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The UAV remote sensing images due to its access to convenient, high resolution, low cost, low risk advantage has been more widely studied and applied to various field. However, due to the characteristics of complex, gray inconsistent, the larger distortion of UAV remote sensing image texture itself, which results the extraction of its characteristics to become one of the difficulties. In this paper,...
Goal of this paper is mapping the 1 μm from the OMEGA spectra in order to study the Martian iron mineralogy. This study is based on the results of Carrozzo et al. [1]. Goal of this paper is to map the 1 μm absorption signature in OMEGA spectra, in order to study the Martian mineralogy. In particular, we search for new spectral indices around the 1-μm absorption and the correlations between them. Due...
This paper enriches the hyperspectral pansharpening field following the development of new instruments. The updated version of SIM-GA imager, designed by Selex ES, is now composed by a panchromatic camera and two spectrometers in the VNIR and SWIR spectral ranges, respectively. Due to the different resolution factors among Panchromatic, VNIR and SWIR, various pansharpening approaches are possible...
Given a raster spatial framework, as well as training and test sets, the spatial decision tree learning (SDTL) problem aims to minimize classification errors as well as salt-and-pepper noise. The SDTL problem is important due to many societal applications such as land cover classification in remote sensing. However, the SDTL problem is challenging due to the spatial autocorrelation of class labels,...
For the complexity of the ship feature classification and sensitivity of optical sensor to weather, airspace, illumination and other marine environment, we propose a new unsupervised multi-ship image segmentation algorithm of remote sensing platforms, including separation from the target area of the adaptive multi threshold criterion, algorithm based on multiscale Ncut hierarchical, multi-objective...
The combination of polarimetric SAR (PolSAR) with the interferometry capability (InSAR) enables the extraction of new features that enhances the development of biomass estimation models. This work aims in demonstrating the importance of the simultaneous use of several types of SAR features for estimating forest biomass. The study site is São Gabriel da Cachoeira, located in the Brazilian Amazon. Forest...
The relationship between X-band Synthetic Aperture Radar (SAR) observations and soil moisture (SM) and surface roughness (SR) is investigated over well-monitored bare agricultural fields, using TerraSAR-X observations at 37.8° (VV and HH polarization) and 42.3° (VV and VH). TerraSAR backscatter increased with increasing SM but exhibited limited sensitivity, the highest (0.14 dB/m3/m3) being in the...
Remote sensing opens a new method for obtaining forest canopy density. The forest resource field inventory data and simultaneous LANDSAT TM data were used to discover the model of estimating forest canopy density based on remote sensing here in Shimian county, Sichuan province, P.R.of China. A lot of derivative data were created from LANDSAT TM data. 1204 forest sub-compartments with inner homogeneity...
Some researches in the field of surveying and mapping showed that it held potentials to derive vegetation height from stereo imagery. However, most of current researches were conducted on aerial images or spaceborne images with very high resolutions (about 0.5m). The resolution of stereo sensors with global coverage is always not so high. The characteristics of digital surface models (DSMs) should...
AIRS, GOSAT and SCIAMACHY are all very important remote sensors in observing atmospheric CH4 concentrations, and produce different observation data which have their own advantages and disadvantages. Therefore, it is important to decide which atmospheric CH4 production is more agreeable to the surface monitor of CH4 concentrations. Taking the WALIGUAN (China) site for example, correlation analysis...
This paper proposes an experimental analysis of the Local Mutual Information (LMI) invariance in the context of unsupervised change detection between multi-spectral images. The conversion from Digital Numbers to Surface Reflectance does not affect theoretically the LMI based change map under the assumption of homogeneous atmospheric conditions. Experiments are conducted with QuickBird bi-temporal...
The analysis of multitemporal remote sensing images is becoming an increasingly important problem because of the upcoming scenario of multispectral satellite constellations monitoring our Planet. Algorithms that can analyze such amount of heterogeneous information are necessary. While linear techniques have been extensively deployed, this work considers a kernel method that finds nonlinear correlations...
Qinghai Lake, which is the largest salt water lake in China and a major obstacle in the burgeoning Eastward desertification from West China, has a vital role in the ecological sustainability of Tibetan Plateau. From the ecological perspective, the environment of Qinghai Lake became worse since the end of last century, while due to its remoteness, the field surveys in this area are difficult to carry...
Quantitative estimation of vegetation water content with remote sensing technique is of great significance for vegetation physiological status and growth trend monitoring. It also provides a theoretical foundation for actual application of vegetation water content diagnosis using remote sensing images in Wild Duck Lake wetland. In this paper the NDVIs and SRs calculated from simulation WorldVeiw-2...
This study presents a detailed analysis of Iterative Self Organizing Data Analysis (ISODATA) clustering for multispectral data classification. ISODATA is an unsupervised classification method which assumes that each class obeys a multivariate normal distribution, hence requires the class means and covariance matrices for each class. In this study, we use ISODATA to classify a diverse tropical land...
Leaf water content (LWC) is an important parameter for evaluating crop health and predicting crop yield. The objective of this study was to compare two methods for the precision of estimating LWC in winter wheat by combining stepwise regression method and partial least squares (SRM-PLS) or PLS based on the relational degree of grey relational analysis (GRA) between water vegetation indexes (WVIs)...
Field surveys were conducted at regreening, jointing, heading and flowering stage in Jiangsu in 2011. The HJ satellite images were downloaded and preprocessed. Wheat grain quality was acquired at maturity. Band values of sampling sites were derived from the satellite images of four growth stages by using GPS information, and the candidate vegetation indices were calculated with the band values. The...
Spatial distribution of farmland organic is essential for soil fertility adjustment, land-use change and sustainable development of agriculture. It is important to develop a rapid method for mapping farmland organic matter at county scale using remote sensing technology. The HJ-1A HSI image used in the paper has 115 bands, which result in good response to soil organic matter. With the support of in-situ...
Sampling basic unit size is considered as a key factor in the process of formulating spatial sampling survey schemes. Reasonable sampling unit size plays an important role for reducing sampling survey cost and improving estimating accuracy of population value. The experiment on optimization of survey unit size was conducted to improve the efficiency of spatial sampling for estimating winter wheat...
Coherent change detection using paired synthetic aperture radar images is typically performed using a classical estimator of coherence applied under an assumption of complex Gaussian data. The magnitudes of the resultant coherence estimates are plotted as an image and used to gauge changes in the observed scene. Here we investigate the suitability of an alternative coherence estimator that further...
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