TOWARD A MULTI-SOURCE REMOTE SENSING WETLAND INVENTORY OF THE USA: PRELIMINARY RESULTS ON WETLAND INVENTORY OF MINNESOTA

Wetlands are highly productive ecosystems that offer unique services on regional and global scales including nutrient assimilation, carbon reduction, geochemical cycling, and water storage. In recent years, however, they are being lost or exploited as croplands due to natural or man-made stressors (1.4 percent in 5 years within the USA). This decline in the extent of wetlands began legislative activity at a national scale that mandate the regulate use of wetlands. As such, the need for cost-effective, robust, and semi-automated techniques for wetland preservation is ever-increasing in the current era. In this study, we developed a workflow for wetland inventorying on a state-wide scale using optimal incorporation of dual-polarimetry Sentinel-1, multi-spectral Sentinel-2 and dual polarimetry ALOS-PALSAR with the Random Forest (RF) classifier in Google Earth Engine (GEE). A total of 45 features from a stack of multi-season/multi-year SAR and Optical imagery (included more than 5000 imagery) was extracted over Minnesota state, USA. We followed the Cowardin classification scheme for clustering the field data. The classification was performed in two levels in 5 different ecozones that cover the Minnesota state. Depending on the availability field data for each ecozone overall accuracies changed from 77% to 85%. The variable importance analysis suggests that Sentinel-2 spectral features are dominant in terms of their capability for wetland delineation. Sentinel-1 backscattering coefficient was also superior among other SAR features. Ultimately, the results of this study shall illustrate the applicability of free of charge earth observation data coupled with the advanced machine learning techniques that are available in GEE for better restoration and management of wetlands.

Quantifying Costs of Urbanisation: Wetland Loss and Impacts in a Rapidly Developing Global City

As cities grow, natural ecosystems decline through conversion to urban environments. Cities are often viewed as biodiversity wastelands, but they can be hotspots of global biodiversity. Urban biodiversity emphasises two fundamentals. First, people living in cities enjoy wildlife and second, there is virtually no planning for species that co-inhabit our cities. If urban biodiversity was a significant part of planning, then we would be far better at integrating green infrastructure into expanding urban environments.Wetlands are among the most important and productive ecosystems in the world. They are the main suppliers of fresh water for human use and provide habitat to critical fauna and flora. In urban areas they are a vital link to nature and social cohesion. Currently, there is an absence of wetland inventory quantifying loss and changes overtime. Hence the broad impacts of urbanisation on wetland loss are difficult to assess.We explored wetland loss and created a wetland inventory for Western Sydney, Australia, one of the world’s fastest growing urban regions. We used satellite imagery to determine wetland number and type, and calculated changes in wetland surface area from 2010-2017. Broad changes to land use were also quantified. We developed species distribution models of a common urban wetland turtle (Chelodina longicollis) that people interact with regularly or have as pets. Chelodina longicollis utilises both aquatic and terrestrial environments, and we determined if changes in distribution were associated with changes in the wetland inventory and urbanisation.Most local government areas (LGA) experienced a decrease in wetland surface area from 2010-2017, ranging from -1% (Cumberland) to -21% (Blacktown). Majority of LGAs experienced a decrease in wetland density, with wetland densities declining by 25% (Blacktown). All LGAs experienced an increase in urban land use, ranging from 3-12%, which was associated with high rates of wetland loss.Changes in turtle distribution over the decade reflects a southern distribution shift away from where wetland losses were concentrated. We estimated that ∼40,000 individual turtles were displaced or killed due to wetland loss and urbanisation.Urbanisation was the leading cause of wetland loss and degradation in Western Sydney between 2010 and 2017. Wetlands provide critical green infrastructure and significant green space for social cohesion in urban areas. Integration of current wetlands, or the creation of functional wetlands, is key for sustainable development of urban landscapes. Urban wetlands (natural and constructed) may provide “biodiversity arks” for endangered species and facilitate community led conservation programs.

Isolating Anthropogenic Wetland Loss by Concurrently Tracking Inundation and Land Cover Disturbance across the Mid-Atlantic Region, U.S.

Global trends in wetland degradation and loss have created an urgency to monitor wetland extent, as well as track the distribution and causes of wetland loss. Satellite imagery can be used to monitor wetlands over time, but few efforts have attempted to distinguish anthropogenic wetland loss from climate-driven variability in wetland extent. We present an approach to concurrently track land cover disturbance and inundation extent across the Mid-Atlantic region, United States, using the Landsat archive in Google Earth Engine. Disturbance was identified as a change in greenness, using a harmonic linear regression approach, or as a change in growing season brightness. Inundation extent was mapped using a modified version of the U.S. Geological Survey’s Dynamic Surface Water Extent (DSWE) algorithm. Annual (2015–2018) disturbance averaged 0.32% (1095 km2 year-1) of the study area per year and was most common in forested areas. While inundation extent showed substantial interannual variability, the co-occurrence of disturbance and declines in inundation extent represented a minority of both change types, totaling 109 km2 over the four-year period, and 186 km2, using the National Wetland Inventory dataset in place of the Landsat-derived inundation extent. When the annual products were evaluated with permitted wetland and stream fill points, 95% of the fill points were detected, with most found by the disturbance product (89%) and fewer found by the inundation decline product (25%). The results suggest that mapping inundation alone is unlikely to be adequate to find and track anthropogenic wetland loss. Alternatively, remotely tracking both disturbance and inundation can potentially focus efforts to protect, manage, and restore wetlands.

Remote Sensing of Boreal Wetlands 1: Data Use for Policy and Management

Wetlands have and continue to undergo rapid environmental and anthropogenic modification and change to their extent, condition, and therefore, ecosystem services. In this first part of a two-part review, we provide decision-makers with an overview on the use of remote sensing technologies for the ‘wise use of wetlands’, following Ramsar Convention protocols. The objectives of this review are to provide: (1) a synthesis of the history of remote sensing of wetlands, (2) a feasibility study to quantify the accuracy of remotely sensed data products when compared with field data based on 286 comparisons found in the literature from 209 articles, (3) recommendations for best approaches based on case studies, and (4) a decision tree to assist users and policymakers at numerous governmental levels and industrial agencies to identify optimal remote sensing approaches based on needs, feasibility, and cost. We argue that in order for remote sensing approaches to be adopted by wetland scientists, land-use managers, and policymakers, there is a need for greater understanding of the use of remote sensing for wetland inventory, condition, and underlying processes at scales relevant for management and policy decisions. The literature review focuses on boreal wetlands primarily from a Canadian perspective, but the results are broadly applicable to policymakers and wetland scientists globally, providing knowledge on how to best incorporate remotely sensed data into their monitoring and measurement procedures. This is the first review quantifying the accuracy and feasibility of remotely sensed data and data combinations needed for monitoring and assessment. These include, baseline classification for wetland inventory, monitoring through time, and prediction of ecosystem processes from individual wetlands to a national scale.

Extracting Impervious Surface from Aerial Imagery Using Semi-Automatic Sampling and Spectral Stability

The quantification of impervious surface through remote sensing provides critical information for urban planning and environmental management. The acquisition of quality reference data and the selection of effective predictor variables are two factors that contribute to the low accuracies of impervious surface in urban remote sensing. A hybrid method was developed to improve the extraction of impervious surface from high-resolution aerial imagery. This method integrates ancillary datasets from OpenStreetMap, National Wetland Inventory, and National Cropland Data to generate training and validation samples in a semi-automatic manner, significantly reducing the effort of visual interpretation and manual labeling. Satellite-derived surface reflectance stability is incorporated to improve the separation of impervious surface from other land cover classes. This method was applied to 1-m National Agriculture Imagery Program (NAIP) imagery of three sites with different levels of land development and data availability. Results indicate improved extractions of impervious surface with user’s accuracies ranging from 69% to 90% and producer’s accuracies from 88% to 95%. The results were compared to the 30-m percent impervious surface data of the National Land Cover Database, demonstrating the potential of this method to validate and complement satellite-derived medium-resolution datasets of urban land cover and land use.