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9 - Forestrygeneration methods result in different studies not being comparable. Thishappens, for example, when studies use different definitions of whatconstitutes a forest or work with different base maps. Lack of backgroundknowledge on the analyst’s part often leads to misinterpretations of naturalphenomena. For example, the impacts of the seasonal monsoon climate onthe appearance of different vegetation types on remotely sensed images areoften completely neglected in studies performed by researchers with littlelocal or forestry-related experience. This may result in grossly biasedestimations of forest cover figures. Lack of funds or time results in the use ofinappropriate data generation methods, with speedy delivery of products ofwhatever quality being given priority over accuracy and reliability. Outsideinterference with study methods and results sometimes involves the deliberatealteration of forest cover figures to make them suit a particular agenda. Datagenerated by national institutions may be subject to this type of bias. In thedilemma of public goods, all those who would benefit from the provision ofsuch goods find it costly to contribute and would prefer others to pay for thegoods instead. This is certainly the case with data on forest cover: due to thehigh cost of their generation, many organisations resort to recycling of existing– and often outdated – data instead of investing in the generation of newdata. It is obvious that in such a situation, accuracy and reliability suffer.Unreliable figures, whatever their cause, are likely to result in poor decisionmaking.Setting political as well as geographical priorities is difficult withoutreliable information about the location and magnitude of deforestationproblems. In fact, the MRC’s Forest and Land Cover Data Set is so far theonly source of reliable information at the basin-wide level, which has beengenerated with an appropriate methodology, d and has been subject toindependent accuracy testing. 38However, even this data set is already out of date. It was last updated in1997, so there is no reliable information about the deforestation that hasoccurred since then. Given the importance of forests for the health of theLMB, an update is urgently required if access to reliable information aboutthe status and trends of the LMB’s forests is deemed important for makingappropriate decisions. Past experience has shown that such an update willcome at a cost. e One possible solution to make monitoring of deforestationeasier and less expensive could be the application of statistically-soundsampling procedures instead of traditional mapping approaches, which wouldmap the whole basin.aassuming all clouds and their shadows in the GIS data set conceal forest, without this assumption23.5 %bassuming all clouds and their shadows in the GIS data set conceal forest, without this assumption40.9 %ccalculated from Forest map on http://www.fao.org/forestry/fo/country index.jsp?lang_id=1&geo_id=39dInterdependent interpretation of satellite image time series, see Forest Cover Monitoring ProjectMRC/GTZ. 1998 [1].eThe Forest Cover Monitoring Project, which created the MRC’s Forest and Land Cover Data Set,had a budget of $ 3.2 million over 6 years.195