| 000 | 06146nas a2200481 a 4500 | ||
|---|---|---|---|
| 005 | 20260817161516.0 | ||
| 008 | 120928s2010 th uu|m rtt 0| a1eng d | ||
| 035 | _a.b1210985x | ||
| 099 | 9 | _aAIT Diss. no.RD-10-06 | |
| 100 | 1 | _aSaroar, Md. Mustafa | |
| 245 | 1 | 0 | _aAdaptation to vulnerability of climate change induced sea level rise in coastal Bangladesh |
| 260 |
_aPathum Thani, Thailand : _bAsian Institute of Technology, _c2010 |
||
| 300 |
_a199 p. : _bill. |
||
| 490 | 1 |
_aDissertation ; _vno. RD-10-06 |
|
| 500 | _aA submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Regional and Rural Development Planning | ||
| 520 | _aClimate change induced sea level rise (SLR) has posed a formidable challenge for people who have been living in the coastal area of Bangladesh. Considerable amount of experts{u2019} opinion based literatures indicate that huge out migration would be obvious due to SLR. They commonly labeled the marginalized people as the prospective migrants. This study was aimed primarily to empirically test whether coastal people intend to out migrate for different projected scenarios of SLR. Then the inquiry was extended to characterize the people likely to migrate, and to identify a range of measures that can reduce the likely trend of out migration. Furthermore, peoples{u2019} climate awareness, adaptive capacity and perception about livelihood insecurity were also studied alongside their current coping practices. The empirical part of this research was conducted in three coastal villages of Kalapara Upazila (sub-district) of Patuakhali district which is susceptible to SLR. This area was selected because it represents typical coastal characteristics. A sample survey of 285 households was randomly done during January-April 2009. The semi-structured questionnaire survey was supplemented by focus group discussions and key informant interviews. Study revealed that respondents used to follow a host of coping and adaptation strategies for livelihood security. Coping and adaptation strategies vary depending on their exposure to hazards, occupational engagement and risk perception. The MANOVA results show that differential perception about livelihood security are primarily associated with peoples{u2019} education, occupation, farmland holding, past exposure to various hazards, access to information, and spatial factors that determine self efficacy and response efficacy. From the OLS regression analysis various {u2018}socio-demographic{u2019} {u2018}access to climate information{u2019} and {u2018}adaptive behavioral{u2019} factors{u2019} have been appeared as the strongest predictors of three dimensions of climate awareness. Even if no population is added in the coastal areas by 2050, almost 5 million population would be SLR refugee from low-lying parts of the coast alone. Multinomial logistic regression (M-logit) model shows that frequent loss of productive day, frequent exposure to flooding, long recovery period from shock, limited access to safe shelter and climate weather information, non-agricultural occupation, higher landholding, higher education are the typical attributes of prospective migrants. Finally, it has identified a wide array of exposure and sensitivity minimization, and adaptive capacity maximization measures that are believed to encourage adaptation in situ.The novelty of the research finding is it has refuted the idea of 2out migration of the most marginalized one only3. Further it has challenged the conventional notion: 2climate refugee is an intractable problem for poor nations3. Indeed, finding confirms that while millions of climate (SLR) refugees seem obvious for Bangladesh, there are ways to avoid such massive scale relocation. Visible initiative for exposure and sensitivity minimization and adaptive capacity maximization as part of anticipatory adaptation planning may encourage adaptation in situ. Therefore, the findings are robust and might help policy makers, planners and development practitioners to initiate appropriate intervention. | ||
| 502 | _aThesis (Ph.D.) - Asian Institute of Technology, 2010 | ||
| 650 | 0 |
_aClimatic changes _zBangladesh |
|
| 650 | 0 |
_aSea level _zBangladesh |
|
| 700 | 1 |
_aRoutray, Jayant Kumar, _eChairperson |
|
| 700 | 0 |
_aSoparth Pongquan, _eExamination Committee |
|
| 700 | 1 |
_aPerera, L.A.S. Ranjith, _eExamination Committee |
|
| 700 | 1 |
_aGengaje, Rajan K., _eExamination committee |
|
| 710 | 2 |
_aNorwegian Ministry of Foreign Affairs, _eScholarship donor |
|
| 810 | 2 |
_aAsian Institute of Technology. _tDissertation ; _vno. RD-10-06 |
|
| 856 |
_3Full-Text _uhttp://203.159.5.9/ait-thesis/detail.php?q=B00730 |
||
| 907 |
_a.b1210985x _bmnait _cz |
||
| 902 | _a240403 | ||
| 998 |
_b0 _c120928 _dm _ea _fz _g0 |
||
| 962 |
_a000:001:PDF:b1210985:000825:0:0:0:0:0:0 _tAbstract _vn |
||
| 945 | _lmnait | ||
| 945 | _lmnait | ||
| 945 | _lmnarc | ||
| 945 | _lmnarc | ||
| 942 | _c22 | ||
| 942 | _c40 | ||
| 942 | _c20 | ||
| 909 |
_aBarcode : 30050120582829 _bCREATED : 2012-09-28 _cRECORD # : i12697424 _dLPATRON : 1028387 _eLCHKIN : 2019-11-25 _f# RENEWALS : 0 _g# OVERDUE : 0 _hIUSE3 : 3 _iTOT CHKOUT : 20 _jTOT RENEW : 13 |
||
| 909 |
_aBarcode : 30050120582852 _bCREATED : 2012-09-28 _cRECORD # : i12697436 _dLPATRON : 1026331 _eLCHKIN : 2020-09-07 _f# RENEWALS : 0 _g# OVERDUE : 0 _hIUSE3 : 6 _iTOT CHKOUT : 21 _jTOT RENEW : 22 |
||
| 909 |
_aBarcode : 30050160001326 _bCREATED : 2016-03-21 _cRECORD # : i12900400 _dLPATRON : 0 _eLCHKIN : - _f# RENEWALS : 0 _g# OVERDUE : 0 _hIUSE3 : 0 _iTOT CHKOUT : 0 _jTOT RENEW : 0 |
||
| 909 |
_aBarcode : 30050120919112 _bCREATED : 2019-11-21 _cRECORD # : i1323190x _dLPATRON : 1028989 _eLCHKIN : 2020-02-20 _f# RENEWALS : 0 _g# OVERDUE : 0 _hIUSE3 : 1 _iTOT CHKOUT : 1 _jTOT RENEW : 1 |
||
| 999 |
_c1557 _d1557 |
||