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Different GIS and remote sensing techniques for detection of changes in vegetation cover : a MFS study in the Nam Ngum and Nam Lik catchment areas in the Lao PDR

Andersson, Kristin and Carlstedt, Jenny (1998) In Lunds universitets Naturgeografiska institution - Seminarieuppsatser
Dept of Physical Geography and Ecosystem Science
Abstract
The Lao People’s Democratic Republic (Lao PDR) is a small landlocked country in South-East Asia, where virgin forest still covers almost 47 % of the country’s total area (1991). Logging offers the potential to improve the economy of the Lao PDR. Besides legal logging activities, illegal logging to provide the population with agricultural land, pasture and firewood is taking place. Since the Lao PDR is mainly comprised of mountainous terrain, and has a poor infrastructure, accessibility to remote areas in the country is limited. To be able to survey the extent of the changes in vegetation that is taking place in these inaccessible areas, remote sensing is an alternative. This study has evaluated some different methods and courses of action... (More)
The Lao People’s Democratic Republic (Lao PDR) is a small landlocked country in South-East Asia, where virgin forest still covers almost 47 % of the country’s total area (1991). Logging offers the potential to improve the economy of the Lao PDR. Besides legal logging activities, illegal logging to provide the population with agricultural land, pasture and firewood is taking place. Since the Lao PDR is mainly comprised of mountainous terrain, and has a poor infrastructure, accessibility to remote areas in the country is limited. To be able to survey the extent of the changes in vegetation that is taking place in these inaccessible areas, remote sensing is an alternative. This study has evaluated some different methods and courses of action to approach the problems of detecting vegetation changes within the Remote Sensing and GIS (Geographical Information Systems) disciplines. Four different satellite image data sets, with differing spatial resolution, have been analysed in the study; the NOAA/NASA Pathfinder AVHRR Land Project 8 km data set, the 1 km AVHRR Global Land Data Set and Landsat MSS and TM images. Depending on the purpose of study, each of the methods tested have their benefits. The results indicate that the 8 kilometre data set provides an extensive temporal coverage, which will never be achieved by the finer resolution data. It is also possible to detect and locate changes in the vegetation cover with the 8 km resolution, assuming that the changes cover a large areal extent (minimum of 32 km2). The finer resolution images (the 1 kilometre data set and the Landsat MSS/TM scenes) benefit however from the gain in spatial precision which facilitates the task of locating smaller areas as well as improves the visual interpretation, although short time-series and higher costs may be a limiting factor. (Less)
Abstract (Swedish)
Populärvetenskaplig sammanfattning: Denna uppsats är ett examensarbete, utfört som ett Minor Field Studie stipendie i Laos. Uppsatsen behandlar temat avskogning - erosion.

Laos är ett land i Sydostasien som gränsar till länderna Thailand, Vietnam, Kambodja, Burma och Kina. 1991 täcktes fortfarande 47 % av landets totala areal av orörda skogar. Laos inriktning mot en marknadsekonomi främjar avverkning av skogarna för att förbättra ekonomin genom export av skogsprodukter samt de övriga naturtillgångar som blir tillgängliga genom exempelvis avverkning för att bygga vägar. Förutom denna lagliga avverkning sker en illegal avverkning för att förse befolkningen med jordbruksmark och bränsle. Eftersom stora delar av de områdena som avverkas... (More)
Populärvetenskaplig sammanfattning: Denna uppsats är ett examensarbete, utfört som ett Minor Field Studie stipendie i Laos. Uppsatsen behandlar temat avskogning - erosion.

Laos är ett land i Sydostasien som gränsar till länderna Thailand, Vietnam, Kambodja, Burma och Kina. 1991 täcktes fortfarande 47 % av landets totala areal av orörda skogar. Laos inriktning mot en marknadsekonomi främjar avverkning av skogarna för att förbättra ekonomin genom export av skogsprodukter samt de övriga naturtillgångar som blir tillgängliga genom exempelvis avverkning för att bygga vägar. Förutom denna lagliga avverkning sker en illegal avverkning för att förse befolkningen med jordbruksmark och bränsle. Eftersom stora delar av de områdena som avverkas illegalt ligger i oåtkomliga, bergiga områden är GIS (Geografiska Informations System) och Fjärranalys alternativ till att lättare upptäcka avskogade områden. Satellitdataset med olika upplösning jämförs i denna uppsats med syfte att försöka finna en passande metod att finna områden som avskogats inom ett dräneringsområde i nordöstra Laos. Laos största damm, Nam Ngum, ligger inom dräneringsområdet och fylls sakta igen av sediment. Man är intresserade av att ta reda på var sedimentet kommer från.

De tre satellitdataset som behandlas i uppsatsen är:

The NOAA/NASA Pathfinder AVHRR Land Project 8 km Data Set
The 1-km AVHRR Global Land Data Set
Tre Landsat MSS / TM scener (upplösning 80/30 m)
För att analysera de två första dataseten används NDVI (Normalised Difference Vegetation Index) bilder. NDVI är ett index mellan olika våglängdsband som satelliten mäter som förbättrar tolkningen av vegetation i bilderna. I Landsat bilderna har vegetationsförändringar tolkats genom visuell tolkning av gräsytor som digitaliserats in, och sedan jämföts mellan de olika åren.

Resultaten av analyserna visar att man med hjälp av satellitbilderna med 8 km’s upplösning kan urskilja större vegetationsförändringar. Den stora fördelen här, är den långa tidsserien som finns att tillgå. De övriga dataseten ger bättre spatiell information och mer exakt position. De är begränsade av korta tidserier, samt kostnad och problemet med moln, som lättare kan förbigås med längre tidsserier. (Less)
Please use this url to cite or link to this publication:
author
Andersson, Kristin and Carlstedt, Jenny
supervisor
organization
year
type
H1 - Master's Degree (One Year)
subject
keywords
remote sensing techniques, GIS, geography, physical geography, vegetation cover, Nam Ngum, Nam Lik, Lao PDR
publication/series
Lunds universitets Naturgeografiska institution - Seminarieuppsatser
report number
52
funder
SIDA, Minor Field Study programme (MFS)
language
English
id
2213523
date added to LUP
2011-11-23 13:04:58
date last changed
2011-11-23 13:08:58
@misc{2213523,
  abstract     = {{The Lao People’s Democratic Republic (Lao PDR) is a small landlocked country in South-East Asia, where virgin forest still covers almost 47 % of the country’s total area (1991). Logging offers the potential to improve the economy of the Lao PDR. Besides legal logging activities, illegal logging to provide the population with agricultural land, pasture and firewood is taking place. Since the Lao PDR is mainly comprised of mountainous terrain, and has a poor infrastructure, accessibility to remote areas in the country is limited. To be able to survey the extent of the changes in vegetation that is taking place in these inaccessible areas, remote sensing is an alternative. This study has evaluated some different methods and courses of action to approach the problems of detecting vegetation changes within the Remote Sensing and GIS (Geographical Information Systems) disciplines. Four different satellite image data sets, with differing spatial resolution, have been analysed in the study; the NOAA/NASA Pathfinder AVHRR Land Project 8 km data set, the 1 km AVHRR Global Land Data Set and Landsat MSS and TM images. Depending on the purpose of study, each of the methods tested have their benefits. The results indicate that the 8 kilometre data set provides an extensive temporal coverage, which will never be achieved by the finer resolution data. It is also possible to detect and locate changes in the vegetation cover with the 8 km resolution, assuming that the changes cover a large areal extent (minimum of 32 km2). The finer resolution images (the 1 kilometre data set and the Landsat MSS/TM scenes) benefit however from the gain in spatial precision which facilitates the task of locating smaller areas as well as improves the visual interpretation, although short time-series and higher costs may be a limiting factor.}},
  author       = {{Andersson, Kristin and Carlstedt, Jenny}},
  language     = {{eng}},
  note         = {{Student Paper}},
  series       = {{Lunds universitets Naturgeografiska institution - Seminarieuppsatser}},
  title        = {{Different GIS and remote sensing techniques for detection of changes in vegetation cover : a MFS study in the Nam Ngum and Nam Lik catchment areas in the Lao PDR}},
  year         = {{1998}},
}