Large scale mapping: an empirical comparison of pixel-based and object-based classifications of remotely sensed data

Bello, Innocent E.; Chigbu, Njike; Agbaje, Ganiy I.

doi:10.4314/sajg.v6i3.1

Cited by 2 publications

(1 citation statement)

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“…Nowadays, the data obtained from Earth Observing Systems such as Sentine-2, Landsat-7, Landsat-8, EOS AM-1 can be used for agricultural purposes [3], they provide multispectral images with spatial resolutions from 10 meters to 250 meters. However, the images obtained from these spacecraft do not allow the creation of large-scale maps (1: 25000 and 1: 10000) of relatively small land plots (for example, farms) [4,5]. Studies have shown the feasibility of using satellite images of very high spatial resolution (≥0.5 m) for the creating and updating of large-scale maps, in terms of accuracy, reliability and efficiency [6,7].…”

Section: Introductionmentioning

confidence: 99%

Creating large-scale maps for agriculture using remote sensing

et al. 2021

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Reliable information on the real state of agricultural lands will be required to the development of appropriate measures for the rational use of agricultural lands. To obtain such information, it is necessary to keep permanent and systematic records and inventories of land resources. Large-scale special plans and maps will be required for accounting, inventory and classification of agricultural land. Currently in Uzbekistan such cartographic materials are being created on the scale 1: 10 000 and 1: 25 000 by administrative and territorial units, farms or individual land plots. The article considers the issues of creation of special maps of agricultural land in scale 1:10000 on the example of Sharof Rashidov district of Jizzakh region using remote sensing data with very high spatial resolution KOMPSAT-3.

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Section: Introductionmentioning

confidence: 99%