Change Detection of Land Use and Land Cover over a Period of 20 Years in Papua New Guinea

Sailesh Samanta,Dilip Kumar Pal

doi:10.4236/ns.2016.83017

Abstract

People have an inherent tenacity to throng coastal regions in pursuit of better living conditions. As such the brisk dynamism of land use/land cover activities in a coastal region becomes obvious. The former keeps changing rapidly due to burgeoning population. A digital change detection analysis is performed with the help of Geographic Information System (GIS) on the Remote Sensing data spanning over last 20 years, complemented by in-situ data and ground truth information. This current research briefly endeavours to find out the nature of change happening in the major three coastal cities of Papua New Guinea (PNG), namely Alotau, capital of Milnebay province; Lae, capital of Morobe province and Port Moresby, capital of Papua New Guinea. Changes in land use and land cover that took place over 20 years have been recorded using Landsat 5 thematic mapper (TM) data of 1992 and Landsat 8 operational land imager (OLI) data. Land use and land cover maps of 1992, and 2013/14, and change detection matrix of 1992-2013/14 are derived. Results show an immensely sprawling urban landscape, evincing about five times growth during 1992 to 2014. At the same time “natural forests” dwindled by 444.96 hectares in Alotau, 6977.25 hectares in Lae and “mangrove” and “grass/shrub land” decreased by 127.78 and 4859.39 hectares respectively around Port Moresby. The above changes owe to ever increasing population pressure, land tenure shift, agriculture and industrial development.

Highlights

Optical remote sensing data of the earth surface can be analyzed to generate thematic information about general land use/land cover [1]
The result of classification of the satellite data should meet some significant criteria for its acceptance by the third party/user. Those criteria are: 1) classification accuracy should be more than 85 percent, 2) accuracy of the individual land use/land cover categories must be approximately equal, 3) repetitive results’ synchronisation from one interpreter to another and one time to another is to be ensured, 4) larger areas must be applicable for classification, 5) the classification must permit vegetation and other types of land cover as surroundings features, 6) temporal resolution and time series data should be suitable for the classification, 7) selection of subcategories can be identified from ground truth collection, 8) aggregation of subcategories must be possible, 9) comparison with future land use/land cover should be considerable, and 10) multiple uses of land should be documented if possible
The objective of this research work is to find out land use/land cover change detection in the period 1992-2013/14 using multi-spectral satellite images

Summary

Introduction

Optical remote sensing data of the earth surface can be analyzed to generate thematic information about general land use/land cover [1]. The result of classification of the satellite data should meet some significant criteria for its acceptance by the third party/user Those criteria are: 1) classification accuracy should be more than 85 percent, 2) accuracy of the individual land use/land cover categories must be approximately equal, 3) repetitive results’ synchronisation from one interpreter to another and one time to another is to be ensured, 4) larger areas must be applicable for classification, 5) the classification must permit vegetation and other types of land cover as surroundings features, 6) temporal resolution and time series data should be suitable for the classification, 7) selection of subcategories can be identified from ground truth collection, 8) aggregation of subcategories must be possible, 9) comparison with future land use/land cover should be considerable, and 10) multiple uses of land should be documented if possible

Methods

Results

Discussion

Conclusion