Wyniki wyszukiwania - Biblioteka Nauki

1

Remote sensing techniques to assess chlorophyll lfuorescence in support of crop monitoring in Poland

100%

Gurdak R. , Bartold M.

Miscellanea Geographica. Regional Studies on Development

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2021

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tom 25

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nr 4

EN

The increase in demand for food and the need to predict the impact of a warming climate on vegetation makes it critical that the best tools for assessing crop production are found. Chlorophyll fluorescence (ChlF) has been proposed as a direct indicator of photosynthesis and plant condition. The aim of this paper is to study the feasibility of estimating ChlF from spectral vegetation indices derived from Sentinel-2, in order to monitor crop stress and investigate ChlF changes in response to surface temperatures and meteorological observations. The regressions between thirty three Sentinel-2-derived VIs, and ChlF measured on the ground were evaluated in order to estimate the best predictors of ChlF. The r-Pearson correlation and polynomial linear regression were used. For maize, the highest correlation between ChlF and VIs were found for NDII (r=0.65) and for SIPI (r=-0.68). The weakest relationship between VIs and ChlF were found for sugar beets. Despite this, it should be noted that the highest correlation for sugar beets appeared for EVI (r=0.45) and S2REP (r=0.43). The results of this study indicate the need for a synergy of low and high resolution satellite data that will enable a more detailed analysis for estimating fluorescence and its relation to climatic conditions, environmental aspects, and VIs derived from satellite images.

2

Estimation of land surface temperature using Landsat satellite data: A case study of Mueang Maha Sarakham District, Maha Sarakham Province, Thailand for the years 2006 and 2015

100%

Rotjanakusol T. , Laosuwan T.

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2018

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tom Vol. 28, No. 4

401--409

EN

At present, the climate has constantly been changing, especially the increase in global average temperature that results in the risk of severe climatic conditions such as heat wave, drought and flood. The objective of this study is to estimate land surface temperature (LST) by applying Landsat satellite data in Mueang Maha Sarakham District, Maha Sarakham Province, Thailand. The study focuses on investigating the temperature changes for the years 2006 and 2015. The research was conducted by analyzing the satellite data in the thermal infrared band with a geo-informatics package software mutually with mathematical models. The operation results indicated that the average LST was at 26.28°C in 2006 and 27.15°C in 2015. In order to verify the accuracy of the data in this study, the results of the annual satellite data analysis were brought to find out a statistical correlation with the LST data from the Meteorological Station of Thai Meteorological Department (TMD). The results indicated that there was a correlation of the data at a high level in 2006 and 2015. The results of this study indicated that the satellite data analysis method is reliable and can be used to analyze, track, and verify data to predict surface temperatures effectively.

3

Links between Land Use Change, Land Surface Temperature and Partridge Distribution – An Analysis of Environmental Factors

88%

El Fallah K. , Ouhakki H. , Adiba A. , El Kharrim K. , Belghyti D.

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tom Vol. 25, iss. 1

260--275

EN

The purpose of this research was to investigate the intricate connections among land use change, land surface temperature, and the distribution of partridges (Alectoris barbara), employing a comprehensive analysis of various environmental factors. Indeed, a variety of geospatial techniques have been used to analyze the spatio-temporal trends in temperature as a function of different classes of vegetation cover, and the geographic distribution of ecological niches for this species in Meknes province was modeled using Maxent 3.2 (Maximum Entropy) software. The study spanned a 22-year timeframe, from 2000 to 2021, during which alterations in each land use category were identified through the utilization of various sensors, incorporating Landsat 7 ETM+ and Landsat 8 OLI/TIRS in the analysis. The results induced a significant change in the land surface temperature (LST) with a range of 15.85–36.20°C, 12.76–38.24°C and 25.73–47.79°C for the years 2000, 2010 and 2020, respectively. However, this change was negatively correlated with the normalized difference vegetation index (NDVI). This decline in vegetation, in turn, manifests as a significant factor contributing to the diminution of partridge distribution. By empirically establishing these connections, the research not only underscores the impact of temperature-induced vegetation changes on partridge habitat but also enhances comprehension of the intricate ecological dynamics governing species distribution in the context of evolving land use patterns.

4

The analysis of fire hotspot distribution in Kalimantan and its relationship with ENSO phases

88%

Zahra R. A. , Nurjani E. , Sekaranom A. B.

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nr 1

75-86

EN

Kalimantan experiences fire hazards almost every year, which threaten the largest tropical forest in Southeast Asia. Climatic conditions, such as increasing surface temperature and decreasing rainfall, become important especially when El Nino Southern Oscillation (ENSO) occurs. Studies on fire are commonly conducted based on the climatic condition such as the dry or wet season, but those which focused on analysis of fire occurrences with the specific ENSO phases are still limited. This study aims to identify the spatial and temporal distribution of rainfall, land surface temperature, and soil moisture and analyses the distribution of hotspots in Kalimantan from 2014 to 2020 during different ENSO phases. The data used are Moderate Resolution Imaging Spectroradiometer (MODIS) for hotspot analysis, Global Precipitation Measurement (GPM) for rainfall analysis, MODIS Land Surface Temperature (LST) for surface temperature analysis and Soil Moisture Active Passive (SMAP) for soil moisture analysis. The methods used were descriptive and spatial analyses based on each ENSO phase, which were then combined to analyse the temporal and spatial distribution of fire, rainfall, LST and soil moisture. The temporal distribution shows a positive relationship between ENSO, rainfall, LST, soil moisture and hotspots with a confidence level of 90% in the dry months of August– October. Fire occurred in most parts of West and Central Kalimantan, associated with low elevation, organic soil types and agricultural peatland. The average trend of increasing hotspots is 17.4% in the El Nino phase and decreasing hot- spots by 84.7% in the La Nina phase during August–October in Kalimantan.

5

Comparison of direct and inverse methods of satellite observations downscaling for the coastal zone area

88%

Chybicki A. , Łubniewski Z.

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tom Vol. 19

55--64

EN

The Earth observation satellite imaging systems have known limitations, especially regarding their spatial and temporal resolution. Therefore, approaches which aim to combine data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution are of high interest. This allows for joint utilization of the advantages of both these types of sensors. As there are several ways to achieve this goal, in this paper two approaches, direct and inverse, of downscaling the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR) were evaluated. The applied downscaling methods utilize biophysical properties of the surface sensed using short wave infrared and thermal band. The presented algorithm evaluation was performed on the basis of a specific test case: the coastal zone area of the Gulf of Gdańsk, Poland. In this context, the objective presented in the study was to compare two methods of downscaling for a specific test case in order to evaluate how the proposed approaches cope with the specific conditions of the coastal zone area.

6

Analysis of cold island effect in city parks from the perspectives of maximum and cumulative values : a case study of Xi'an City

88%

Zhang Y. , Wang Q. , Kong Y. , Quan J. , Zhang Y. , Zhang Y.

Archives of Environmental Protection

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2024

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tom Vol. 50, no 1

95--109

EN

The continuous process of urbanization and climate change has led to severe urban heat island (UHI) effects. Constructing parks with cooling capabilities is considered an effective measure to alleviate UHI effects. However, most studies only quantify the cooling effect from a maximum value perspective, lacking a measure of temperature diffusion in space. This study combines the perspectives of maximum value and accumulation to define a cold island index, quantifying the cooling effect of 40 urban parks in the main urban area of Xi'an city. The results show that, on average, urban parks can reduce the surrounding environment by approximately 2.3℃, with a cooling range of about 127.1ha, which is three times the park area. Different factors drive the measurement of the cooling effect using different cold island indexes, but all indexes are highly correlated with green space area. There are significant differences in the cooling effect among different types of parks, and overall, ecological parks have the best cooling effect. The directional spread of internal cold islands in parks is most related to park shape, while external spread is related to surrounding green spaces. The research results have practical value in the construction of parks with cooling effects and the sustainable development of cities in urban planning processes.

7

Regional Mapping of Land Surface Temperature (LST), Land Surface Emissivity (LSE) and Normalized Difference Vegetation Index (NDVI) of South-South Coastal Settlements of Rivers State in Nigeria

75%

Nwaerema P. , Ajiere S.

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tom 28

76-86

EN

This study is the regional mapping of Land Surface temperature (LST), Land Surface Emissivity (LSE) and Normalized Difference Vegetation Index (NDVI) of south-south coastal settlements of Rivers State in Nigeria. The Google Earth Engine (GEE) of satellite remote sensing origin was used in the study. It was observed that land surface area of the south-south coastal settlements of the region hosting a total population of 3,344,706 persons had undergone severe modification and alteration of vegetal cover by increased human activities especially in the central area. Emissivity in the region increased from the center to the rural settlements with values ranging 0.98 to 0.99 and difference of 0.01 indicating that there was increased modification of the regional land surface. Land surface temperature decreased from the regional center to the rural settlements ranging between 22.12 ºC to 35.99 ºC with a difference of 13.87 ºC. However, LST was scattered in different settlement spots especially in the northern region such as Aleto, Finema (south); Rumuolu, Odogwa, Abara, Umuechem, Rumuola, Ambroda (north) among others. The normalized vegetation index showed -0.54358 to 0.409327 having the difference of 0.952907 indicating greater variation in vegetal cover across the region. Thus, NDVI in the region increased from the regional center to the outskirts of the area. Urbanization in the south-south region of Rivers State had extended severely to the rural settlements. Therefore, it is recommended that policy makers and regional planners should protect the area from adverse vegetal lost and heat effects by implementing regional greening practices.

8

Monitoring of Land Surface Temperature from Landsat Imagery: A Case Study of Al-Anbar Governorate in Iraq

63%

Morsy S. , Ahmed S.

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tom Vol. 17, no. 3

61--81

EN

Land surface temperature (LST) estimation is a crucial topic for many applications related to climate, land cover, and hydrology. In this research, LST estimation and monitoring of the main part of Al-Anbar Governorate in Iraq is presented using Landsat imagery from five years (2005, 2010, 2015, 2016 and 2020). Images of the years 2005 and 2010 were captured by Landsat 5 (TM) and the others were captured by Landsat 8 (OLI/TIRS). The Single Channel Algorithm was applied to retrieve the LST from Landsat 5 and Landsat 8 images. Moreover, the land use/land cover (LULC) maps were developed for the five years using the maximum likelihood classifier. The difference in the LST and normalized difference vegetation index (NDVI) values over this period was observed due to the changes in LULC. Finally, a regression analysis was conducted to model the relationship between the LST and NDVI. The results showed that the highest LST of the study area was recorded in 2016 (min = 21.1°C, max = 53.2°C and mean = 40.8°C). This was attributed to the fact that many people were displaced and had left their agricultural fields. Therefore, thousands of hectares of land which had previously been green land became desertified. This conclusion was supported by comparing the agricultural land areas registered throughout the presented years. The polynomial regression analysis of LST and NDVI revealed a better coefficient of determination (R2) than the linear regression analysis with an average R2 of 0.423.

9

A study of thermal controls in rapidly developing city using remotely sensed satellite data: spatiotemporal perspective

63%

Mahmood K. , Raza S. A. , Fatima S. Y.

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tom Vol. 69, no. 1

365--379

EN

The unsusual rise in the land surface temperature is playing a vital role toward the rapid and intense changes in global climate. Occurrence of certain land use land cover and alternative changes in them is the prime cause of bringing extreme changes in temperature. In this research, using 30-year long time series (1988–2018) data from Landsat satellites for understanding relation of mean temperature with the two largest and main controlling land use classes (vegetation and built-up) in a rapidly urbanizing district, Lahore. For this purpose, multivariate statistical approaches of scatter plot and correlation coefcient were employed. Temperatures, vegetative and built-up areas were derived using a combination of diferent spatiotemporal tools in a specifcally designed model. Critical analysis suggests breaking up of investigation timeline in two portions based on changing trend. A 23-year period from 1989 to 2011 (Temporal Window-1) and a 6-year period from 2013 to 2018 (Temporal Window-2) were tested separately for the same arguments. Vegetative area showed an increase throughout the temporal window-1 and then a rapid decrease from 2013 to 2018, while built-up area and mean temperature presented an ever-increasing trend during both temporal windows but with much higher rates in second window. Correlation of tempera ture with the both the investigated thermal controls has found getting strong in Temporal Window-2 showing that relation of these landcover areas with temeperature is not linear and severity is increasing with time. Moreover, temperature is found to be strongly dependent upon changes in built-up areas than that of vegetative areas. So, an increase in built-up area has much more devastating efects over the temperature rather than decrease in vegetative area. It was concluded that Lahore district is contributing in global warming more rapidly than it had ever done before.