|
Forest ecosystem is the main component of the terrestrial biosphere, and the estimation of forest biomass is a necessary condition for the analysis of carbon cycle and regional carbon budget in land ecosystem. As an active detection method, space borne Lidar can directly obtain the information of vertical structure of vegetation, and its retrieval of forest biomass has obvious advantages compared with optical and microwave remote sensing methods. The Lidar obtains the forest three-dimensional structure through the discrete radiation of the echo data in the spot, and then collectively invert the amount of the forest biomass and its spatial distribution pattern through a number of discrete sampling data in a certain region. Obviously, the density of Lidar discrete sampling points is an important factor that determines the fine degree of forest biomass and its spatial distribution pattern. The first generation vegetation measurement Lidar uses linear detection system, which has a large power consumption, limited power supply capacity, and volume and heat dissipation of the satellite platform. The density of the observation point is low, usually 1 to 2 points per square kilometer, which leads to the poor mapping ability of the regional forest biomass. In order to solve the low density of observation points and improve the mapping ability of Lidar in the region of forest biomass, this paper proposes a kind of second generation of vegetation Lidar based on few-photon mode. The application background, the principle of small photon detection and the composition of the system is discussed. The demand for the energy of the laser emission pulse is lower than that of the linear system. Under the condition of the same resource on the satellite, the density of the sampling point is higher than that of the linear system. Therefore, the second generation vegetation Lidar can better depict the number and spatial distribution pattern of regional forest biomass.
|
