The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Sebastian Martinuzzi - One of the best experts on this subject based on the ideXlab platform.
-
land development land use and urban sprawl in puerto rico integrating remote sensing and population Census Data
Landscape and Urban Planning, 2007Co-Authors: Sebastian Martinuzzi, William A Gould, Olga Ramos M GonzalezAbstract:The island of Puerto Rico has both a high population density and a long history of ineffective land use planning. This study integrates geospatial technology and population Census Data to understand how people use and develop the lands. We define three new regions for Puerto Rico: Urban (16%), Densely Populated Rural (36%), and Sparsely Populated Rural (48%). Eleven percent of the island is composed of urban/built-up surfaces. A large part of these developments occur in both low-density patterns of construction and sparsely populated neighborhoods. Half of the urban development occurs outside of urban centers. This analysis helps differentiate zones in the landscape with different uses and conditions, identifying not only urban and rural settings, but also the interface where development occurs in a territory dominated by forests and pastures, analogous to a wildland urban interface. The ineffective plan of land development has left a high degree of urban sprawl in 40% of island, where cities and towns appear typically surrounded by sprawl. The San Juan Metropolitan Area is one of the most expanded urbanized areas with a population of 2–2.5 million, comparable with the most sprawled cities of the U.S. mainland. This study reinforces the need for an efficient land use planning, and provides information to support research and planning efforts related to land development and conservation. It represents the first approach integrating satellite imagery with population Census Data for studying the human environment in the Caribbean.
Guilherme Depaula - One of the best experts on this subject based on the ideXlab platform.
-
The distributional effect of climate change on agriculture: Evidence from a Ricardian quantile analysis of Brazilian Census Data
Journal of Environmental Economics and Management, 2020Co-Authors: Guilherme DepaulaAbstract:Abstract The economic impact of global warming likely varies across farms because of differences in climate, technology, and adaptive capacity. Therefore, aggregate estimates of the average effect of warming may be insufficient to model climate change vulnerability. In this study, I propose a quantile model for the distributional effect of climate change. I estimate interquantile regressions of land value on climate using agricultural Census Data for 464,277 commercial farms in Brazil. I find that the effects of climate change in Brazilian agriculture vary significantly by climate, land quality, and irrigation choice. A 1 °C of warming is more detrimental to farms in warm climates, those with high-quality land, and those using irrigation. A 100-mm decrease in annual precipitation is more damaging to farms in dry climates, those with low-quality land, and those using irrigation. The heterogeneity in climate change effects is particularly large within the subset of farms in the warmest or the driest climates, as the most vulnerable farms appear to be those that have reached their limits for climate adaptation.
-
the distributional impact of climate change in brazilian agriculture a ricardian quantile analysis with Census Data
2018Co-Authors: Guilherme DepaulaAbstract:Abstract: The economic impact of global warming varies across firms because of differences in climate, technology, and adaptive capacity. Aggregate estimates of the average effect of warming are thus insufficient to model climate change vulnerability in developing countries. In this study, I measure the distributional effect of climate change in Brazilian agriculture by estimating the quantile and interquantile regressions of land value on climate, using agricultural Census Data for 490,000 commercial farms. The effect of a 1°C rise in average temperature on land values ranges from -5% for the most productive farmers located in the colder South region to -34% for the least productive farmers located in the warmer North region. The impact is most severe in the extreme 0.01 quantile of the land value distribution. The productivity inequality between farms in the extremes of the distribution of land values may double with marginal warming.
Olga Ramos M Gonzalez - One of the best experts on this subject based on the ideXlab platform.
-
land development land use and urban sprawl in puerto rico integrating remote sensing and population Census Data
Landscape and Urban Planning, 2007Co-Authors: Sebastian Martinuzzi, William A Gould, Olga Ramos M GonzalezAbstract:The island of Puerto Rico has both a high population density and a long history of ineffective land use planning. This study integrates geospatial technology and population Census Data to understand how people use and develop the lands. We define three new regions for Puerto Rico: Urban (16%), Densely Populated Rural (36%), and Sparsely Populated Rural (48%). Eleven percent of the island is composed of urban/built-up surfaces. A large part of these developments occur in both low-density patterns of construction and sparsely populated neighborhoods. Half of the urban development occurs outside of urban centers. This analysis helps differentiate zones in the landscape with different uses and conditions, identifying not only urban and rural settings, but also the interface where development occurs in a territory dominated by forests and pastures, analogous to a wildland urban interface. The ineffective plan of land development has left a high degree of urban sprawl in 40% of island, where cities and towns appear typically surrounded by sprawl. The San Juan Metropolitan Area is one of the most expanded urbanized areas with a population of 2–2.5 million, comparable with the most sprawled cities of the U.S. mainland. This study reinforces the need for an efficient land use planning, and provides information to support research and planning efforts related to land development and conservation. It represents the first approach integrating satellite imagery with population Census Data for studying the human environment in the Caribbean.
Mikhail Prokopenko - One of the best experts on this subject based on the ideXlab platform.
-
creating a surrogate commuter network from australian bureau of statistics Census Data
Scientific Data, 2019Co-Authors: Kristopher M Fair, Cameron Zachreson, Mikhail ProkopenkoAbstract:Between the 2011 and 2016 national Censuses, the Australian Bureau of Statistics changed its anonymity policy compliance system for the distribution of Census Data. The new method has resulted in dramatic inconsistencies when comparing low-resolution Data to aggregated high-resolution Data. Hence, aggregated totals do not match true totals, and the mismatch gets worse as the Data resolution gets finer. Here, we address several aspects of this inconsistency with respect to the 2016 usual-residence to place-of-work travel Data. We introduce a re-sampling system that rectifies many of the artifacts introduced by the new ABS protocol, ensuring a higher level of consistency across partition sizes. We offer a surrogate high-resolution 2016 commuter Dataset that reduces the difference between the aggregated and true commuter totals from ~34% to only ~7%, which is on the order of the discrepancy across partition resolutions in Data from earlier years.
-
creating a surrogate commuter network from australian bureau of statistics Census Data
arXiv: Databases, 2018Co-Authors: Kristopher M Fair, Cameron Zachreson, Mikhail ProkopenkoAbstract:Between the 2011 and 2016 national Censuses, the Australian Bureau of Statistics changed its anonymity policy compliance system for the distribution of Census Data. This change has resulted in a lack of consistency over the different partition resolutions that define the sizes of local populations. Here, we address this inconsistency with respect to the 2016 usual-residence to place-of-work travel Data. The lack of consistency manifests in several ways that can dramatically influence the mobility network derived from this Data. For example, it introduces a strong correlation between the total number of commuters accounted for in the Database and the size of the population partition used to create the network. This results in up to ~30% of the working population disappearing for the highest-resolution partition scheme. Here, we introduce a re-sampling system that rectifies many of these artifacts, ensuring a higher level of consistency in the derived mobility network across partition sizes. We offer a surrogate high-resolution 2016 commuter Database that reduces the discrepancy between commuter totals from ~30% to only ~7%, which is on the order of the discrepancy introduced by the privacy policy compliance system used in earlier years.
Xiaoguang Qin - One of the best experts on this subject based on the ideXlab platform.
-
combining remote sensing and ground Census Data to develop new maps of the distribution of rice agriculture in china
Global Biogeochemical Cycles, 2002Co-Authors: Steve Frolking, Jianjun Qiu, Stephen Boles, Xiangming Xiao, Jiyuan Liu, Yahui Zhuang, Xiaoguang QinAbstract:[1] Large-scale assessments of the potential for food production and its impact on biogeochemical cycling require the best possible information on the distribution of cropland. This information can come from ground-based agricultural Census Data sets and/ or spaceborne remote sensing products, both with strengths and weaknesses. Official cropland statistics for China contain much information on the distribution of crop types, but are known to significantly underestimate total cropland areas and are generally at coarse spatial resolution. Remote sensing products can provide moderate to fine spatial resolution estimates of cropland location and extent, but supply little information on crop type or management. We combined county-scale agricultural Census statistics on total cropland area and sown area of 17 major crops in 1990 with a fine-resolution land-cover map derived from 1995–1996 optical remote sensing (Landsat) Data to generate 0.5� resolution maps of the distribution of rice agriculture in mainland China. Agricultural Census Data were used to determine the fraction of crop area in each 0.5� grid cell that was in single rice and each of 10 different multicrop paddy rice rotations (e.g., winter wheat/ rice), while the remote sensing land-cover product was used to determine the spatial distribution and extent of total cropland in China. We estimate that there were 0.30 million km 2 of paddy rice cropland; 75% of this paddy land was multicropped, and 56% had two rice plantings per year. Total sown area for paddy rice was 0.47 million km 2 . Paddy rice agriculture occurred on 23% of all cultivated land in China. INDEX TERMS: 0315 Atmospheric Composition and Structure: Biosphere/atmosphere interactions; 1615 Global Change: Biogeochemical processes (4805); KEYWORDS: paddy rice, maps, China, multicropping rotation, Landsat