Engineering topics

Zhang, Ping

Publications and source records attributed to Zhang, Ping.

At least 37 records · Page 2

NASA NTRS2017

Regional Impacts of Urbanization in the United States

We simulate the impact of impervious surface areas (ISA) on the U.S. local and regional climate. At a local scale, we find the urban area warmer than the surrounding vegetation in most cities, except in arid climate cities where urban temperature is cooler for much of the daytime. For all 9 regions studied, simulated results show that the growing season maximum surface temperature difference between urban and the dominant vegetation occurs around mid-day and is strongest in the northern regions. Regional temperature differences of 3.0 C, 3.4 C, and 3.9 C were simulated in the Northeast, Midwest, and Northwest, respectively. In these regions evaporative cooling, during the growing season, creates a stronger urban heat island (UHI). The UHI is less pronounced during winter when vegetation is dormant. Our results suggest that the ISA temperature is set by building material's characteristics and its departure from that of the surrounding vegetation is essentially driven by evaporative cooling. Except when rainfall is small, the highest surface runoff to precipitation ratios are simulated in most cities, especially when precipitation events occur as heavy downpours. In terms of photosynthesis, we provide a detailed distribution of maximum production in the U.S., a needed product for policy and urban planners.

Bounoua, Lahouari↗

NASA NTRS2016

Using Landsat, MODIS, and a Biophysical Model to Evaluate LST in Urban Centers

In this paper, we assessed and compared land surface temperature (LST) in urban centers using data from Landsat, MODIS, and the Simple Biosphere model (SiB2). We also evaluated the sensitivity of the models LST to different land cover types, fractions (percentages), and emissivities compared to reference points derived from Landsat thermal data. This was demonstrated in three climatologically- and morphologically-different cities of Atlanta, GA, New York, NY, and Washington, DC. Our results showed that in these cities SiB2 was sensitive to both the emissivity and the land cover type and fraction, but much more sensitive to the latter. The practical implications of these results are rather significant since they imply that the SiB2 model can be used to run different scenarios for evaluating urban heat island (UHI) mitigation strategies. This study also showed that using detailed emissivities per land cover type and fractions from Landsat-derived data caused a convergence of the model results towards the Landsat-derived LST for most of the studied cases. This study also showed that SiB2 LSTs are closer in magnitude to Landsat-derived LSTs than MODIS-derived LSTs. It is important, however, to emphasize that both Landsat and MODIS LSTs are not direct observations and, as such, do not represent a ground truth. More studies will be needed to compare these results to in situ LST data and provide further validation.

Al-Hamdan, Mohammad Z.↗

NASA NTRS2016

Mapping Impact of Urbanization in the Continental U.S. From 2001-2020

We combine Landsat and Moderate Resolution Imaging Spectroradiometer (MODIS) products to create observation-based and scenario-based maps characterizing distant-past, recent-past, present, and near-future land cover and land use change in the continental United States at a 5km scale. These maps show the nature and impact of urbanization across the continental U.S. from 2001 to 2020 with focus on the relationship between population and urban growth and how it varies across the U.S. The influence of culture on urbanization characteristics are revealed in the results at city-scale, helping to provide insight into both past and projected urbanization trends.

Bounoua, Lahouari↗

NASA NTRS2016

Mapping Impact of Urbanization in the Continental U.S. from 2001 - 2020

Bounoua, Lahouari↗

NASA NTRS2016

Modeling Impact of Urbanization in US Cities Using Simple Biosphere Model SiB2

We combine Landsat- and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based products, as well as climate drivers from Phase 2 of the North American Land Data Assimilation System (NLDAS-2) in a Simple Biosphere land surface model (SiB2) to assess the impact of urbanization in continental USA (excluding Alaska and Hawaii). More than 300 cities and their surrounding suburban and rural areas are defined in this study to characterize the impact of urbanization on surface climate including surface energy, carbon budget, and water balance. These analyses reveal an uneven impact of urbanization across the continent that should inform upon policy options for improving urban growth including heat mitigation and energy use, carbon sequestration and flood prevention.

Zhang, Ping↗

NASA NTRS2016

Mapping Impact of Urbanization in the Continental U.S. from 2001-2020

Data fusion, from Landsat and MODIS, was used to characterize US buildup and to derive a plausible 2020 impervious surface area (ISA) projection based on observed rates of ISA change as a function of population from 2006 to 2011. The analysis shows that urbanization in the U.S. implicitly includes a cultural character whereby depending on the region, cities are either built horizontally with large ISA per capita or vertically with a minimal spatial footprint. This cultural character can also be forced by land availability, topography and inland water. In other regions, cities seem to have adapted to their population growth and adjusted their ISA use per capita.

ISA↗

NASA NTRS2016

Modeling the Urban Impact on Semiarid Surface Climate: A Case Study in Marrakech, Morocco

We combine Landsat and MODIS data in the Simple Biosphere Model to assess the impact of urbanization on surface climate in a semiarid city in North Africa. The model simulates highest temperatures in urban class, with spring average maximum temperature differences to other land cover classes ranging between 1.6 C and 6.0 C. During summer, these maximum temperature differences are smallest (0.5 C) with barelands and highest (8.3 C) with irrigated lawns. This excess heating is simulated above and beyond a seasonal temperature average of about 30 C during spring and 44 C during summer. On annual mean, a full urbanization scenario decreases the carbon fixation by 0.13 MtC and increases the daytime mean surface temperature by 1.3 C. This may boost the city energy consumption by 5.72%. Under a 'smart growth' scenario, whereby the city expands on barelands to cover 50% of the study region and all remaining barelands converted to orchards, the carbon fixation is enhanced by 0.04 MtC with a small daytime temperature increase of 0.2 C. Our results indicate that vegetation can mitigate the urban heating. The hydrological cycle indicates that highest ratio of surface runoff to precipitation (43.8%) occurs in urban areas, versus only 16.7 % for all cover types combined.

Lachir, Asia↗

NASA NTRS2015

Mapping Biophysical Parameters for Land Surface Modeling over the Continental US Using MODIS and Landsat

In terms of the space cities occupy, urbanization appears as a minor land transformation. However, it permanently modifies land's ecological functions, altering its carbon, energy, and water fluxes. It is therefore necessary to develop a land cover characterization at fine spatial and temporal scales to capture urbanization's effects on surface fluxes. We develop a series of biophysical vegetation parameters such as the fraction of photosynthetically active radiation, leaf area index, vegetation greenness fraction, and roughness length over the continental US using MODIS and Landsat products for 2001. A 13-class land cover map was developed at a climate modeling grid (CMG) merging the 500mMODIS land cover and the 30m impervious surface area from the National Land Cover Database. The landscape subgrid heterogeneity was preserved using fractions of each class from the 500 m and 30 m into the CMG. Biophysical parameters were computed using the 8-day composite Normalized Difference Vegetation Index produced by the North American Carbon Program. In addition to urban impact assessments, this dataset is useful for the computation of surface fluxes in land, vegetation, and urban models and is expected to be widely used in different land cover and land use change applications.

Biophysical↗

NASA NTRS2014

Comparison of MODIS Land Surface Temperature and Air Temperature over the Continental USA Meteorological Stations

The National Land Cover Database (NLCD) Impervious Surface Area (ISA) and MODIS Land Surface Temperature (LST) are used in a spatial analysis to assess the surface-temperature-based urban heat island's (UHIS) signature on LST amplitude over the continental USA and to make comparisons to local air temperatures. Air-temperature-based UHIs (UHIA), calculated using the Global Historical Climatology Network (GHCN) daily air temperatures, are compared with UHIS for urban areas in different biomes during different seasons. NLCD ISA is used to define urban and rural temperatures and to stratify the sampling for LST and air temperatures. We find that the MODIS LST agrees well with observed air temperature during the nighttime, but tends to overestimate it during the daytime, especially during summer and in nonforested areas. The minimum air temperature analyses show that UHIs in forests have an average UHIA of 1 C during the summer. The UHIS, calculated from nighttime LST, has similar magnitude of 1-2 C. By contrast, the LSTs show a midday summer UHIS of 3-4 C for cities in forests, whereas the average summer UHIA calculated from maximum air temperature is close to 0 C. In addition, the LSTs and air temperatures difference between 2006 and 2011 are in agreement, albeit with different magnitude.

Land Surface Temperature↗

NASA NTRS2013

Linking Climate to Incidence of Zoonotic Cutaneous Leishmaniasis (L. major) in Pre-Saharan North Africa

Shifts in surface climate may have changed the dynamic of zoonotic cutaneous leishmaniasis (ZCL) in the pre-Saharan zones of North Africa. Caused by Leishmania major, this form multiplies in the body of rodents serving as reservoirs of the disease. The parasite is then transmitted to human hosts by the bite of a Phlebotomine sand fly (Diptera: Psychodidae) that was previously fed by biting an infected reservoir. We examine the seasonal and interannual dynamics of the incidence of this ZCL as a function of surface climate indicators in two regions covering a large area of the semi-arid Pre-Saharan North Africa. Results suggest that in this area, changes in climate may have initiated a trophic cascade that resulted in an increase in ZCL incidence. We find the correlation between the rainy season precipitation and the same year Normalized Difference Vegetation Index (NDVI) to be strong for both regions while the number of cases of ZCL incidence lags the precipitation and NDVI by 2 years. The zoonotic cutaneous leishmaniasis seasonal dynamic appears to be controlled by minimum temperatures and presents a 2-month lag between the reported infection date and the presumed date when the infection actually occurred. The decadal increase in the number of ZCL occurrence in the region suggests that changes in climate increased minimum temperatures sufficiently and created conditions suitable for endemicity that did not previously exist. We also find that temperatures above a critical range suppress ZCL incidence by limiting the vector's reproductive activity.

NDIV↗

NASA NTRS2011

Exploring the Influence of Impervious Surface Density and Shape on Urban Heat Islands in the Northeast USA Using MODIS and Landsat

Impervious surface area (ISA) from the National Land Cover Database (NLCD) 2001 and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature and its relationship to settlement size and shape, development intensity distribution, and land cover composition for 42 urban settlements embedded in forest biomes in the Northeastern United States. Development intensity zones, based on percent ISA, are defined for each urban area emanating outward from the urban core to nearby rural areas and are used to stratify land surface temperature. The stratification is further constrained by biome type and elevation to insure objective intercomparisons between urban zones within an urban settlement and between settlements. Stratification based on ISA allows the definition of hierarchically ordered urban zones that are consistent across urban settlements and scales. In addition to the surrounding ecological context, we find that the settlement size and shape as well as the development intensity distribution significantly influence the amplitude of summer daytime UHI. Within the Northeastern US temperate broadleaf mixed forest, UHI magnitude is positively related to the logarithm of the urban area size. Our study indicates that for similar urban area sizes, the development intensity distribution is one of the major drivers of UHI. In addition to urban area size and development intensity distribution, this analysis shows that both the shape of the urban area and the land cover composition in the surrounding rural area play an important role in modulating the UHI magnitude in different urban settlements. Our results indicate that remotely sensed urban area size and shape as well as the development intensity distribution influence UHI amplitude across regional scales.

Zhang, Ping↗

NASA NTRS2011

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Zhang, Ping↗

NASA NTRS2011

Assessing the Urban Heat Island Effect Across Biomes in the Continental USA Using Landsat and MODIS

Impervious surface area (ISA) from the Landsat TM and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined across urban gradients and used to stratify sampling of LST and NDVI. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban - rural temperature difference) with the largest 8 C (average) for cities built in mixed forest biomes. For all cities ISA is the primary driver for increase in temperature explaining 70% of the total variance. Annually, urban areas are warmer than the non-urban fringe by 2.9 C, except in biomes with arid and semiarid climates. The average amplitude of the UHI is asymmetric with a 4.3 C difference in summer and 1.3 C in winter. In desert environments, UHI's point to a possible heat sink effect. Results show that the urban heat island amplitude increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.

Imhoff, Marc L.↗

NASA NTRS2010

Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship with development intensity, size, and ecological setting for more than 3000 urban settlements globally. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby nonurban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to ensure objective intercomparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass shrubs biomes; and only a weak UHI or sometimes an urban heat sink (UHS) in cities in arid and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) with the difference in vegetation density between urban and rural zones represented by the MODIS normalized difference vegetation index (NDVI). Globally averaged, the daytime UHI amplitude for all settlements is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers compared with 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude, with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variance is explained by ISA for urban settlements within forests at mid to high latitudes. This percentage will increase to more than 80% when only settlements in the US are examined.

Zhang, Ping↗

NASA NTRS2010

Remote Sensing of the Urban Heat Island Effect Across Biomes in the Continental USA

Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the nonurban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban-rural temperature difference) the largest (8 C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9 C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3 C temperature difference in summer and only 1.3 C in winter. In desert environments, the LST's response to ISA presents an uncharacteristic "U-shaped" horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI's calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes.

Imhoff, Marc L.↗

NASA NTRS2010

Characterizing Urban Heat Islands of Global Settlements Using MODIS and Nighttime Lights Products

Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship to development intensity, size, and ecological setting for more than 3000 urban settlements over the globe. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby non-urban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to insure objective inter-comparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass/shrub biomes, and only a weak UHI or sometimes an Urban Heat Sink (UHS) in cities in and and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) to the difference in vegetation density between urban and rural zones represented by MODIS Normalized Difference Vegetation Index (NDVI). Globally averaged, the daytime UHI amplitude for all settlement is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers, compared to 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variances is explained by ISA for urban settlements within forests at mid-to-high latitudes. This percentage will increase to more than 80% when only USA settlements are examined.

Zhang, Ping↗

NASA NTRS2006

The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products

The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.

Huang, Dong↗

NASA NTRS2005

Assessment of the Broadleaf Crops Leaf Area Index Product from the Terra MODIS Instrument

The first significant processing of Terra MODIS data, called Collection 3, covered the period from November 2000 to December 2002. The Collection 3 leaf area index (LAI) and fraction vegetation absorbed photosynthetically active radiation (FPAR) products for broadleaf crops exhibited three anomalies (a) high LAI values during the peak growing season, (b) differences in LAI seasonality between the radiative transfer-based main algorithm and the vegetation index based back-up algorithm, and (c) too few retrievals from the main algorithm during the summer period when the crops are at full flush. The cause of these anomalies is a mismatch between reflectances modeled by the algorithm and MODIS measurements. Therefore, the Look-Up-Tables accompanying the algorithm were revised and implemented in Collection 4 processing. The main algorithm with the revised Look-Up-Tables generated retrievals for over 80% of the pixels with valid data. Retrievals from the back-up algorithm, although few, should be used with caution as they are generated from surface reflectances with high uncertainties.

Tan, Bin↗