Combining airborne laser scanning and Landsat data for statistical modeling of soil carbon and tree biomass in Tanzanian Miombo woodlands.

BACKGROUND: Soil carbon and biomass depletion can be used to identify and quantify degraded soils, and by using remote sensing, there is potential to map soil conditions over large areas. Landsat 8 Operational Land Imager satellite data and airborne laser scanning data were evaluated separately and in combination for modeling soil organic carbon, above ground tree biomass and below ground tree biomass. The test site is situated in the Liwale district in southeastern Tanzania and is dominated by Miombo woodlands. Tree data from 15 m radius field-surveyed plots and samples of soil carbon down to a depth of 30 cm were used as reference data for tree biomass and soil carbon estimations. RESULTS: Cross-validated plot level error (RMSE) for predicting soil organic carbon was 28% using only Landsat 8, 26% using laser only, and 23% for the combination of the two. The plot level error for above ground tree biomass was 66% when using only Landsat 8, 50% for laser and 49% for the combination of Landsat 8 and laser data. Results for below ground tree biomass were similar to above ground biomass. Additionally it was found that an early dry season satellite image was preferable for modelling biomass while images from later in the dry season were better for modelling soil carbon. CONCLUSION: The results show that laser data is superior to Landsat 8 when predicting both soil carbon and biomass above and below ground in landscapes dominated by Miombo woodlands. Furthermore, the combination of laser data and Landsat data were marginally better than using laser data only.

Countrywide estimates of forest variables using satellite data and field data from the National Forest Inventory.

About 55% of the land area in Sweden is covered by forest. Presently, there is no uniform and geographically explicit description of the forest cover for Sweden. Independent data sources already existing are satellite data from Landsat TM and SPOT HRV, map masks and forest inventory plots. Together, they provide the possibility of computing estimates of forest variables such as stem volume and stand age. The accuracy for these estimations will be low on the pixel level, but higher on a stand level. This type of raster-based forest data is useful for authorities when planning how timber resources should be utilized or for monitoring purposes. The production line that was developed to create a countrywide database of forest variable estimates in a cost-efficient way is described. Accuracy of forest variable estimates for an area in southwestern Sweden was assessed at stand level. Results showed 33% overall root mean square error for the estimates of total wood volume, and 23% for the age estimates.

Conflict resolution by participatory management: remote sensing and GIS as tools for communicating land-use needs for reindeer herding in northern Sweden.

When seeking to resolve complex land-management issues, geographical assessment of resources that are in short supply or in dispute can aid the communication of knowledge and the understanding among and between different stakeholders. In this paper, we illustrate how remote sensing and GIS can be used to gather and compile information regarding land-use activities and patterns among reindeer herders and other land users (forestry, mining, tourism, etc) in northern Sweden. The project represents a novel user-oriented effort largely based on the work carried out by the principal end user, i.e. the reindeer herders themselves. The basis for development of land-use plans for reindeer husbandry, was the following: to collect and digitally systemize traditional ecological and landscape knowledge of reindeer habitat use; to integrate this information with results from field inventories and satellite-based vegetation classifications; to map activities of other land users. The resulting land-use plans provide information that can facilitate consultation between the reindeer herders and other stakeholders and can facilitate operational work in reindeer management. This project can serve as a model for participatory involvement and planning, bringing indigenous knowledge and advanced remote-sensing techniques together in an interactive process.