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1. Reconstructing Historical Forest Cover and Land Use Dynamics in the Northeastern United States Using Geospatial Analysis and Airborne LiDAR

   https://doi.org/https://doi.org/10.1080/24694452.2020.1856640  

   Johnson, K.; Ouimet, W. (March 2021, Annals of the American Association of Geographers)

   null (Ed.)

   The northeastern United States experienced extensive deforestation during the seventeenth through twentieth centuries primarily for European agriculture, which peaked in the mid-nineteenth century, and followed by widespread farmstead abandonment and reforestation. Analysis of airborne light detection and ranging (LiDAR) data has revealed thousands of historical land-use features with topographic signatures across the landscape under the region’s now-dense forest canopy. This study investigates two different types of features—stone walls and relict charcoal hearths—both of which are associated with widespread deforestation in the region. Our results demonstrate that LiDAR is an effective tool in reconstructing and quantifying the distribution and magnitude of historical forest cover using these relict land use features as a reliable proxy. Furthermore, these methods allow for direct quantification of cumulative land clearing over time in each town, in addition to the extent, intensity, and spatial distribution of cleared land and forest cover. 

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2. Mapping Relict Charcoal Hearths in New England Using Deep Convolutional Neural Networks and LiDAR Data

   https://doi.org/10.3390/rs13224630  

   Suh, Ji Won; Anderson, Eli; Ouimet, William; Johnson, Katharine M.; Witharana, Chandi (November 2021, Remote Sensing)

   Advanced deep learning methods combined with regional, open access, airborne Light Detection and Ranging (LiDAR) data have great potential to study the spatial extent of historic land use features preserved under the forest canopy throughout New England, a region in the northeastern United States. Mapping anthropogenic features plays a key role in understanding historic land use dynamics during the 17th to early 20th centuries, however previous studies have primarily used manual or semi-automated digitization methods, which are time consuming for broad-scale mapping. This study applies fully-automated deep convolutional neural networks (i.e., U-Net) with LiDAR derivatives to identify relict charcoal hearths (RCHs), a type of historical land use feature. Results show that slope, hillshade, and Visualization for Archaeological Topography (VAT) rasters work well in six localized test regions (spatial scale: <1.5 km2, best F1 score: 95.5%), but also at broader extents at the town level (spatial scale: 493 km2, best F1 score: 86%). The model performed best in areas with deciduous forest and high slope terrain (e.g., >15 degrees) (F1 score: 86.8%) compared to coniferous forest and low slope terrain (e.g., <15 degrees) (F1 score: 70.1%). Overall, our results contribute to current methodological discussions regarding automated extraction of historical cultural features using deep learning and LiDAR. 

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3. “New” cyanobacterial blooms are not new: two centuries of lake production are related to ice cover and land use

   https://doi.org/10.1002/ecs2.3170  

   Ewing, Holly A.; Weathers, Kathleen C.; Cottingham, Kathryn L.; Leavitt, Peter R.; Greer, Meredith L.; Carey, Cayelan C.; Steele, Bethel G.; Fiorillo, Alyeska U.; Sowles, John P. (June 2020, Ecosphere)

   Abstract Recent cyanobacterial blooms in otherwise unproductive lakes may be warning signs of impending eutrophication in lakes important for recreation and drinking water, but little is known of their historical precedence or mechanisms of regulation. Here, we examined long‐term sedimentary records of both general and taxon‐specific trophic proxies from seven lakes of varying productivity in the northeastern United States to investigate their relationship to historical in‐lake, watershed, and climatic drivers of trophic status. Analysis of fossil pigments (carotenoids and chlorophylls) revealed variable patterns of past primary production across lakes over two centuries despite broadly similar changes in regional climate and land use. Sediment abundance of the cyanobacteriumGloeotrichia,a large, toxic, nitrogen‐fixing taxon common in recent blooms in this region, revealed that this was not a new taxon in the phytoplankton communities but rather had been present for centuries. Histories ofGloeotrichiaabundance differed strikingly across lakes and were not consistently associated with most other sediment proxies of trophic status. Changes in ice cover most often coincided with changes in fossil pigments, and changes in watershed land use were often related to changes inGloeotrichiaabundance, although no single climatic or land‐use factor was associated with proxy changes across all seven lakes. The degree to which changes in lake sediment records co‐occurred with changes in the timing of ice‐out or agricultural land use was negatively correlated with the ratio of watershed area to lake area. Thus, both climate and land management appeared to play key roles in regulation of primary production in these lakes, although the manner in which these factors influenced lakes was mediated by catchment morphometry. Improved understanding of the past interactions between climate change, land use, landscape setting, and water quality underscores the complexity of mechanisms regulating lake and cyanobacterial production and highlights the necessity of considering these interactions—rather than searching for a singular mechanism—when evaluating the causes of ongoing changes in low‐nutrient lakes. 

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4. Four-century history of land transformation by humans in the United States (1630–2020): annual and 1 km grid data for the HIStory of LAND changes (HISLAND-US)

   https://doi.org/10.5194/essd-15-1005-2023  

   Li, Xiaoyong; Tian, Hanqin; Lu, Chaoqun; Pan, Shufen (January 2023, Earth System Science Data)

   Abstract. The land of the conterminous United States (CONUS) hasbeen transformed dramatically by humans over the last four centuries throughland clearing, agricultural expansion and intensification, and urban sprawl.High-resolution geospatial data on long-term historical changes in land useand land cover (LULC) across the CONUS are essential for predictiveunderstanding of natural–human interactions and land-based climatesolutions for the United States. A few efforts have reconstructed historicalchanges in cropland and urban extent in the United States since themid-19th century. However, the long-term trajectories of multiple LULCtypes with high spatial and temporal resolutions since the colonial era(early 17th century) in the United States are not available yet. Byintegrating multi-source data, such as high-resolution remote sensingimage-based LULC data, model-based LULC products, and historical censusdata, we reconstructed the history of land use and land cover for theconterminous United States (HISLAND-US) at an annual timescale and 1 km × 1 km spatial resolution in the past 390 years (1630–2020). The results showwidespread expansion of cropland and urban land associated with rapid lossof natural vegetation. Croplands are mainly converted from forest, shrub,and grassland, especially in the Great Plains and North Central regions.Forest planting and regeneration accelerated the forest recovery in theNortheast and Southeast since the 1920s. The geospatial and long-termhistorical LULC data from this study provide critical information forassessing the LULC impacts on regional climate, hydrology, andbiogeochemical cycles as well as achieving sustainable use of land in thenation. The datasets are available at https://doi.org/10.5281/zenodo.7055086 (Li et al., 2022). 

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5. High‐resolution airborne Light Detection and Ranging data, ethics and archaeology: Considerations from the northeastern United States

   https://doi.org/10.1002/arp.1836  

   Johnson, Katharine M.; Ives, Timothy H.; Ouimet, William B.; Sportman, Sarah P. (July 2021, Archaeological Prospection)

   Abstract Publicly available Light Detection and Ranging (LiDAR) datasets have become widely accessible in the northeastern United States and beyond in the past 10 years. The increase in dataset availability and accessibility coupled with a number of publications detailing the types of cultural features that can be identified has made it necessary to explore and discuss positive impacts and risks to cultural features on this landscape. Access to detailed, documented locations of archaeological resources at state or federal agencies in the United States is typically limited to those with certain credentials, yet many locations of features and sites, both documented and undocumented, are now available to anyone who can access these datasets and effectively interpret them. This presents a challenge for cultural resource management professionals and the field of archaeology; for while LiDAR datasets have had many positive impacts, it is not yet obvious what the unintended impacts of feature exposure might be. Risks to sites are worth considering in the northeastern United States, where (1) region‐wide LiDAR data are publicly available and accessible, (2) many cultural features are widely accessible and not well monitored and (3) case studies have been published that provide guidance on how to identify specific types of cultural landscape features using LiDAR data. We discuss the nuances of those topics here, provide examples of how the datasets have impacted archaeology in the northeastern United States and explore possible mitigation strategies to maintain data accessibility while also protecting important cultural features in this region. 

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