EVALUATION OF THE POTENTIAL OF GREEN ROOFS APPLIED TO AN URBAN FABRIC USING GIS AND REMOTE SENSING DATA CASE OF THE NADOR CITY / MOROCCO

Abstract. Accelerated urban growth has affected many of the planet's natural processes. In cities, most of the surface is covered with asphalt and cement, which has changed the water and air cycles. To restore the balance of urban ecosystems, cities must find the means to create green spaces in an increasingly gray world. Green spaces provide the city and its inhabitants a better living environment. This article uses Nador city as a case study area, this project consists in studying the possibility for the roofs to receive vegetation. The first axis of this project is the quantification of the current vegetation cover at ground level by calculating the Normalized Difference Vegetation Index (NDVI) based on Satellite images Landsat 8, then the classification of the LiDAR point cloud, and the generation of a digital surface model (DSM) of the urban area. This type of derived data was used as the basis for the various stages of estimating the potential plant cover at the roof level. In order to study the different possible scenarios, a set of criteria was applied, such as the minimum roof area, the inclination and the duration of the sunshine on the roof, which is calculated using the linear model of angstrom Prescott based on solar radiation. The study shows that in the most conservative scenario, 21771 suitable buildings that had to be redeveloped into green roofs, with an appropriate surface area of 369.26Ha allowing a 63,40% increase in the city's green space by compared to the current state contributing to the improvement of the quality of life and urban comfort. The average budget for the installation of green roofs in a building with a surface area of 100 m2 varies between 60000dh and 170000dh depending on the type of green roofs used, extensive or intensive. These results would enable planners and researchers in green architecture sciences to carry out more detailed planning analyzes.

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A new method for estimating of evapotranspiration and surface soil moisture from optical and thermal infrared measurements: the simplified triangle

10.31219/osf.io/65xkt ◽

2020 ◽

Author(s):

Toby N. Carlson ◽

George Petropoulos

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Heat Fluxes ◽

Surface Model ◽

Landsat 8 ◽

Simple Method ◽

Practical Applications ◽

Infrared Measurements

Earth Observation (EO) provides a promising approach towards deriving accurate spatiotemporal estimates of key parameters characterizing land surface interactions, such as latent (LE) and sensible (H) heat fluxes as well as soil moisture content. This paper proposes a very simple method to implement, yet reliable to calculate evapotranspiration fraction (EF) and surface moisture availability (Mo) from remotely sensed imagery of Normalized Difference Vegetation Index (NDVI) and surface radiometric temperature (Tir). The method is unique in that it derives all of its information solely from these two images. As such, it does not depend on knowing ancillary surface or atmospheric parameters, nor does it require the use of a land surface model. The procedure for computing spatiotemporal estimates of these important land surface parameters is outlined herein stepwise for practical application by the user. Moreover, as the newly developedscheme is not tied to any particular sensor, it can also beimplemented with technologically advanced EO sensors launched recently or planned to be launched such as Landsat 8 and Sentinel 3. The latter offers a number of key advantages in terms of future implementation of the method and wider use for research and practical applications alike.

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Multi-criteria modelling of drought: a study of Brandenburg Federal State, Germany

Modeling Earth Systems and Environment ◽

10.1007/s40808-021-01197-2 ◽

2021 ◽

Author(s):

Christopher Ihinegbu ◽

Taiwo Ogunwumi

Keyword(s):

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Agricultural Land ◽

Federal State ◽

Landsat 8 ◽

Gis And Remote Sensing ◽

Drought Assessment

AbstractDrought is the absence or below-required supply of precipitation, runoff and or moisture for an extended time period. Modelling drought is relevant in assessing drought incidence and pattern. This study aimed to model the spatial variation and incidence of the 2018 drought in Brandenburg using GIS and remote sensing. To achieve this, we employed a Multi-Criteria Approach (MCA) by using three parameters including Precipitation, Land Surface Temperature and Normalized Difference Vegetation Index (NDVI). We acquired the precipitation data from Deutsche Wetterdienst, Land Surface Temperature and NDVI from Landsat 8 imageries on the USGS Earth Explorer. The datasets were analyzed using ArcGIS 10.7. The information from these three datasets was used as parameters in assessing drought prevalence using the MCA. The MCA was used in developing the drought model, ‘PLAN’, which was used to classify the study area into three levels/zones of drought prevalence: moderate, high and extreme drought. We went further to quantify the agricultural areas affected by drought in the study area by integrating the land use map. Results revealed that 92% of the study area was severely and highly affected by drought especially in districts of Oberhavel, Uckermark, Potsdam-Staedte, and Teltow-Flaeming. Finding also revealed that 77.54% of the total agricultural land falls within the high drought zones. We advocated for the application of drought models (such as ‘PLAN’), that incorporates flexibility (tailoring to study needs) and multi-criteria (robustness) in drought assessment. We also suggested that adaptive drought management should be championed using drought prevalence mapping.

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Quantitative Assessment of Land Cover Sensitivity to Desertification in Maigatari Local Government Area, Jigawa State, Nigeria

Journal of Applied Sciences and Environmental Management ◽

10.4314/jasem.v24i9.4 ◽

2020 ◽

Vol 24 (9) ◽

pp. 1509-1517

Author(s):

A. Ahmed ◽

S. Abba ◽

F. Siriki ◽

B. Maman

Keyword(s):

Land Cover ◽

Land Degradation ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Soil Depth ◽

Plant Cover ◽

Organic Matter Content ◽

Matter Content ◽

Landsat 8 ◽

Topographic Map

Desertification alludes to land degradation in arid, semi-arid and sub-humid regions resulting from various variables, counting climatic variations and human activities. When land degradation transpire within the world’s drylands. It regularly makes desert-like conditions. Land degradation occurs all over, but is characterized as desertification when it occurs within the drylands. The study employed adjusted MEDALUS methodology using eleven indicators rainfall, evapotranspiration, aridity, soil texture, soil depth, slope gradient, drainage density, plant cover, erosion protection, sensitivity desertification index and Normalized Difference Vegetation Index (NDVI). Remote Sensing and GIS were the main techniques used in the indices computations and mapping. Thus, Shuttle Rader Topographic Map (SRTM) and Landsat 8 satellite imagery for the year 2019 with 30 meter resolution, captured in the month of August (rainy season), covering the study area were acquired from Global Land cover Facility (GLCF) University of Maryland. The study finds that the duration and intensity of rainfall is declining especially at the edge of the desert, extreme north and western part of the area. Rain quickly drained through infiltration and surface runoff which carried the little nutrients attached to the soil. Rainfall and climate is of arid type recording about 300-400mm of rainfall and the soil is low in organic matter content making it weak and less fertile and support only the cultivation of cereals and legumes. The study recommends that there is need to strengthen the laws and policies in controlling desertification and land degradation, establishment of shelterbelts to control desertification and act also as wind breakers and encourage the use of modern techniques such as drip irrigation to check the rate of infiltration and runoff. Keyword: Desertification; Sensitivity; MEDALUS; GIS; Maigatari

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IDENTIFIKASI PERUBAHAN KERAPATAN VEGETASI KOTA MANADO TAHUN 2001 SAMPAI 2015

MAJALAH ILMIAH GLOBE ◽

10.24895/mig.2017.19-1.448 ◽

2017 ◽

Vol 19 (1) ◽

pp. 65

Author(s):

Nurlita Indah Wahyuni ◽

Diah Irawati Dwi Arini ◽

Afandi Ahmad

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landsat 8 ◽

Vegetation Density ◽

Forage Crops ◽

Area Change ◽

Gis And Remote Sensing ◽

Crown Density ◽

Landsat 7 ◽

The Impact

ABSTRAKKebutuhan manusia akan lahan di wilayah perkotaan menyebabkan perubahan fungsi lahan terutama pada area bervegetasi. Penelitian bertujuan untuk mengkaji perubahan kerapatan vegetasi tahun 2001 dan 2015 di Kota Manado serta pengaruhnya terhadap kualitas lingkungan. Penelitian dimulai dengan melakukan pengumpulan data citra satelit Landsat 7 tahun 2001 tanggal akuisisi 14 Februari 2001 dan Landsat 8 tanggal akusisi 25 Maret 2015, data-data pendukung lainnya yaitu peta administrasi kota Manado tahun 2010, peta rupa bumi kota Manado skala 1:50.000. Metode yang digunakan dalam penelitian ini adalah perbandingan nilai normalized difference vegetation index (NDVI) dengan kanal merah (red) dan infra merah dekat (NIR) yang sudah dikonversi ke nilai reflektan. Teknik analisis menggunakan Sistem Informasi Geografis (SIG) dan penginderaan jauh dengan menentukan kerapatan vegetasi dan diklasifikasikan menjadi kelas kerapatan. Hasil penelitian menunjukkan bahwa perbandingan kelas kerapatan antara 2001 dan 2015 sebagai berikut kelas tidak bervegetasi (air dan awan) mengalami peningkatan sebesar 14,29%, kelas tidak rapat (lahan kosong, pemukiman, bangunan, dan industri) mengalami peningkatan sebesar 42,56%, kelas cukup rapat (tegalan dan tumbuhan ternak) mengalami peningkatan sebesar 48,94%, kelas rapat (perkebunan, sawah kering, dan semak belukar) mengalami penurunan sebesar 68,46% dan kelas sangat rapat (hutan lebat) mengalami penurunan sebesar 314,07%. Selama kurun waktu 15 tahun penurunan areal bervegetasi di Kota Manado diperkirakan 10,57%. Perubahan areal bervegetasi di Kota Manado signifikan terjadi karena kegiatan reklamasi pantai menjadi lahan terbangun serta lahan kosong dan perkebunan menjadi perumahan. Dampak yang saat ini mulai dirasakan dengan adanya perubahan areal bervegetasi adalah peningkatan suhu dan polusi udara di wilayah perkotaan.Kata kunci:Landsat, Normalized Difference Vegetation Index (NDVI), kerapatan, Kota Manado ABSTRACTHuman demand on urban land has brought various impacts toward land use, one of them is vegetation area change. This study aims to identify vegetation density change between period 2001 and 2015 in Manado area along with its influence toward environment quality. The data was collected from Landsat 7 imagery with acquisition date on February 14th 2001 and Landsat 8 imagery with acquisition date on March 25th 2015. Supporting data i.e. administrative map of Manado City in 2010 and basic map of Manado in scale 1:50.000. We compared normalized difference vegetation index (NDVI) between red band and near infra red (NIR) band. Geographic Information System (GIS) and remote sensing techniques were used to determine and classify crown density of vegetation. The result showed that the density class comparison between 2001 and 2015 were: no vegetation (water body and cloud) increased 14,29%, low dense (bareland, residence, buildings and industry) increased 42,56%, moderately dense (garden and forage crops) increased 48,94%, dense (plantation, dry field and shrubs) decreased 68,46% and highly dense (forest) decreased 314,07%. In the period 15 years there was decreasing of vegetation area in Manado city 10,57% approximately. The significance change of Manado City was occurred due to coast reclamation into building area as well as bare land and plantation become residence. The impact of vegetation area change is the increasing of temperature and air pollution in urban area.Keywords: Landsat, Normalized Difference Vegetation Index (NDVI), density, Manado City

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Using Landsat 8 data to compare percent impervious surface area and normalized difference vegetation index as indicators of urban heat island effects in Connecticut, USA

Environmental Earth Sciences ◽

10.1007/s12665-020-09159-0 ◽

2020 ◽

Vol 79 (18) ◽

Author(s):

Zhiyuan Yang ◽

Chandi Witharana ◽

James Hurd ◽

Kao Wang ◽

Runmei Hao ◽

...

Keyword(s):

Urban Heat Island ◽

Surface Area ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Impervious Surface ◽

Landsat 8 ◽

Heat Island ◽

Impervious Surface Area ◽

Urban Heat

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Geomorphologic Change in Nagavali River Basin: Geospatial Approach

International Journal of Environment and Climate Change ◽

10.9734/ijecc/2021/v11i1230574 ◽

2021 ◽

pp. 235-250

Author(s):

Siba Prasad Mishra ◽

Ashish Patel ◽

Abhisek Mishra ◽

Chandan Kumar

Keyword(s):

Land Use ◽

Land Cover ◽

River Basin ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landsat 8 ◽

Gis And Remote Sensing ◽

Human Habitation ◽

Soil Water Resources

The Nagavali river basin (NRB), along east coast of India investigated for its land use and land cover changes (LULCC) in the golden spike period of Anthropocene Epoch. Attempts made to assess the vicissitudes, causes, and consequences of natural resources, and soil/water resources of the NRB in last three decades as significant changes in hydro-climatic variables occurred. The interstate basin is well developed in lower reaches (north Andhra Pradesh) whereas upper stretches, South Odisha is less organized. GIS and remote sensing are efficient tools for an ideal study of LULCC of the area. Present work evaluates the dynamics of LULCC of NRB. LANDSAT-5, LANDSAT-8, of 1990, 2000, 2010 and 2020, respectively, were digitally classified for land use land cover mapping. The changing aspects of LULCC critically analyzed for three span, 1990–2000, 2000–2010 and 2010–2020. Through Normalized Difference Vegetation Index (NDVI) of the NRB examined carefully to assess the recent LULCC pattern. Major changes are sue to exchanges of areas are in between forest and built-up land followed by water body. The transformations are from forest to human habitation; especially built-up area that constitutes major percentage of the total landscape. The study shows that emphasis is necessary on more water consolidation projects in the upper Nagavali Basin considering the long-term LULC trend analysis.

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A New Method for Estimating of Evapotranspiration and Surface Soil Moisture from Optical and Thermal Infrared Measurements: The Simplified Triangle

10.31219/osf.io/qy57k ◽

2019 ◽

Cited By ~ 1

Author(s):

Toby N. Carlson ◽

George Petropoulos

Keyword(s):

Soil Moisture ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Heat Fluxes ◽

Surface Model ◽

Landsat 8 ◽

Simple Method ◽

Practical Applications ◽

Infrared Measurements

Earth Observation (EO) provides a promising approach towards deriving accurate spatiotemporal estimates of key parameters characterizing land surface interactions, such as latent (LE) and sensible (H) heat fluxes as well as soil moisture content. This paper proposes a very simple method to implement, yet reliable to calculate evapotranspiration fraction (EF) and surface moisture availability (Mo) from remotely sensed imagery of Normalized Difference Vegetation Index (NDVI) and surface radiometric temperature (Tir). The method is unique in that it derives all of its information solely from these two images. As such, it does not depend on knowing ancillary surface or atmospheric parameters, nor does it require the use of a land surface model. The procedure for computing spatiotemporal estimates of these important land surface parameters is outlined herein stepwise for practical application by the user. Moreover, as the newly developed scheme is not tied to any particular sensor, it can also be implemented with technologically advanced EO sensors launched recently or planned to be launched such as Landsat 8 and Sentinel 3. The latter offers a number of key advantages in terms of future implementation of the method and wider use for research and practical applications alike.

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Seasonal analysis on land surface temperature (LST) and normalized difference vegetation index (NDVI) variations in the Iguatu semi-arid hinterland, ceará

International Journal of Hydrology ◽

10.15406/ijh.2021.05.00290 ◽

2021 ◽

Vol 5 (6) ◽

pp. 289-294

Author(s):

Yara Batista Gomes ◽

Isorlanda Caracristi

Keyword(s):

Surface Temperature ◽

Urban Area ◽

Land Surface ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Plant Cover ◽

Landsat 8 ◽

Wet Season ◽

Seasonal Behavior ◽

South Central

The following paper analyzes the seasonal behavior of surface temperature and vegetation conditions from Landsat 8 satellite images in Iguatu, located in South-central Ceará, Brazil. The guiding method was the Urban Climate System (UCS) along with works with specific literature. Concerning the LSTs during the wet season, the urban area recorded 30.8°C, whereas the countryside verified milder thermal conditions than in downtown, especially in the southwestern region (19.2°C to 23.1°C). The NDVI values in April (wet season) for the urban area and part of the suburbs showed (0.00) because of civil constructions and little vegetation present in the area, except for the surroundings of the Bastiana and Cocobó lagoons – ranging between (0.59 and 0.79), which represents a green area. In August (dry season), there was an expressive spatial distribution of surface temperature around 32 °C. The NDVI was (-0.01) in the densely occupied area and (0.67) in the urban lagoons during the same period. The land use and its plant cover reflect significantly in the distribution and intensity of surface temperatures, as verified in the research.

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TEMPERATURA DE SUPERFÍCIE E A RELAÇÃO COM O ÍNDICE DE VEGETAÇÃO POR DIFERENÇA NORMALIZADA (NDVI) NA MICROBACIA DO RIO DA BATATEIRAS, CRATO-CE

Revista da Casa da Geografia de Sobral (RCGS) ◽

10.35701/rcgs.v21n2.548 ◽

2019 ◽

Vol 21 (2) ◽

pp. 1310-1320

Author(s):

Cícera Celiane Januário da Silva ◽

Vinicius Ferreira Luna ◽

Joyce Ferreira Gomes ◽

Juliana Maria Oliveira Silva

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Temperature Measurement ◽

Rainy Season ◽

Satellite Images ◽

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Landsat 8 ◽

Low Density ◽

Difference Map

O objetivo do presente trabalho é fazer uma comparação entre a temperatura de superfície e o Índice de Vegetação por Diferença Normalizada (NDVI) na microbacia do rio da Batateiras/Crato-CE em dois períodos do ano de 2017, um chuvoso (abril) e um seco (setembro) como também analisar o mapa de diferença de temperatura nesses dois referidos períodos. Foram utilizadas imagens de satélite LANDSAT 8 (banda 10) para mensuração de temperatura e a banda 4 e 5 para geração do NDVI. As análises demonstram que no mês de abril a temperatura da superfície variou aproximadamente entre 23.2ºC e 31.06ºC, enquanto no mês correspondente a setembro, os valores variaram de 25°C e 40.5°C, sendo que as maiores temperaturas foram encontradas em locais com baixa densidade de vegetação, de acordo com a carta de NDVI desses dois meses. A maior diferença de temperatura desses dois meses foi de 14.2°C indicando que ocorre um aumento da temperatura proporcionado pelo período que corresponde a um dos mais secos da região, diferentemente de abril que está no período de chuvas e tem uma maior umidade, presença de vegetação e corpos d’água que amenizam a temperatura.Palavras-chave: Sensoriamento Remoto; Vegetação; Microbacia. ABSTRACTThe objective of the present work is to compare the surface temperature and the Normalized Difference Vegetation Index (NDVI) in the Batateiras / Crato-CE river basin in two periods of 2017, one rainy (April) and one (September) and to analyze the temperature difference map in these two periods. LANDSAT 8 (band 10) satellite images were used for temperature measurement and band 4 and 5 for NDVI generation. The analyzes show that in April the surface temperature varied approximately between 23.2ºC and 31.06ºC, while in the month corresponding to September, the values ranged from 25ºC and 40.5ºC, and the highest temperatures were found in locations with low density of vegetation, according to the NDVI letter of these two months. The highest difference in temperature for these two months was 14.2 ° C, indicating that there is an increase in temperature provided by the period that corresponds to one of the driest in the region, unlike April that is in the rainy season and has a higher humidity, presence of vegetation and water bodies that soften the temperature.Key-words: Remote sensing; Vegetation; Microbasin.RESUMENEl objetivo del presente trabajo es hacer una comparación entre la temperatura de la superficie y el Índice de Vegetación de Diferencia Normalizada (NDVI) en la cuenca Batateiras / Crato-CE en dos períodos de 2017, uno lluvioso (abril) y uno (Septiembre), así como analizar el mapa de diferencia de temperatura en estos dos períodos. Las imágenes de satélite LANDSAT 8 (banda 10) se utilizaron para la medición de temperatura y las bandas 4 y 5 para la generación de NDVI. Los análisis muestran que en abril la temperatura de la superficie varió aproximadamente entre 23.2ºC y 31.06ºC, mientras que en el mes correspondiente a septiembre, los valores oscilaron entre 25 ° C y 40.5 ° C, y las temperaturas más altas se encontraron en lugares con baja densidad de vegetación, según el gráfico NDVI de estos dos meses. La mayor diferencia de temperatura de estos dos meses fue de 14.2 ° C, lo que indica que hay un aumento en la temperatura proporcionada por el período que corresponde a uno de los más secos de la región, a diferencia de abril que está en la temporada de lluvias y tiene una mayor humedad, presencia de vegetación y cuerpos de agua que suavizan la temperatura.Palabras clave: Detección remota; vegetación; Cuenca.

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Mapping Public Urban Green Spaces Based on OpenStreetMap and Sentinel-2 Imagery Using Belief Functions

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10040251 ◽

2021 ◽

Vol 10 (4) ◽

pp. 251

Author(s):

Christina Ludwig ◽

Robert Hecht ◽

Sven Lautenbach ◽

Martin Schorcht ◽

Alexander Zipf

Keyword(s):

Vegetation Index ◽

Normalized Difference Vegetation Index ◽

Open Data ◽

Green Spaces ◽

Data Sets ◽

Urban Green ◽

Urban Green Spaces ◽

Urban Quality Of Life ◽

Shafer Theory ◽

Sentinel 2

Public urban green spaces are important for the urban quality of life. Still, comprehensive open data sets on urban green spaces are not available for most cities. As open and globally available data sets, the potential of Sentinel-2 satellite imagery and OpenStreetMap (OSM) data for urban green space mapping is high but limited due to their respective uncertainties. Sentinel-2 imagery cannot distinguish public from private green spaces and its spatial resolution of 10 m fails to capture fine-grained urban structures, while in OSM green spaces are not mapped consistently and with the same level of completeness everywhere. To address these limitations, we propose to fuse these data sets under explicit consideration of their uncertainties. The Sentinel-2 derived Normalized Difference Vegetation Index was fused with OSM data using the Dempster–Shafer theory to enhance the detection of small vegetated areas. The distinction between public and private green spaces was achieved using a Bayesian hierarchical model and OSM data. The analysis was performed based on land use parcels derived from OSM data and tested for the city of Dresden, Germany. The overall accuracy of the final map of public urban green spaces was 95% and was mainly influenced by the uncertainty of the public accessibility model.

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