High Spatial Resolution Mapping of Dykes Using Unmanned Aerial Vehicle(UAV) Photogrammetry: New Insights On Emplacement Processes

Remote sensing has played a pivotal role in our understanding of the geometry of dykes and dyke swarms on Earth,Venus and Mars(West and Ernst,1991;Mege and Masson,1995;Ernst et al.,2005).Since the 1970’s

Mapping of QTL for Fiber Length Using Interspecific Gossypium hirsutum × G.barbadense F_2 Population

Cotton occupies a pre-eminent place among cash crops as it guides the destiny of a large section of the farming community as well as that of a flourishing textile industry.As the yarn manufacturing industry has undergone a technological revolution,more emphasis is given to quality of the raw

Constructing Molecular Marker Linkage Maps of Chromosome 14Sh and 22Sh and QTL Mapping for Major Traits by Use of Substitution Lines of Gossypium hirsutum L.

CSB14Sh,which is isogenic for its recurrent parent TM-1 except for chromosome 14 short arm,was crossed with TM-1,and the F2 population was produced.A total of 3800 SSR primer pairs covering the whole genome were used to screen polymorphism among two parents,TM-1 and CSB14Sh,

Monitoring Land Use and Infrastructure Changes in Industrial Complex Using Geo-Informatics Technology in Gujarat State, India

In the present study, detailed investigations have been carried out in Petroleum, Chemicals and Petrochemical Investment Region (PCPIR) area in Vygra and Bharuch Talukas in Bharuch district of Gujarat State. Indian Remote Sensing Satellite (IRS-P6) LISS-III, LISS-IV and CARTOSAT digital data covering PCPIR area in Bharuch district for the period of January & February of 2011, 2012 and 2013 was analyzed for land use/land cover mapping and monitoring the changes in land use. Various thematic land use/land cover maps were prepared and GIS database for various thematic layers have been generated using satellite and ground based information. The results indicate that the major land use in the PCPIR area is agriculture with crop lands ranging from 61 to 63 per cent of the total area. Crop land has decreased from 64.7% during 2011 to 62.7% during 2013 in the PCPIR region. Area under plantations in PCPIR area has also decreased from 5.5% during 2011 to 5.2% during 2012. The industrial area has increased from 6.0% to 7.6% of the total area of the PCPIR region. The total built-up area (industries & village area) has increased from 7.1% during 2011 to 8.7% during 2013. Tree plantations in the area of around 42 ha were carried out by GIDC during 2012 and 2013 to increase the green cover in the PCPIR area.

The Review of Land Use/Land Cover Mapping AI Methodology and Application in the Era of Remote Sensing Big Data

With the increasing number of remote sensing satellites,the diversification of observation modals,and the continuous advancement of artificial intelligence algorithms,historically opportunities have been brought to the applications of earth observation and information retrieval,including climate change monitoring,natural resource investigation,ecological environment protection,and territorial space planning.Over the past decade,artificial intelligence technology represented by deep learning has made significant contributions to the field of Earth observation.Therefore,this review will focus on the bottlenecks and development process of using deep learning methods for land use/land cover mapping of the Earth’s surface.Firstly,it introduces the basic framework of semantic segmentation network models for land use/land cover mapping.Then,we summarize the development of semantic segmentation models in geographical field,focusing on spatial and semantic feature extraction,context relationship perception,multi-scale effects modelling,and the transferability of models under geographical differences.Then,the application of semantic segmentation models in agricultural management,building boundary extraction,single tree segmentation and inter-species classification are reviewed.Finally,we discuss the future development prospects of deep learning technology in the context of remote sensing big data.

Three-dimensional Dominant Frequency Mapping Using Autoregressive Spectral Analysis of Atrial Electrograms of Patients in Persistent Atrial Fibrillation

Areas with high frequency activity within the atrium are thought to be 'drivers' of the rhythm in patients with atrial fibrillation (AF) and ablation of these areas seems to be an effective therapy in e-liminating DF gradient and restoring sinus rhythm. Clinical groups have applied the traditional FFT-based approach to generate the three-dimensional dominant frequency (3D DF) maps during electro-physiology (EP) procedures but literature is restricted on using alternative spectral estimation tech-niques that can have a better frequency resolution that FFT-based spectral estimation.

Assessing the suitability of GlobeLand30 for mapping land cover in Germany

Global land cover(LC)maps have been widely employed as the base layer for a number of applications including climate change,food security,water quality,biodiversity,change detection,and environmental planning.Due to the importance of LC,there is a pressing need to increase the temporal and spatial resolution of global LC maps.A recent advance in this direction has been the GlobeLand30 dataset derived from Landsat imagery,which has been developed by the National Geomatics Center of China(NGCC).Although overall accuracy is greater than 80%,the NGCC would like help in assessing the accuracy of the product in different regions of the world.To assist in this process,this study compares the GlobeLand30 product with existing public and online datasets,that is,CORINE,Urban Atlas(UA),OpenStreetMap,and ATKIS for Germany in order to assess overall and per class agreement.The results of the analysis reveal high agreement of up to 92%between these datasets and GlobeLand30 but that large disagreements for certain classes are evident,in particular wetlands.However,overall,GlobeLand30 is shown to be a useful product for characterizing LC in Germany,and paves the way for further regional and national validation efforts.

How does map use differ in virtual reality and desktop-based environments?

Maps based on virtual reality(VR)are evolving and are being increasingly used in the field of geography.However,the advantages of VR based on the map use processes of users over desktop-based environments(DEs)are not fully understood.In this study,an experiment was conducted in which 120 participants performed map use tasks using maps and globes in VR and DE.The participants’eye movements and questionnaires were collected to compare the map use performance differences.We analyzed the general metrics,information searching and processing metrics of participants(e.g.response time,RT;average fixation duration,AFD;average saccade duration,ASD;saccade frequency,SF,etc.)using maps and globes in different environments.We found that the participants using VR processed information more efficiently(AFDDE=233.34 ms,AFDVR=173.09 ms),and the participants using DE had both a significantly shorter response time(RT_(DE)=88.68 s,RT_(VR)=124.05 s)and a shorter visual search time(ASD_(DE)=60.78 ms,ASD_(VR)=112.13 ms;SF_(DE)=6.30,SF_(VR)=2.07).We also found similarities in accuracy,satisfaction and readability.These results are helpful for designing VR maps that can adapt to human cognition and reflect the advantages of VR.

Selected issues of cartographic communication optimization for emergency centers

Cartographic communication and support within emergency management(EM)are complicated issues with changing demands according to the incident extent and phase of the EM cycle.Keeping in mind the specifics of each purpose,it is obvious that spatial data used for maps preparation and production must be differently visualized even for the same type of emergency incident(traffic accident,fire,and natural disaster).Context-based cartography is a promising methodology to deal with the changing demands of an operational EM center.An overview of cartographic communication is presented within the context of an operational EM center,activities of particular actors,and map use supporting the incident elimination.The authors of the paper respond to a series of questions,for example:what is the current cartographic support of operational EM in the Czech Republic in Digital Earth conditions?What possibilities are there to improve the cartographic communication?How can contextual cartographic services be implemented in a Web environment and how can the usability of results be tested?The paper gives several examples of the usage of cartographic technologies in map creation for various emergency situations.

Evaluation of diverse classification approaches for land use/cover mapping in a Mediterranean region utilizing Hyperion data

Information on Earth’s land surface cover is commonly obtained through digital image analysis of data acquired from remote sensing sensors.In this study,we evaluated the use of diverse classification techniques in discriminating land use/cover types in a typical Mediterranean setting using Hyperion imagery.For this purpose,the spectral angle mapper(SAM),the object-based and the non-linear spectral unmixing based on artificial neural networks(ANNs)techniques were applied.A further objective had been to investigate the effect of two approaches for training sites selection in the SAM classification,namely of the pixel purity index(PPI)and of the direct selection of training points from the Hyperion imagery assisted by a QuickBird imagery and field-based training sites.Objectbased classification outperformed the other techniques with an overall accuracy of 83%.Sub-pixel classification based on the ANN showed an overall accuracy of 52%,very close to that of SAM(48%).SAM applied using the training sites selected directly from the Hyperion imagery supported by the QuickBird image and the field visits returned an increase accuracy by 16%.Yet,all techniques appeared to suffer from the relatively low spatial resolution of the Hyperion imagery,which affected the spectral separation among the land use/cover classes.