Location of agricultural areas through high resolution satellite images in different areas of Costa Rica

 

保存先:
書誌詳細
著者: Aguilar-Martínez, Andrey
フォーマット: artículo original
状態:Versión publicada
出版日付:2019
その他の書誌記述:With the passing of days, the agricultural frontier is reduced and an exact control of the amount of area destined to agriculture and which crops are developed in a region is lost. The objective of the study is to generate a supervised classification of satellite images to obtain agricultural areas through a map of land use. Four high-resolution satellite images were used, in addition to the Quantum GIS free software. The process of this project consisted of requesting the chosen images to carry out the study, in the QGIS software the red, green and blue band were joined; later an orthorectification was carried out to adjust the position of the image, an unsupervised classification was obtained to create a previous version of land use; then, in the field work, a drone was used to corroborate confusing coverage or in case of presence of a cloud in the image. Finally, supervised classification was made, according to the number of discriminated coverages. In all four images there is an important presence of agricultural use; where only in the partial image of the canton of Pérez Zeledón, there is a higher percentage of land with pastures than for agriculture, the images of León Cortés, Pacayas and Cañas show a predominance of agriculture, there being a great difference between the crops present. The derived information is important for territorial ordering, agricultural censuses, crop prediction, market regulation.
国:RepositorioTEC
機関:Instituto Tecnológico de Costa Rica
Repositorio:RepositorioTEC
言語:Español
OAI Identifier:oai:repositoriotec.tec.ac.cr:2238/11913
オンライン・アクセス:https://revistas.tec.ac.cr/index.php/tec_marcha/article/view/4258
https://hdl.handle.net/2238/11913
Access Level:acceso abierto
キーワード:Satellite images
supervised classification
agricultural area
drone
Imágenes satelitales
clasificacion supervisada
area agricla
dron