Fire models and methods to map fuel types: The role of remote sensing.

Understanding fire is essential to improving forest management strategies. More specifically, an accurate knowledge of the spatial distribution of fuels is critical when analyzing, modelling and predicting fire behaviour. First, we review the main concepts and terminology associated with forest fuels and a number of fuel type classifications. Second, we summarize the main techniques employed to map fuel types starting with the most traditional approaches, such as field work, aerial photo interpretation or ecological modelling. We pay special attention to more contemporary techniques, which involve the use of remote sensing systems. In general, remote sensing systems are low-priced, can be regularly updated and are less time-consuming than traditional methods, but they are still facing important limitations. Recent work has shown that the integration of different sources of information andmethods in a complementary way helps to overcome most of these limitations. Further research is encouraged to develop novel and enhanced remote sensing techniques

The European Space Agency BIOMASS mission: Measuring forest above-ground biomass from space

The primary objective of the European Space Agency's 7th Earth Explorer mission, BIOMASS, is to determine the worldwide distribution of forest above-ground biomass (AGB) in order to reduce the major uncertainties in calculations of carbon stocks and fluxes associated with the terrestrial biosphere, including carbon fluxes associated with Land Use Change, forest degradation and forest regrowth. To meet this objective it will carry, for the first time in space, a fully polarimetric P-band synthetic aperture radar (SAR). Three main products will be provided: global maps of both AGB and forest height, with a spatial resolution of 200 m, and maps of severe forest disturbance at 50 m resolution (where “global” is to be understood as subject to Space Object tracking radar restrictions). After launch in 2022, there will be a 3-month commissioning phase, followed by a 14-month phase during which there will be global coverage by SAR tomography. In the succeeding interferometric phase, global polarimetric interferometry Pol-InSAR coverage will be achieved every 7 months up to the end of the 5-year mission. Both Pol-InSAR and TomoSAR will be used to eliminate scattering from the ground (both direct and double bounce backscatter) in forests. In dense tropical forests AGB can then be estimated from the remaining volume scattering using non-linear inversion of a backscattering model. Airborne campaigns in the tropics also indicate that AGB is highly correlated with the backscatter from around 30 m above the ground, as measured by tomography. In contrast, double bounce scattering appears to carry important information about the AGB of boreal forests, so ground cancellation may not be appropriate and the best approach for such forests remains to be finalized. Several methods to exploit these new data in carbon cycle calculations have already been demonstrated. In addition, major mutual gains will be made by combining BIOMASS data with data from other missions that will measure forest biomass, structure, height and change, including the NASA Global Ecosystem Dynamics Investigation lidar deployed on the International Space Station after its launch in December 2018, and the NASA-ISRO NISAR L- and S-band SAR, due for launch in 2022. More generally, space-based measurements of biomass are a core component of a carbon cycle observation and modelling strategy developed by the Group on Earth Observations. Secondary objectives of the mission include imaging of sub-surface geological structures in arid environments, generation of a true Digital Terrain Model without biases caused by forest cover, and measurement of glacier and icesheet velocities. In addition, the operations needed for ionospheric correction of the data will allow very sensitive estimates of ionospheric Total Electron Content and its changes along the dawn-dusk orbit of the mission

Understanding ‘saturation’ of radar signals over forests

There is an urgent need to quantify anthropogenic influence on forest carbon stocks. Using satellite-based radar imagery for such purposes has been challenged by the apparent loss of signal sensitivity to changes in forest aboveground volume (AGV) above a certain ‘saturation’ point. The causes of saturation are debated and often inadequately addressed, posing a major limitation to mapping AGV with the latest radar satellites. Using ground- and lidar-measurements across La Rioja province (Spain) and Denmark, we investigate how various properties of forest structure (average stem height, size and number density; proportion of canopy and understory cover) simultaneously influence radar backscatter. It is found that increases in backscatter due to changes in some properties (e.g. increasing stem sizes) are often compensated by equal magnitude decreases caused by other properties (e.g. decreasing stem numbers and increasing heights), contributing to the apparent saturation of the AGV-backscatter trend. Thus, knowledge of the impact of management practices and disturbances on forest structure may allow the use of radar imagery for forest biomass estimates beyond commonly reported saturation points

Radar Remote Sensing of Forests Using CARABAS and ERS

Forests cover more than 30% of the Earth\u27s land surface, and represent an important resource. In order to manage this resource effectively, accurate and up-to-date information is required on the extent and state of the forests. Radar remote sensing offers the possibility of providing some of this information. This thesis studies the potential of two SAR (synthetic aperture radar) systems for measuring forest stem volume. Case studies, of Scandinavian coniferous forests, have been used to develop models, which can be used to help interpret the results, to improve parameter retrieval accuracy, and to make predictions about the capabilities of the techniques. Firstly, repeat-pass interferometry with the ERS (European Remote Sensing) satellite has been investigated. The coherence measurements presented show the potential for estimating stem volume. Unfortunately, the accuracy of stem volume retrieval is unreliable, depending on weather conditions. In the best cases, standwise estimates of stem volume show accuracies similar to those obtained with ground-based methods. The use of coherence for detecting disturbance of the forest (clear-cutting) is also investigated, showing the possibility of using repeat-pass satellite interferometry for monitoring changes in forest cover. CARABAS is a very low frequency (VHF-band), high-resolution, airborne SAR system. Using long wavelengths (3-15 m), CARABAS penetrates forest canopies, and measures backscattering from the tree trunks. The theories and observations presented indicate that the scattering strength is directly related to stem volume, and that stem volume retrieval with CARABAS has potentially high accuracy. In particular, CARABAS is suited for dense forests, where other remote sensing techniques fail. The backscatter is very sensitive to terrain slopes; which must be corrected for when estimating stem volume. A model has been developed for this purpose, indicating the feasibility of compensating for the effects of slopes

Radar Remote Sensing of Forests Using CARABAS and ERS

Forests cover more than 30% of the Earth's land surface, and represent an important resource. In order to manage this resource effectively, accurate and up-to-date information is required on the extent and state of the forests. <p />Radar remote sensing offers the possibility of providing some of this information. This thesis studies the potential of two SAR (synthetic aperture radar) systems for measuring forest stem volume. Case studies, of Scandinavian coniferous forests, have been used to develop models, which can be used to help interpret the results, to improve parameter retrieval accuracy, and to make predictions about the capabilities of the techniques. <p />Firstly, repeat-pass interferometry with the ERS (European Remote Sensing) satellite has been investigated. The coherence measurements presented show the potential for estimating stem volume. Unfortunately, the accuracy of stem volume retrieval is unreliable, depending on weather conditions. In the best cases, standwise estimates of stem volume show accuracies similar to those obtained with ground-based methods. The use of coherence for detecting disturbance of the forest (clear-cutting) is also investigated, showing the possibility of using repeat-pass satellite interferometry for monitoring changes in forest cover. <p />CARABAS is a very low frequency (VHF-band), high-resolution, airborne SAR system. Using long wavelengths (3-15 m), CARABAS penetrates forest canopies, and measures backscattering from the tree trunks. The theories and observations presented indicate that the scattering strength is directly related to stem volume, and that stem volume retrieval with CARABAS has potentially high accuracy. In particular, CARABAS is suited for dense forests, where other remote sensing techniques fail. The backscatter is very sensitive to terrain slopes; which must be corrected for when estimating stem volume. A model has been developed for this purpose, indicating the feasibility of compensating for the effects of slopes