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Student Number 970202602
Author Lalu Muhamad(¼B®¶ª@)
Author's Email Address lmjaelani@geodesy.its.ac.id
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Department Master of Science Program in Remote Sensing Science and Technology
Year 2009
Semester 2
Degree Master
Type of Document Master's Thesis
Language English
Title Estimating Net Primary Productivity (NPP) on Tropical Rain Forest Using MODIS Observation Data
Date of Defense 2010-06-07
Page Count 114
Keyword
  • APAR
  • FPAR
  • MODIS
  • MODPRI
  • NPP
  • PAR
  • Rs
  • Abstract Estimating Net Primary Productivity (NPP) on Tropical Rain Forest Using MODIS Observation Data
    Net Primary Productivity (NPP) is known as an important index for evaluating the carbon cycle in forest ecosystem. However, due to the factors of large area and lack of ground measurement data in tropical forest, it is hard to understand how forest ecosystem runs by land materials. Therefore, we use remote sensing data to estimate the three important parameters of NPP in tropical rain forest such as Light Use Efficiency (LUE), Fraction of Photosynthetically Active Radiation absorbed by vegetation (FPAR), and Photosynthetically Active Radiation absorbed by vegetation (PAR). 
    Basically, the Monteith equation is used to measure aboveground NPP in the tropical forest. Rahman et al. (2004) proposed a micrometeorological model to estimate ¡¥¡¥continuous field¡¦¡¦ LUE for terrestrial vegetation using MODIS Photochemical Reflectance Index (MODPRI) from the MODIS ocean bands. FPAR is calculated from Normalized Difference Vegetation Index (NDVI). PAR is from 45 % of incoming shortwave solar radiation (Rs). In this study, we use MODIS data from 2000 to 2006 and compare the results with MOD17 of NASA Product. Absorbed Photosynthetically Active Radiation (APAR) from in-situ data (2001 and 2002) of Bukit Soeharto (BKS) site of micrometeorological station is used to produce a NPP APAR. Then, it¡¦s a reference data in this study.
    The main objective of this study is to get a new method to estimate NPP from MODIS remotely sensed data without using micrometeorological information over the study areas. This method creates a challenge to monitor ecosystem productivity in global area and even in difficultly-accessed regions.
    The results show estimated value for the distribution of NPP over Borneo Island by three methods : NPP Rs, NPP MOD17 and NPP APAR. These values are 1076.546 gC m-2 y-1; 3028.850 gC m-2 y-1; 1615.509 gC m-2 y-1 in 2001, and 1522.324 gC m-2 y-1; 2890.467 gC m-2 y-1; 1987.113 gC m-2 y-1 in 2002, respectively. NPP Rs and NPP MOD17 values showed that there is no correlation between them. NPP Rs and NPP APAR outcomes represent good correlation in the trend of 2001 and 2002 data.
    From this result we can conclude that: the NPP data provided by NASA is overestimated in this region, NPP Rs gives better result in comparison with NPP APAR, although it is still underestimated. Improved methods for estimating NPP by using MODIS observation data is needed to be developed. With advanced study employing the methodology of this study, better accuracy in estimating NPP can be achieved.
    Table of Content Chinese Abstracti
    English Abstractiii
    Acknowledgmentsiv
    Table of Contentsv
    List of Figuresviii
    List of Tablesxi
    Explanation of Symbolsxii
    I.INTRODUCTION1
    1.1 Global Warming and Climate Change1
    1.2 Global Carbon Cycle and Ecosystem3
    1.3 Tropical Forest and Global Carbon Cycle 7
    1.4 Remote Sensing and Ecosystem Productivity Modelling9
    1.5 Objectives 11
    1.6 Some Facts 11
    1.7 Research Approach12
    II.METHODS AND MATERIALS14
    2.1 Study Area 14
    2.1.1 Geographic Location14
    2.1.2 Climate14
    2.1.3 Vegetation Cover and Topography15
    2.2 Research Methods19
    2.2.1 Normalized Difference Vegetation Index (NDVI)20
    2.2.2 Incoming Shortwave Radiation (Rs)20
    2.2.3 Estimating Photosynthetic Light Use Efficiency (LUE)22
    2.2.4 Estimating fraction Photosynthetically Active Radiation (FPAR)23
    2.2.5 Estimating Photosynthetically Active Radiation (PAR)24
    2.2.6 NPP Rs25
    2.2.6 NPP APAR (APAR from in situ data)26
    2.3 Materials26
    2.3.1 MODIS Product Overview26
    2.3.2 MODIS Level-1B Product29
    2.3.3 MODIS Geolocation Product32
    2.3.4 NPP MOD17 Product32
    2.3.5 APAR BKS Data 33
    III.DATA PROCESSING35
    3.1 Geo-referencing MOD02135
    3.2 Resizing MOD02142
    3.3 Subsetting MOD021 using AOI45
    3.4 Resizing and Subsetting MOD0350
    3.5 Calculating NPP Rs Using MATLAB53
    3.6 Calculating NPP APAR Using MATLAB56
    3.7 Adjusting NPP MOD17 Using MATLAB58
    IV.RESULT AND DISCUSSION60
    4.1 MOD021 and MOD03 Data60
    4.2 BKS¡¦ APAR Data66
    4.3 NPP APAR 68
    4.4 NPP Rs71
    4.5 NPP MOD1778
    4.6 Comparing NPP Rs, NPP MOD17 and NPP APAR85
    V.CONCLUSIONS 88
    Bibliographies90
    Appendices 92
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    Advisor
  • Yuei An, Liou(¼B»¡¦w)
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    Date of Submission 2010-07-12

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