How may deforestation rates and political instruments affect land use patterns and Carbon emissions in the semi-arid Chaco, Argentina?

2020 ◽  
Vol 99 ◽  
pp. 104985
Author(s):  
Pablo Baldassini ◽  
Camilo Ernesto Bagnato ◽  
José María Paruelo
Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 141
Author(s):  
Qiaowen Lin ◽  
Lu Zhang ◽  
Bingkui Qiu ◽  
Yi Zhao ◽  
Chao Wei

Nowadays, China is the world’s second largest economy and largest carbon emitter. This paper calculates the carbon emission intensity and the carbon emissions per capita of land use in 30 provinces at the national level in China from 2006 to 2016. A spatial correlation model is used to explore its spatiotemporal features. The results show that (1) China’s land use carbon emissions continued to grow from 2006 to 2016. The spatial heterogeneity of carbon emission intensity of land use initially decreased and then increased during this period. The carbon emission of land use pattern reached a peak in 2015 and the land use carbon emission intensity was relatively lower in east China; (2) southern China accounts for a majority of the total Chinese carbon sink. Better economic structure, land use structure and industrial structure will lead to lower carbon emission intensity of land use; (3) carbon emissions per capita of land use in China are affected not only by land development intensity, urbanization level, and energy consumption structure, but also by the population policy. It is significant to formulate differentiated energy and land use policies according to local conditions. This study not only provides a scientific basis for formulating different carbon emission mitigation policies for the local governments in China, but also provides theoretical reference for other developing countries for sustainable development. It contributes to the better understanding of the land use patterns on carbon emissions in China.


1993 ◽  
Vol 14 (1) ◽  
pp. 25-42 ◽  
Author(s):  
Jordan E. Kerber

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.


2021 ◽  
Vol 13 (4) ◽  
pp. 631
Author(s):  
Kyle D. Woodward ◽  
Narcisa G. Pricope ◽  
Forrest R. Stevens ◽  
Andrea E. Gaughan ◽  
Nicholas E. Kolarik ◽  
...  

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.


2013 ◽  
Vol 35 (1) ◽  
pp. 48-70 ◽  
Author(s):  
Andrea Sarzynski ◽  
George Galster ◽  
Lisa Stack

Sign in / Sign up

Export Citation Format

Share Document