scholarly journals Tree Water Status in Apple Orchards Measured by Means of Land Surface Temperature and Vegetation Index (LST–NDVI) Trapezoidal Space Derived from Landsat 8 Satellite Images

2019 ◽  
Vol 12 (1) ◽  
pp. 70 ◽  
Author(s):  
Mohammad Zare ◽  
Katrin Drastig ◽  
Manuela Zude-Sasse
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Satellite Images ◽  
Vegetation Index ◽  
Irrigation System ◽  
Water Status ◽  
Irrigation Management ◽  
Landsat 8 ◽  
Apple Orchards

In this study, the split window (SW) method was applied for land surface temperature (LST) retrieval using Landsat 8 in two apple orchards (Glindow, Altlandsberg). Four images were acquired during high demand of irrigation water from July to August 2018. After pre-processing images, the normalized difference vegetation index (NDVI) and LST were calculated by red, NIR, and thermal bands. The results were validated by interpolated infrared thermometer (IRT) measurements using the inverse distance weighting (IDW) method. In the next step, the temperature vegetation index (TVDI) was calculated based on the trapezoidal NDVI/LST space to determine the water status of apple trees in the case studies. Results show good agreement between interpolated LST using IRT measurements and remotely sensed LST calculation using SW in all satellite overpasses, where the absolute mean error was between 0.08 to 4.00 K and root mean square error (RMSE) values ranged between 0.71 and 4.23 K. The TVDI spatial distribution indicated that the trees suffered from water stress on 7 and 23 July and 8 August 2018 in Glindow apple orchard with the mean value of 0.69, 0.57, and 0.73, whereas in the Altlandsberg orchard on 17 August, the irrigation system compensated the water deficit as indicated by the TVDI value of 0.34. Moreover, a negative correlation between TVDI and vegetation water content (VWC) with correlation coefficient (r) of −0.81 was observed. The corresponding r for LST and VWC was equal to −0.89, which shows the inverse relation between water status and temperature-based indices. The results indicate that the LST and/or TVDI calculation using the proposed methods can be effectively applied for monitoring tree water status and support irrigation management in orchards using Landsat 8 satellite images without requiring ground measurements.

scholarly journals The Effects of Land Use Zoning and Densification on Changes in Land Surface Temperature in Seoul

2019 ◽  
Vol 11 (24) ◽  
pp. 7056 ◽  
Author(s):  
Jae-Ik Kim ◽  
Myung-Jin Jun ◽  
Chang-Hwan Yeo ◽  
Ki-Hyun Kwon ◽  
Jun Yong Hyun
Keyword(s):  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Descriptive Analysis ◽  
Landsat 8 ◽  
Land Use Type ◽  
Coverage Ratio

This study investigated how changes in land surface temperature (LST) during 2004 and 2014 were attributable to zoning-based land use type in Seoul in association with the building coverage ratio (BCR), floor area ratio (FAR), and a normalized difference vegetation index (NDVI). We retrieved LSTs and NDVI data from satellite images, Landsat TM 5 for 2004 and Landsat 8 TIRS for 2014 and combined them with parcel-based land use information, which contained data on BCR, FAR, and zoning-based land use type. The descriptive analysis results showed a rise in LST for the low- and medium-density residential land, whereas significant LST decreases were found in high-density residential, semi-residential, and commercial areas over the time period. Statistical results further supported these findings, yielding statistically significant negative coefficient values for all interaction variables between higher-density land use types and a year-based dummy variable. The findings appear to be related to residential densification involving the provision of more high-rise apartment complexes and government efforts to secure more parks and green spaces through urban redevelopment and renewal projects.

scholarly journals Missing Pixel Reconstruction on Landsat 8 Analysis Ready Data Land Surface Temperature Image Patches Using Source-Augmented Partial Convolution

2020 ◽  
Vol 12 (19) ◽  
pp. 3143
Author(s):  
Maosi Chen ◽  
Zhibin Sun ◽  
Benjamin H. Newell ◽  
Chelsea A. Corr ◽  
Wei Gao
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Satellite Images ◽  
Superior Performance ◽  
Source Image ◽  
Landsat 8 ◽  
Validation Metrics ◽  
Image Patches ◽  
Color Scales

Missing pixels is a common issue in satellite images. Taking Landsat 8 Analysis Ready Data (ARD) Land Surface Temperature (LST) image as an example, the Source-Augmented Partial Convolution v2 model (SAPC2) is developed to reconstruct missing pixels in the target LST image with the assistance of a collocated complete source image. SAPC2 utilizes the partial convolution enabled U-Net as its framework and accommodates the source into the framework by: (1) performing the shared partial convolution on both the source and the target in encoders; and (2) merging the source and the target by using the partial merge layer to create complete skip connection images for the corresponding decoders. The optimized SAPC2 shows superior performance to four baseline models (i.e., SAPC1, SAPC2-OPC, SAPC2-SC, and STS-CNN) in terms of nine validation metrics. For example, the masked MSE of SAPC2 is 7%, 20%, 44%, and 59% lower than that of the four baseline models. On the six scrutinized cases, the repaired target images generated by SAPC2 have the fewest artifacts near the mask boundary and the best recovery of color scales and fine textures compared with the four baseline models.

scholarly journals Geospatial Monitoring on Land Surface Temperature and Vegetation Dynamics: A Case of a City Area in Khulna, Bangladesh

2020 ◽  
Vol 3 (2) ◽  
pp. a35-43
Author(s):  
MD. NAZMUL HAQUE ◽  
NOWRIN RAHMAN KHANAM ◽  
MEHNAZ NANJIBA
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Vegetation Index ◽  
Landsat 8 ◽  
Environmental Condition ◽  
Infrared Sensor ◽  
The Third ◽  
Canopy Area

Land surface temperature and vegetation cover are two important parameters to evaluate the climate change and environmental condition. The current study is carried out in respect of monitoring the changing phenomena of climate and environment. The area selected to conduct the study was ward number 1, 2 and 3 of Khulna City Corporation), from the third largest city of Bangladesh. This study is corresponding through the calculation of Land Surface Temperature (LST) and Normalized Differential Vegetation Index (NDVI) for two different years, 2010 and 2018. LST and NDVI are observed to realize the association between surface temperature and amount of vegetation. With the help of ArcGIS 10.5, LST and NDVI calculations are done using Landsat 5 Thermal Mapper, Landsat 8 Operational Land Imager and Thermal Infrared Sensor images (for 2010 and 2018, respectively) collected from USGS Earth Explorer. The findings of the study specify that the highest temperature in 2018 is 32.5˚C in ward 2 and in 2010 it was 27.5˚C in ward 3, though the overall vegetation amount decreased in 2018, About 18, 900 square meter of very low canopy area has increased in ward 3 from the period of 2010 to 2018 and in the same time 35, 100 square meter of low canopy area has been decreased for the overall study area. However, parts of the study area of ward no. 3 had faced a significant increase in vegetation cover which is the cause of low temperature compared to ward 1 and 2 in 2018.

scholarly journals Application of Geo-informatics Technology to Access the Surface Temperature Using LANDSAT 8 OLI/TIRS Satellite Data: A Case Study in Ampara District in Sri Lanka

2020 ◽  
Author(s):  
Ibra Lebbe Mohamed Zahir
Keyword(s):  
Sri Lanka ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Surface Emissivity ◽  
Land Surface Emissivity

Land Surface Temperature is a one of the key variable of Global climate changes and model which estimate radiating budget in heat balance as control of climate model. It is a major influenced factor by the ability of the surface emissivity. In this study, were used Landsat 8 satellite image that have Operational Land Imager and Thermal Infrared Sensor to calculate Land Surface Temperature through geospatial technology over Ampara district, Sri Lanka. The Land Surface Temperature was estimated with respect to Land Surface Emissivity and Normalized Difference Vegetation Index values determined from the Red and Near Infrared channels. Land Surface Emissivity was processed directly by the thermal Infrared bands. Pixels based calculation were used to effort at LANDSAT 8 images that thermal Band 10 various dates in this study. The results were achievable to compute Normalized Difference Vegetation Index, Land Surface Emissivity, and Land Surface Temperature with applicable manner to compare with land use/ land cover data. It determines and predicts the changes of surface temperature to favorable to decision making process for the society. Study area faces seasonal drought in Sri Lanka, the prediction method that how land can be efficiently used with the present condition. Therefore, the Land Surface Temperature estimation can prove whether new irrigation systems for agricultural activities or can transformed source of energy into useful form that introducing solar hubs for energy production in future.

scholarly journals Investigating Land Surface Temperature Changes Using Landsat Data in Konya, Turkey

2016 ◽  
Vol XLI-B8 ◽  
pp. 285-289 ◽  
Author(s):  
O. Orhan ◽  
M. Yakar
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Salt Lake ◽  
Meteorological Data ◽  
Landsat 8 ◽  
Remotely Sensed Data ◽  
Landsat 5 Tm

The main purpose of this paper is to investigate multi-temporal land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) changes of Konya in Turkey using remotely sensed data. Konya is located in the semi-arid central Anatolian region of Turkey and hosts many important wetland sites including Salt Lake. Six images taken by Landsat-5 TM and Landsat 8- OLI satellites were used as the basic data source. These raw images were taken in 1984, 2011 and 2014 intended as long-term and short-term. Firstly, those raw images was corrected radiometric and geometrically within the scope of project. Three mosaic images were obtained by using the full-frame images of Landsat-5 TM / 8- OLI which had been already transformed comparison each other. Then, Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI) maps have been produced to determine the dimension of the drought. The obtained results showed that surface temperature rates in the basin increased about 5°C between 1984 and 2014 as long periods, increased about 2-3°C between 2011and 2014 as short periods. Meteorological data supports the increase in temperature.

scholarly journals ASSESSMENT OF RELATIONSHIP BETWEEN LAND SURFACE TEMPERATURE AND NORMALIZED DIFFERENT VEGETATION INDEX USING LANDSAT IMAGES IN SOME REGIONS OF DIYALA GOVERNORATE

2021 ◽  
Vol 52 (4) ◽  
pp. 793-801
Author(s):  
Al-Jbouri & Al-Timimi
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Conditions ◽  
Landsat 8 ◽  
Landsat Images ◽  
Remote Sensing Techniques ◽  
The Relationship

Agriculture is the most important and most dependent economic activity and influenced by climatic conditions as the climate elements represented by solar radiation, temperature, wind and relative humidity. Therefore, is necessary that analyze and understand the relationship between climate and agriculture. The aim of this study to assessment the relationship between land surface temperature (LST) and normalized difference vegetation index (NDVI) for three regions of Diyala Governorate in Iraq (Al Muqdadya, Baladrooz, and Baquba) by through using of remote sensing techniques and geographic information system (GIS).The Normalized difference vegetation index NDVI and land surface temperature (LST) were used in two of the Landsat-5 ETM + and Landsat-8 OLI satellite imagery during the years 1999 and 2019.  The results showed that increased in NDVI and decreased in LST for 2019, while for 1999 increased in LST and decreased in NDVI for the three regions. Finally, the regression was used to obtain that correlation between LST and NDVI. It was concluded that the correlation coefficient between NDVI and LST is negative, where the strongest correlation was 0.76 for Baquba and weakest correlation was 0.55 for Muqdadyia.

scholarly journals Deteksi Perubahan Suhu Permukaan Menggunakan Data Satelit Landsat Multi-Waktu Studi Kasus Cekungan Bandung

2018 ◽  
Vol 19 (2) ◽  
pp. 145 ◽  
Author(s):  
Widya Ningrum ◽  
Ida Narulita
Keyword(s):  
Land Use ◽  
Temperature Distribution ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Surface Temperature Distribution

ABSTRACTThe rapid population growth and development of infrastructure in the Bandung basin has triggered an uncontrolled land use changes. The changes of land use will impact on land surface temperature distribution. Finally, these changes will give influence on climate. Land surface temperature is one of the important climatic elements in the energy balance. Changes in land surface temperature variations will potentially change other elements of the climate. The purpose of this paper is to obtain and to analyze the changes of surface temperature distribution in Bandung basin using multi temporal satellite data processing that is Landsat 5 and Landsat 8 in 2004, 2009 and 2014. Near Infrared Channel (Near Infrared/NIR) and visible wave channels (Visible band) have used to obtain the value Normalized Difference Vegetation Index/NDVI index and Albedo. Land and vegetation emissivity value and thermal band have used to determine land surface temperature. The results showed that the surface temperature distribution of Bandung basin has been changes characterized by the presence of two hotspot characters i.e. hot areas in urban and hot areas in non-urban area. The area is characterized by decreasing vegetation index values, increasing albedo values and increasing on surface temperature.  Land Surface Temperatures average value increased by 1.3°C. Land surface temperature tends to rise supposed as a result of changes in vegetated area into open area and the build area  Keywords: land surface temperature, normalized difference vegetation index, albedoABSTRAKPesatnya pertumbuhan penduduk dan perkembangan infrastruktur di cekungan Bandung telah memicu perubahan tutupan lahan yang tidak terkendali. Perubahan tutupan lahan akan mempengaruhi distribusi suhu permukaan. Hal tersebut pada akhirnya nanti akan mempengaruhi iklim. Suhu permukaan merupakan salah satu unsur iklim yang penting dalam neraca energi. Perubahan variasi suhu permukaan berpotensi mengubah unsur unsur iklim yang lainnya. Tujuan makalah ini adalah untuk mengetahui dan menganalisis perubahan distribusi suhu permukaan di cekungan Bandung melalui pengolahan data satelit multi waktu yaitu Landsat 5 dan Landsat 8 tahun 2004, 2009, 2014 dan 2016. Kanal Inframerah Dekat (Near Infrared/NIR) dan kanal gelombang tampak (Visible band) digunakan untuk memperoleh nilai Indeks Kehijauan Vegetasi (Normalized Difference Vegetation Index/NDVI) dan Albedo. Nilai emisivitas dari tanah dan vegetasi serta Band termal digunakan untuk menentukan nilai Suhu Permukaan Tanah.Hasil penelitian menunjukkan bahwa di cekungan Bandung telah terjadi perubahan distribusi suhu permukaan yang dicirikan oleh adanya dua karakter hotspot yaitu daerah panas di daerah urban dan daerah panas di daerah non-urban. Daerah tersebut dicirikan menurunnya nilai indeks vegetasi, menurunnya nilai albedo dan meningkatnya nilai suhu permukaan tanah. Nilai rataan Suhu Permukaan Tanah tahun 2005 - 2014 meningkat sebesar 1.3°C. Kecenderungan naik ini diduga sebagai akibat adanya perubahan tutupan lahan bervegetasi menjadi daerah yang lebih terbuka dan daerah terbangun.Kata kunci: suhu permukaan, indeks kehijauan vegetasi, albedo 

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

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.

scholarly journals THE EFFECTS OF BUILT-UP AND GREEN AREAS ON THE LAND SURFACE TEMPERATURE OF THE KUALA LUMPUR CITY

2017 ◽  
Vol XLII-4/W5 ◽  
pp. 107-112 ◽  
Author(s):  
N. A. Isa ◽  
W. M. N. Wan Mohd ◽  
S. A. Salleh
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Urban Areas ◽  
Vegetation Index ◽  
Urban Climate ◽  
Geographical Information ◽  
Landsat 8 ◽  
Kuala Lumpur ◽  
Green Areas

A common consequence of rapid and uncontrollable urbanization is Urban Heat Island (UHI). It occurs due to the negligence on climate behaviour which degrades the quality of urban climate condition. Recently, addressing urban climate in urban planning through mapping has received worldwide attention. Therefore, the need to identify the significant factors is a must. This study aims to analyse the relationships between Land Surface Temperature (LST) and two urban parameters namely built-up and green areas. Geographical Information System (GIS) and remote sensing techniques were used to prepare the necessary data layers required for this study. The built-up and the green areas were extracted from Landsat 8 satellite images either using the Normalized Difference Built-Up Index (NDBI), Normalized Difference Vegetation Index (NDVI) or Modified Normalize Difference Water Index (MNDWI) algorithms, while the mono-window algorithm was used to retrieve the Land Surface Temperature (LST). Correlation analysis and Multi-Linear Regression (MLR) model were applied to quantitatively analyse the effects of the urban parameters. From the study, it was found that the two urban parameters have significant effects on the LST of Kuala Lumpur City. The built-up areas have greater influence on the LST as compared to the green areas. The built-up areas tend to increase the LST while green areas especially the densely vegetated areas help to reduce the LST within an urban areas. Future studies should focus on improving existing urban climatic model by including other urban parameters.

ANALISIS SPASIAL KERAPATAN BANGUNAN DAN PENGARUHNYA TERHADAP SUHU Studi Kasus di Kabupaten Bogor

2019 ◽  
Vol 3 ◽  
pp. 529
Author(s):  
Mega Adeanti ◽  
Muhammad Chaidir Harist
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Level 1

Kabupaten Bogor merupakan salah satu kabupaten yang saat ini pembangunannya cukup berkembang. Pada tahun 2016 jumlah penduduk di Kabupaten Bogor berjumlah 5.715.009 jiwa. Bertambahnya penduduk menyebabkan berkurangnya lahan dengan tutupan vegetasi menjadi daerah yang terbangun, dari bertambahnya lahan terbangun meyebabkan meningkatnya suhu di Kabupaten Bogor. Dengan pemanfaatan Sistem Informasi Geografis (SIG) dapat diketahui peningkatan suhu akibat dari padatnya bangunan di Kabupaten Bogor. Melalui pengolahan Citra Landsat 8 OLI/TIRS C1 Level-1 dengan ukuran 30 x 30 m tahun 2018 digunakan metode Normalized Difference Vegetation Index (NDVI) untuk mengetahui indeks kerapatan vegetasi, Normalized Difference Built Index (NDBI) untuk mengetahui kerapatan bangunan, dan metode Land Surface Temperature (LST) untuk mengetahui suhu permukaan di Kabupaten Bogor. Hasil yang didapatkan dari penelitian ini adalah semakin rapatnya bangunan maka suhu semakin tinggi dan sebaliknya, begitu juga dengan luas dari wilayah yang mengalami kenaikan suhu.

Sign in / Sign up

Export Citation Format

Share Document