The fate of private lands is widely seen as key to the fate of biodiversity in much of the world. Organizations that work to protect biodiversity on private lands often hope that conservation actions on one piece of land will leverage the actions of surrounding landowners. Few researchers have, however, examined whether protected lands do in fact encourage land conservation nearby or how protected lands affect development in the surrounding landscape. Using spatiotemporal data sets on land cover and land protection for three sites (western North Carolina, central Massachusetts, and central Arizona), we examined whether the existence of a protected area correlates with an increased rate of nearby land conservation or a decreased rate of nearby land development. At all sites, newly protected conservation areas tended to cluster close to preexisting protected areas. This may imply that the geography of contemporary conservation actions is influenced by past decisions on land protection, often made for reasons far removed from concerns about biodiversity. On the other hand, we found no evidence that proximity to protected areas correlates with a reduced rate of nearby land development. Indeed, on two of our three sites the development rate was significantly greater in regions with more protected land. This suggests that each conservation action should be justified and valued largely for what is protected on the targeted land, without much hope of broader conservation leverage effects.

ABSTRACT:Availability of multispectral remote sensing data cheaply and its higher spectral resolution compared to remote sensing data with higher spatial resolution has proved valuable for geological mapping exploitation and mineral mapping. This has benefited applications such as landslide quantification, fault pattern mapping, rock and lineament mapping especially with advanced remote sensing techniques and the use of short wave infrared bands. While Landsat and Aster data have been used to map geology in arid areas and band ratios suiting the application established, mapping in geology in highland regions has been challenging due to vegetation land cover. The aim of this study was to map geology and investigate bands suited for geological applications in a study area containing semi arid and highland characteristics. Therefore, Landsat 7 (ETM+, 2000) and Landsat 8 (OLI, 2014) were compared in determining suitable bands suited for geological mapping in the study area. The methodology consist performing principal component and factor loading analysis, IHS transformation and decorrelation stretch of the FCC with the highest contrast, band rationing and examining FCC with highest contrast, and then performing knowledge base classification. PCA factor loading analysis with emphasis on geological information showed band combination (5, 7, 3) for Landsat 7 and (6, 7, 4) for Landsat 8 had the highest contrast and more contrast was enhanced by performing decorrelation stretch. Band ratio combination (3/2, 5/1, 7/3) for Landsat 7 and (4/3, 6/2, 7/4) for Landsat 8 had more contrast on geologic information and formed the input data in knowledge base classification. Lineament visualisazion was achieved by performing IHS transformation of FCC with highest contrast and its saturation band combined as follows: Landsat 7 (IC1, PC2, saturation band), Landsat 8 (IC1, PC4, saturation band). The results were compared against existing geology maps and were superior and could be used to update the existing maps.* Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.

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This study describes the development of a semi-automatic object-based image analysis approach for the detection and quantification of deforestation in Zalingei, Darfur, in consequence of the increasing concentration of refugees or internally displaced persons (IDPs) in the region. The classification workflow is based on a multi-scale approach, ranging from the analysis of high resolution SPOT-4 to very high resolution IKONOS and QuickBird satellite imagery between 2003 and 2008. The overall accuracy rates for the classification of the SPOT 4 data ranged from 92% up to 95%, while those for the QuickBird and IKONOS classification have shown values of 88 and 87%, respectively. The resulting trends in woody vegetation cover were compared with the development of the local population and the variability of precipitation. The results show that the strong increase in human population in the Zalingei IDP camps can be associated with considerable decrease in woody vegetation in the camp vicinity.

ABSTRACT:The OSM project provides a geodata basis for the entire world under the CC-SA licence agreement. But some parts of the world are mapped more densely compared to other regions. However, many less developed countries show a lack of valid geo-information. Africa for example is a sparsely mapped continent. During a huge Ebola outbreak in 2014 the lack of data became apparent. Help organization like the American Red Cross and the Humanitarian Openstreetmap Team organized mappings campaign to fill the gaps with valid OSM geodata. This paper gives a short introduction into this mapping activity.