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Highlights • Experts largely disagree on visually interpreted shadows. • A risk-based shadow detection method is presented. • Difference in shadow detected automatically and by the experts is within expectations. Abstract Land cover identification and area quantification are key aspects in determining support payments to farmers under the European Common Agricultural Policy. Agricultural land is monitored using the Land Parcel Identification System and visual image interpretation. However, shadows covering reference parcel boundaries can hinder effective delineation. Visual interpretation of shadows is labor intensive and subjective, while automated methods give reproducible results. In this paper we compare shadow detection on satellite imagery obtained by expert photointerpretation to a proposed automated, data-driven method. The latter automated method is a thresholding approach employing both panchromatic and multispectral imagery, where the former has a finer spatial resolution than the latter. Thresholds are determined from automatically generated training data using a risk-based approach. Comparison of the total shadow area per scene showed that more pixels were labelled as shadow by the automatic procedure than by visual interpretation. However, the union of shadow area independently identified by twelve experts on a subscene was larger than the automatically determined shadow area. The limited intersection of the shadow areas identified by the experts demonstrated that experts strongly disagreed in their interpretations. The shadow area labelled by the automated method was in between the intersection and the union of the areas interpreted by experts. Furthermore, the automated shadow detection method is reproducible and reduces the interpretation effort and skill required. [ABSTRACT FROM AUTHOR]

Abstract Regulation of Lake Ontario water levels since the St. Lawrence Seaway began operation in the early 1960s reduced the range of lake-level fluctuations and resulted in alteration of wetland plant communities, especially invasion of sedge/grass meadow marsh by cattails. A new regulation plan was implemented in January 2017 that seeks to restore some of the natural range in lake levels to benefit the environment. An adaptive management process accompanied the new Plan 2014, requiring before-after data for evaluation. Aerial photographs from 2014/2015 were obtained from existing sources for 16 wetlands previously assessed from 2001 photographs, and photointerpretation was used to re-map the vegetation types from the earlier study. The updated data set provides further information on wetland response to lake-level regulation. Overall, area of Meadow Marsh decreased from 2001 to 2014/2015 in most wetlands. In some cases, losses were due to increased Cattail abundance and in others to Mixed Emergent abundance. Although area of Cattail did increase at half the sites, expansion landward into Meadow Marsh was likely limited to an upper elevation with drier soils that had not been flooded for at least 15 years. Waterward expansion of Cattail was slow because it occurs by formation of vegetatively-expanding floating mats. The updated data set can now serve as a baseline for future adaptive management evaluations, including response to extreme high lake levels in 2017 and future low lake levels that Plan 2014 should allow during periods of low water supply. [ABSTRACT FROM AUTHOR]

High-resolution aerial images allow detailed analyses of periglacial landforms, which is of particular importance in light of climate change and resulting changes in active layer thickness. The aim of this study is to show possibilities of using UAV-based photography to perform spatial analysis of periglacial landforms on the Demay Point peninsula, King George Island, and hence to supplement previous geomorphological studies of the South Shetland Islands. Photogrammetric flights were performed using a PW-ZOOM fixed-winged unmanned aircraft vehicle. Digital elevation models (DEM) and maps of slope and contour lines were prepared in ESRI ArcGIS 10.3 with the Spatial Analyst extension, and three-dimensional visualizations in ESRI ArcScene 10.3 software. Careful interpretation of orthophoto and DEM, allowed us to vectorize polygons of landforms, such as (i) solifluction landforms (solifluction sheets, tongues, and lobes); (ii) scarps, taluses, and a protalus rampart; (iii) patterned ground (hummocks, sorted circles, stripes, nets and labyrinths, and nonsorted nets and stripes); (iv) coastal landforms (cliffs and beaches); (v) landslides and mud flows; and (vi) stone fields and bedrock outcrops. We conclude that geomorphological studies based on commonly accessible aerial and satellite images can underestimate the spatial extent of periglacial landforms and result in incomplete inventories. The PW-ZOOM UAV is well suited to gather detailed geomorphological data and can be used in spatial analysis of periglacial landforms in the Western Antarctic Peninsula region. [ABSTRACT FROM AUTHOR]

The central Platte River in Nebraska, USA, has undergone substantial channel narrowing since basin settlement in the mid-nineteenth century. Many researchers have studied the causes of channel narrowing and its implications for endangered species that use wide, shallow channel segments with barren sandbars. As a result, changes in metrics such as unvegetated channel width have been studied. With few exceptions, these measures are estimated from aerial imagery without mention of error in relation to actual channel conditions and/or investigator bias. This issue is not unique to central Platte River studies, as a general lack of commentary is apparent regarding the direct comparison of channel planform characteristics interpreted from aerial imagery relative to those measured in the field. Here we present a case study where data collected by the Platte River Recovery Implementation Program was used to make multiple comparisons using three years of field-measured unvegetated channel widths and those photointerpreted from aerial imagery. Widths were interpreted by three investigators, who identified similar widths in almost all cases. Photointerpretation from imagery collected during the fall resulted in unvegetated width estimates that were more consistent with field measurments than estimates derived using imagery collected in June. Differences were attributed to three main factors: (1) influences of discharge on photointerpretation of unvegetated channel width; (2) increases in vegetative cover throughout the growing season; and (3) resolution of imagery. Most importantly, we concluded that photointerpretation of unvegetated widths from imagery collected during high flows can result in significant over estimation of unvegetated channel width. [ABSTRACT FROM AUTHOR]

Urban agriculture (UA) has been acknowledged for several positive effects such as access to fresh food, human activities moderation, agro-biodiversity and social and cultural relationships. In the city of Rome due to social and economic trends this kind of activity is spreading, but so far very few attempts have been addressed to inventorying the UA areas (e.g., community gardens, residential gardens, school gardens, illegal vegetable gardens, urban farms, etc.). Some mapping experiences have been carried out but all lack of a well-established methodology to be applied for a complete inventory. In this paper we propose a conceptual framework and methodology for mapping the UA in Rome through Earth Observation techniques by using the concepts of photointerpretation and the features of the most used web-mapping services. Google Earth has been used as a basic tool for visual interpretation and polygon digitalization, while other services have been used for the availability of additional features (e.g., the oblique view of Microsoft Bing Maps). The integration of the web-mapping services combined with ancillary data improved the UA site detection, allowing to define both the land use and the UA typologies. We argue that the integration of the web-mapping services for building urban agricultural land use datasets is cost-effective compared to processing commercial remote sensing images. The inventory can enable administrators to perform analysis about the interactions between agricultural activities and the urban environment, and to enact informed policies for green and vacant urban spaces management. [ABSTRACT FROM AUTHOR]

Abstract: The U.S. state of Maryland needs to monitor land use change in order to address land management objectives. This paper presents a change detection method that, through automation and standard geographic information system (GIS) techniques, facilitates the estimation of landscape change via photointerpretation. Using the protocols developed, we show a net loss of forest land, with losses due primarily to urban development and most gains in forest land coming from agricultural land conversions. This study indicates that about 75,000 photo plots would be needed to estimate land use change in Maryland at the county-level, assuming a uniform sampling intensity and a maximum desired county-level sampling error of 20 percent, with an estimated time requirement of 125 h. The protocol we present for designing, planning and conducting a photointerpretation-based land use change procedure can be used by other regions and is well suited for land use change monitoring, assuming that analysis of opportunity costs suggests that existing or new remotely sensed imagery classifications do not meet user needs. [Copyright &y& Elsevier]

Abstract: Although always a part of city life, urban agriculture has recently attracted increased attention from diverse groups in the United States, which promote it as a strategy for stimulating economic development, increasing food security and access, and combatting obesity and diabetes, among other goals. Developing effective policies and programs at the city or neighborhood level demands as a first step the accurate mapping of existing urban agriculture sites. Mapping efforts in major U.S. cities have been limited in their focus and methodology. Focusing on public sites of food production, such as community gardens, they have overlooked the actual and potential contribution of private spaces, including home food gardens, to local food systems. This paper describes a case study of urban agriculture in Chicago which used the manual analysis of high-resolution aerial images in Google Earth in conjunction with ArcGIS to identify and map public and private spaces of food production. The resulting spatial dataset demonstrates that urban agriculture is an extensive land use type with wide variations in the distribution of sites across the city. Only 13% of sites reported to be community gardening projects by nongovernment organizations and government agencies were determined, through image analysis, to be sites of food production. The production area of home gardens identified by the study is almost threefold that of community gardens. Study results suggest opportunities may exist for scaling up existing production networks—including home food gardens—and enhancing community food sovereignty by leveraging local knowledges of urban agriculture. [Copyright &y& Elsevier]

Photointerpretation studies were conducted to evaluate vegetation changes in wetlands of Lake Ontario and the upper St. Lawrence River associated with regulation of water levels since about 1960. The studies used photographs from 16 sites (four each from drowned river mouth, barrier beach, open embayment, and protected embayment wetlands) and spanned a period from the 1950s to 2001 at roughly decadal intervals. Meadow marsh was the most prominent vegetation type in most wetlands in the late 1950s when water levels had declined following high lake levels in the early 1950s. Meadow marsh increased at some sites in the mid-1960s in response to low lake levels and decreased at all sites in the late 1970s following a period of high lake levels. Typha increased at nearly all sites, except wave-exposed open embayments, in the 1970s. Meadow marsh continued to decrease and Typha to increase at most sites during sustained higher lake levels through the 1980s, 1990s, and into 2001. Most vegetation changes could be correlated with lake-level changes and with life-history strategies and physiological tolerances to water depth of prominent taxa. Analyses of GIS coverages demonstrated that much of the Typha invasion was landward into meadow marsh, largely by Typha x glauca. Lesser expansion toward open water included both T. x glauca and T. angustifolia. Although many models focus on the seed bank as a key component of vegetative change in wetlands, our results suggest that canopy-dominating, moisture-requiring Typha was able to invade meadow marsh at higher elevations because sustained higher lake levels allowed it to survive and overtake sedges and grasses that can tolerate periods of drier soil conditions. [ABSTRACT FROM AUTHOR]