Press Release on Remote Sensing Research: February -2019

A sensible UAV Remote Sensing Methodology to get Multispectral Orthophotos for Vineyards: Estimation of Spectral reflection factor victimisation Compact Digital Cameras

This paper explores the employment of compact digital cameras to remotely estimate spectral reflectivity supported remote-controlled aerial vehicle imagination. 2 digital cameras, one unedited and one altered, were wont to collect four bands of spectral info (blue, green, red, and near-infrared [NIR]). The altered camera had its internal hot mirror removed to permit the sensing element to be to boot sensitive to NIR. Through on-ground experimentation with spectral targets and a spectroradiometer, the sensitivity and skills of the cameras were discovered. This info together with on-the-spot collected spectral knowledge were wont to aid in changing aerial imagination digital numbers to estimates of scaled surface reflectivity victimization the empirical line methodology. The ensuing pictures were wont to produce spectrally-consistent orthophotomosaics of a farm study web site. Individual bands were afterward valid with in place spectroradiometer knowledge. Results show that red and NIR bands exhibited the most effective work (R2: zero.78 for red; zero.57 for NIR). [1]

Advances in Infrasonic Remote Sensing Methods

Infrasound recordings may be used as input to inversion procedures to delineate the vertical structure of temperature and wind in an exceedingly vary of altitudes wherever ground-based or satellite measurements are rare and where fine-scale part structures don’t seem to be resolved by this atmospheric specifications. As infrasound is measured worldwide, this permits for a far off sensing technique that may be applied globally. This chapter provides an outline of recently developed inaudible¬† remote sensing ways. The ways vary from linearized inversions to direct search methods likewise as interferometric techniques for part infrasound. The analysis of numerical weather prediction (NWP) merchandise shows the supplemental worth of infrasound, e.g., throughout sudden¬† stratospheric warming (SSW) and equinox periods. The potential transition toward assimilation of infrasound in numerical weather prediction models is mentioned. [2]

Chapter sixteen – Remote Sensing in Lineament Identification: Examples from Western Republic of India

Remote sensing satellite pictures are studied visually in distinctive completely different lineaments and to so interpret the tectonics. The known lineaments from representational process ought to be valid (at least partially) by field information. Variation of voidance patterns and vegetation trends may indicate the presence of various structures like domes, synclines, etc., further as sure lineaments. Digital elevation model pictures give a more robust plan concerning geography elevation and so facilitate in delineating geologic structures. once the launch of Google Earth, high-resolution satellite pictures are freely accessible, so researchers will use those for various purposes: prefield reconnaissance mission survey, lineament identification in remote areas, virtual munition, etc. Here we have a tendency to analyze satellite pictures from completely different intra- and pericratonic basins of western Asian nation. Toward the tip of the chapter, some issues are conferred associated with lineament identification from Google Earth professional satellite representational process. The solutions are given within the Appendix. [3]

Model fuses social media, remote sensing knowledge with goal of distinguishing nuclear threats

A new procedure model permits researchers to draw on unremarkably incompatible knowledge sets, like satellite imagination and social media posts, to answer questions on what’s happening in targeted locations. The researchers developed the model to function a tool for distinctive violations of nuclear non-proliferation agreements. [4]

Application of Remote Sensing (RS) and Geographic system (GIS) in Erosion Risk Mapping: Case Study of Oluyole geographical region, Ibadan, Nigeria

Soil erosion is one among the foremost unresolved issues of rural agriculture. The causes of eating away within the study space are serious precipitation, persistent drought, farming activities, deforestation and indiscriminate bush burning that expose soil to impact of rain drop. This study is geared toward applying Remote Sensing (RS) and Geographic data system (GIS) in erosion risk mapping in Oluyole catchment basin. Remote Sensing (RS) and Geographic data system (GIS) techniques were accustomed plan the erosion risk areas. Google Earth and LANDSAT ETM+ were accustomed acquire the satellite imageries of Oluyole catchment basin. victimization high resolution imageries, a Digital Elevation Model (DEM) was developed with surfboarder eight and ArcGIS ten.0 to spot erosion risk areas. The Triangulated Irregular Network (TIN), flow length, flow accumulation and slope maps of the study space were generated with the employment of Digital Elevation Model. The slope, flow accumulation and flow length maps were combined with land use map to provide erosion risk map with the employment of map pure mathematics in ArcGIS ten.0 software. [5]

Reference

[1] Mathews AJ. A practical UAV remote sensing methodology to generate multispectral orthophotos for vineyards: Estimation of spectral reflectance using compact digital cameras. InGeospatial Intelligence: Concepts, Methodologies, Tools, and Applications 2019 (pp. 298-322). IGI Global. (web link)

[2] Assink J, Smets P, Marcillo O, Weemstra C, Lalande JM, Waxler R, Evers L. Advances in infrasonic remote sensing methods. InInfrasound Monitoring for Atmospheric Studies 2019 (pp. 605-632). Springer, Cham. (web link)

[3] Dasgupta S, Mukherjee S. Remote sensing in lineament identification: examples from western India. InDevelopments in Structural Geology and Tectonics 2019 Jan 1 (Vol. 5, pp. 205-221). Elsevier. (web link)

[4] Model fuses social media, remote sensing data with goal of identifying nuclear threats

Date: July 23, 2018

Source: North Carolina State University (web link)

[5] Application of Remote Sensing (RS) and Geographic Information System (GIS) in Erosion Risk Mapping: Case Study of Oluyole Catchment Area, Ibadan, Nigeria

O. I. Ojo

Department of Agricultural Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.

T.P. Abegunrin

Department of Agricultural Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria

M.O. Lasisi (web link)

Department of Agricultural and Bio- Environmental Engineering, The Federal Polytechnic, Ado-Ekiti, Nigeria.

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