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Target detection (TD) is one of the fundamental tasks in hyperspectral imagery (HSI) processing. Sparse representation (SR) as a novel tool is powerful in accurate detection of target of interest. In this paper, SR approach within disconnected spatial support is proposed for effective TD in HSI. For conventional sparse representation, an HSI pixel is represented as a sparse vector whose non-zero entries...
Aiming at the high accuracy and speed requirements of images registration for multiband data or hyperspectral data, a new method which combines scale invariant feature transform (SIFT) with vegetation index analysis is put forward. Firstly, feature points extracted by SIFT algorithm are classified into two sets — points on vegetation area and points on non-vegetation area, which is based on vegetation...
In this paper, we present a method to detect changes in high resolution remote sensing images based on superparsing proposed by Tighe et al. By comparing with several superpixel segmentation methods, we choose the SLIC (Simple Linear Iterative Clustering) method which can keep image boundary, produce consistent superpixels with similar size and shape, and also calculates fast. After superpixel segmentation,...
In this paper, we have compared the accuracy of four supervised classification as Mahalanobis, Maximum Likelihood Classification (MLC), Minimum distance and Parallelepiped classification with remote sensing Landsat images of different time period and sensors. We have used Landsat Multispectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper+ (ETM+) images of 1972, 1998 and 2013 respectively...
With development of hyperspectral imaging, it is possible to identify and classify land cover with more details in remote sensing applications. Selection of a minimal and efficient subset from the huge amount of features is an important challenge for classification problems. Almost all approaches for feature selection, which represented in literature, involve a search algorithm for selection of the...
Contour-based registration provides a feasible approach to object-based change detection with the development of segmentation techniques in remote sensing. In this paper, an affine-invariant registration algorithm based on orthogonal projection matrices is proposed for object-based change detection. First, we extract the objects of interest using segmentation technique and detect the curvature extreme...
The objective of this paper is to describe the method of crops pattern change allocation, and to simulate the crops pattern in Heilongjiang province utilizing crop pattern simulator (CROPS) model. In this study, based on interpreted remote sensing data and crops pattern statistical data, CROPS model simulates long time series crop spatial pattern. Firstly, crops pattern and driving factor analysis...
Depth is an essential characteristic of flood inundation in hydro-ecological research. Several studies have tried to estimate inundation depth from remotely sensed image and digital elevation model (DEM) data by applying a series of cross section profiles along the centerline of a river reach. This method requires a large amount of manual work in order to identify the centerlines and cross sections,...
In view of the problem occurred in those studies on crop planting acreage estimation using estimators at home and abroad, such as just one single estimator (simple estimator or regression estimator) is used to extrapolate the population values and estimate sampling errors; the efficiencies of population extrapolation are not evaluated among multiple estimators quantitatively; furthermore, the estimator...
One of the most important applications of remote sensing in urban area is impervious surface information extraction. Previous research has shown that satellite imagery has the potential and advantage for impervious surface estimating. In particular, the high resolution imagery, which has a spatial resolution in the meter to sub-meter range, is very useful for high accuracy mapping and monitoring of...
Identify the amount and spatial distribution of reserve cultivatable land resources is the basis for its development to increase crop planting areas. Taking Jiaxiang county of Shandong Province of China as a case study, this paper conducted image segmentation and merge based on RapidEye image data (5m spatial resolution) after data preprocessing. Then, object-oriented approach was used to classify...
Due to increasing global demand for natural rubber products, rubber (Hevea brasiliensis) plantation expansion has occurred in many regions where it was originally considered unsuitable. However, accurate maps of rubber plantations are not available, which substantially constrain our understanding of the environmental and socio-economic impacts of rubber plantation expansion. In this study, the rubber...
Artificial Neural Networks (ANNs) have been useful for decades to the development of image classification algorithms applied to several different fields. Image classification is the major component of the remote sensing to extract some of the important spatially variable parameters, such as land cover and land use (LCLU). The aim of this study is to investigate the capability of Artificial Neural...
Nitrogen is an important organic element during the growth of the crop, the accuracy of estimation for the crop N status may improve fertilizer N use efficiency. The chlorophyll content has a close relationship with the Nitrogen content. The multispectral remote sensing data may be used to assess crop N status by estimating chlorophyll content. This paper used the statistical model and the physical...
The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. While most existing researches focus on extracting elementary features such as basic terrains and individual objects, the detection of compound feature is still a challenge. This paper proposes a semi-automated approach integrating supervised image...
This research aims at evaluating the potential of multi-temporal images acquired in April-June period for crop mapping before harvest in Kashgar China. Firstly, images of both Landsat-5 TM and Huan Jing (HJ)-1 CCD data were used to acquire an image time series with 30 m spatial resolution and 15 day temporal resolution during the entire growing season. Subsequently, period-by-period separability of...
Desertified karst region is a focal area of vegetation recovery and ecological restoration in southwest China, and vegetation is an important and sensitive factor to reflect the changes of ecological environment in karst region. Recently, with the development and application of imaging spectrometer, remote sensing technology plays an important role in large-scale karst vegetation investigation. Remote...
The aim of this study was to investigate the use of a logistic model to determine the growth properties of Eichhornia crassipes (EC), in particular the area of EC. The area of EC was measured using Alos satellite images and GPS. The measurements were shown to lead to an accurate area-related logistic model of EC. This indicates that there is a possibility of obtaining the growth area of EC from a...
Landsat acquires the longest space-based moderateresolution land remote sensing images continuously. Compared with the other earlier Landsat satellites, Landsat 8 has several new characteristics in spectral bands, spectral range and radiometric resolution. Therefore, there is a strong requirement to analyze the characteristics of the Landsat 8 for land cover classification, global change research...
For Zhanghe areas, we utilized the Landsat5 TM images of 2010 to complete the region's land use classification based on the maximum likelihood method. Analyzing the constraints of land use classification in the research area, our classification method includes 4 aspects: cloud and hillshade were classified at first and then reprocessed separately; water body was classified combining supervised classification...
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