scholarly journals Using Synthetic Remote Sensing Indicators to Monitor the Land Degradation in a Salinized Area

2021 ◽  
Vol 13 (15) ◽  
pp. 2851
Author(s):  
Tao Yu ◽  
Guli Jiapaer ◽  
Anming Bao ◽  
Guoxiong Zheng ◽  
Liangliang Jiang ◽  
...  
Keyword(s):  
Land Degradation ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Salt Content ◽  
Principal Component ◽  
Water Withdrawal ◽  
Moisture Index ◽  
High Positive Correlation ◽  
Amu Darya

Land degradation poses a critical threat to the stability and security of ecosystems, especially in salinized areas. Monitoring the land degradation of salinized areas facilitates land management and ecological restoration. In this research, we integrated the salinization index (SI), albedo, normalized difference vegetation index (NDVI) and land surface soil moisture index (LSM) through the principal component analysis (PCA) method to establish a salinized land degradation index (SDI). Based on the SDI, the land degradation of a typical salinized area in the Central Asia Amu Darya delta (ADD) was analysed for the period 1990–2019. The results showed that the proposed SDI had a high positive correlation (R2 = 0.89, p < 0.001) with the soil salt content based on field sampling, indicating that the SDI can reveal the land degradation characteristics of the ADD. The SDI indicated that the extreme and strong land degradation areas increased from 1990 to 2019, mainly in the downstream and peripheral regions of the ADD. From 1990 to 2000, land degradation improvement over a larger area than developed, conversely, from 2000 to 2019, and especially, from 2000 to 2010, the proportion of land degradation developed was 32%, which was mainly concentrated in the downstream region of the ADD. The spatial autocorrelation analysis indicated that the SDI values of Moran’s I in 1990, 2000, 2010 and 2019 were 0.82, 0.78, 0.82 and 0.77, respectively, suggesting that the SDI was notably clustered in space rather than randomly distributed. The expansion of unused land due to land use change, water withdrawal from the Amu Darya River and the discharge of salt downstream all contributed to land degradation in the ADD. This study provides several valuable insights into the land degradation monitoring and management of this salinized delta and similar settings worldwide.

scholarly journals Modeling the Radial Stem Growth of the Pine (Pinus sylvestris L.) Forests Using the Satellite-Derived NDVI and LST (MODIS/AQUA) Data

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 12
Author(s):  
Yulia Ivanova ◽  
Anton Kovalev ◽  
Vlad Soukhovolsky
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Principal Component ◽  
Stem Growth ◽  
Forest Growth ◽  
Parabolic Approximation ◽  
New Approach ◽  
The Relationship ◽  
Tree Increment

The paper considers a new approach to modeling the relationship between the increase in woody phytomass in the pine forest and satellite-derived Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) (MODIS/AQUA) data. The developed model combines the phenological and forest growth processes. For the analysis, NDVI and LST (MODIS) satellite data were used together with the measurements of tree-ring widths (TRW). NDVI data contain features of each growing season. The models include parameters of parabolic approximation of NDVI and LST time series transformed using principal component analysis. The study shows that the current rate of TRW is determined by the total values of principal components of the satellite indices over the season and the rate of tree increment in the preceding year.

scholarly journals A Study of Desertification Using Remote Sensing Techniques in Basra Governorate, South Iraq

2021 ◽  
pp. 912-926
Author(s):  
Fadel Abbas Zwain ◽  
Thair Thamer Al-Samarrai ◽  
Younus I. Al-Saady
Keyword(s):  
Remote Sensing ◽  
Land Degradation ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Arid Zone ◽  
Sand Dunes ◽  
Risk Index ◽  
Anthropogenic Factors ◽  
Landsat Images

Iraq territory as a whole and south of Iraq in particular encountered rapid desertification and signs of severe land degradation in the last decades. Both natural and anthropogenic factors are responsible for the extent of desertification. Remote sensing data and image analysis tools were employed to identify, detect, and monitor desertification in Basra governorate. Different remote sensing indicators and image indices were applied in order to better identify the desertification development in the study area, including the Normalized difference vegetation index (NDVI), Normalized Difference Water Index (NDWI), Salinity index (SI), Top Soil Grain Size Index (GSI) , Land Surface Temperature (LST) , Land Surface Soil Moisture (LSM), and Land Degradation Risk Index (LDI) which was used for the assessment of degradation severity .Three Landsat images, acquired in 1973, 1993, and 2013, were used to evaluate the potential of using remote sensing analysis in desertification monitoring. The approach applied in this study for evaluating this phenomenon was proven to be an effective tool for the recognition of areas at risk of desertification. The results indicated that the arid zone of Basra governorate encounters substantial changes in the environment, such as decreasing surface water, degradation of agricultural lands (as palm orchards and crops), and deterioration of marshlands. Additional changes include increased salinization with the creeping of sand dunes to agricultural areas, as well as the impacts of oil fields and other facilities.

scholarly journals SURFACE TEMPERATURE DYNAMICS IN RESPONSE TO LAND COVER TRANSFORMATION

2020 ◽  
Vol 11 (2) ◽  
pp. 94-110 ◽  
Author(s):  
Syed Riad Morshed Riad Morshed ◽  
Md. Abdul Fattah ◽  
Asma Amin Rimi ◽  
Md. Nazmul Haque
Keyword(s):  
Land Cover ◽  
Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Landsat 8 ◽  
Moisture Index ◽  
Type Transformation ◽  
Spatial Environment ◽  
Supervised Image Classification

This research assessed the micro-level Land Surface Temperature (LST) dynamics in response to Land Cover Type Transformation (LCTT) at Khulna City Corporation Ward No 9, 14, 16 from 2001 to 2019, through raster-based analysis in geo-spatial environment. Satellite images (Landsat 5 TM and Landsat 8 OLI) were utilized to analyze the LCTT and its influences on LST change. Different indices like Normalized Difference Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Buildup Index (NDBI) were adopted to show the relationship against the LST dynamics individually. Most likelihood supervised image classification and land cover change direction analysis shows that about 27.17%, 17.83% and 4.73% buildup area has increased at Ward No 9, 14, 16 correspondingly. On the other hand, the distribution of change in average LST shows that water, vacant land, and buildup area recorded the highest increase in temperature by 2.720C, 4.150C, 4.590C, respectively. The result shows the average LST increased from 25.800C to 27.150C in Ward No 9, 26.840C to 27.230C in Ward No 14 and 26.870C to 27.120C in Ward No 16. Here, the most responsible factor is the transformation of land cover in buildup areas.

scholarly journals Environmental sensitivity to mosquito transmitted diseases in El-Fayoum using spatial analyses

2020 ◽  
Vol 167 ◽  
pp. 03002
Author(s):  
Asmaa M. El-Hefni ◽  
Ahmed M. El-Zeiny ◽  
Hala A. Effat
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Malaria Vectors ◽  
Moisture Index ◽  
Risk Area ◽  
Gis Modeling ◽  
Breeding Sites ◽  
Mosquito Breeding ◽  
Fayoum Governorate

El-Fayoum governorate has unique characteristics which induces mosquito proliferation and thus increased the risk arisen from diseases transmission. Present study explores the role of remote sensing and GIS modeling integrated with field survey for mapping mosquito breeding sites and the areas under risk of diseases transmission in El-Fayoum governorate. Entomological surveys were conducted for a total number of 40 accessible breeding sites during the period 12-16 November 2017. A calibrated Landsat OLI image, synchronized with the field trip, was processed to produce Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), and Land Surface Temperature (LST). A cartographic GIS model was generated to predict breeding sites in the whole governorate and to assess the potential risk. The main filarial disease vector (Culex pipiens) was abundant at Atsa district, while Malaria vectors (Anopheles sergentii and Anopheles multicolor) were mainly distributed in El-Fayoum and Youssef El-Seddiq districts. Means levels of NDVI, NDMI and LST at breeding habitats were recorded; 0.18, 0.08 and 21.75° C, respectively. Results of the model showed that the highest predicted risk area was reported at Atsa district (94.4 km2) and Yousef El-Sediq (81.8 km2) while the lowest prediction was observed at Abshawai district (35.9 km2). It can be concluded that Atsa, Yousef El-Sedik and El-Fayoum districts are more vulnerable to Malaria and Filaria diseases outbreaks, thus precaution and pest control methods must be applied to mitigate the possible risks.

scholarly journals Impact of COVID-19 Induced Lockdown on Environmental Quality in Four Indian Megacities Using Landsat 8 OLI and TIRS-Derived Data and Mamdani Fuzzy Logic Modelling Approach

2020 ◽  
Vol 12 (13) ◽  
pp. 5464 ◽  
Author(s):  
Sasanka Ghosh ◽  
Arijit Das ◽  
Tusar Kanti Hembram ◽  
Sunil Saha ◽  
Biswajeet Pradhan ◽  
...  
Keyword(s):  
Environmental Quality ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fuzzy Ahp ◽  
Landsat 8 ◽  
Moisture Index ◽  
Biophysical Parameters ◽  
The World

The deadly COVID-19 virus has caused a global pandemic health emergency. This COVID-19 has spread its arms to 200 countries globally and the megacities of the world were particularly affected with a large number of infections and deaths, which is still increasing day by day. On the other hand, the outbreak of COVID-19 has greatly impacted the global environment to regain its health. This study takes four megacities (Mumbai, Delhi, Kolkata, and Chennai) of India for a comprehensive assessment of the dynamicity of environmental quality resulting from the COVID-19 induced lockdown situation. An environmental quality index was formulated using remotely sensed biophysical parameters like Particulate Matters PM10 concentration, Land Surface Temperature (LST), Normalized Different Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). Fuzzy-AHP, which is a Multi-Criteria Decision-Making process, has been utilized to derive the weight of the indicators and aggregation. The results showing that COVID-19 induced lockdown in the form of restrictions on human and vehicular movements and decreasing economic activities has improved the overall quality of the environment in the selected Indian cities for a short time span. Overall, the results indicate that lockdown is not only capable of controlling COVID-19 spread, but also helpful in minimizing environmental degradation. The findings of this study can be utilized for assessing and analyzing the impacts of COVID-19 induced lockdown situation on the overall environmental quality of other megacities of the world.

scholarly journals Characterization of comprehensive drought events associated with the ENSO warm phase through satellite images in the Valle del Cauca Colombia

DYNA ◽  
2020 ◽  
Vol 87 (214) ◽  
pp. 204-214
Author(s):  
Carlos David Ojeda Flechas ◽  
Jaime Alejandro Burbano Rodriguez ◽  
Yesid Carvajal Escobar ◽  
Francisco Luis Hernández Torres
Keyword(s):  
Land Surface ◽  
Satellite Images ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Standardized Precipitation Index ◽  
Principal Component ◽  
Severe Drought ◽  
Enso Events ◽  
Susceptibility Model ◽  
Valle Del Cauca

The Synthesized Drought Index in the Valle del Cauca was evaluated, applying Principal Component Analysis to satellite images that described: Land Surface Temperature, Normalized Difference Vegetation Index and Precipitation. The magnitude of drought represented by this index was identified in the first component and validated with the Quarterly Standardized Precipitation Index (SPI – 3), obtained from 78 weather stations, which achieved correlations of between 0.55 and 0.71 during warm ENSO events. Comprehensive drought in the department was characterized by exhibiting areas of non-drought in the southwest, in the center-south a transition phase from wet to extremely dry, the Inter-Andean Valley showed sectors of severe drought, and to the east, extremely dry areas. Additionally, in a pilot municipality in the driest area of the department, a susceptibility model was implemented to detect areas affected by drought, applying the Analytical Hierarchical Process.

scholarly journals Assessing the Relationship among the Land Surface Features: A Geographic Information System (GIS) and Remote Sensing (RS) Based Approach for City Area

2021 ◽  
Vol 8 (2) ◽  
pp. 935-952
Author(s):  
Sharmin Siddika ◽  
Md. Nazmul Haque ◽  
Mizbah Ahmed Sresto
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Moisture Index ◽  
Gis And Remote Sensing ◽  
Positive Correlation

Due to climate change and urbanization, it is important to monitor and evaluate the components of the environment. For this reason, ward-22 and ward-27 of the Khulna City Corporation (KCC) area have been selected for the study. This research seeks to identify the existing land use profile and assess the land surface components such as topography, Normalized Difference Buildup Index (NDBI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Normalized Difference Salinity Index (NDSI) and Land Surface Temperature (LST) to measure the relationships among the land surface components. The land use land cover map shows that about 59% of ward-22 and 71.5% area of ward-27 are built-up areas. Both of the wards contain little amount of water body, vegetation and open space. Both of the wards have residential land use types with commercial purposes on the periphery. Accordingly, 63.32% and 65% of structures of ward-22 and 27 are pucca. The land surface components reveal that both areas contain lower slopes, less vegetation, less moisture, severe salinity, highly built-up areas, and high land surface temperature. The relationships among the land surface components show that NDVI has a negative relation with LST and NDBI whereas NDVI represents a positive correlation with NDMI. On the other hand, NDBI shows a positive correlation with LST whereas NDMI negatively correlates with LST. NDSI and topography reflect no meaningful relationship between NDBI, NDVI, LST, and NDMI. However, the research findings may be essential to city planners and decision-makers for incorporating better urban management at the micro level concerning climate change.

scholarly journals Identification of desertified and preserved areas in a conservation unit in the state of Paraíba – Brazil

2021 ◽  
Author(s):  
Leandro F. da Silva ◽  
Bartolomeu I. De Souza ◽  
Rafael Camara Artigas
Keyword(s):  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Soil Surface ◽  
Conservation Unit ◽  
Moisture Index ◽  
Rainy Period ◽  
Colour Image ◽  
Semi Arid Region ◽  
Set Of Points

The objective of this study is to identify and analyse the main characteristics of areas potentially degraded by desertification and of preserved areas using the Soil Surface Moisture Index (SSMI), alongside the Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI). The study is based on a set of points obtained in the field and from the RGB false colour image for the Environmental Protection Areas (EPA) of the Cariri, in the semi-arid region of Paraíba, using a space-time cross-section covering both rainy and dry periods. The results showed that at all points in Desertified Areas, the main characteristics were a low SSMI, high LST and low NDVI in both periods. The Preserved Areas, on the other hand, presented a high SSMI, moderate LST and high NDVI in the rainy period, with the same characteristics repeated in the dry period for SSMI and NDVI, but with a low LST. Timely identification of these characteristics, both in areas degraded by desertification and in better preserved areas, can provide useful information for future decisions relating to the physical and territorial management of the Conservation Unit.

scholarly journals Spatial Distribution Of Andaliman Potential Habitat (Zanthoxylum acanthopodium DC.) in Samosir Island, North Sumatera

2019 ◽  
Vol 9 (4) ◽  
pp. 861-871
Author(s):  
Lasriama Siahaan ◽  
Iwan Hilwan ◽  
Yudi Setiawan
Keyword(s):  
Distribution Pattern ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Natural Habitat ◽  
Principal Component ◽  
Bare Soil ◽  
Suitable Habitat ◽  
Plantation Forest ◽  
Moisture Index ◽  
Morisita Index

Andaliman breeding and regeneration (Zanthoxylum acanthopodium DC.) in its natural habitat tends to be slow and difficult. The purpose of this research was to determine the distribution pattern, spatial character, and potential suitable habitat for andaliman growth with a suitability model approach in Samosir island, North Sumatera. Andaliman distribution pattern based on the calculation of the Standard Morisita Index (Ip) shows various patterns. There are three categories of distribution pattern, depends on the Standard Morisita Index  The distribution patterns on each plot based on the calculation are: random (Location 1 – open area (Ip = 0.00)), uniform (Location 2 – plantation forest (Ip = -0.77); Location 3 –  open field (Ip = -0.09)), and clump (Location 4 – plantation forest (Ip = 0.36)). Analysis of habitat suitability for andaliman used spatial modelling with the Principal Component Analysis (PCA) approach. This method utilized ecological variables, i.e.: Bare Soil Index (BSI), slope, Digital Elevation Model (DEM), rainfall, Normalized Difference Moisture Index (NDMI), and Normalized Difference Vegetation Index (NDVI). The result is  69.8% of Samosir Island is suitable for andaliman, while 26.4% of it is considered as highly suitable habitat.

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