000			02695cab a2200313Ia 45 0
001			u192980
003			SIRSI
008			110620s2009 ua ss b eng d
040			_aEAL
041			_aeng _bara
090			_aART MJAE V26 No1 2
100	1		_aRoanhorse, A.
240	1	0	_aMisr Journal of Agricultural Engineering, 2009 v.26 (1) _h[electronic resource].
245	1	0	_aSelecting the best remote sensing platform for agricultural assessment using multi-objective analysis _h[electronic resource].
246	1	5	_aاختيار أنسب نظام استشعار عن بعد للتقييم الزراعي باستخدام تحليل الأهداف المتعددة.
300			_ap.11-43.
504			_aIncludes references.
520			_aRemote sensing has been identified as a cost-effective technology for site-specific management. This technology offers geographically extensive and continuous assessment of plants, soil and water resources, and other land surface phenomena. Selection of the best available remote sensing technology is determined in most cases by platform and sensor attributes. If these attributes can be quantified, then a multi-objective analysis may be performed to assess quantitatively the tradeoffs between different sensor and platform attributes, identifying the best overall technology. Pioneer work was presented by applying multi-objective analyses to remote sensing technology. Experts were surveyed to identify the best overall technology for agricultural purposes at three different pixel sizes: very fine (<5 cm), fine to moderate (0.5 m – 1.0 m), and moderate to coarse resolutions (0.1 km – 1.0 km). Platform technologies included hand held sensors, booms, remotely piloted vehicles, unmanned aerial vehicles, manned aircraft, Quickbird, Landsat, AVHRR, MODIS, ASTER, and SPOT. Plurality voting, Borda count, Hare system, and pairwise voting were used to analyze survey responses. Results suggest hand held sensors and manned aircraft platforms were favored for applications requiring very fine and fine to moderate spatial resolutions. AVHRR and MODIS were rated equally as the best alternatives for applications requiring moderate to coarse resolution imagery.
546			_aSummary in Arabic.
650		0	_aAgricultural estimating and reporting _xRemote sensing.
650		0	_aAerial photography in agriculture.
650		0	_aRemote sensing _xTesting.
700	1		_aEl Shikha, D.
700	1		_aSzidarovszky, F.
700	1		_aWaller, P.
773	0		_tMisr Journal of Agricultural Engineering. _g2009.v.26(1) _x1687-384X _7nnas _wu192786
856	4	0	_uhttp://nile.enal.sci.eg/EALE/2009/MJAE/2609/1/11.pdf _zFull Text Article.
596			_a1
942			_cAR _2lcc
999			_c46570 _d46570