Your search found 6 records
1 Chowdhury, A.. 1987. Tokyo, Japan: Institute for the Study of Languages and Cultures of Asia and Africa. 33p. (Studies in socio-cultural change in rural village in Bangladesh no.5)
(Location: IWMI-HQ Call no: 307.72 G584 CHO Record No: H04863)
2 Chowdhury, A.. 1987. Studies in socio-cultural change in rural villages in Bangladesh, no.5. Tokyo, Japan: Institute for the Study of Languages and Cultures of Asia and Africa. 33p.
(Location: IWMI-HQ Call no: 307.72 G584 CHO Record No: H05199)
3 Hossain, M.; Lewis, D.; Bose, M. L.; Chowdhury, A.. 2003. Rice research, technological progress, and impacts on the poor: The Bangladesh case (Summary report) IFPRI. iv, 65p. (EPTD discussion paper no.110)
Agricultural research ; Rice ; Poverty ; Non-governmental organizations ; Households ; Income / Bangladesh
(Location: IWMI-HQ Call no: P 6853 Record No: H034580)
4 Chowdhury, A.; Ghosh, Surajit; Holmatov, Bunyod. 2024. Earth observation-based rice mapping studies in Vietnamese Mekong Delta compared to global context: a bibliometric analysis. Sustainability, 16(1):189. [doi: https://doi.org/10.3390/su16010189]
Rice ; Mapping ; Earth observation satellites ; Bibliometric analysis ; Remote sensing ; Food security ; Sustainable Development Goals ; Goal 2 Zero hunger ; Goal 15 Life on land ; Goal 13 Climate action ; Goal 6 Clean water and sanitation ; Landsat ; Moderate resolution imaging spectroradiometer ; Deltas / Vietnam / Mekong Delta
(Location: IWMI HQ Call no: e-copy only Record No: H052473)
https://www.mdpi.com/2071-1050/16/1/189/pdf?version=1703490171
https://vlibrary.iwmi.org/pdf/H052473.pdf
https://vlibrary.iwmi.org/pdf/H052473.pdf
(4.44 MB) (4.44 MB)
A bibliometric study on mapping the rice cropping systems in VMD is crucial for understanding the trend of EO-based rice mapping and how remote sensing technologies are essential to address the food security issue in the region. This article presents an overview of Earth observation (EO)-based rice mapping strategies since 1979, prioritizing the scope of data, approaches, and techniques derived from 3700 research articles worldwide and contrasting them with the Vietnamese Mekong Delta (VMD). Various quantitative analyses were conducted through bibliometric analysis using the VOS viewer and Scopus database. Optical images, particularly the Landsat (~16%) and MODIS (~12%) time series datasets, were the most commonly utilized globally. MODIS data (~31%) had the highest share in the VMD context, followed by Landsat data (~19%), while Sentinel series (~13% for global and ~16% for VMD) data became more popular in recent years. Research on rice mapping using UAVs has been gradually creeping into rice mapping research globally, but a gap is yet to be filled in the VMD. The most widely used approaches for rice mapping globally were Random Forest, Support Vector Machine, and Principal Component Analysis. Spectral indices like EVI, NDVI, and RVI were commonly used for rice mapping and monitoring. The findings underscore the critical role of EO-based rice mapping studies in the VMD in addressing sustainability and food security challenges.
5 Ghosh, Surajit; Mallick, A.; Dawn, A.; De Sarkar, K.; Chowdhury, A.; Kour, S.; Ghosh, A.; Holmatov, Bunyod. 2023. Digital data and tools for managing agriculture: focusing on earth observation data and climate change. Proceedings of the Training Workshop on Digital Data and Tools for Managing Agriculture: Focusing on Earth Observation Data and Climate Change, Bhubaneswar, India, 21-23 December 2023. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Low-Emission Food Systems; CGIAR Initiative on Resilient Cities. 51p.
Digital technology ; Data ; Digital agriculture ; Climate change ; Earth observation satellites / India
(Location: IWMI HQ Call no: e-copy only Record No: H052510)
(3.31 MB)
The report presents the prime aims, objectives, discussions and insights from the “Training Workshop on Digital Data and Tools for Managing Agriculture: Focusing on Earth Observation Data and Climate Change” organized at IIIT Bhubaneshwar from 21st to 23rd December 2023. The workshop was attended by 81 participants and jointly conducted by IIIT Bhubaneshwar, IWMI, and IEEE GRSS Kolkata Chapter. The primary objective of the workshop was to equip participants with practical skills and knowledge to utilize digital data and tools, especially Earth observation data, for effective agricultural management in the context of climate change and make evidence-based decisions to confront challenges in the food system, urban water pollution, GHG emissions & nexus. The programme encompassed the challenges posed by population growth, climate change and urbanization on the water, food and energy nexus, and the need to address the complexities to achieve sustainable development and mitigate environmental impacts is necessary. Through various sessions, the workshop highlighted concerns about GHG emissions and their mitigation by transitioning to renewable energy, carbon capture and storage, water hyacinth mapping in urban and peri-urban wetlands, Artificial Intelligence/Machine Learning (AI/ML) applications for rice mapping, flood damage assessment, maternal, infant and young children nutrition deficit under extreme weather conditions, agricultural data collection tools and sustainable agriculture practices. The CGIAR’s Mitigate+: Low-Emission Food Systems Initiative focuses on reducing emissions from the food systems by developing robust science, data, and evidence (among other activities). Another initiative by CGIAR on Resilient Cities generates evidence, technologies, and capacities that help improve urban food systems and secure equitable job and business opportunities, healthy diets for all, human and environmental health, and a reduced carbon footprint. Both initiatives provided resources to support the training workshop to empower students, researchers, scientists, academicians, decision-makers, and policymakers with cutting-edge knowledge and tools to integrate digital data into agricultural management practices. Participants learned about the latest advancements in Earth observation technologies, big data analytics, and digital tools that can help predict and make robust, evidence-based decisions as they confront challenges in the food system, urban water pollution, strategies to reduce GHG emissions, and tackling the nexus challenges. Thus, the workshop was envisioned as a catalyst to empower the agricultural community with digital tools and data, fostering resilience and productivity in the face of climate change. The criticality of Earth Observation (EO) data and digital tools in informing agricultural management decisions was rigorously examined and elucidated through a comprehensive program comprising six keynote addresses, nine scholarly lectures and six practical demonstrations, all facilitated by esteemed national (including IIT Guwahati, IIWM, Assam University, OSDMA, SAADRI, and SPARC) and international institutions (such as IWMI, World Bank, and DLR). A pre-event catch up with the participants was held on the first day session as a social ice-breaking session. The discourse was further enriched by an expert panel discussion on the ‘Role of Digital Tools in Mitigating Climate Change Effects on Agriculture’, an intensive brainstorming session entitled ‘Data Science and Sustainability Challenge’ and a showcase of research presentation by the participants. These engagements highlighted the practical and innovative usages of EO data for managing agriculture in the context of climatic challenges and emphasized how such strategic applications contribute towards attaining the SDGs. Of the 82 participants, 63% are male, and 37% are female. Among the attendees, 52% were at the graduate and post-graduate level, while 26% of the participants were research scholars from various Indian institutions. Of the other participants, 22% were faculty and professionals. This diversity of participants demonstrates the programme’s appeal to different professionals and researchers. The participants come from multiple institutions, including renowned universities and research centres across India like IIT Roorkee, BIT Mesra, ISI Kolkata, Techno Main Salt Lake, IIT Kharagpur, IIT Mandi, Fakir Mohan University, KIIT, and many more. This institutional diversity indicates the programme’s broader reach and appeal among academic and research organizations. These analytics provide valuable insights into the participants’ gender distribution, designations, education levels, and institutional affiliations. The inclusivity and diversity, reflected in gender representation and institutional affiliations, created a dynamic and comprehensive learning community. The diverse curriculum gave them valuable knowledge and skills to solve real-life challenges associated with major natural disasters.
6 Ghosh, Surajit; De Sarkar, K.; Chowdhury, A.; Holmatov, Bunyod; Rajakaruna, Punsisi. 2023. The greenhouse gas emissions estimates of hydropower reservoirs in Vietnam using G-res Tool: bridging climate change mitigation with sustainability frameworks. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Initiative on Low-Emission Food Systems. 52p.
Greenhouse gas emissions ; Estimation ; Hydropower ; Reservoirs ; Climate change mitigation ; Sustainability ; Frameworks ; Bibliometric analysis ; Policies / Vietnam / Ban Ve Reservoir / Binh Dien Reservoir / Ho Ham Thuan Reservoir / Ho Hoa Binh Reservoir / Ho Song Hinh Reservoir / Thac Ba Reservoir / Yali Reservoir
(Location: IWMI HQ Call no: e-copy only Record No: H052593)
(3.06 MB)
Quantifying greenhouse gas (GHG) emissions in hydropower reservoirs is linked with national and international sustainability objectives. Deploying scalable and effective cloud-based technologies improves the accessibility, reproducibility, and timeliness of the quantification process. This novel strategy promotes global sustainability in the hydropower industry while making it easier to comply with environmental regulations. It can promote informed decision-making, increase transparency, and expedite the transition to clean energy sources. Considering the use of cloud computing in GHG quantification can support global efforts to mitigate climate change and advance the development of hydropower systems into more sustainable global infrastructure. Earth Observation (EO) data with cloud computing facilities such as Google Earth Engine (GEE) and G-res (an online tool by the International Hydropower Association) can help fill in the missing data gaps and calculate GHG emissions from hydropower reservoirs in Vietnam following IPCC recommendations for estimating GHG emissions. Seven hydropower reservoirs (Ban Ve, Binh Dien, Ho Ham Thuan, Ho Hoa Binh, Ho Song Hinh, Thac Ba and Yali) from different parts of Vietnam were selected as test cases for calculating GHG emissions using the G-res tool. The initial results from the analysis show that the Binh Dien reservoir reports the highest GHG aerial emission rate per year, while the lowest has been observed for the Thac Ba reservoir. Similarly, the highest emission rate has been observed for the Ban Ve reservoir, while the lowest has been recorded for the Thac Ba reservoir. The initial results reported here provide an understanding of GHG emissions from the hydropower reservoirs (test cases) and are needed to be verified with the respective reservoir authorities for actual emissions.
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