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The accurate information of forest cover change is important to measure the amount of carbon release and sink. The newly-available remote sensing based products and method such as Daichi Forest/Non-Forest (FNF), Global Forest Change (GFC) datasets and Semi-automatic Claslite systems offers the benefit to derive these information in a quick and simple manner. We measured the accuracy by constructing area-proportion error matrix from 388 random sample points and assessed the consistency analysis by looking at the spatial pattern of deforestation and regrowth from built-up area, roads, and rivers from 2010 – 2015 in Katingan district, Central Kalimantan. Accuracy assessment showed that those 3 datasets indicate low to medium accuracy level in which the highest accuracy was achieved by Claslite who produced 71 % ± 5 % of overall accuracy. The consistency analysis provides a similar spatial pattern of deforestation and regrowth measured from the road, river, and built-up area though their distance sensitivity are different one to another.

Land use and land cover (LULC) change causes biodiversity decline through loss, alteration, and fragmentation of habitats. There are uncertainties on how LULC will change in the future and the effect of such change on biodiversity. In this paper we applied the Land Change Modeler (LCM) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Scenario Generator tool to develop three spatially explicit LULC future scenarios from 2015 to 2030 in the Pulang Pisau district of Central Kalimantan, Indonesia. The district is experiencing a rapid loss of biodiversity as a result of unprecedented LULC changes. Further, we used the InVEST Habitat Quality model to map habitat quality as a proxy to biodiversity in each of the scenarios. We find habitat quality decline is largest in a scenario where past trends of LULC change continue, followed by a scenario with planned agricultural expansion. Alternately, a conservation-oriented scenario results in significant improvements in habitat quality for biodiversity. This information can support in developing appropriate land use policy for biodiversity conservation in Indonesia.