Tag Archive | Deforestation

Annual Forest Loss – A comparison between global forest loss datasets

The start of this year was marked by the publication of two new global datasets for environmental analysis. My impression is that both of those datasets will be of increasing importance in ecological analysis in the future (even though their value for conservation biology has been actively criticized, see Tropek et al. 2014). Thus there is a need to assess the accuracy of their forest loss detection over time and if they are consistent.

The first dataset is the already famous Global Forest Map published by Hansen et al. (2013) in Science end of last year. The temporal span of their dataset goes back from the year 2000 up to the year 2012 and by using only Landsat data in a temporal time-series analysis they got a pretty decent high-resolution land-cover product. Although the resolution of the Hansen dataset is great (30m global average coming from Landsat) Hansen et al. decided to only publish the year 2000 baseline with the forest cover. They provide us with aggregated loss, gain and loss per year layers though, but nevertheless the user has no option to reproduce a similar product for the year 2012.

The other dataset is the combined published result from a 4 year long monitoring by the japanese satellite ALOS-PALSAR. They decided to release a global forest cover map at a 50m spatial resolution, which in contrast to Hansen can be acquired for the whole time-frame of the ALOS-PALSAR mission. It thus has a temporal coverage of the whole globe from the year 2007 until 2010. The data can be acquired on their homepage after getting an account. The ALOS PALSAR data has a nice temporal span and can be downloaded for multiple years, thus in theory allowing to make temporal comparisons and predictions about future land-use trends. However I am a bit concerned about the accuracy of their classifications as I have found multiple errors already in the area I am working in.

Classification Errors with the ALOS PALSAR dataset. Suddenly there are huge waterbodies in the Savanna near Kilimanjaro

Classification Errors with the ALOS PALSAR dataset. Suddenly there are huge waterbodies (blue) in the Savanna near Kilimanjaro

Because I am interested in using the ALOS PALSAR dataset in my analysis (how often do you get a nice spatial-temporal dataset of forest cover) I made a comparison between the forest loss detected in my area of interest for both datasets. It should be noted that is a comparison between different satellite sensors as well and not only by classification algorithms. So we are not comparing products from the same data source.

So what is the plan for our comparison:

  • We downloaded the whole ALOS PALSAR layers for all years covered of the area around Kilimanjaro in northern Tanzania (N00, E035). We then extracted only the forest cover (Value == 1) and calculate the difference between years to acquire the forest loss for the year 2008,2009 and 2010 respectively.
  • From the Google Engine app we downloaded the “loss per year” dataset and cropped it to our area of interest. Furthermore we are only interested in the aggregated Forest loss in the years 2008, 2009 and 2010 which we have available in the ALOS PALSAR dataset. We furthermore resampled the Hansen dataset up to 50m to match up with the ALOS PALSAR resolution.

The Result:

I haven’t found a fancy way to display this simple comparison, so here comes just the result table. As predicted (if you look at it visually),the ALOS PALSAR algorithm overshots the amount of forest loss a lot.

year 2007-2008 2008-2009 2009-2010
Hansen Forest Loss cells 262 304 529
ALOS PALSAR Forest Loss cells 26995 24970 16297
Equal cells in both 17 30 131


So which one is right? I personally trust Hansens data a lot more. Especially because I found them to be pretty consistent in my area of study. For me the ALOS PALSAR data is not useable yet until the authors have figured out ways to improve their classification. It can be concluded that users should not forget that those Forest Cover products are ultimately just the result of a big un-supervised algorithm who doesn’t discriminate between right and wrong. Without validation and careful consideration of the observer you might end up having wrong results.

Interesting Paper: Current and future nature-based tourism in the Eastern Arc Mountains

Greetings from Moshi, Tanzania, where I am still busy with the fieldwork. Just want to point the dear readers to a new paper, that is currently in Press in “Ecosystem Services”. Titled “The current and future value of nature-based tourism in the Eastern Arc Mountains of Tanzania” the study analyses and gives estimates for the current and future economic value of nature-based tourism in Tanzania. The analysis is based on a dataset including the spatial location of lodgings and visitor estimates and provides predictive outlooks for two different land-use scenarios (no-change, hopeful-future). They conclude that eco-tourism in the Tanzanian EAM (Eastern Arc Mountains) can provide, among other values for ecosystem service, substantial revenue in the future if the management effectiveness of protected areas can be improved.

Bayliss, J., et al., The current and future value of nature-based tourism in the Eastern Arc Mountains
of Tanzania. Ecosystem Services (2014), http://dx.doi.org/10.1016/j.ecoser.2014.02.006i

Sadly they only included the EAM from Tanzania in their study and thus left out the Taita Hills. During my stay in Taita I observed multiple disturbances such as fuelwood extractions and larger loggings in the last forest patches of Taita. Having multiple endemic bird (Taita Thrush, Taita Apalis, …) and plant species (eg. Saintpaulia teitensis) the forests of the Taita hills surely can be considered a part of the renown EAM Biodiversity hotspot. But due to the high population density at Taita there should be more economic opportunities and initiatives, such as the Taita-Taveta Wildlife Forum has been promoting, to increase the support of both local people and government to protect these last forest patches and ensure future connectivity.


Fuelwood collection. Photographed near Ngangao Forest

Fuelwood collection. Photographed near Ngangao Forest

Recent loggings within parts of Vuria Forest.

Recent loggings within parts of Vuria Forest.

Anyway, lets hope that this study can back up some arguments in the science-policy dialog with decision makers in Tanzania and abroad.

BIOFRAG – Biodiversity responses to Forest Fragmentation

Another interesting project closely related to PREDICTS is the BIOFRAG Project, which tries to construct a global database of research papers dealing with Forest Fragmentation and its impacts on Biodiversity taxa. One final goal of the BIOFRAG project is the development of a new fragmentation index using watersheds delineation algorithm and fragment descriptors in order to characterize Fragment traits. I am very interested in seeing the final outcome of this approach and maybe I even find the time to implement their algorithm in LecoS for QGIS as soon as it is released. Their database paper, lead authored by Marion Pfeifer, was just released to the public as open-access paper. You can read it in full here.

Pfeifer et al. (2014) BIOFRAG – a new database for analyzing BIOdiversity responses to forest FRAGmentation. Ecology and Evolution. doi: 10.1002/ece3.1036

If you consider of contributing data then more information can be found on the BIOFRAG blog and all researchers involved with forest fragmentation research should consider contributing to them and also to PREDICTS   (see here) if you haven’t already done so. And as usual: If you were studying in Africa, then please get in touch with me! I will contact you as soon as I return from my Fieldwork in Kenya and Tanzania at the end of May.

Global Forest Change data now available for Download

The previously reported Global Forest data from Hansen et al. (2013) is now finally up for download.

Access the data here, but beware of the size of the individual granules as they easily be some gigabytes. The time for some awesome analysis and probably a bunch of papers has come…


Interesting Paper and Data: Global Forest Loss (Hansen et al. 2013)

Just some moments ago (on the 15th of November 2013, so not yet in Europe 😀 ) a new very interesting paper came out in Science presenting a new High-resolution dataset of global forest loss in the last decade. It is written by the authors of already existing widely used datasets, such as GLCF and CARPE, in corporation with Google.

Hansen et al. (2013), High-Resolution Global Maps of 21st-Century Forest Cover Change

“In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year.”

Not surprisingly only the tropical rain-forest was found to posses a negative trend in the last decade. Most likely because of shifting agriculture, clash-and-burn practices and large scale deforestations due to monoculture cultivation of Palmoil, Soy and Jatropha. Quite impressively they used over  654,178 Landsat images in a time-series analysis to in characterize forest extent and change in the time from 2000 to 2012. Google apparently helped out with the computation (cloud-computing). And the best thing is: You can view the data

Google Viewer of Hansens et al. 2013 forest loss dataset

Google Viewer of Hansens et al. 2013 forest loss dataset

online via Google.

Online view of Global Forest Change

At the bottom you can find a Data download link, which makes the whole thing very interesting for follow-up research! Check it out!

EDIT: Apparently download is not yet available for the public. Will keep you updated!

Palmoil in Cameroon

This blog is also about Conservation projects and campaigns and i always wanted to write a little post about the campaign i am involved in since the very start.

Location of the SGSOC Plantation in Africa

As part of the SAVE Wildlife Conservation Fund i engage myself against a huge palmoil-plantation in south west Cameroon. A big American concern tries to establish a 70.000 hectare big plantation right in the middle of several world-famous national parks such as the Korup National Park.

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