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Showing 11 results for Ndvi

Mrs. Zeinab Zaheri Abdehvand, Dr. Mostafa Kabolizadeh,
Volume 0, Issue 0 (3-1921)

In vast areas, the possibility of simultaneous access to satellite images with appropriate spatial resolution, such as Landsat images, is always a challenge. In addition, the temporal resolution of the Landsat satellite does not provide the possibility of examining short-term changes in phenomena such as vegetation. The aim of this research is to use the temporal and spatial fusion techniques of Landsat-8 and MODIS satellite images in preparing the Normalized Vegetation Detection Index (NDVI) map. For this purpose, six image fusion algorithms, including NNDiffuse (Nearest Neighbor Diffusion), PC (Principal Component), Brovey, CN (Color Normalized), Gram-Schmidt, and SFIM, have been used in an experimental area in Khuzestan province. After evaluating the results of the algorithms and choosing the most appropriate fusion algorithm, based on the statistical indicators of the spectral (correlation coefficient) and spatial (Laplacen filter) criteria of each of the algorithms, the spectral and spatial information of the reflection of red and near-infrared of 8 mosaicked Landsat-8 images (30 m) were combined with the red and near-infrared bands of one MODIS image (250 m). In order to investigate the vegetation cover, the NDVI was prepared with the fused satellite image in the Khuzestan province. The results of the research have shown that the NNDiffuse integration fusion algorithm has a very good accuracy among other algorithms in terms of the spatial evaluation index and spectral quality criteria. Therefore, this algorithm was recruited to combine the red and near-infrared bands of Landsat-8 and MODIS images. Compared to the original Landsat-8 image, the NDVI map prepared by this algorithm has the lowest statistical error of RMSE (0.1234) and MAE (0.081), respectively.
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Volume 16, Issue 41 (6-2016)

Drought phenomenon with different goals including planning, water sources management and dealing with the problems due to water shortage has been investigated by most scholars. This research examined the relationship between drought and the normalized difference vegetation index (NDVI)in Qorveh and Dehgolan region in Kurdistan, Iran. To determine years with meteorological drought, index of Standard Z during a 20 year period time (1387-1368) has been applied. The results of the statistical data in Ghorveh station in 2008 with total annual rainfall of 155 mm and Z index of -2.31, in 2000 with total rainfall of 253.1 and Z index of -1.5 and in 2001 with 239.5 rainfall and Z index of -1.22. Were determined as drought indeces. MODIS satellite images were used to assess the ecological drought. Associated with each image to a randomly selected sample of 500 places in the software ERDAS, NDVI values were calculated for these images. satellite image processing results and  Normalized Difference Vegetation Index (NDVI) indicates a low index values in the years 2000, 2001 and 2008 Were determined as ecological drought years of 2001 samples had the lowest NDVI and central parts of the area under irrigation has almost lost its vegetation.

Adel Nabi Zadeh Balkhanloo, Zahra Hejazizadeh, Parviz Zeaiean Firoozabadi,
Volume 18, Issue 50 (3-2018)

Continuous decline in Lake Urmia water levels In recent years, the decline of rainfall and river flows and constant droughts has become the main concern of the people and the people. To study climate change and increase of temperature in the catchment area of ​​Lake Urmia, two factors for measuring the temperature and properties of satellite images were used which indicate the importance of land surface temperature changes (LST) and normalized vegetation differences (NDVI). This study was carried out using the satellite data of the periodic watershed (2008-2008) to investigate the spatial relationship between NDVI-Ts and NDVI-ΔT to investigate the actual agricultural drought occurrence. The goal is to extract the VTCI (vegetation temperature index) index, which is capable of identifying drought stress at regional scale. The results showed that the slope is negative for the warm edge, where it is positive for the cold edge. The gradient gradient shows that the maximum temperature is reduced when the NDVI value increases for any interval. The slope on the cold edge indicates that the minimum temperature rises when the NDVI value rises. Overall, at the warm and cold edges, it has been observed that the drought trend over 2009-2008 is higher than in 2010. In the days of Julius Day 257, the slope of the cold edge from 2008 to 2010 is decreasing. But at the hot edge, intercept pixels for 2008 is more than 323 degrees Kelvin, where in 2009-2010 it is less than 323 degrees Kelvin. In general, the correlation coefficient (R2) is different in the TS-NDVI spacing between (0.90-0.99). The present study showed that with the integration of satellite satellite data with meteorological data, the VTCI threshold for drought stress varies from year to year depending on the data conditions.

Dr Vahid Riahi, Dr Parviz Zeaiean Firouzabadi, Dr Farhad Azizpour, Ms Parastoo Darouei,
Volume 19, Issue 52 (3-2019)

The cognition of cropping pattern is important for planning and resource management .Remote sensing as a science and technology of spatial information and geographic information system due to having the analytical facilities can play a key role in determining the distribution of crops and their lands under cultivation. In this research, in order to identify and separate the lands under cultivation of the dominant crops in Lenjanat of Isfahan province, the multi-temporal images of Landsat 8 satellite, OLI sensor were used in the dates of April 17, July 6, and August 23 in 2016. Using maximum likelihood classification and normalized difference vegetation index (NDVI) of the agriculture crops in different periods of growth and according to their cropping calendar, the map of the cropping pattern of the area was determined. To evaluate the accuracy of the results, the produced maps were examined with reference data. Kappa coefficient and overall accuracy were 0.88 and 90%, respectively, in maximum likelihood classification, and 0.90 and 93%, respectively, in NDVI. Furthermore, statistics presented by Agricultural Jihad Organization of Isfahan province in the 2015-2016 crop year was used for evaluation. The results showed that there were differences equal to 10.2%, 18.6% and 1.8%, in the area under cultivation of wheat and barley, rice, and potato and forage, respectively, in maximum likelihood classification, comparing with the statistics of Agriculture Jihad while the results of NDVI comparing with Jihad statistics showed the errors equal to 6.6 %, 6.5 % and 3.2%, respectively, that indicated the better performance of temporal vegetation indices in estimation of area under cultivation according to its phenology. Investigation of land use and cropping pattern of this area indicate a high centralization of agricultural lands with high water requirements and industries on the proximity of Zayanderud River which necessitates the spatial analysis of land use in this area.

Mohammad Hossein Nasserzadeh, Zahra Hejazizadeh, Zahra Gholampour, Bohloul Alijani,
Volume 20, Issue 57 (6-2020)

The plant community in an area is the most sensitive indicator of climate. A visual comparison of climate and vegetation on a global scale immediately reveals a strong correlation between climatic and vegetation zones and this relationship, of course, are not co-incidental.  The main object of this study is to reveal the spatiotemporal association between climatic factors andvegetation Cover (NDVI) incorporate MODIS and TRMM product in Kohkiloyeh O Boirahmad province of Iran. So that the in this paer we use MOD13Q1  of MODIS product as NDVI layer for study area. MOD11A2 as landsurface temperature and 3B43 TRMM as meanmonthly accumulative rainfall for study area during 2002 to 2012 in 0.25° spatial resolution also were used as climatic factors. We use the correlation and cross-correlation analysis in 0.95 confident level(P_value =0.05) to detection the spatial and temporal association between the NDVI and 2 climatic Factor(LST and rainfall). The results indicated that during winter (December to March) the spatial distribution of NDVI is highly correlated with LST spatial distribution. In these months the pixels which have the high value of NDVI are spatiallyassociated with the pixels which have highest value of LST (6 to 14C°).As can be seen in table 1. Season the spatial correlation among NDVI and LST is so high which is statistical significant in 0.99 confident level  in winter. In transient months such as May, October and November,(temperate months in study region ) the spatial correlation among NDVI and LST is falling to 0.30 to 0.35 which is not statistical significant in 0.95 confident level. Finally in summer season or warm months including Jun to September, we found the minimum spatial association among the NDVI and LST.. In temporal aspect we found that the maximum correlation between NDVI and LST simultaneously appears and not whit lag time. The spatial correlation of NDVI and TRMM monthly accumulative rainfall was statistical significant in spring season (April to Jun) by 1 month lag time in remain months we don’t find any significant correlation between NDVI and rainfall.

Dr Parviz Zeaiean Firoozabadi,
Volume 20, Issue 59 (12-2020)

Various satellite remote sensing data, images and products have proven their place in drought, drought and agriculture studies since the production of this type of information resource. Visible, near-infrared and thermal bands are among the most widely used in the production of products such as vegetation and surface temperature. In this study, from MODIS sensor data to investigate and find the coefficients of spatial relationship between vegetation-surface temperature index (NDVI-TS) and NDVI-ΔTS to extract the time of agricultural drought from June to October 2007 to 2010 in the catchment Siminehrood has been extracted from the Temperature-Vegetation Condition Index (VTCI) and the Water Lack Index (WDI), which are able to detect drought stress on a regional scale. The results of this study showed that in both indicators, the drought stress situation was higher in 2007 and 2008. Also based on the NDVI-TS space relationship in all the years 2007 to 2010 the high slope of the triangular space for the hot edge is negative. This means that with increasing NDVI, the LST level decreases while for the cold edge the slope is positive. In addition, the slope obtained from the NDVI-ΔTS space relationship is negative for the dry line, ie the dry line or the minimum transpiration-sweat line (ETR) shows a negative correlation with NDVI. While for the wet line, especially in 2010, the slope is positive and in other years, no significant change is seen. The present study showed that the VTCI threshold for drought stress was severe in 2007 and 2008.

Abdolmajid Ahmadi, Ebrahim Akbari, Javad Jamalabadi, Maryam Alemohammad,
Volume 22, Issue 64 (3-2022)

Awareness of the status of vegetation, land use change and surface temperature in each region, and the timing and location of their changes over time are important for micro and macro planning. In order to make optimal use of land, knowledge of land use changes is necessary, which is usually possible by detecting and predicting land use changes. Measuring the role of researches and researchers has been instrumental in the study of natural resources, especially vegetation, surface temperature and user variations in each location, as well as the availability of information for different times for valuable studies. In this study, ETM and OLI were used to study the process of land use change, vegetation cover, surface temperature, and hazards caused by them in perennial seasons. The results show that the area of use changes over the period 2000-2010 has decreased the area of use of the developed area, agricultural and growing gardens and the area of land and rangelands. Artificial vegetation has risen in aggregate and rangeland lands are showing a decreasing trend. Due to the importance of vegetation and its role in reducing the temperature of the earth's surface, the trend has been decreasing in regions with intensive vegetation and high temperature. Also, in the period from 2010 to 2017, the range was further increased and the city's growth continued sporadically, causing environmental changes and rising temperatures in the city. The change in the city's increased range has increased environmental risks, including the loss of good agricultural land and the increase in the temperature of the city. Due to the fact that most agricultural land is located in the vicinity of the city under cultivation of saffron, which in the warm seasons does not have surface coatings, changes in the type of cultivation can also affect the temperature of the earth.

Khadijeh Mikaeli Hajikandi, Behrooz Sobhani, Saeid Varamesh,
Volume 23, Issue 68 (3-2023)

Study of land use/cover changes is widely used in environmental planning. During the last decade, growing increase of aridity in Uromiyah Basin has become a major regional and even national problem. The purpose of this study is to reveal the changes in land use/cover in the southern and southeastern parts of the basin with using 2 images for month of July of 2000 to 2017. Landsat TM and OLI data and NDVI were used for classification this study. Land use/cover maps in the two studied years were provided using Maximum Likelihood Classifier (MLC) algorithm applied on two series data including spectral bands (data series 1) also spectral bands and filter texture layer (data series 2) and six categories of land use/cover containing Irrigated Farmland, Dry Farmland, garden, rangeland, bare land and water bodies were distinguished.. The accuracy of the produced maps were assessed and compared with the training samples derived from Google Earth images and Kappa Index, overral accuracy, producer accuracy and user accuracy. The results demonstrated that the maps produced using the data series 1 have higher accuracy and the overall accuracy of the maps of 2000 and 2017 using the data series 2 are 98.93 and 98.29 and these values for data series 1 were gained 99.28 and 91.45, respectively. In additional, texture filtering decreased amount of mixing between classes of rangeland, Irrigated Farmland and garden. The results of change detection showed considerable increase in the area of Irrigated Farmland (13.44) and garden 1.85 (27.24) an also at the studied period, the area of the water bodies and rangeland were decreased to 1.58 and 22.94%.
Hadi Zare Khormizie, Hamid Reza Ghafarian Malamiri,
Volume 23, Issue 69 (6-2023)

Knowledge of rangeland vegetation characteristics as well as factors affecting it in environmental planning, land management and sustainable development is very important. However, regional and up-to-date maps of pasture vegetation cover are not always available. In this study, in order to plot the vegetation cover percentage of the rangelands and monitor its changes in drought and wet periods, NDVI products of MODIS sensor during the years from 2000 to 2017 with a spatial resolution of 250 m and a 16-day time resolution, and The SPI drought index were used. The study area is the part of the rangelands located in the Southern province of Yazd. In 2013, in order to provide ground truth data, a field work was done to take the sampling rate of vegetation from the rangeland level in the study area. According to the results, the NDVI index has a good ability to map vegetation cover, so the coefficient of determination (R2) between this index and the sample points was 0.71. Based on the results, the average vegetation cover of the studied area was 11.3% during the years 2000 to 2017. The highest and lowest amount of vegetation cover in the study area was in 2000 and 2002, with moderate mild conditions and very severe drought, respectively (14.6% and 9.2% respectively). The most important factors influencing the vegetation cover in the study area are rainfall and drought periods, so that the coefficient of determination (R2) between the SPI drought index and the average vegetation percentage was 0.85. In general, based on the results there is a high potential for assessing and monitoring rangeland vegetation changes using satellite data and remote sensing technique.
Sara Kaviani Ahangar, Rasool Mahdavi, Gholamreza Zehtabian, Hamid Gholami, Ashok K Chapagain,
Volume 24, Issue 72 (3-2024)

Desertification is a serious environmental and socio-economic threat to the planet. The aim of this study is to use a scientific, reasonable and repeatable method to evaluate the process of vegetation and land use as two important factors in the process of desertification on different scales (local-regional and global). In this study, Sarvestan plain in Fars province was selected as the study area. For this purpose, Landsat images were used for TM (1993), ETM + (2001 and 2006) and OLI / TIRS (2016). Image monitoring was performed using image differentiation, NDVI index difference and land use maps. In 1993, 2001, and 1993, and 2016 difference maps, the decrease in the amount of water in the mouth of Lake Maharloo can be clearly seen as increasing changes in the infrared band. The results of the difference between the vegetation index and the increase in vegetation in the form of agricultural lands in 2016 compared to 2006 and 1993. According to the results of the monitoring classification, from 1993 to 2016, irrigated areas decreased from 7.11 hectares to 0.7575 hectares, on the other hand, the level of saline lands increased from 143.99 hectares to 223.83 hectares and the level of cultivated lands increased. (Agricultural and horticultural) has increased from 113.28 hectares to 14/2014 hectares, which due to the importance of saline lands and land use change indicators in the studies of the desertification assessment process, it can be concluded that the desertification process in the study area is growing.
Shamsallah Asgari, Tayeb Razi, Mohamadreza Jafari, Ali Akbar Noroozi,
Volume 25, Issue 76 (3-2025)

Due to the importance of forests in natural and anthropogenic environment, the effects of meteorological drought on the dryness of oak forests in Ilam province were investigated. The main purpose of this study was to determine the relationship of Zagros forests with drought occurring in the area. The results of the Standard Precipitation Index (SPI) for the time periods showed that the most drought occurred in 2007, 2008, 2011, 2015 and 2016. Remote sensing data (MODIS images) were used to investigate the vegetation trend (NDVI) of trees during the period 2016–2016. The vegetation trend (NDVI) was significant over the period with the index drought index (SPI) with R2 = 0.9999. Ground harvesting of oak drying points and simulation using Landsat satellite imagery with 15 m pixel output from GIS software showed that 17894 hectares of area forests from 2000 to 2016 were dried and destroyed and prepared with oak forest and integrated layer. The output layers from the drought zoning were shown visually and the statistical analysis was performed in three 5-year time series. The results of these analyzes from 2002 to 2006 showed that the correlation coefficient between meteorological drought and oak drought 96.6% with a coefficient of determination R2 = 0.985, for the time series of 2007 to 2011 the correlation coefficient between scratches Meteorological and oak dryness of 95.4% with R2 = 0.980 and coefficient of correlation for meteorological drought and oak drought of 98.8% and R2 = 0.995 of coefficient respectively. Its fluctuations in time series show the intensity and duration of the drying up of oak forests in the region. According to the results of this study, it is predicted that if the drought goes through this process, 1118.4 hectares of oak forests in Ilam province will be dried and destroyed annually.

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