Author
Amanda Cutler
Bio: Amanda Cutler is an academic researcher. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.
Papers
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TL;DR: In this article, the authors analyzed remotely sensed data sources to evaluate land-use history within the Peruvian department of Amazonas and demonstrates the utility of comparing present and past land use patterns using continuous datasets, as a complement to the often dispersed and discrete data produced by archaeological and paleoecological field studies.
Abstract: This paper analyzes remotely sensed data sources to evaluate land-use history within the Peruvian department of Amazonas and demonstrates the utility of comparing present and past land-use patterns using continuous datasets, as a complement to the often dispersed and discrete data produced by archaeological and paleoecological field studies. We characterize the distribution of ancient (ca. AD 1–1550) terracing based on data drawn from high-resolution satellite imagery and compare it to patterns of deforestation between 2001 and 2019, based on time-series Landsat data. We find that the patterns reflected in these two datasets are statistically different, indicating a distinctive shift in land-use, which we link to the history of Inka and Spanish colonialism and Indigenous depopulation in the 15th through 17th centuries AD as well as the growth of road infrastructure and economic change in the recent past. While there is a statistically significant relationship between areas of ancient terracing and modern-day patterns of deforestation, this relationship ultimately explains little (6%) of the total pattern of modern forest loss, indicating that ancient land-use patterns do not seem to be structuring modern-day trajectories of land-use. Together, these results shed light on the long-term history of land-use in Amazonas and their enduring legacies in the present.
4 citations
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TL;DR: Wang et al. as discussed by the authors explored the spatiotemporal characteristics of forest loss in the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR).
Abstract: Under the backdrop of achieving carbon neutrality and accelerating urbanization, China’s forests face unprecedented pressures. This study explored the spatiotemporal characteristics of forest loss in the urban agglomeration in the middle reaches of the Yangtze River (UAMRYR). The dynamic mechanism of forest loss caused by fire, logging, construction, and pollution was also analyzed using spatial database development, polygon superposition analysis, grid system construction, and coordinate system calculation. The results show that the forest loss in the UAMRYR experienced three stages: continuous acceleration (1990–2010), peak (2010–2015), and slight decline (2015–2020). Rapid urban expansion is the primary cause of forest loss, and the three metropolitan areas had the fastest urban expansion and the most severe forest loss. Due to the success of afforestation efforts, the forest loss caused by fire, logging, and pollution was restored by 80%, while most of the forest losses caused by construction are permanent. Given the current forest loss trends, large expanses of forests in the UAMRYR are at risk of being destroyed and causing serious damage to the region’s ecological environment. Forest losses can be significantly reduced by guiding the rational expansion of cities, supporting afforestation for urban construction projects, strengthening forest fire risk investigation, and implementing ecological reconstruction of polluted areas.
3 citations
TL;DR: Using a Random Forest algorithm and Landsat satellite data, the authors quantifies archaeological site destruction attributed to land use land cover change in Peru's lower Moche Valley between 1985-2020.
Abstract: The destruction of archaeological sites and the loss of archaeological landscapes remains a global concern as populations and urban areas continue to expand. Archaeological sites are not only significant to local communities, national identities, and modern tourist economies but also provide critical knowledge of past socio-cultural interactions, settlement patterns, human-environment relationships, and risk mitigation strategies. While archaeological landscapes and site destruction have remained outside of traditional land use land cover change (LULCC) studies, they are a form of urban and agricultural land use. By conceptualizing archaeological site destruction within land change science, this study provides an innovative approach for assessing “what's left” of historically surveyed archaeological landscapes. Using a Random Forest algorithm and Landsat satellite data, this study quantifies archaeological site destruction attributed to land use land cover change in Peru's lower Moche Valley between 1985-2020. Over 400 archaeological sites previously recorded during the Chan Chan-Moche Valley Project (CCMVP, 1969-1974) are analyzed. Results indicate that less than a quarter of the original CCMVP sites remain on the landscape. The primary drivers of LULCC in the lower Moche Valley include population growth, migration, and government policies, while secondary drivers include heritage values. Positioning archaeological survey data within land change science and integrating machine learning techniques can benefit historic survey reassessments globally and provides significant knowledge of archaeological site destruction and the socio-economic conditions that underly dynamic landscape changes.