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You searched for: Journal International journal of remote sensing Remove constraint Journal: International journal of remote sensing Publication Year 2017 Remove constraint Publication Year: 2017 Source 2017 v.38 no.23 Remove constraint Source: 2017 v.38 no.23
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1. A central-point-enhanced convolutional neural network for high-resolution remote-sensing image classification

Author:
Pan, Xin; Zhao, Jian
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6554-6581
ISSN:
1366-5901
Subject:
land cover; neural networks; regression analysis; remote sensing; support vector machines; translation (genetics)
Abstract:
... As one of the most important algorithms in the field of deep learning technology, the convolutional neural network (CNN) has been successfully applied in many fields. CNNs can recognize objects in an image by considering morphology and structure rather than simply individual pixels. One advantage of CNNs is that they exhibit translational invariance; when an image contains a certain degree of dist ...
DOI:
10.1080/01431161.2017.1362131

2. A comparison of gap-filling approaches for Landsat-7 satellite data

Author:
Yin, Gaohong; Mariethoz, Gregoire; Sun, Ying; McCabe, Matthew F.
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6653-6679
ISSN:
1366-5901
Subject:
Landsat; algorithms; geostatistics; image analysis; kriging; land cover; landscapes; prediction; regression analysis; remote sensing
Abstract:
... The purpose of this study is to assess the relative performance of four different gap-filling approaches across a range of land-surface conditions, including both homogeneous and heterogeneous areas as well as in scenes with abrupt changes in landscape elements. The techniques considered in this study include: (1) Kriging and co-Kriging; (2) geostatistical neighbourhood similar pixel interpolator ...
DOI:
10.1080/01431161.2017.1363432

3. A comparison of pixel-based decision tree and object-based Support Vector Machine methods for land-cover classification based on aerial images and airborne lidar data

Author:
Wu, Qiong; Zhong, Ruofei; Zhao, Wenji; Fu, Han; Song, Kai
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7176-7195
ISSN:
1366-5901
Subject:
aerial photography; cameras; decision support systems; environmental assessment; land cover; landscapes; lidar; monitoring; remote sensing; roads; support vector machines; trees
Abstract:
... Precisely monitoring land cover/use is crucial for urban environmental assessment and management. Various classification techniques such as pixel-based and object-based approaches have advantages and disadvantages. In this article, based on our experiment data from an unmanned platform carried lidar scanner system and camera, we explored and compared classification accuracies of pixel-based decisio ...
DOI:
10.1080/01431161.2017.1371864

4. A comparison of the performance of some extreme learning machine empirical models for predicting daily horizontal diffuse solar radiation in a region of southern Iran

Author:
Hosseini Nazhad, Seyed Hossein; Lotfinejad, Mohammad Mehdi; Danesh, Malihe; ul Amin, Rooh; Shamshirband, Shahaboddin
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6894-6909
ISSN:
1366-5901
Subject:
algorithms; cities; data collection; models; prediction; remote sensing; solar radiation; Iran
Abstract:
... This study uses the empirical models of extreme learning machine (ELM) method to predict daily horizontal diffuse solar radiation (HDSR). As a possibility for modification, the recent hybrid ELM methods such as complex ELM (C-ELM), self-adaptive evolutionary ELM (SaE-ELM), and online sequential ELM (OS-ELM) have been developed for the prediction of the daily HDSR. The empirical model of ELM predic ...
DOI:
10.1080/01431161.2017.1368098

5. Adaptive remote-sensing image fusion based on dynamic gradient sparse and average gradient difference

Author:
Li, Weisheng; Hu, Xin; Du, Jiao; Xiao, Bin
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7316-7332
ISSN:
1366-5901
Subject:
algorithms; image analysis; models; remote sensing
Abstract:
... A new method for remote-sensing image fusion based on variational methods and the image objective evaluation model is proposed. Different from the previous methods, the proposed method does not make big improvement on the variational model but focuses on how to make the calculation of existing method more accurate. The problem is that in the solving process of some variational models, it cannot be ...
DOI:
10.1080/01431161.2017.1371863

6. Aeroplane detection in very-high-resolution images using deep feature representation and rotation-invariant Hough forests

Author:
Li, Dilong; Yu, Yongtao; Guan, Haiyan; Zhong, Liang
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6882-6893
ISSN:
1366-5901
Subject:
airplanes; detection; image analysis; remote sensing
Abstract:
... This letter proposes a processing chain for detecting aeroplanes from very high-resolution (VHR) remotely sensed images with the fusion of deep feature representation and rotation-invariant Hough forests. First, superpixel segmentation is used to generate meaningful and non-redundant patches. Second, deep learning techniques are exploited to construct a multi-layer feature encoder for representing ...
DOI:
10.1080/2150704X.2017.1363430

7. Analysing changes of the Poyang Lake water area using Sentinel-1 synthetic aperture radar imagery

Author:
Zeng, Lingfang; Schmitt, Michael; Li, Lin; Zhu, Xiao Xiang
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7041-7069
ISSN:
1366-5901
Subject:
Landsat; cloud cover; drought; dry season; freshwater lakes; image analysis; issues and policy; moderate resolution imaging spectroradiometer; monitoring; reflectance; remote sensing; surface water; synthetic aperture radar; wetlands; winter; China
Abstract:
... Poyang Lake is the largest freshwater lake in China. Monitoring changes of its water area is essential for the conservation of important wetlands and ecological resources, and plays an important role for sustainable water use and management. Landsat and Moderate-Resolution Imaging Spectroradiometer (MODIS) sensor images are widely used for mapping waterbodies, because of their sensitivity for spec ...
DOI:
10.1080/01431161.2017.1370151

8. A new difference image creation method based on deep neural networks for change detection in remote-sensing images

Author:
Cao, Guo; Wang, Bisheng; Xavier, Haro-Carrión; Yang, Di; Southworth, Jane
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7161-7175
ISSN:
1366-5901
Subject:
algorithms; cluster analysis; data collection; neural networks; quantitative analysis; remote sensing
Abstract:
... In this article, we propose a novel difference image (DI) creation method for unsupervised change detection in multi-temporal multi-spectral remote-sensing images based on deep learning theory. First, we apply deep belief network to learn local and high-level features from the local neighbour of a given pixel in an unsupervised manner. Second, a back propagation algorithm is improved to build a DI ...
DOI:
10.1080/01431161.2017.1371861

9. An improved method to estimate reference cloud-free images for the visible band of geostationary satellites

Author:
Tornow, Florian; Clerbaux, Nicolas; Ipe, Alessandro; Urbain, Manon
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7220-7241
ISSN:
1366-5901
Subject:
climatology; dust storms; geophysics; ice; remote sensing; satellites; snow; Polar Regions
Abstract:
... Geostationary images have been used frequently in the past 50 years to derive geophysical information. As a complement to all-sky observations, clear-sky counterparts play an important role in the derivation of cloud properties. We investigated ways to improve estimates of top-of-atmosphere (TOA) visible clear-sky images, over the full spatial and temporal resolution of Meteosat First Generation ( ...
DOI:
10.1080/01431161.2017.1372859

10. An improvement method for circular synthetic aperture radar imaging

Author:
Jia, Gaowei; Gu, Chengfei; Chang, Wenge; Li, Xiangyang
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6492-6504
ISSN:
1366-5901
Subject:
image analysis; models; remote sensing; synthetic aperture radar
Abstract:
... Circular synthetic aperture radar (CSAR) is the imaging mode when the radar moves along a circular path and the observed area is always covered by the wave beam. It is different from traditional SAR modes (strip-map SAR and spotlight SAR) and has potential advantages such as 360° observation, target recognition, and three-dimensional reconstruction. According to the imaging processing of CSAR, mot ...
DOI:
10.1080/01431161.2017.1356485

11. A novel ship classification approach for high resolution SAR images based on the BDA-KELM classification model

Author:
Wu, Jun; Zhu, Yu; Wang, Zhicheng; Song, Zhengji; Liu, Xinggao; Wang, Wenhai; Zhang, Zeyin; Yu, Yusheng; Xu, Zhipeng; Zhang, Tianjian; Zhou, Jiehan
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6457-6476
ISSN:
1366-5901
Subject:
Anisoptera (Odonata); data collection; monitoring; neural networks; remote sensing; support vector machines; synthetic aperture radar
Abstract:
... Ship classification based on synthetic aperture radar (SAR) images is a crucial component in maritime surveillance. In this article, the feature selection and the classifier design, as two key essential factors for traditional ship classification, are jointed together, and a novel ship classification model combining kernel extreme learning machine (KELM) and dragonfly algorithm in binary space (BD ...
DOI:
10.1080/01431161.2017.1356487

12. A novel unsupervised Levy flight particle swarm optimization (ULPSO) method for multispectral remote-sensing image classification

Author:
Li, Huapeng; Zhang, Shuqing; Zhang, Ce; Li, Ping; Cropp, Roger
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6970-6992
ISSN:
1366-5901
Subject:
Landsat; Markov chain; algorithms; landscapes; remote sensing; spectral analysis; thematic maps
Abstract:
... The rapid development of earth observation technology has produced large quantities of remote-sensing data. Unsupervised classification (i.e. clustering) of remote-sensing images, an important means to acquire land-use/cover information, has become increasingly in demand due to its simplicity and ease of application. Traditional methods, such as k-means, struggle to solve this NP-hard (Non-determi ...
DOI:
10.1080/01431161.2017.1368102

13. Application of remote sensing in estimating maize grain yield in heterogeneous African agricultural landscapes: a review

Author:
Chivasa, Walter; Mutanga, Onisimo; Biradar, Chandrashekhar
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6816-6845
ISSN:
1366-5901
Subject:
Zea mays; agricultural land; corn; early warning systems; energy requirements; food security; grain yield; monitoring; remote sensing; spectral analysis; staple foods; surveys; Africa
Abstract:
... Maize (Zea mays L.) is the second most commonly grown crop worldwide and number one staple food in Africa where it accounts for more than 50% of the energy requirements. However, despite its widespread cultivation and the significance of maize information in Africa, maize crop maps and yield forecasts are hardly available. Yet, systematic area, spatial distribution, and maize yield estimates are i ...
DOI:
10.1080/01431161.2017.1365390

14. Assessing leaf scale measurement for nitrogen content of oil palm: performance of discriminant analysis and Support Vector Machine classifiers

Author:
Amirruddin, Amiratul Diyana; Muharam, Farrah Melissa; Mazlan, Norida
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7260-7280
ISSN:
1366-5901
Subject:
Elaeis guineensis; annuals; crops; discriminant analysis; leaves; nitrogen; nitrogen content; remote sensing; seedlings; support vector machines
Abstract:
... Nitrogen (N) is a crucial element in sustaining oil palm production. However, assessing N status of tall perennial crops such as oil palm is complex and not as straightforward as assessing annual crops, due to complex N partitioning, age, and larger amounts of respiratory loads. Hence, the objectives of this study were to evaluate the potential of spectral measurements obtained from leaf scale and ...
DOI:
10.1080/01431161.2017.1372862

15. Assessing the relationship between sky view factor and land surface temperature to the spatial resolution

Author:
Scarano, M.; Mancini, F.
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6910-6929
ISSN:
1366-5901
Subject:
Landsat; construction materials; data collection; digital database; heat; heat island; humidity; pollutants; remote sensing; surface temperature; thermal properties
Abstract:
... This article compares the land surface temperature (LST) and sky view factor (SVF) as indicator of the impact of urban morphology on the urban heat island effect. For this purpose, the work investigates the dependence of this relationship to spatial resolutions varying from coarse to very fine and related scaling effect. For this purpose, several daytime Landsat 8, Advanced Spaceborne Thermal Emis ...
DOI:
10.1080/01431161.2017.1368099

16. A surface soil temperature retrieval algorithm based on AMSR-E multi-frequency brightness temperatures

Author:
Han, Menglei; Lu, Hui; Yang, Kun; Qin, Jun; Chen, Yingying; Zhao, Long; Lazhu,
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6735-6754
ISSN:
1366-5901
Subject:
algorithms; energy balance; frozen soils; microwave radiometers; regression analysis; remote sensing; soil temperature; soil water; vegetation; water vapor; China
Abstract:
... In this study, a multi-frequency statistical algorithm is proposed for retrieving surface soil temperature () from AMSR-E (Advanced Microwave Scanning Radiometer for Earth Observation System) brightness temperature () observations. The algorithm was developed based on a regression analysis between from all AMSR-E bands and the corresponding in situ observed by a soil moisture and temperature netwo ...
DOI:
10.1080/01431161.2017.1363438

17. Automated mapping of landforms through the application of supervised classification to lidAR-derived DEMs and the identification of earthquake ruptures

Author:
Wei, Zhanyu; He, Honglin; Hao, Haijian; Gao, Wei
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7196-7219
ISSN:
1366-5901
Subject:
digital elevation models; earthquakes; engineering; geophysics; image interpretation; landforms; lidar; morphometry; remote sensing; risk; statistical analysis; China
Abstract:
... The objective of this article was to apply supervised classification to accomplish automated landform mapping using four morphometric parameters. The approach was tested on high-resolution light detection and ranging (lidar) elevation data from the northern flank of the Dushanzi Anticline, western China. The morphometric parameters were calculated by applying a moving window to the lidar-derived d ...
DOI:
10.1080/01431161.2017.1372861

18. A WTLS-based rational function model for orthorectification of remote-sensing imagery

Author:
Ge, Yong; Wei, Yongzhao; Song, Yongze; Wu, Tianjun; Stein, Alfred; Guo, Xian; Zhou, Chenghu; Ma, Jianghong
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7281-7301
ISSN:
1366-5901
Subject:
least squares; methodology; models; remote sensing
Abstract:
... The rational function model (RFM) is widely applied to orthorectification of aerial and satellite imagery. This article proposes a new method named Ortho-WTLS to solve the RFM in remote-sensing imagery orthorectification. Based on a weighted total least squares (WTLS) estimator, the proposed method allows one to handle coordinates of ground control points (GCPs) that contain errors and are of uneq ...
DOI:
10.1080/01431161.2017.1372860

19. Classification of the Yellow River delta area using fully polarimetric SAR measurements

Author:
Buono, A.; Nunziata, F.; Migliaccio, M.; Yang, X.; Li, X.
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 6714-6734
ISSN:
1366-5901
Subject:
algorithms; coasts; polarimetry; remote sensing; river deltas; synthetic aperture radar; China; Yellow River
Abstract:
... In this study, an analysis of the polarimetric synthetic aperture radar (SAR) capabilities to classify coastal areas is undertaken. The Yellow River delta (China) is selected as the test case since it represents an extraordinary environmental and economical area, which is characterized by a very heterogeneous scattering scenario, as witnessed by official reference data, provided by the Chinese gov ...
DOI:
10.1080/01431161.2017.1363437

20. Detection of attitude constant error and in-orbit calibration for the three-line CCD sensor of the ZY-3 satellite

Author:
Chen, Yifu; Qiu, Zhenge; Xie, Zhong; Le, Yuan; Fang, Shenghui
Source:
International journal of remote sensing 2017 v.38 no.23 pp. 7333-7356
ISSN:
1366-5901
Subject:
geometry; image analysis; mathematical models; remote sensing; satellites
Abstract:
... In-orbit calibration of satellite optical sensors is of crucial importance for improving the accuracy and stability of high-resolution satellite stereo mapping and positioning. For the in-orbit calibration of Ziyuan 3 (ZY-3), the first Chinese three-line stereo mapping satellite, a rigorous imaging geometric model of the three-line sensors is established and the internal systematic error is modell ...
DOI:
10.1080/01431161.2017.1372858