Tallying impervious area in agricultural land by combining high-resolution satellite imagery and lidar data

Nurahida Laili, Wang Chi-Kuei, Wu Kuan-Ting

Research output: Contribution to conferencePaperpeer-review

Abstract

The shift in the use of agriculture land area had been undergone for recent years. In Taiwan, there are many cases where the agriculture area is not being cultivated but it is used for different purpose. In this study, we call this area as the impervious area. Impervious area evolves many kinds of purposes such as housing, factory, warehouse, graveyard, etc. The loss of farmland could further lead to the threat of national food production shortage and also soil pollution. For this reason, a periodical assessment to record the change of total farmland area is important to be carried out. The task could be laborious since Taiwan has an immense agriculture land area. An approach was proposed by utilizing the integration of Pleiades high-resolution satellite imagery and LiDAR data. The pansharpened Pleiades image was processed by using Normalized Digital Vegetation Index (NDVI) algorithm. The height information derived from LiDAR data was processed to produce the Normalized Digital Surface Model (nDSM). The candidate impervious area was selected by setting a NDVI threshold and a nDSM threshold. A pixel-based unsupervised classification would be carried out to this smaller extent of Pleiades. As the result, the time required for processing the images to delineate the impervious area could be reduced.

Original languageEnglish
Publication statusPublished - 2017
Event38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017 - New Delhi, India
Duration: 2017 Oct 232017 Oct 27

Other

Other38th Asian Conference on Remote Sensing - Space Applications: Touching Human Lives, ACRS 2017
CountryIndia
CityNew Delhi
Period17-10-2317-10-27

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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