International Journal of Remote Sensing Applications最新文献

{"title":"LAI Improved to Dry Forest in Semiarid of the Brazil","authors":"J. Galvíncio, M. Moura, T. G. F. Silva, B. B. Silva, C. R. Naue","doi":"10.14355/IJRSA.2013.0304.04","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.04","url":null,"abstract":"Savannas are globally important ecosystems of great significance to human economies. Savannas exist in water-limited regions which forces tree canopies open and heterogeneous. The open canopy structure allows grass to co-dominate in the savannas by occupying different niches in space and time. Leaf area index (LAI) and fraction of photosynthetically active radiation absorbed by vegetation (FPAR) characterize vegetation canopy functioning and energy absorption capacity. LAI and FPAR are key parameters in most ecosystem productivity models and global models of climate, hydrology, biogeochemistry and ecology. Given the above, this study aimed to develop an equation of LAI calibrated by savannah in semiarid northeastern Brazil and proposed a model to better estimate the LAI for dry forest, such as the savanna (Caatinga). The model developed in this study may be used to improve the estimates of Leaf Area Index [LAI] in dry forest with NDVI. One model for savanna-specific of leaf area index (LAI) has been developed. The use of S Curve statistical methods to calibrate the leaf area index (LAI) proved to be an efficient method. The model development gives good results in most of the LAI range known for Caatinga stands in Northeast of Brazil. The Root Mean Square Error (RMSE) calculated on an independent LAI dataset was 0.10, which is about 6% of the average measured LAI. This method offers a simple and operational alternative to application of complex and computationally intensive techniques, and could be used to design other species-specific LAIs. This study reinforces the importance of developing models to better estimate the LAI in different ecosystems since there are no similarities of the LAI between dry and humid climate.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126692560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring of Atmospheric Particles in Beijing and Dunhuang Using a Raman Lidar with Enhanced Dynamics","authors":"Pan Chao, Yiming Zhao, Chen Lin, Yang Xiaoyu, Shang Yanan, Liu Bo, Wang Lidong, A. Boselli, G. Pisani, N. Spinelli, Xuan Wang","doi":"10.14355/IJRSA.2013.0304.11","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.11","url":null,"abstract":"In high urbanized areas, the atmospheric particulate matter concentration (the so called PM) can exceeds the healthy limit values. Human activities, such as the burning of fossil fuels, industrial activities, and ground transport contribute to measured PM exceedance. Natural contribution is originated mainly from dust storms and volcanic eruptions. The Gobi desert, for instance, is the major source of mineral dust in China, that is one of the most interesting regions for aerosol study being surrounded by the main sources of anthropogenic and natural aerosol. On the base of the above considerations, the need of a new advanced scanning lidar system raised in order to better understand the formation, emission and diffusion of particulate from natural and anthropic sources and to evaluate their relative contribution, to characterize the chemical and physical properties of atmospheric aerosols, their spatial and temporal distribution and the main transport mechanisms. To this aim, a new, versatile and portable Raman scanning lidar system has been designed and developed in the frame of the AMPLE (Aerosol Multi-wavelength Polarization Lidar Experiment) project, the first action of the recently founded China-Italy Laser Remote Sensing Joint Research Center between the National Consortium of Italian Universities for the Physical Science of the Matter (CNISM) and the Beijing Research Institute for Telemetry (BRIT). The AMPLE lidar device has been installed at the Beijing Research Institute for Telemetry in the Beijing city area, which is strongly affected from anthropogenic pollution and sand dust from Gobi desert in order to carry out 4-D (space and time) imaging of the atmospheric aerosol distributions, their optical properties, and microphysical characterization. A first demonstrative measurement campaign has been performed on May 2013 in Beijing, while on August 2013 AMPLE has been carried in Dunhuang close to the Gobi desert and far away from the urban area, in order to study sand dust directly at source. Results of those measurements are described in this paper.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"373 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122501403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Lithology Identification of the North Qilian Belt by Surface Temperature and Spectral Emissivity Information Derived from ASTER TIR Data","authors":"Qin Yang, Xiangnan Liu, Xuqing Li, Chao Ding, Fan Yang","doi":"10.14355/IJRSA.2013.0304.09","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.09","url":null,"abstract":"Lithology units have been identified in northern Qilian belt by using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) thermal infrared (TIR)L1B data which contains both surface temperature and spectral emissivity information. As mafic-to-untramafic units have higher surface temperature than other geologic units, surface temperature images were generated to identify the dolerite and peridotite etc. Reference to analysis of thermal spectra characteristics of geological units from JHU spectral library, a new ASTER colored composite band ratio combination band 11/12: band 12/10: band 12/14 as R:G:B was applied successfully to distinguish quartz-rich felsic units and feldspathic rocks from the large meadow in the study area , with the band ratio and de-correlation techniques. To clarify the geological boundaries and remove the vegetation effect more effective, NDVI image and false color composite image composed of band 3: band 2 : band 1 visible to near infrared bands were also generated. The result indicated that combination of TIR FCC image, VNIR FCC image, temperature image and NDVI image for the study lithology mapping works well and matches the field geological","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131457753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Neural Network and Random Forest Approaches for Modeling of Sea Surface Salinity","authors":"Meiling Liu, Xiangnan Liu, Jiale Jiang, Xiaopeng Xia","doi":"10.14355/IJRSA.2013.0304.08","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.08","url":null,"abstract":"Ocean salinity is a key parameter in oceanic and climate studies, and the accurate estimation of sea surface salinity (SSS) of coastal water is of great scientific interest. This paper reports on a modeling study of SSS using artificial neural network (ANN) and random forest (RF) algorithm. Hong Kong Sea, China was used as case study. Sea biochemistry and sea physical parameters were collected. Sea surface temperature (SST), pH, chlorophyll-a (Chl-a) and total inorganic nitrogen (TIN) were selected as input variables of models. The assessment models were based on a back propagation (BP) neural network and RF algorithm. The results showed that an optimum BP neural network prediction model has 4-20-4-1 network architecture with gradient descent learning algorithm and an activation function including the sigmoid tangent function in the input layer, a hidden layer and linear functions in the output layer. While the optimum RF model was obtained, when RF algorithm had a mtry value of 32 with ntree=2000 and nodesize=4. Optimum BP and RF models for estimating SSS performed well at prediction, regardless of training or testing sets with R 2 above 0.8. Compared with the BP model, RF model was usually slightly stable in models’ performance with respect to different models’ parameters. This research verified that the BP model and RF algorithm could provide an effective and faithful estimation of SSS of coastal water based on sea biochemistry and physical parameters.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"518 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116247204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using Geographical Information System (GIS) and Satellite Remote Sensing for Understanding the Impacts of Land Cover on Apiculture over Time","authors":"H. Abou-Shaara","doi":"10.14355/IJRSA.2013.0304.01","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.01","url":null,"abstract":"The development of apiculture is strongly related to the suitable land cover, mainly the availability of honey plants. The land cover is not stable over time due to the human activities. The honey yield per honey bee colony has been reduced greatly in El-Behera Governorate, Egypt over time. The decline in the cultivated areas is considered to be the main cause for the low honey yield. In this research, the land cover changes were investigated during a long period of time from 1970s till 2000s to understand the possible roles of the land cover changes on apiculture and low honey yield. The GIS and Landsat satellite images in combination with Google Earth historical images were used for land cover change analysis. The obtained results showed a relative increase in the cultivated areas over time with approximately the presence of the same plant types. Therefore, the low honey production can not be explained by the decline in the cultivated areas.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127952283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determination and Structural Analysis of the Lahijan Transverse Fault in Forestall Region of Alborz Mountains, Iran: A Geospatial Application","authors":"H. Safari, M. Ghasemi, R. R. Pash","doi":"10.14355/IJRSA.2013.0304.06","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.06","url":null,"abstract":"The Lahijan fault zone (LFZ) is a transverse fault placed in a Forestall area of western Alborz Range, and cuts across this fold-thrust belt along the Sepid-rud valley. The results were later completed with field investigations. Analysis of the results of Geoinformatics Techniques (GiT) helped us to determine the limits and kinematics of the main fault zone and other related faults. The results showed that LFZ with N55E general strike, 90 km length and 30 km width extend from Sepid-rud dam to the Lahijan city. This fault zone, as a transversal fault, truncated and offset the western part of Alborz fold-thrust belt and thus, caused many structural complexities in this region. The results of structural investigations showed that LFZ was established as a leftlateral strike-slip fault zone. Several fault trends are generated by this tectonic regime.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125079363","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Polarization Lidar Calibration Techniques and Sensitivity Analysis","authors":"Yiming Zhao, A. Boselli, L. Nasti, G. Pisani, N. Spinelli, Xuan Wang","doi":"10.14355/IJRSA.2013.0304.12","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.12","url":null,"abstract":"Calibrated lidar measurements of linear depolarization ratio provide highly reliable information to discriminate between spherical and non-spherical particles in the atmosphere and to distinguish between liquid and solid phase clouds. In this paper three different calibration techniques are described. For each technique a sensitivity analysis is performed and the different contributions to the total error are evaluated. The stability of atmosphere, the laser source polarization degree, the accuracy of polarization alignment and the background radiation are taken into account in the simulated depolarization measurements. The influence of these parameters and the choice of calibration range and calibration height are studied also. Two calibration techniques were experimentally validated by more than 28 calibration measurements in nearly 5 months. Furthermore aerosol depolarization measurements taken after the calibration are presented.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124674487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Iterative Multi-Frame Super-Resolution Image Reconstruction via Variance-Based Fidelity to the Data","authors":"A. Panagiotopoulou","doi":"10.14355/IJRSA.2013.0304.05","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.05","url":null,"abstract":"Multi-frame Super-Resolution (SR) image reconstruction creates a single High-Resolution (HR) image from a sequence of Low-Resolution (LR) frames. Apart from resolution increment, blurring and noise removal is also achieved. In stochastic regularized methods, the SR problem is formulated by means of two terms, the data-fidelity term and the regularization term. In the present work, a novel estimator named Var − norm has been proposed for utilization in the data-fidelity term. This estimator presents a simple mathematical form based on the variance of the SR estimation error, i.e. on the difference between the estimated LR frame and the corresponding measured LR frame. The introduced Var − norm estimator is combined with the Bilateral Total Variation (BTV) regularization to formulate a novel SR method. The SR performance of the proposed method is directly compared with that of two SR techniques existing in the literature. Experimentation proves that the proposed method outperforms the existing methods.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133081994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forest Leaf Area Index Estimated from Tonal and Spatial Indicators Based on IKONOS_2 Imagery","authors":"Z. Gu, W. Ju, Yibo Liu, Dengqiu Li, Weiliang Fan","doi":"10.14355/IJRSA.2013.0304.02","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.02","url":null,"abstract":"The linkage of four spectral vegetation indices (VI) and 12 texture measures (TEX) derived from an IKONOS-2 image with leaf area index (LAI) measured in the urban area of Nanjing city, China was analyzed. Models for retrieving LAI based on VI or/and TEX were established for planted low broad-leaf forest (PLB), planted mature forest (PMF), natural broad-leaf forest (NBF), and all measured plots (ALLv), respectively. The VIs were calculated from multi-spectral bands at four radiometric correction levels, and the textures were computed from the panchromatic band of the image. The results showed that LAIs are positively related to vegetation indices (r = 0.419 – 0.737), and high correlation coefficients were found between LAI and textures. For regularly planted forests, LAI was strongly correlated with both VI and TEX, and the ‘best’ models could be established only using texture measures. The determination coefficients (R 2 ) were 0.787 and 0.626 for PLB and PMF, respectively. In contrast, VI is a better predictor of LAI than texture measures for NBF. When VIs and TEXs work together, the R 2 of the ‘best’ model was 0.764 for ALLv plots. This study indicated that these two measurements should be effectively integrated for reliably retrieving forest LAI from highresolution remote sensing data.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116795184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Retrieval of Moisture and Temperature Index Based on ASTER Data","authors":"Jinming Sha, Xiaomei Li, B. Xiao","doi":"10.14355/IJRSA.2013.0304.07","DOIUrl":"https://doi.org/10.14355/IJRSA.2013.0304.07","url":null,"abstract":"Soil moisture and land surface temperature are the important factors in the physical process of the regional and global surface. Accordingly, multiple thermal infrared sensors have been sent into the outer space to monitor the hydrothermal factor of the global or regional area dynamically. This research used ASTER L1B data transited on the morning of May 23rd, 2001. L 1B data is based on L 1A data, produced by using its own parameters to finish radiometric correction as well as geometric correction. In the case of default, UTM projection is utilized. This research was performed in a region of Fuzhou. Because of the high spatial and spectral resolution of ASTER data, at the same time, with the help of MODIS data and split-window algorithm, the authors retrieved the moisture and temperature index in the region of complex topography.","PeriodicalId":219241,"journal":{"name":"International Journal of Remote Sensing Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123632267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}