scholarly journals Applying Remote Sensing Technologies in Urban Landscapes of the Mediterranean

2020 ◽  
Vol 2 (1) ◽  
pp. 27-36
Author(s):  
Celestina M. G. Pedras ◽  
Helena Maria Fernandez ◽  
Rui Lança ◽  
Fernando Granja-Martins
Keyword(s):  
Mediterranean Climate ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Landscape ◽  
Urban Landscapes ◽  
Climate Data ◽  
Water Requirements ◽  
The Mediterranean ◽  
Almost All

There has been increasing pressure on water resources in cities due to the proliferation of urban green areas. In the Mediterranean climate, only a small part of the plants’ water needs is supplied by rainfall during the winter months. Thus, in Algarve (Portugal) irrigation of the urban landscapes is required almost all year round. The aims of this study were to evaluate the maintenance of the urban landscapes of São Brás de Alportel (Algarve) during a year, based on the characterization of the vegetation of the urban gardens, the climate data, the analysis of the irrigation systems, the calculation of the plants water requirements and the normalized difference vegetation index (NDVI). By crossing all this information, it was possible to understand if the current maintenance level is the most suitable for sustainable irrigated urban landscapes. In most of the gardens, it was possible to establish a relationship between the gross irrigation water requirements and NDVI. In general, the NDVI allowed us to study the urban landscape, through the monthly observation of the differences in the appearance and development of the vegetation.

scholarly journals Evaluating the Temperature Difference Parameter in the SSEBop Model with Satellite-Observed Land Surface Temperature Data

2019 ◽  
Vol 11 (16) ◽  
pp. 1947 ◽  
Author(s):  
Lei Ji ◽  
Gabriel B. Senay ◽  
Naga M. Velpuri ◽  
Stefanie Kagone
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Temperature Difference ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Weather Data ◽  
Climate Data ◽  
Modis Data ◽  
South Central

The Operational Simplified Surface Energy Balance (SSEBop) model uses the principle of satellite psychrometry to produce spatially explicit actual evapotranspiration (ETa) with remotely sensed and weather data. The temperature difference (dT) in the model is a predefined parameter quantifying the difference between surface temperature at bare soil and air temperature at canopy level. Because dT is derived from the average-sky net radiation based primarily on climate data, validation of the dT estimation is critical for assuring a high-quality ETa product. We used the Moderate Resolution Imaging Spectroradiometer (MODIS) data to evaluate the SSEBop dT estimation for the conterminous United States. MODIS data (2008–2017) were processed to compute the 10-year average land surface temperature (LST) and normalized difference vegetation index (NDVI) at 1 km resolution and 8-day interval. The observed dT (dTo) was computed from the LST difference between hot (NDVI < 0.25) and cold (NDVI > 0.7) pixels within each 2° × 2° sampling block. There were enough hot and cold pixels within each block to create dTo timeseries in the West Coast and South-Central regions. The comparison of dTo and modeled dT (dTm) showed high agreement, with a bias of 0.8 K and a correlation coefficient of 0.88 on average. This study concludes that the dTm estimation from the SSEBop model is reliable, which further assures the accuracy of the ETa estimation.

scholarly journals Detecting Patterns of Vegetation Gradual Changes (2001–2017) in Shiyang River Basin, Based on a Novel Framework

2019 ◽  
Vol 11 (21) ◽  
pp. 2475 ◽  
Author(s):  
Ju Wang ◽  
Yaowen Xie ◽  
Xiaoyun Wang ◽  
Jingru Dong ◽  
Qiang Bie
Keyword(s):  
River Basin ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Logistic Function ◽  
Linear Pattern ◽  
Shiyang River Basin ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
High Consistency ◽  
Almost All

A lot of timeseries satellite products have been well documented in exploring changes in ecosystems. However, algorithms allowing for measuring the directions, magnitudes, and timing of vegetation change, evaluating the major driving factors, and eventually predicting the future trends are still insufficient. A novel framework focusing on addressing this problem was proposed in this study according to the temporal trajectory of Normalized Difference Vegetation Index (NDVI) timeseries of Moderate Resolution Imaging Spectroradiometer (MODIS). It divided the inter-annual changes in vegetation into four patterns: linear, exponential, logarithmic, and logistic. All the three non-linear patterns were differentiated automatically by fitting a logistic function with prolonged NDVI timeseries. Finally, features of vegetation changes including where, when and how, were evaluated by the parameters in the logistic function. Our results showed that 87.39% of vegetation covered areas (maximum mean growing season NDVI in the 17 years not less than 0.2) in the Shiyng River basin experienced significant changes during 2001–2017. The linear pattern, exponential pattern, logarithmic pattern, and logistic pattern accounted for 36.53%, 20.16%, 15.42%, and 15.27%, respectively. Increasing trends were dominant in all the patterns. The spatial distribution in both the patterns and the transition years at which vegetation gains/losses began or ended is of high consistency. The main years of transition for the exponential increasing pattern, the logarithmic increasing pattern, and the logarithmic increasing pattern were 2008–2011, 2003–2004, and 2009–2010, respectively. The period of 2006–2008 was the foremost period that NDVIs started to decline in Liangzhou Oasis and Minqin Oasis where almost all the decreasing patterns were concentrated. Potential disturbances of vegetation gradual changes in the basin are refer to as urbanization, expansion or reduction of agricultural oases, as well as measures in ecological projects, such as greenhouses building, afforestation, grazing prohibition, etc.

scholarly journals Water requirement and crop coefficients of sorghum in Apodi Plateau

2021 ◽  
Vol 25 (10) ◽  
pp. 684-688
Author(s):  
João G. A. Lima ◽  
José Espínola Sobrinho ◽  
José F. de Medeiros ◽  
Paula C. Viana ◽  
Rudah M. Maniçoba
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Irrigation Management ◽  
High Growth ◽  
Crop Coefficient ◽  
Northeastern Brazil ◽  
Crop Evapotranspiration ◽  
Water Requirements ◽  
Total Crop ◽  
Crop Coefficients

ABSTRACT Sorghum is of significant economic importance for Northeastern Brazil, since it exhibits high growth rates in regions with irregular rainfall distribution and high temperatures, and is an alternative to corn, which has greater water requirements. Despite being a traditional crop in the region, there are few studies on irrigation management in the Apodi plateau. The aim of this study was to determine the evapotranspiration of the crop and the crop coefficient (Kc) for the different stages of sorghum growth in two cycles, and establish the relationship between the Kc and the normalized difference vegetation index (NDVI) obtained by radiometry. Two weighing lysimeters were used to estimate crop evapotranspiration (ETc). Reference evapotranspiration (ETo) was estimated by the Penman-Monteith method (FAO) and the crop coefficient determined using two methodologies: simple Kc and dual Kc. Total crop evapotranspiration in the two cycles was 452 and 557 mm. The ETc value was 23% higher in the second cycle compared to the first. The maximum Kc values for the first and second cycles were 1.21 and 1.35, respectively, using the dual Kc methodology. The linear relationship found between the Kc values and the NDVI allows monitoring and estimating the water requirements of the crop.

scholarly journals Dynamics of Vegetation Greenness and Its Response to Climate Change in Xinjiang over the Past Two Decades

2021 ◽  
Vol 13 (20) ◽  
pp. 4063
Author(s):  
Jie Xue ◽  
Yanyu Wang ◽  
Hongfen Teng ◽  
Nan Wang ◽  
Danlu Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Dynamic Change ◽  
Google Earth ◽  
Arid Areas ◽  
Climate Data ◽  
Northern Margin ◽  
The Past

Climate change has proven to have a profound impact on the growth of vegetation from various points of view. Understanding how vegetation changes and its response to climatic shift is of vital importance for describing their mutual relationships and projecting future land–climate interactions. Arid areas are considered to be regions that respond most strongly to climate change. Xinjiang, as a typical dryland in China, has received great attention lately for its unique ecological environment. However, comprehensive studies examining vegetation change and its driving factors across Xinjiang are rare. Here, we used the remote sensing datasets (MOD13A2 and TerraClimate) and data of meteorological stations to investigate the trends in the dynamic change in the Normalized Difference Vegetation Index (NDVI) and its response to climate change from 2000 to 2019 across Xinjiang based on the Google Earth platform. We found that the increment rates of growth-season mean and maximum NDVI were 0.0011 per year and 0.0013 per year, respectively, by averaging all of the pixels from the region. The results also showed that, compared with other land use types, cropland had the fastest greening rate, which was mainly distributed among the northern Tianshan Mountains and Southern Junggar Basin and the northern margin of the Tarim Basin. The vegetation browning areas primarily spread over the Ili River Valley where most grasslands were distributed. Moreover, there was a trend of warming and wetting across Xinjiang over the past 20 years; this was determined by analyzing the climate data. Through correlation analysis, we found that the contribution of precipitation to NDVI (R2 = 0.48) was greater than that of temperature to NDVI (R2 = 0.42) throughout Xinjiang. The Standardized Precipitation and Evapotranspiration Index (SPEI) was also computed to better investigate the correlation between climate change and vegetation growth in arid areas. Our results could improve the local management of dryland ecosystems and provide insights into the complex interaction between vegetation and climate change.

scholarly journals Paisagem urbana, espaços públicos e a gestão territorial em cidades médias paulistas: reflexões a partir de São Carlos, SP, Brasil

Terr Plural ◽  
2019 ◽  
Vol 13 (3) ◽  
pp. 141-164 ◽  
Author(s):  
Renata Bovo Peres ◽  
Sandra Regina Mota Silva ◽  
Luciana Bongiovanni Martins Schenk
Keyword(s):  
Urban Planning ◽  
Urban Landscape ◽  
Spatial Dynamics ◽  
Public Spaces ◽  
Sao Paulo ◽  
Urban Landscapes ◽  
São Paulo ◽  
Specific Context ◽  
Paulo State

This paper discusses the relationships between urban landscape, public spaces, and territorial management in one medium-sized city of São Paulo state. Three sets of approach are outlined: the establishment of parameters for the characterization of the medium-sized cities of São Paulo; the specific context of São Carlos, with biophysical characteristics conjugated with the socio-spatial dynamics of development and expansion; and the challenges and perspectives in the configuration and management of public spaces and urban landscapes. It is intended to reflect on articulations between the fields of landscape and urban planning and indicate applications to the studied context, with integrations between design, instruments, legislation, and public policies.

scholarly journals Paisagem urbana, espaços públicos e a gestão territorial em cidades médias paulistas: reflexões a partir de São Carlos, SP, Brasil

Terr Plural ◽  
2019 ◽  
Vol 13 (3) ◽  
pp. 141-164
Author(s):  
Renata Bovo Peres ◽  
Sandra Regina Mota Silva ◽  
Luciana Bongiovanni Martins Schenk
Keyword(s):  
Urban Planning ◽  
Urban Landscape ◽  
Spatial Dynamics ◽  
Public Spaces ◽  
Sao Paulo ◽  
Urban Landscapes ◽  
São Paulo ◽  
Specific Context ◽  
Paulo State

This paper discusses the relationships between urban landscape, public spaces, and territorial management in one medium-sized city of São Paulo state. Three sets of approach are outlined: the establishment of parameters for the characterization of the medium-sized cities of São Paulo; the specific context of São Carlos, with biophysical characteristics conjugated with the socio-spatial dynamics of development and expansion; and the challenges and perspectives in the configuration and management of public spaces and urban landscapes. It is intended to reflect on articulations between the fields of landscape and urban planning and indicate applications to the studied context, with integrations between design, instruments, legislation, and public policies.

scholarly journals The Utility of Sentinel-2 Spectral Data in Quantifying Above-Ground Carbon Stock in an Urban Reforested Landscape

2021 ◽  
Vol 13 (21) ◽  
pp. 4281
Author(s):  
Mthembeni Mngadi ◽  
John Odindi ◽  
Onisimo Mutanga
Keyword(s):  
Climate Change ◽  
Ecosystem Services ◽  
Spectral Data ◽  
Carbon Stock ◽  
Climate Change Mitigation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Landscapes ◽  
Change Mitigation ◽  
Sentinel 2

The transformation of the natural landscape into an impervious surface due to urbanization has often been considered an important driver of environmental change, affecting essential urban ecological processes and ecosystem services. Continuous forest degradation and deforestation due to urbanization have led to an increase in atmospheric carbon emissions, risks, and impacts associated with climate change within urban landscapes and beyond them. Hence, urban reforestation has become a reliable long-term alternative for carbon sink and climate change mitigation. However, there is an urgent need for spatially accurate and concise quantification of these forest carbon stocks in order to understand and effectively monitor the accumulation and progress on such ecosystem services. Hence, this study sought to examine the prospect of Sentinel-2 spectral data in quantifying carbon stock in a reforested urban landscape using the random forest ensemble. Results show that Sentinel-2 spectral data estimated reforested forest carbon stock to an RMSE between 0.378 and 0.466 t·ha−1 and R2 of 79.82 and 77.96% using calibration and validation datasets. Based on random forest variable selection and backward elimination approaches, the red-edge normalized difference vegetation index, enhanced vegetation index, modified simple ratio index, and normalized difference vegetation index were the best subset of predictor variables of carbon stock. These findings demonstrate the value and prospects of Sentinel-2 spectral data for predicting carbon stock in reforested urban landscapes. This information is critical for adopting informed management policies and plans for optimizing urban reforested landscapes carbon sequestration capacity and improving their climate change mitigation potential.

scholarly journals SPATIAL DISAGGREGATION OF LANDSAT-DERIVED LAND SURFACE TEMPERATURE OVER A HETEROGENEOUS URBAN LANDSCAPE USING PLANETSCOPE IMAGE DERIVATIVES

2020 ◽  
Vol XLIII-B5-2020 ◽  
pp. 115-122
Author(s):  
J. A. Cruz ◽  
J. A. Santos ◽  
A. Blanco
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Urban Landscape ◽  
Bare Soil ◽  
Ordinary Least Squares ◽  
Urban Landscapes ◽  
Ols Regression ◽  
Explanatory Variables

Abstract. Satellite-derived land surface temperature (LST) is frequently utilized to characterize the intensity of urban heat island (UHI) effect in highly urbanized and rapidly urbanizing cities. However, current spaceborne thermal sensors cannot capture temperature variations within heterogeneous urban landscapes at finer scales due to its coarse spatial resolution. This study aims to apply Regression-Kriging (RK) method to downscale a 30-meter Landsat-derived LST to 3 meters using different PlanetScope image derivatives. To avoid multicollinearity, exploratory regression was performed to reduce the initial set of 16 indices to 7 explanatory variables, namely, Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI), Normalized Pigment Chlorophyll Ratio Index (NPCRI), Visible Green-based Built-up Index (VgNIR-BI), Mean, Entropy, and Homogeneity. Ordinary Least Squares (OLS) regression was applied to fit the models and the residuals of the best performing models were interpolated using Ordinary Kriging technique and added back to the downscaled LST. The model with the highest accuracy was obtained using the combination of MSAVI, EVI, and Mean, with an R2 of 0.75 and RMSE of 1.12 °C, 0.58 °C, 0.80 °C, and 1.45 °C in estimating the LST of built-up, bare soil, vegetation, and water classes, respectively. The results indicate that the inclusion of textural features in the regression could improve model accuracy without increasing the variance of coefficient estimates. Moreover, RK method (RMSE = 1.10–1.16 °C) was proven to be a reliable downscaling technique because it redistributes the spatial variability of LST that were not preserved in the OLS regression (RMSE = 1.60–1.75 °C).

scholarly journals Quantifying Drought Sensitivity of Mediterranean Climate Vegetation to Recent Warming: A Case Study in Southern California

2019 ◽  
Vol 11 (24) ◽  
pp. 2902 ◽  
Author(s):  
Chunyu Dong ◽  
Glen MacDonald ◽  
Gregory S. Okin ◽  
Thomas W. Gillespie
Keyword(s):  
High Temperatures ◽  
Southern California ◽  
Mediterranean Climate ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coastal Sage Scrub ◽  
Drought Severity ◽  
Vegetation Types ◽  
Drought Sensitivity ◽  
The Future

A combination of drought and high temperatures (“global-change-type drought”) is projected to become increasingly common in Mediterranean climate regions. Recently, Southern California has experienced record-breaking high temperatures coupled with significant precipitation deficits, which provides opportunities to investigate the impacts of high temperatures on the drought sensitivity of Mediterranean climate vegetation. Responses of different vegetation types to drought are quantified using the Moderate Resolution Imaging Spectroradiometer (MODIS) data for the period 2000–2017. The contrasting responses of the vegetation types to drought are captured by the correlation and regression coefficients between Normalized Difference Vegetation Index (NDVI) anomalies and the Palmer Drought Severity Index (PDSI). A novel bootstrapping regression approach is used to decompose the relationships between the vegetation sensitivity (NDVI–PDSI regression slopes) and the principle climate factors (temperature and precipitation) associated with the drought. Significantly increased sensitivity to drought in warmer locations indicates the important role of temperature in exacerbating vulnerability; however, spatial precipitation variations do not demonstrate significant effects in modulating drought sensitivity. Based on annual NDVI response, chaparral is the most vulnerable community to warming, which will probably be severely affected by hotter droughts in the future. Drought sensitivity of coastal sage scrub (CSS) is also shown to be very responsive to warming in fall and winter. Grassland and developed land will likely be less affected by this warming. The sensitivity of the overall vegetation to temperature increases is particularly concerning, as it is the variable that has had the strongest secular trend in recent decades, which is expected to continue or strengthen in the future. Increased temperatures will probably alter vegetation distribution, as well as possibly increase annual grassland cover, and decrease the extent and ecological services provided by perennial woody Mediterranean climate ecosystems as well.

scholarly journals Vegetation Change and Its Response to Climate Change between 2000 and 2016 in Marshes of the Songnen Plain, Northeast China

2020 ◽  
Vol 12 (9) ◽  
pp. 3569 ◽  
Author(s):  
Yanji Wang ◽  
Xiangjin Shen ◽  
Ming Jiang ◽  
Xianguo Lu
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Maximum Temperature ◽  
Climate Data ◽  
Songnen Plain ◽  
Asymmetric Effects ◽  
Climate Change Effects

Songnen Plain is a representative semi-arid marshland in China. The Songnen Plain marshes have undergone obvious loss during the past decades. In order to protect and restore wetland vegetation, it is urgent to investigate the vegetation change and its response to climate change in the Songnen Plain marshes. Based on the normalized difference vegetation index (NDVI) and climate data, we investigated the spatiotemporal change of vegetation and its relationship with temperature and precipitation in the Songnen Plain marshes. During 2000–2016, the growing season mean NDVI of the Songnen Plain marshes significantly (p < 0.01) increased at a rate of 0.06/decade. For the climate change effects on vegetation, the growing season precipitation had a significant positive effect on the growing season NDVI of marshes. In addition, this study first found asymmetric effects of daytime maximum temperature (Tmax) and nighttime minimum temperature (Tmin) on NDVI of the Songnen Plain marshes: The growing season NDVI correlated negatively with Tmax but positively with Tmin. Considering the global asymmetric warming of Tmax and Tmin, more attention should be paid to these asymmetric effects of Tmax and Tmin on the vegetation of marshes.

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