Some Problems of Measuring Land Use in Underdeveloped Countries: The Land Use Survey of Malawi

Stobbs, A. R.

doi:10.1179/caj.1968.5.2.107

Cited by 5 publications

(2 citation statements)

References 1 publication

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Several alternative methods have been used: (a) stratify the region geometrically and then randomly select points within each square or rectangle (Berry and Baker, 1968). The number of points may be determined by utilizing formulae, (Stobbs, 1968;Alford et al, 1974); (b) stratify the region by interpreted land use categories, then estimate the total number of sample points that could be visited due to the constraints imposed by time and money, and subsequently distribute them proportionally by area (Zonneveld, 1974). (c) stratify the region by interpreted category.…”

Section: Sampling Proceduresmentioning

confidence: 99%

“…No indication of sampling method or suggestions on appropriate number of sampling sites was given, but they did include some criteria for establishing interpretation accuracy, including the 85-95% limits suggested by Anderson ( 1971). Stobbs (1968) used a random sampling method to meastire land use in Malawi. He calculated the number of points to be sampled on each photograph by using a pre-determined formula.…”

Section: Sampling Proceduresmentioning

confidence: 99%

See 1 more Smart Citation

Remote Sensing: Statistical Testing of Thematic Map Accuracy

Genderen¹,

Lock²,

Vass³

1978

Remote Sensing of Environment

View full text Add to dashboard Cite

In order to achieve wider acceptance among users of thematic maps derived from remote sensing data, the interpreter must be able to specify the accuracy of his product. This requires a valid sampling procedure to estimate classification accuracy. Although several alternative methods have been used in the past, none provide sufficient statistical justification for the allocation of sample points in each category of land use using remote sensing imagery, This paper describes a more detailed and more reliable method for determining the most appropriate (i.e., minimum,) sample size. The concept developed and described in the paper incorporates the probability of making incorrect interpretations at particular prescribed accuracy levels, for a certain number of errors, for a particular sample size. The remote sensing sampling strategy presented has the added advantage that it can easily be adapted for use with most forms of remote sensing imagery, including orbital data. It provides a reliable framework for testing the accuracy of any remote sensing image interpretation -based land use classification using the minimum number of sample points; thereby saving time and money, especially if it is employed in operational surveys where high specification accuracy levels need to be guaranteed.

show abstract

Section: Sampling Proceduresmentioning

confidence: 99%

Section: Sampling Proceduresmentioning

confidence: 99%