Siddhartho Shekhar Paul (author)
Jiangbing Li (Thesis advisor)
University of Northern British Columbia (Degree granting institution)

2014

Master of Science (MSc)

Environmental Science

Number of pages in document: 145

This thesis study was conducted to capture the land use and land cover (LULC) change dynamics in Kiskatinaw River Watershed, BC, Canada. A combination of remote sensing, GIS and modeling approach was utilized for this purpose. Landsat TM and ETM+ satellite images of the years 1984, 1999 and 2010 were analyzed using object oriented image classification technique to produce LULC maps and detect the associated changes. The dynamic nature of different forest types, increase in built-up area and significant depletion of wetlands were found to be notable among the detected LULC changes. Thereafter, a multi-layer perception neural network technique was used to model transition potentials of various LULC types, which was later realized with a Markov Chain land use model to predict future changes. The integration of advanced satellite remote sensing tools and neural network aided Markov Chain modeling was illustrated to be an effective means for LULC change detection and prediction in Kiskatinaw River Watershed. --Leaf ii.

Watersheds -- Research -- British Columbia -- Kiskatinaw River.
Land use, Rural -- British Columbia -- Kiskatinaw River Watershed.
Landscape assessment -- British Columbia -- Kiskatinaw River Watershed.

https://doi.org/10.24124/2014/bpgub962

thesis