A contextual classification method for recognizing land use patterns in high resolution remotely sensed data

1982 ◽  
Vol 15 (4) ◽  
pp. 317-324 ◽  
Author(s):  
Stephen W Wharton
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Remotely Sensed ◽  
Classification Method ◽  
Remotely Sensed Data ◽  
Land Use Patterns ◽  
Use Patterns

Remotely-sensed land use patterns and the presence of Anopheles larvae (Diptera: Culicidae) in Sukabumi, West Java, Indonesia

2008 ◽  
Vol 33 (1) ◽  
pp. 30-39 ◽  
Author(s):  
Craig A. Stoops ◽  
Yoyo R. Gionar ◽  
Shinta ◽  
Priyanto Sismadi ◽  
Agus Rachmat ◽  
...  
Keyword(s):  
Land Use ◽  
Remotely Sensed ◽  
Land Use Patterns ◽  
West Java ◽  
Use Patterns

Detecting the Development of Land Use Patterns for Building in Urban Areas by Using High Resolution Image

2013 ◽  
Vol 15 (3) ◽  
pp. 160
Author(s):  
A Amar
Keyword(s):  
Land Use ◽  
High Resolution ◽  
Urban Areas ◽  
Rapid Development ◽  
Secondary Data ◽  
Survey Method ◽  
Field Observations ◽  
Land Use Patterns ◽  
Spatial Image ◽  
Use Patterns

This study aimed at obtaining factual information and overview to the development of land use patterns for buildings in urban areas by interval time period, both spatially and aspatially, by utilizing high-resolution satellite photo image (high resolution spatial image) combined with field observations. This research used survey method approach. The data of this study consisted of primary and secondary data classified into spatial and aspatial data in the form of time series obtained through documents recording techniques, field observations, previous mapping sources, as well as depth interviews. The analysis technique used Image Processing Analysis through programs and software Arc View. The result of research showed that there was a quite rapid development of land use patterns for building in Palu within the last 50 years (≤ 1970 till 2010) It had building addition in 65,173 units (82.28%), from 14,032 units in ≤1970 to 79,205 units in 2010, and the addition of extensive use of land for building was 4723.52 ha (89.06%), from 516.98 ha in ≤ 1970 to 4723.52 ha in 2010. The development level of land use patterns for building was getting along with the size of distribution and population growth in Palu.

scholarly journals Linking Past and Present Land-Use Histories in Southern Amazonas, Peru

2021 ◽  
Vol 13 (12) ◽  
pp. 2274
Author(s):  
Daniel Plekhov ◽  
Parker VanValkenburgh ◽  
Paul Abrams ◽  
Amanda Cutler ◽  
Justin Han ◽  
...  
Keyword(s):  
Land Use ◽  
Field Studies ◽  
Remotely Sensed Data ◽  
Land Use Patterns ◽  
Use Patterns ◽  
History Of ◽  
High Resolution Satellite Imagery ◽  
Shed Light ◽  
Past Land Use

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.

Conducting “Siteless Survey”: Results from Coastal New England

1993 ◽  
Vol 14 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Jordan E. Kerber
Keyword(s):  
Land Use ◽  
New England ◽  
Rhode Island ◽  
Careful Consideration ◽  
Archaeological Survey ◽  
Land Use Patterns ◽  
Use Patterns ◽  
Statistical Validity ◽  
Survey Results ◽  
Survey Strategy

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.

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

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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