Good Morning, America! The explosive U.S. awakening to the need for adaptation

Since the early years of the 21st century, and in particular since 2007, the U.S. has been awakening rapidly to the fact that climate change is underway and that even if stringent efforts are undertaken to mitigate greenhouse gas emissions, adaptation to the unavoidable impacts from the existing commitment to climate change is still needed and needs to be begun now. This report provides an historical overview of the public, political, and scientific concern with adaptation in the United States. It begins by briefly distinguishing ongoing, historical adaptation to environmental circumstances from deliberate adaptation to human‐induced climate change. It then describes the shift from the early concerns with climate change and adaptation to the more recent awakening to the need for a comprehensive approach to managing the risks from climate change. Ranging from the treatment of the topic in the news media to the drafting of bills in Congress, to state and local government activities with considerable engagement of NGOs, scientists and consultants, it is apparent that adaptation has finally, and explosively, emerged on the political agenda as a legitimate and needed subject for debate. At the same time, the current policy rush is not underlain by widespread public engagement and mobilization nor does it rest on a solid research foundation. Funding for vulnerability and adaptation research, establishing adequate decision support institutions, as well as the building of the necessary capacity in science, the consulting world, and in government agencies, lags far behind the need. (PDF contains 42 pages)

Linear Chromatic Adaptation Transform Based on Delaunay Triangulation

Computer vision algorithms that use color information require color constant images to operate correctly. Color constancy of the images is usually achieved in two steps: first the illuminant is detected and then image is transformed with the chromatic adaptation transform ( CAT). Existing CAT methods use a single transformation matrix for all the colors of the input image. The method proposed in this paper requires multiple corresponding color pairs between source and target illuminants given by patches of the Macbeth color checker. It uses Delaunay triangulation to divide the color gamut of the input image into small triangles. Each color of the input image is associated with the triangle containing the color point and transformed with a full linear model associated with the triangle. Full linear model is used because diagonal models are known to be inaccurate if channel color matching functions do not have narrow peaks. Objective evaluation showed that the proposed method outperforms existing CAT methods by more than 21%; that is, it performs statistically significantly better than other existing methods.