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https://elibrary.tucl.edu.np/handle/123456789/5456Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | ADB; Dillon, Andrew; Rao, Lakshman Nagraj | - |
| dc.date.accessioned | 2021-10-05T15:03:48Z | - |
| dc.date.available | 2021-10-05T15:03:48Z | - |
| dc.date.issued | 2018-03 | - |
| dc.identifier.isbn | N/A | - |
| dc.identifier.isbn | N/A | - |
| dc.identifier.issn | 2313-6537 | - |
| dc.identifier.issn | 2313-6545 | - |
| dc.identifier.uri | https://www.adb.org/publications/land-measurement-bias-gps-satellite-data | - |
| dc.identifier.uri | https://elibrary.tucl.edu.np/handle/123456789/5456 | - |
| dc.description | Using Google Earth in agricultural land measurements as an alternative technique produces land area estimates close to Global Positioning System (GPS) estimates at reduced fieldwork costs. Traditionally, data on agricultural land size is collected through farmer self-reports in surveys, which has been shown to vary significantly from more accurate estimates derived from Global Positioning System (GPS). However, using GPS introduces significant time and financial costs. This paper proposes using Google Earth for land area measurement and compares estimates with GPS and farmer self-reports. Results show that Google Earth-based land area estimates are very similar to GPS measures, but reduce fieldwork costs by nearly 38%. As remotely sensed data becomes publicly available, it may become a less expensive alternative to link to survey data than rely on GPS measurement. | - |
| dc.format.extent | 32 | - |
| dc.subject.other | Agriculture and natural resources | - |
| dc.subject.other | Economics | - |
| dc.subject.other | Information and Communications Technology | - |
| dc.title | Land Measurement Bias: Comparisons from Global Positioning System, Self-Reports, and Satellite Data | - |
| local.publication.country | Regional - Asia and the Pacific | - |
| Appears in Collections: | ADB Collections | |
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