Mountain Livelihoods

Mountain people already live in a fragile landscape. Their marginalization makes them even more sensitive to environmental degradation.  Practices in farming and grazing that enabled people to thrive in the past may not continue to be effective as ecosystems degrade, population dynamics shift and a rapidly changing world puts pressure on communities.

Supporting mountain people in adapting to rapid and unpredictable change is an important area of work for ICIMOD. Researching and piloting programs on high value products, innovative livelihood options and rural income generation strategies lie at the heart of efforts to help the people of the Hindu Kush Himalayas cope with the effects of socioeconomic and environmental change.

Reducing poverty and improving the environment must be linked together if the livelihoods of mountain people are to be sustainable for the future.


Relevant Publications

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Datasets

Resilient Mountain Solution (RMS) and RMS Poverty and Vulnerability Assessment (PVA) is a ward level household survey to have get a deeper understanding of Dadeldhura site. The survey was a part of the case study at covering multiple issues focusing on agricultural and animal husbandry practices, energy use, environmental and socioeconomic changes faced, their impact and coping to identify emerging issues, determinants of vulnerability and develop solution to improve their resilience for enhanced livelihoods. The survey covers 110 households across the 5 wards of Bhageswor rural municipality in Dadeldhura which was purposively selected. Household selection for the survey was done following random sampling method within the wards.


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Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


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Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


View Metadata

Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


View Metadata

Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


View Metadata

Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


View Metadata

Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


View Metadata

Nepal is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


View Metadata

Bangladesh is one of the most flood affected country in the world. The frequency, intensity and duration of floods has been increased during last few decades. Due to increased population settlements in floodplains and irregular development damage of infrastructure, crop and property has increased creating severe impact on lives and livelihood. Understanding the severity and identification of extent and types of flood damage is highly important to plan effective response. The aim of this study was to develop appropriate methodology to determine extent of flood and damaged areas in near real time basis to support operational response. We have used Sentinel-1 synthetic aperture radar (SAR) images to generate flood extend data for the year 2017.


View Metadata

Poverty and Vulnerability Assessment (PVA) is a district level household survey to understand vulnerability of households to environmental and socioeconomic changes with focus on mountain specificity as well as their coping strategies and adaptive capacity. Under the Adaptation to Change program, the Himalaya Climate Change Adaptation Programme (HICAP) initiative have conducted the survey among 1987 households across 5 prefectures in Yunnan provinces in the Upper Brahmaputra sub-basin in China. The households were selected following a probability based multi-stage cluster sampling approach.


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