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Rahman, Nik Norulaini Nik Ab
- Effect of Upstream on Downstream Due to Spatio-Temporal Land Use Land Cover Changes in Kelantan, Peninsular Malaysia
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Authors
Mohd Talha Anees
1,
K. Abdullah
1,
M. N. M. Nawawi
1,
Nik Norulaini Nik Ab Rahman
2,
Abd. Rahni Mt. Piah
3,
M. I. Syakir
4,
A. K. Mohd. Omar
4
Affiliations
1 School of Physics, Universiti Sains Malaysia, 11800 Minden, Penang, MY
2 School of Distance Education, Universiti Sains Malaysia, 11800 Minden, Penang, MY
3 School of Mathematics, University Sains Malaysia, 11800, Minden, Penang, MY
4 School of Industrial Technology, Universiti Sains Malaysia, 11800 Minden, Penang, MY
1 School of Physics, Universiti Sains Malaysia, 11800 Minden, Penang, MY
2 School of Distance Education, Universiti Sains Malaysia, 11800 Minden, Penang, MY
3 School of Mathematics, University Sains Malaysia, 11800, Minden, Penang, MY
4 School of Industrial Technology, Universiti Sains Malaysia, 11800 Minden, Penang, MY
Source
Nature Environment and Pollution Technology, Vol 16, No 1 (2017), Pagination: 29-35Abstract
The present study deals with the effects of upstream spatio-temporal land use land cover (LULC) changes on downstream by the use of Landsat and Google Earth data in Kelantan, Peninsular Malaysia. The study involves mosaic of multi-temporal satellite data of Landsat-5 TM of 2005 and Landsat-8 OLI_TIRS of 2015, which have been analysed visually. The study reveals that the effect of major spatio-temporal LULC changes of upstream can cause river overflows and flash flood at downstream. The major LULC changes noticed were decrease in dense forest 798.89 km2 (5.30%) at up and midstream and mixed horticulture 263.34 km2 (1.74%) at mid and downstream, while increase in forest (416.82 km2) at midstream and scrub (190.62 km2) at upstream due to transformation from dense forest. Furthermore, increment in uncultivated land (68.33 km2) and palm oil (372.66 km2) plantation activities at both up and midstream was observed. The accuracy assessment result of the study shows that study was accurate with overall accuracy of 91.4%.Keywords
Flood, Landsat, Land use Land Cover, Remote Sensing, GIS.Full Text
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