# IEEE Transactions on Geoscience and Remote Sensing

## Issue 5  Part 1 • May 2013

This issue contains several parts.Go to:  Part 2

## Filter Results

Displaying Results 1 - 25 of 38
• ### [Front cover]

Publication Year: 2013, Page(s): C1
| PDF (271 KB)
• ### IEEE Transactions on Geoscience and Remote Sensing publication information

Publication Year: 2013, Page(s): C2
| PDF (141 KB)

Publication Year: 2013, Page(s):2485 - 2486
| PDF (129 KB)
• ### Uncertainties in Estimating Normalized Difference Temperature Index From TOA Radiances

Publication Year: 2013, Page(s):2487 - 2497
Cited by:  Papers (4)
| | PDF (671 KB) | HTML

The widely used surface temperature/vegetation index ($T_{s}$ /normalized difference vegetation index) triangle method provides an effective way to estimate surface turbulent energy fluxes and soil moisture. This type of method mainly relies on the normalized difference temperature index (NDTI), which is usually calculated from land... View full abstract»

• ### Analysis of Range Measurements From a Pulsed Airborne $hbox{CO}_{2}$ Integrated Path Differential Absorption Lidar

Publication Year: 2013, Page(s):2498 - 2504
Cited by:  Papers (4)
| | PDF (637 KB) | HTML

• ### Bistatic Vector 3-D Scattering From Layered Rough Surfaces Using Stabilized Extended Boundary Condition Method

Publication Year: 2013, Page(s):2722 - 2733
Cited by:  Papers (9)
| | PDF (2429 KB) | HTML

A model of 3-D electromagnetic scattering from multiple rough surfaces within homogeneous-layered or vertically inhomogeneous media is developed in this work. This model, aimed at radar remote sensing of surface-to-depth profiles of soil moisture, computes total bistatic radar cross sections from the multilayer structure based on the scattering matrix approach, cascading the scattering matrices of... View full abstract»

• ### Combining Support Vector Machines and Markov Random Fields in an Integrated Framework for Contextual Image Classification

Publication Year: 2013, Page(s):2734 - 2752
Cited by:  Papers (70)
| | PDF (1652 KB) | HTML

In the framework of remote-sensing image classification, support vector machines (SVMs) have lately been receiving substantial attention due to their accurate results in many applications as well as their remarkable generalization capability even with high-dimensional input data. However, SVM classifiers are intrinsically noncontextual, which represents an important limitation in image classificat... View full abstract»

• ### Hyperspectral Data Geometry-Based Estimation of Number of Endmembers Using p-Norm-Based Pure Pixel Identification Algorithm

Publication Year: 2013, Page(s):2753 - 2769
Cited by:  Papers (22)
| | PDF (1403 KB) | HTML

Hyperspectral endmember extraction is a process to estimate endmember signatures from the hyperspectral observations, in an attempt to study the underlying mineral composition of a landscape. However, estimating the number of endmembers, which is usually assumed to be known a priori in most endmember estimation algorithms (EEAs), still remains a challenging task. In this paper, assuming hyperspect... View full abstract»

• ### Latent Dirichlet Allocation for Spatial Analysis of Satellite Images

Publication Year: 2013, Page(s):2770 - 2786
Cited by:  Papers (24)
| | PDF (4220 KB) | HTML

This paper describes research that seeks to supersede human inductive learning and reasoning in high-level scene understanding and content extraction. Searching for relevant knowledge with a semantic meaning consists mostly in visual human inspection of the data, regardless of the application. The method presented in this paper is an innovation in the field of information retrieval. It aims to dis... View full abstract»

## Aims & Scope

IEEE Transactions on Geoscience and Remote Sensing (TGRS) is a monthly publication that focuses on the theory, concepts, and techniques of science and engineering as applied to sensing the land, oceans, atmosphere, and space; and the processing, interpretation, and dissemination of this information.

Full Aims & Scope

## Meet Our Editors

Editor-in-Chief
Simon H. Yueh
Jet Propulsion Laboratory