Predicting Land-Cover Changes with Gray Systems Theory and Multitemporal Aerial Photographs

Ruiliang Pu; Peng Gong

doi:10.1080/10824009809480506

Predicting Land-Cover Changes with Gray Systems Theory and Multitemporal Aerial Photographs

Research output: Contribution to journal › Article › peer-review

Abstract

In this study, we report a new technique based on gray systems theory for land-cover change prediction. Historical land-cover data were obtained from aerial photo interpretation. Change prediction was carried out for seven land-cover types in Claremont Canyon, Alameda County, California. The prediction results demonstrated that the prediction technique was effective.

Original language	American English
Journal	Geographic Information Sciences
Volume	4
DOIs	https://doi.org/10.1080/10824009809480506
State	Published - Dec 1 1998
Externally published	Yes

Disciplines

Earth Sciences

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10.1080/10824009809480506License: CC BY

https://doi.org/10.1080/10824009809480506

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title = "Predicting Land-Cover Changes with Gray Systems Theory and Multitemporal Aerial Photographs",

abstract = " In this study, we report a new technique based on gray systems theory for land-cover change prediction. Historical land-cover data were obtained from aerial photo interpretation. Change prediction was carried out for seven land-cover types in Claremont Canyon, Alameda County, California. The prediction results demonstrated that the prediction technique was effective.",

author = "Ruiliang Pu and Peng Gong",

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AU - Gong, Peng

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Y1 - 1998/12/1

N2 - In this study, we report a new technique based on gray systems theory for land-cover change prediction. Historical land-cover data were obtained from aerial photo interpretation. Change prediction was carried out for seven land-cover types in Claremont Canyon, Alameda County, California. The prediction results demonstrated that the prediction technique was effective.

AB - In this study, we report a new technique based on gray systems theory for land-cover change prediction. Historical land-cover data were obtained from aerial photo interpretation. Change prediction was carried out for seven land-cover types in Claremont Canyon, Alameda County, California. The prediction results demonstrated that the prediction technique was effective.

UR - https://digitalcommons.usf.edu/geo_facpub/407

UR - https://doi.org/10.1080/10824009809480506

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DO - 10.1080/10824009809480506

M3 - Article

VL - 4

JO - Geographic Information Sciences

JF - Geographic Information Sciences

ER -

Predicting Land-Cover Changes with Gray Systems Theory and Multitemporal Aerial Photographs

Abstract

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