Multiband Imaging CMOS Image Sensor with Multi-Storied Photodiode Structure †

We developed a multiband imaging CMOS image sensor (CIS) with a multi-storied photodiode structure, which comprises two photodiode (PD) arrays that capture two different images, visible red, green, and blue (RGB) and near infrared (NIR) images at the same time. The sensor enables us to capture a wide variety of multiband images which is not limited to conventional visible RGB images taken with a Bayer filter or to invisible NIR images. Its wiring layers between two PD arrays can have an optically optimized effect by modifying its material and thickness on the bottom PD array. The incident light angle on the bottom PD depends on the thickness and structure of the wiring and bonding layer, and the structure can act as an optical filter. Its wide-range sensitivity and optimized optical filtering structure enable us to create the images of specific bands of light waves in addition to visible RGB images without designated pixels for IR among same pixel arrays without additional optical components. Our sensor will push the envelope of capturing a wide variety of multiband images

Spatial Simulation Modelling of Future Forest Cover Change Scenarios in Luangprabang Province, Lao PDR

Taking Luangprabang province in Lao Peoples’s Democratic Republic (PDR) as an example, we simulated future forest cover changes under the business-as-usual (BAU), pessimistic and optimistic scenarios based on the Markov-cellular automata (MCA) model. We computed transition probabilities from satellite-derived forest cover maps (1993 and 2000) using the Markov chains, while the “weights of evidence” technique was used to generate transition potential maps. The initial forest cover map (1993), the transition potential maps and the 1993–2000 transition probabilities were used to calibrate the model. Forest cover simulations were then performed from 1993 to 2007 at an annual time-step. The simulated forest cover map for 2007 was compared to the observed (actual) forest cover map for 2007 in order to test the accuracy of the model. Following the successful calibration and validation, future forest cover changes were simulated up to 2014 under different scenarios. The MCA simulations under the BAU and pessimistic scenarios projected that current forest areas would decrease, whereas unstocked forest areas would increase in the future. Conversely, the optimistic scenario projected that current forest areas would increase in the future if strict forestry laws enforcing conservation in protected forest areas are implemented. The three simulation scenarios provide a very good case study for simulating future forest cover changes at the subnational level (Luangprabang province). Thus, the future simulated forest cover changes can possibly be used as a guideline to set reference scenarios as well as undertake REDD/REDD+ preparedness activities within the study area