FACULTY OF ENGINEERING AND SUSTAINABLE DEVELOPMENT Department of Industrial Development, IT and Land Management Forestry carbon sequestration and trading: a case of Mau Forest Complex in Kenya Forest Change detection and carbon trading Kevine Okoth Otieno 2016 Student thesis, Master degree (one year), 15 HE Geomatics Master Programme in Geomatics Degree Project in Geomatics & Land Management (DPGEOLM) Supervisor: Anders Brandt Examiner: Markku Pyykönen & Ding Ma Abstract The global temperature is at an all-time high, the polar ice is melting, the sea levels are rising and the associated disasters are a time bomb. These variations in temperature are thought to trace roots to anthropogenic sources. In order to mitigate these changes and slow down the rate of warming, several efforts have been made locally and internationally. One of the agreed up-on way to do this is by using forests as reservoirs for carbon since carbon is one of those greenhouses gasses responsible for the warming. Mau forest, in Kenya, is one of those ecosystems where degradation has happened tremendously, though still viewed as a potential site for reclamation. Using GIS and remote sensing analysis of Landsat images, the study sought to compare various change detection techniques, find the amount of biomass lost or gained in the forest and the possible income accrued in case the forest is placed under the Kyoto protocol’s Clean Development Mechanism (CDM). Various vegetation ratios were used in the study ranging from NDVI, NDII to RSR. The results obtained from these ratios were not quite convincing as setting threshold for the ratios to separate dense forest from other forms of vegetation was not straightforward. As a consequence, the three ratios NDVI, NDII and RSR were combined and substituted for RGB bands respectively. A classification was done using this combination and the results compared to classifications based on tasselled cap and principal component analysis (PCA). The results of the various methods showed that the forest has lost its biomass over time. The methods indicated that the section of the forest studied lost between 8088 ha and 9450 ha of dense forest land between 1986 and 2010. This is between 29% and 35% of forest cover lost depending on the various methods of change detection used. This acreage when converted into forest biomass at a rate of 236 Mg.ha-1 gives a value of between 1908768 tons and 2230200 tons of carbon. If the Mau forest were registered as Kyoto compliant, then in the carbon market, this would have been a loss of between $24.1m and $ 28.2m according to California carbon dashboard (28th, May 2015). This is a huge sum of money if paid to a rural community as benefits from carbon sequestration via forestry. Such are the amounts that a community can earn by protecting a forest for the purposes of carbon sequestration and trading. Keywords: carbon, indices, NDVI, change detection, biomass, remote sensing Acknowledgement I would like to acknowledge God for granting me the chance to study in a foreign land and have the opportunity to carry out this work. My sincere gratitude is equally extended to my supervisor Dr Anders Brandt for pointing out the errors in my work and making suggestions. I should also not forget to mention Nancy to whom I wrote constantly whenever a method was not adding up, thank you. My appreciation also goes to all the other staff and students in the department of Geomatics, you shaped me and sharpened me in a myriad of ways. I extend my sincere gratitude to the examiner Markku and the co-examiner, Ding Ma. Your patience and tolerance is humbling. Your criticism of my work has been motivating and makes me want to give my best all the time. Thank you. To my classmates, you made me feel at home away from home. I enjoyed the harmony. Jon and Fadi, you were like elder brothers to me. Thank you abundantly, I cherish every single moment we shared. To Judyannet, thank you for being you and keeping me under pressure. Dedication This piece of work is dedicated to Jacob Alex Otieno K’Achila - Lihudu. You have been an oasis of hope in my deserts of calamities. I might have grown into a silent young man, but in my silence I do admire your approach to life. As a family, your support over the years has been tremendous. Mum and dad, I wish you could see eye to eye once again. An old tree spells miseries to the nesting birds when it is uprooted. Your stubbornness is messing us up. It is tearing down the morale and our moral standings grow shakier with time. I cannot raise my head in a crowd anymore! To Gonza Okoyo Otieno, you are my mother’s last born. I wish you could embrace life with all the seriousness it deserves. I do pray that the Almighty God leads you in his way. Finally, to Lolah Namuria Wafula, it was raining when you were born. On a careful scrutiny, it was not rain, the angels were weeping for losing one of them to the world! I love you my angel. You are the best thing that ever happened. Whether you know this, I do not know. Table of contents 1 INTRODUCTION ............................................................................................................. 1 1.1 Background ................................................................................................................. 1 1.2 Aims and objectives of the study ................................................................................ 1 2 CARBON TRADING AND CHANGE DETECTION ..................................................... 3 2.1 Benefits of carbon sequestration ................................................................................. 4 2.2 Potential in Africa ....................................................................................................... 5 2.3 Challenges ................................................................................................................... 5 2.4 Methods of change detection....................................................................................... 6 2.4.1 Rationing .............................................................................................................. 7 2.4.2 Normalised Difference Vegetation Index – NDVI .............................................. 8 2.4.3 Simple ratio - (NIR / R) ....................................................................................... 8 2.4.4 Normalized difference infrared index – NDII ..................................................... 9 2.4.5 Image differencing ............................................................................................... 9 2.4.6 Change vector analysis – CVA ............................................................................ 9 2.4.7 Classification – post classification ..................................................................... 10 2.4.8 Principal component analysis – PCA ................................................................. 10 2.4.9 Tasselled cap indices.......................................................................................... 12 2.4.10 Soil Adjusted Vegetation Index ......................................................................... 12 2.5 Allometric equations ................................................................................................. 12 2.6 Carbon trading ........................................................................................................... 13 3 STUDY AREA ................................................................................................................ 14 3.1 Mau Forest Complex ................................................................................................. 14 3.2 Government’s efforts to protect the Mau .................................................................. 15 4 METHODS ...................................................................................................................... 16 4.1 Data pre-processing ................................................................................................... 16 4.2 Indices ....................................................................................................................... 17 4.3 PCA ........................................................................................................................... 19 4.4 Tasselled cap ............................................................................................................. 19 4.5 Allometric equations ................................................................................................. 19 4.6 Carbon trading ........................................................................................................... 19 5 FINDINGS ....................................................................................................................... 20 5.1 Results and discussions ............................................................................................. 20 5.2 Limitations ................................................................................................................ 27 5.3 Conclusions and recommendations ........................................................................... 27 6 REFERENCES ................................................................................................................ 29 1 INTRODUCTION 1.1 Background Sequestering carbon is seen as one way of slowing down the pace at which global warming is happening. There are many ways of sequestration, using both artificial and natural sinks which stores carbon for a