Land-Use Patterns in the Classification of Cities: The Israeli Case

Selecting an effective archaeological survey takes careful consideration given the interaction of several variables, such as the survey's goals, nature of the data base, and budget constraints. This article provides justification for a “siteless survey” using evidence from a project on Potowomut Neck in Rhode Island whose objective was not to locate sites but to examine the distribution and density of prehistoric remains to test an hypothesis related to land use patterns. The survey strategy, random walk, was chosen because it possessed the advantages of probabilistic testing, as well as the ease of locating sample units. The results were within the limits of statistical validity and were found unable to reject the hypothesis. “Siteless survey” may be successfully applied in similar contexts where the distribution and density of materials, as opposed to ambiguously defined sites, are sought as evidence of land use patterns, in particular, and human adaptation, in general.

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The effects of different land use patterns on the microclimate and ecosystem services in the agro-pastoral ecotone of Northern China

Ecological Indicators ◽

10.1016/j.ecolind.2019.105522 ◽

2019 ◽

Vol 106 ◽

pp. 105522 ◽

Cited By ~ 3

Author(s):

Yuejuan Yang ◽

Kun Wang

Keyword(s):

Land Use ◽

Ecosystem Services ◽

Northern China ◽

Land Use Patterns ◽

Use Patterns

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Modeling Community-Scale Natural Resource Use in a Transboundary Southern African Landscape: Integrating Remote Sensing and Participatory Mapping

Remote Sensing ◽

10.3390/rs13040631 ◽

2021 ◽

Vol 13 (4) ◽

pp. 631

Author(s):

Kyle D. Woodward ◽

Narcisa G. Pricope ◽

Forrest R. Stevens ◽

Andrea E. Gaughan ◽

Nicholas E. Kolarik ◽

...

Keyword(s):

Remote Sensing ◽

Land Use ◽

Resource Use ◽

Training Data ◽

Systems Science ◽

Participatory Mapping ◽

Land Use Patterns ◽

Modeling Framework ◽

Use Patterns ◽

Human Habitation

Remote sensing analyses focused on non-timber forest product (NTFP) collection and grazing are current research priorities of land systems science. However, mapping these particular land use patterns in rural heterogeneous landscapes is challenging because their potential signatures on the landscape cannot be positively identified without fine-scale land use data for validation. Using field-mapped resource areas and household survey data from participatory mapping research, we combined various Landsat-derived indices with ancillary data associated with human habitation to model the intensity of grazing and NTFP collection activities at 100-m spatial resolution. The study area is situated centrally within a transboundary southern African landscape that encompasses community-based organization (CBO) areas across three countries. We conducted four iterations of pixel-based random forest models, modifying the variable set to determine which of the covariates are most informative, using the best fit predictions to summarize and compare resource use intensity by resource type and across communities. Pixels within georeferenced, field-mapped resource areas were used as training data. All models had overall accuracies above 60% but those using proxies for human habitation were more robust, with overall accuracies above 90%. The contribution of Landsat data as utilized in our modeling framework was negligible, and further research must be conducted to extract greater value from Landsat or other optical remote sensing platforms to map these land use patterns at moderate resolution. We conclude that similar population proxy covariates should be included in future studies attempting to characterize communal resource use when traditional spectral signatures do not adequately capture resource use intensity alone. This study provides insights into modeling resource use activity when leveraging both remotely sensed data and proxies for human habitation in heterogeneous, spectrally mixed rural land areas.

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