamics of climate, carbon and water, but remain poorly understood. In this study we utilized Moderate Resolution Imaging Spectroradiometer (MODIS) terrestrial ecosystem variables to analyze Amazon rainforest dynamics utilizing the satellite products; vegetation indices (VI), leaf area index (LAI), fraction of absorbed...
A number of the major human infectious diseases (like malaria and dengue) and Desert Locusts that still plague the developing world are sensitive to inter-seasonal and inter-decadal changes in environment and climate. Monitoring variations in environmental conditions such as rainfall and vegetation helps decision-makers at Ministries of Agriculture and Ministries of Health to assess the risk levels...
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