Evaluation of object-based image analysis techniques on very high-resolution satellite image for biomass estimation in a watershed of hilly forest of Nepal

Hussin, Y.A.; Gilani, Hammad; Leeuwen, Louise van; Murthy, M. S. R.; Shah, Rachna; Baral, Srijana; Tsendbazar, Nandin‐Erdene; Shrestha, Stal; Shah, Shyam Kumar; Qamer, Faisal Mueen

doi:10.1007/s12518-014-0126-z

Cited by 41 publications

(12 citation statements)

References 51 publications

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“…Until space-borne Lidar sensors become available, scaling-up plot-level forest AGB by combining airborne Lidar and MODIS data provide an alternative solution for estimating forest AGB at large scales. Such estimates would be useful in numerous ecological and environmental applications (Hussin et al, 2014;Kattenborn et al, 2015;McRoberts et al, 2014;Schlerf and Hussin, 2011).…”

Section: Issues In Applying Forest Agb Estimation At Large Scalesmentioning

confidence: 99%

“…Even though traditional field methods such as destructive sampling or allometric equations are able to provide accurate references for forest AGB at individual plots, validation of coarseresolution satellite-derived AGB is extremely difficult due to subpixel spatial variation of MODIS and mismatched footprints between satellite observations and field measurements. One method is to derive regional forest AGB from high-spatial and low-temporal resolution satellite imagery such as Worldview, Landsat TM, SAR and Quickbird (Hussin et al, 2014;Kattenborn et al, 2015;Schlerf and Hussin, 2011;Cutler et al, 2012;Gonzalez et al, 2010). Though some studies have reported that combining optical satellite imagery at different spatial resolutions is useful for mapping forest AGB, other studies revealed that forest structures also influenced total AGB of forests (Cutler et al, 2012;Foody et al, 2003;Leboeuf et al, 2012;Luther et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

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Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass

Guo

Tao

et al. 2015

ISPRS Journal of Photogrammetry and Remote Sensing

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Section: Issues In Applying Forest Agb Estimation At Large Scalesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass

Guo

Tao

et al. 2015

ISPRS Journal of Photogrammetry and Remote Sensing

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“…VHR satellite images are commonly used in the forestry sector for the extraction of forest parameters, especially in assessing deforestation and forest degradation rates for better management and decision making (Hussin et al 2014;Huang et al 2009b). In this study, which used VHR satellite images, a decrease was observed in closed canopies of Pinus wallichiana and Pinus roxburghii, which led to an increase in the open canopy covers of both Pinus species.…”

Section: Discussionmentioning

confidence: 99%

Evaluation of state and community/private forests in Punjab, Pakistan using geospatial data and related techniques

et al. 2015

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“…E-Learning can be used to increase accessibility and internationalisation in higher education. Properly developed courses, based on content and pedagogy used by world leading partners, combined with extensive market investigations, tested by pilot students and external experts, increase quality and relevance ( Chemura, van Duren, & van Leeuwen, 2015;Hussin et al, 2014). New communication and administrative tools will build capacity within management.…”

Section: Methodsmentioning

confidence: 99%

Features of the International MSC Educational Programme in Environmental Management and Modelling

Pilesjö

Mansourian

Runnström

et al. 2018

Geodesy and Cartography

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“International Msc Educational Programme in Environmental Management and Modelling” (GeoNetC) is a European Commission funded project under ERASMUS+: Higher Education – International Capacity Building programme (Project No 561967-EPP-1-2015-1-SE-EPPKA2-CBHE-JP). It began in October 2015 and ended in October 2018. Initiated by the Lund University and partners from the Middle East countries, the GeoNetC project is an ambitious project aiming to match labour market needs with geospatial education offer both in Europe and Middle East countries. The aim of this three-year project is to enable European universities to exchange best practices and innovation with each other and with Middle Eastern universities regarding the mismatch between Europe’s geospatial education and training and the geospatial education in Middle East countries. There is a growing need for well-trained students at all levels – vocational, bachelors, masters – in the field of geospatial technologies. Obviously there is a growing number of jobs available in land surveying, mapping data collection, data processing, data delivery and turning data into information in both European and Middle East countries. Through cooperation, all partners will improve the quality of their respective academic programs. The European partners will make their courses more attractive and well adjusted for students from the Middle East. As well, they will increase the general quality and add state-of-the-art learning components to their offerings, and the partners from the region will significantly increase the academic level and quality in the education they provide. There will be spin-offs into other subjects than environment/Geomatics, since both the pedagogic models developed (e.g. e-Learning) and communication and administrative tools can be used throughout the partner universities. Therefore, this partnership cooperation will be of great value to Partner Countries as well as to Programme Countries. A number of distance learning courses/modules are developed jointly by partner institutions in Europe and the Middle East. The main aim of the network is to promote the use of spatial information and earth observation for environmental management and modelling through capacity building and institutional development, via a network in which all partners would contribute from their own positions of strength. All 13 modules are following EU higher education standards regarding e.g. ECTS, and learning outcomes. The outcome of the project, in terms of courses/modules, will be freely used among the partners, with the possibilities of offering individual courses or a whole MSc programme, whether individually or together. All produced material was evaluated/quality controlled by an external evaluation group of independent experts within environmental management and modelling, higher education, as well as pedagogy.

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Evaluation of object-based image analysis techniques on very high-resolution satellite image for biomass estimation in a watershed of hilly forest of Nepal

Cited by 41 publications

References 51 publications

Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass

Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass

Evaluation of state and community/private forests in Punjab, Pakistan using geospatial data and related techniques

Features of the International MSC Educational Programme in Environmental Management and Modelling

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