Your search found 5 records
1 Liu, G.; Xu, M.; Rui, L.; Walker, J.; Hu, W. 2002. Assessment of a small catchment on the Loess Plateau. In McVicar, T. R.; Rui, L.; Walker, J.; Fitzpatrick, R. W.; Changming, L. (Eds.), Regional water and soil assessment for managing sustainable agriculture in China and Australia. Canberra, Australia: ACIAR. pp.139-154.
Catchment areas ; Watersheds ; Soil properties ; Ecosystems ; Assessment ; Soil conservation / China / Loess Plateau
(Location: IWMI-HQ Call no: 631.7.1 G592 MCV Record No: H032996)
2 Rui, L.; Liu, G.; Xie, Y.; Qinke, Y.; Liang, Y. 2002. Ecosystem rehabilitation on the Loess Plateau. In McVicar, T. R.; Rui, L.; Walker, J.; Fitzpatrick, R. W.; Changming, L. (Eds.), Regional water and soil assessment for managing sustainable agriculture in China and Australia. Canberra, Australia: ACIAR. pp.358-365.
(Location: IWMI-HQ Call no: 631.7.1 G592 MCV Record No: H033013)
3 Roelcke, M.; Han, Y.; Schleef, K. H.; Zhu, J. G.; Liu, G.; Cai, Z. C.; Richter, J. 2004. Recent trends and recommendations for nitrogen fertilization in intensive agriculture in Eastern China. Pedosphere, 14(4):449-460.
(Location: IWMI-HQ Call no: PER Record No: H036123)
4 Tang, B.-H.; Shrestha, B.; Li, Z.-L.; Liu, G.; Ouyang, H.; Gurung, D. R.; Amarnath, Giriraj; Aung, K. S. 2013. Determination of snow cover from MODIS data for the Tibetan Plateau Region. International Journal of Applied Earth Observation and Geoinformation, 21:356-365. [doi: https://doi.org/10.1016/j.jag.2012.07.014]
Snow cover ; Cloud cover ; Satellite surveys ; Data ; Mapping ; Indicators ; Algorithms / Central Asia / China / Tibet / Tibetan Plateau
(Location: IWMI HQ Call no: e-copy only Record No: H045039)
(1.65 MB)
This paper addresses a snow-mapping algorithm for the Tibetan Plateau region using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Accounting for the effects of the atmosphere and terrain on the satellite observations at the top of the atmosphere (TOA), particularly in the rugged Tibetan Plateau region, the surface reflectance is retrieved from the TOA reflectance after atmospheric and topographic corrections. To reduce the effect of the misclassification of snow and cloud cover, a normalized difference cloud index (NDCI) model is proposed to discriminate snow/cloud pixels, separate from the MODIS cloud mask product MOD35. The MODIS land surface temperature (LST) product MOD11 L2 is also used to ensure better accuracy of the snow cover classification. Comparisons of the resulting snow cover with those estimated from high spatial-resolution Landsat ETM+ data and obtained from MODIS snow cover product MOD10 L2 for the Mount Everest region for different seasons in 2002, show that the MODIS snow cover product MOD10 L2 overestimates the snow cover with relative error ranging from 20.1% to 55.7%, whereas the proposed algorithm estimates the snow cover more accurately with relative error varying from 0.3% to 9.8%. Comparisons of the snow cover estimated with the proposed algorithm and those obtained from MOD10 L2 product with in situ measurements over the Hindu Kush-Himalayan (HKH) region for December 2003 and January 2004 (the snowy seasons) indicate that the proposed algorithm can map the snow cover more accurately with greater than 90% agreement.
5 Meng, F.; Yuan, Q.; Bellezoni, R. A.; de Oliveira, J. A. P.; Hu, Y.; Jing, R.; Liu, G.; Yang, Z.; Seto, K. C. 2023. The food-water-energy nexus and green roofs in Sao Jose Dos Campos, Brazil, and Johannesburg, South Africa. npj Urban Sustainability, 3:12. [doi: https://doi.org/10.1038/s42949-023-00091-3]
Energy consumption ; Energy demand ; Water conservation ; Food security ; Food production ; Nexus approaches ; Sustainability ; Rainwater harvesting ; Environmental impact ; Ecological footprint ; Urban areas ; Carbon footprint ; Water footprint ; Transboundary waters ; Infrastructure / Brazil / South Africa / Sao Jose dos Campos / Johannesburg
(Location: IWMI HQ Call no: e-copy only Record No: H051940)
https://www.nature.com/articles/s42949-023-00091-3.pdf?pdf=button%20sticky
https://vlibrary.iwmi.org/pdf/H051940.pdf
https://vlibrary.iwmi.org/pdf/H051940.pdf
(2.52 MB) (2.52 MB)
Green roofs affect the urban food-water-energy nexus and have the potential to contribute to sustainability. Here we developed a generalizable methodology and framework for data-sparse cities to analyze the food-water-energy nexus of green roofs. Our framework integrates the environmental costs and benefits of green roofs with food-water-energy systems and makes it possible to trace energy-water-carbon footprints across city boundaries. Testing the framework in São José dos Campos (SJC), Brazil and Johannesburg, South Africa, we found that green roofs are essentially carbon neutral and net energy consumers from a life cycle perspective. SJC is a net water beneficiary while Johannesburg is a net water consumer. Rainwater utilization could save irrigated water, but requires 1.2 times more energy consumption. Our results show that SJC and Johannesburg could direct their green roof development from local food production and energy saving, respectively and highlight opportunities for green roof practices in cities.
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