Jane Whitcomb

Mapping vegetated wetlands of Alaska using L-band radar satellite imagery.

Wetlands act as major sinks and sources of important atmospheric greenhouse gases and can switch between atmospheric sink and source in response to climatic and anthropogenic forces in ways that are poorly understood. Despite their importance in the carbon cycle, the locations, types, and extents of northern wetlands are not accurately known. We have used two seasons of L-band synthetic aperture radar (SAR) imagery to produce a thematic map of wetlands throughout Alaska. The classification is developed using the Random Forests decision tree algorithm with training and testing data compiled from the National Wetlands Inventory (NWI) and the Alaska Geospatial Data Clearinghouse (AGDC). Mosaics of summer and winter Japanese Earth Resources Satellite 1 (JERS-1) SAR imagery were employed together with other inputs and ancillary datasets, including the SAR backscatter texture map, slope and elevation maps from a digital elevation model (DEM), an open-water map, a map of proximity to water, data collection dates, and geographic latitude. The accuracy of the resulting thematic map was quantified using extensive ground reference data. This approach distinguished as many as nine different wetlands classes, which were aggregated into four vegetated wetland classes. The per-class average error rate for aggregate wetlands classes ranged between 5.0% and 30.5%, and the total aggregate accuracy calculated based on all classified pixels was 89.5%. As the first high-resolution large-scale synoptic wetlands map of Alaska, this product provides an initial basis for improved characterization of land-atmosphere CH4 and CO2 fluxes and climate change impacts associated with thawing soils and changes in extent and drying of wetland ecosystems.

Evaluation of ALOS PALSAR Data for High-Resolution Mapping of Vegetated Wetlands in Alaska

As the largest natural source of methane, wetlands play an important role in the carbon cycle. High-resolution maps of wetland type and extent are required to quantify wetland responses to climate change. Mapping northern wetlands is particularly important because of a disproportionate increase in temperatures at higher latitudes. Synthetic aperture radar data from a spaceborne platform can be used to map wetland types and dynamics over large areas. Following from earlier work by Whitcomb et al. (2009) using Japanese Earth Resources Satellite (JERS-1) data, we applied the “random forests” classification algorithm to variables from L-band ALOS PALSAR data for 2007, topographic data (e.g., slope, elevation) and locational information (latitude, longitude) to derive a map of vegetated wetlands in Alaska, with a spatial resolution of 50 m. We used the National Wetlands Inventory and National Land Cover Database (for upland areas) to select training and validation data and further validated classification results with an independent dataset that we created. A number of improvements were made to the method of Whitcomb et al. (2009): (1) more consistent training data in upland areas; (2) better distribution of training data across all classes by taking a stratified random sample of all available training pixels; and (3) a more efficient implementation, which allowed classification of the entire state as a single entity (rather than in separate tiles), which eliminated discontinuities at tile boundaries. The overall accuracy for discriminating wetland from upland was 95%, and the accuracy at the level of wetland classes was 85%. The total area of wetlands mapped was 0.59 million km2, or 36% of the total land area of the state of Alaska. The map will be made available to download from NASA’s wetland monitoring website.

Wetlands map of Alaska using L-Band radar satellite imagery

We have used two seasons of L-band SAR imagery to produce a thematic map of wetlands throughout Alaska. The classification was developed using the Random Forests statistical decision tree algorithm. Input data included mosaics of summer and winter JERS-1 SAR imagery with associated image collection dates, summer and winter SAR backscatter texture, elevation, slope, proximity to water, and geographic latitude. The accuracy of the resulting thematic map was quantified using extensive ground reference data. The overall aggregate accuracy calculated based on all classified pixels was 89.5%, with individual per-tile aggregate accuracies ranging from 80% to 97%. As the first high-resolution large-scale synoptic wetlands map of Alaska, this product provides the basis for improved characterization of land- atmosphere CH4 and CO2 fluxes and climate change impacts associated with thawing soils and changes in extent and drying of wetland ecosystems.

Decadal change in northern wetlands based on differential analysis of JERS and PALSAR data

We have been developing a continental-scale map of the North American boreal wetlands based on L-Band SAR imagery collected in 1997–1998 by the Japanese Earth Resources Satellite (JERS) [1]. The map currently covers the entire state of Alaska, identifying up to nine wetlands classes and two uplands classes. We have also recently obtained and classified a region of L-Band SAR imagery collected in 2007 by the Advanced Land Observing Satellite (ALOS) Phased Array L-Band SAR (PALSAR). Herein, we compare the results of the PALSAR classification to those of the JERS classification in order to detect changes in wetlands type or extent during the decade-long interval between the two sets of SAR imagery.

Mapping Canadian wetlands using L-band radar satellite imagery S

Previously, we have developed a robust algorithm for mapping boreal wetlands using L-band satellite radar imagery, and in particular have used the method to produce a complete vegetated wetlands map of Alaska using the JERS radar data. In this work, we apply this algorithm to produce a static map of Canadian wetlands from the 1997–98 era JERS radar data at 100-m resolution, to be followed in the future by 2007-era ALOS/PALSAR maps.

Soil Moisture Profiles and Temperature Data from SoilSCAPE Sites, USA

This data set contains in-situ soil moisture profile and soil temperature data collected at 20-minute intervals at SoilSCAPE (Soil moisture Sensing Controller and oPtimal Estimator) project sites in four states (California, Arizona, Oklahoma, and Michigan) in the United States. SoilSCAPE used wireless sensor technology to acquire high temporal resolution soil moisture and temperature data at up to 12 sites over varying durations since August 2011. At its maximum, the network consisted of over 200 wireless sensor installations (nodes), with a range of 6 to 27 nodes per site. The soil moisture sensors (EC-5 and 5-TM from Decagon Devices) were installed at three to four depths, nominally at 5, 20, and 50 cm below the surface. Soil conditions (e.g., hard soil or rocks) may have limited sensor placement. Temperature sensors were installed at 5 cm depth at six of the sites. Data collection started in August 2011 and continues at eight sites through late 2016. The data enables estimation of local-scale soil moisture at high temporal resolution and validation of remote sensing estimates of soil moisture at regional (airborne, e.g. NASAs Airborne Microwave Observation of Subcanopy and Subsurface Mission - AirMOSS) and national (spaceborne, e.g. NASAs Soil Moisture Active Passive - SMAP) scales.

Mapping and change detection for boreal wetlands of North America based on JERS and PALSAR data

We have been developing high-resolution thematic maps of wetlands throughout the North American boreal regions. We assemble a wetlands map for each region based on data collected during the late 1990s, then construct a second map based on data collected during the late 2000s. Comparison of the two maps then makes it possible to assess changes that have occurred over the course of the intervening decade..

Method for upscaling in-situ soil moisture measurements for calibration and validation of smap soil moisture products

In order to provide a reliable source of ground-based validation data for the SMAP mission at spatial scales of 3 km, 9 km and 36 km, we have developed a new regression-based method capable of yielding highly-accurate upscaled soil moisture estimates based on sparse, irregularly-spaced soil moisture measurements.

Decadal changes in the type and extent of Wetlands in Alaska using L-band SAR data — A preliminary analysis

Northern peatlands are estimated to hold about 30 % of the total global pool of soil carbon or 13 % of the total terrestrial carbon in the biosphere [1]. The warmer, drier conditions being experienced throughout the Arctic appear to be accelerating both aerobic and anaerobic decomposition of northern peatland soils, thereby increasing emissions of methane (CH4) and carbon dioxide (CO2) [2]. If continued, this trend could cause northern peatlands to become major sources of atmospheric carbon, with existing models predicting large increases in CH4 emissions as CO2 levels continue to rise [3]. To better understand sources, sinks, and net fluxes of atmospheric CO2 and CH4 validated high-resolution maps of the extent and distribution of northern wetlands are needed [4].