Challenges and Barriers Recruitment of Professionals and Management Trainees in a Transitional Situation to the New Normal

The purpose of this study is to find out the obstacles faced in recruiting professional and management trainees in the transition situation to the new normal. Competition in the global business world requires company management to be more concerned in managing human resources in it. However, in the new normal situation, several challenges and obstacles in professional recruitment are difficult to attract Candidates with the Right Qualifications, Incomplete Company-Related Information, Ineffective Channels Used, Limited Access to Required Devices and others. All recruitment processes including selection can be done online, the right solution during a pandemic

Assessment of Mining Extent and Expansion in Myanmar Based on Freely-Available Satellite Imagery

Using freely-available data and open-source software, we developed a remote sensing methodology to identify mining areas and assess recent mining expansion in Myanmar. Our country-wide analysis used Landsat 8 satellite data from a select number of mining areas to create a raster layer of potential mining areas. We used this layer to guide a systematic scan of freely-available fine-resolution imagery, such as Google Earth, in order to digitize likely mining areas. During this process, each mining area was assigned a ranking indicating our certainty in correct identification of the mining land use. Finally, we identified areas of recent mining expansion based on the change in albedo, or brightness, between Landsat images from 2002 and 2015. We identified 90,041 ha of potential mining areas in Myanmar, of which 58% (52,312 ha) was assigned high certainty, 29% (26,251 ha) medium certainty, and 13% (11,478 ha) low certainty. Of the high-certainty mining areas, 62% of bare ground was disturbed (had a large increase in albedo) since 2002. This four-month project provides the first publicly-available database of mining areas in Myanmar, and it demonstrates an approach for large-scale assessment of mining extent and expansion based on freely-available data

Boxplot comparing mean canopy cover as measured by Hansen et al. (2013) for intact and degraded forests in different forest regions of Myanmar between 2002 and 2014.

<p>Northern Sagaing = mostly mixed deciduous and evergreen forest; Southern Sagaing = mixed deciduous and dry dipterocarp forest; Tanintharyi = tropical evergreen forest. (A) Canopy cover values for intact forest; (B) Canopy Cover values for degraded forest; (C) Location of Landsat tiles used for comparison.</p

Losing a jewel—Rapid declines in Myanmar’s intact forests from 2002-2014

<div><p>New and rapid political and economic changes in Myanmar are increasing the pressures on the country’s forests. Yet, little is known about the past and current condition of these forests and how fast they are declining. We mapped forest cover in Myanmar through a consortium of international organizations and environmental non-governmental groups, using freely-available public domain data and open source software tools. We used Landsat satellite imagery to assess the condition and spatial distribution of Myanmar’s intact and degraded forests with special focus on changes in intact forest between 2002 and 2014. We found that forests cover 42,365,729 ha or 63% of Myanmar, making it one of the most forested countries in the region. However, severe logging, expanding plantations, and degradation pose increasing threats. Only 38% of the country’s forests can be considered intact with canopy cover >80%. Between 2002 and 2014, intact forests declined at a rate of 0.94% annually, totaling more than 2 million ha forest loss. Losses can be extremely high locally and we identified 9 townships as forest conversion hotspots. We also delineated 13 large (>100,000 ha) and contiguous intact forest landscapes, which are dispersed across Myanmar. The Northern Forest Complex supports four of these landscapes, totaling over 6.1 million ha of intact forest, followed by the Southern Forest Complex with three landscapes, comprising 1.5 million ha. These remaining contiguous forest landscape should have high priority for protection. Our project demonstrates how open source data and software can be used to develop and share critical information on forests when such data are not readily available elsewhere. We provide all data, code, and outputs freely via the internet at (for scripts: <a href="https://bitbucket.org/rsbiodiv/" target="_blank">https://bitbucket.org/rsbiodiv/</a>; for the data: <a href="http://geonode.themimu.info/layers/geonode:myan_lvl2_smoothed_dec2015_resamp" target="_blank">http://geonode.themimu.info/layers/geonode:myan_lvl2_smoothed_dec2015_resamp</a>)</p></div

Remaining and lost intact forest (ha) for Myanmar townships between 2002 and 2014.

<p>Remaining and lost intact forest (ha) for Myanmar townships between 2002 and 2014.</p

Remaining large and intact forest landscapes in Myanmar 2014.

<p>Remaining large and intact forest landscapes in Myanmar 2014.</p

Boxplot comparing mean canopy cover as measured by Hansen et al. (2013) for intact and degraded forests in different forest regions of Myanmar between 2002 and 2014.

<p>Northern Sagaing = mostly mixed deciduous and evergreen forest; Southern Sagaing = mixed deciduous and dry dipterocarp forest; Tanintharyi = tropical evergreen forest. (A) Canopy cover values for intact forest; (B) Canopy Cover values for degraded forest; (C) Location of Landsat tiles used for comparison.</p

Land cover and land use categories used for forest mapping in Myanmar.

<p>Land cover and land use categories used for forest mapping in Myanmar.</p