scholarly journals A New Approach for Land Degradation and Desertification Assessment Using Geospatial Techniques

2017 ◽  
Author(s):  
Masoud Masoudi ◽  
Parviz Jokar ◽  
Biswajeet Pradhan
Keyword(s):  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Evaluation Method ◽  
Low Cost ◽  
United Nations Environment Programme ◽  
Geospatial Techniques ◽  
New Approach ◽  
Khuzestan Province ◽  
Current State

Abstract. Land degradation reduces production of biomass and vegetation cover in every land uses. The lack of specific data related to degradation is a severe limitation for its monitoring. Assessment of current state of land degradation or desertification is very difficult because this phenomena includes several complex processes. For that reason, there is no common agreement has been achieved among the scientific community for its assessment. This study was carried out as an attempt to develop a new approach for land degradation assessment based on its current state by modifying of FAO1/UNEP2 index and normalized difference vegetation index (NDVI) index in Khuzestan province, placed in the southwestern part of Iran. The proposed evaluation method is easy to understand the degree of destruction due to low cost and save time. Results showed that based on percent of hazard classes in current condition of land degradation, the most widespread and minimum area of hazard classes are moderate (38.6 %) and no hazard (0.65 %) classes, respectively. While results in the desert area of study area showed that severe class is much widespread than other hazard classes, showing environmentally bad situation in the study area. Statistical results indicated that degradation is highest in desert and then rangeland compared to dry cultivation and forest. Also statistical test showed average of degradation amount in the arid region is higher than other climates. It is hoped that this attempt using geospatial techniques will be found applicable for other regions of the world and better planning and management of lands, too. 1 Food and Agriculture Organization 2 United Nations Environment Programme

scholarly journals A new approach for land degradation and desertification assessment using geospatial techniques

2018 ◽  
Vol 18 (4) ◽  
pp. 1133-1140 ◽  
Author(s):  
Masoud Masoudi ◽  
Parviz Jokar ◽  
Biswajeet Pradhan
Keyword(s):  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Evaluation Method ◽  
Statistical Tests ◽  
United Nations Environment Programme ◽  
Geospatial Techniques ◽  
New Approach ◽  
Khuzestan Province ◽  
Current State

Abstract. Land degradation reduces the production of biomass and vegetation cover for all forms of land use. The lack of specific data related to degradation is a severe limitation for its monitoring. Assessment of the current state of land degradation or desertification is very difficult because this phenomenon includes several complex processes. For that reason, no common agreement has been achieved among the scientific community for its assessment. This study was carried out as an attempt to develop a new approach for land degradation assessment, based on its current state by modifying of Food and Agriculture Organization (FAO)–United Nations Environment Programme (UNEP) index and the normalized difference vegetation index (NDVI) index in Khuzestan province, southwestern Iran. Using the proposed evaluation method it is easy to understand the degree of destruction caused by the pursuit of low costs and in order to save time. Results showed that based on the percent of hazard classes in the current condition of land degradation, the most and least widespread areas of hazard classes are moderate (38.6 %) and no hazard (0.65 %) classes, respectively. Results in the desert component of the study area showed that the severe class is much more widespread than the other hazard classes, which could indicate an environmentally dangerous situation. Statistical results indicated that degradation is highest in deserts and rangeland areas compared to dry cultivated areas and forests. Statistical tests also showed that the average degradation amount in the arid region is higher than in other climates. It is hoped that this study's use of geospatial techniques will be found to be applicable in other regions of the world and can also contribute to better planning and management of land.

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 Testing Possible Scenario-Based Responses of Vegetation Under Expected Climatic Changes in Khuzestan Province

2021 ◽  
Vol 14 ◽  
pp. 117862212110133
Author(s):  
Hadi Eskandari Damaneh ◽  
Meysam Jafari ◽  
Hamed Eskandari Damaneh ◽  
Marjan Behnia ◽  
Asadollah Khoorani ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Kendall Test ◽  
Baseline Period ◽  
System Model ◽  
Future Period ◽  
Khuzestan Province ◽  
Ecosystem Planning ◽  
Slope Estimator ◽  
Precipitation And Temperature

Projections of future scenarios are scarce in developing countries where human activities are increasing and impacting land uses. We present a research based on the assessment of the baseline trends of normalized difference vegetation index (NDVI), precipitation, and temperature data for the Khuzestan Province, Iran, from 1984 to 2015 compiled from ground-based and remotely sensed sources. To achieve this goal, the Sen’s slope estimator, the Mann-Kendall test, and Pearson’s correlation test were used. After that, future trends in precipitation and temperature were estimated using the Canadian Earth System Model (CanESM2) model and were then used to estimate the NDVI trend for two future periods: from 2016 to 2046 and from 2046 to 2075. Our results showed that during the baseline period, precipitation decreased at all stations: 33.3% displayed a significant trend and the others were insignificant ones. Over the same period, the temperature increased at 66.7% of stations while NDVI decreased at all stations. The NDVI–precipitation relationship was positive while NDVI–temperature showed an inverse trend. During the first of the possible future periods and under the RCP2.6, RCP4.5, and RCP8.5 scenarios, NDVI and precipitation decreased, and temperatures significantly increased. In addition, the same trends were observed during the second future period; most of these were statistically significant. We conclude that much assessments are valuable and integral components of effective ecosystem planning and decisions.

scholarly journals Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3676 ◽  
Author(s):  
Hao Chen ◽  
Xiangnan Liu ◽  
Chao Ding ◽  
Fang Huang
Keyword(s):  
Trend Analysis ◽  
Land Degradation ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growing Season ◽  
Practical Method ◽  
Large Area ◽  
Modis Ndvi ◽  
Daily Precipitation Data ◽  
Improved Model

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000–2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.

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 Regrowth and ornamental traits of bermudagrass fertilized with sewage sludge

2020 ◽  
Vol 26 (3) ◽  
pp. 390-398
Author(s):  
Philippe Solano Toledo Silva ◽  
Alessandro Reinaldo Zabotto ◽  
Patrick Luan Ferreira dos Santos ◽  
Matheus Vinícius Leal do Nascimento ◽  
Armando Reis Tavares ◽  
...  
Keyword(s):  
Sewage Sludge ◽  
Soil Solution ◽  
Digital Image Analysis ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Aesthetic Aspect ◽  
Positive Correlations ◽  
The Aesthetic ◽  
Ornamental Traits

Abstract The sewage sludge is a low-cost material and sustainable alternative to substitute chemical fertilizers on ornamental lawns and gardens. Thus, the objective was to evaluate the effects of the application of sewage sludge on the regrowth and ornamental traits of DiscoveryTM bermudagrass. The experiment was carried out during the fall/winter of 2019. The turf was removed and left the soil exposed for a new grass regrowth. The treatments applied were 0, 357, 714, 1,071 and 1,428 g m-2 sewage sludge spread evenly on the lawn in a single dose. The evaluations were carried out after 120 days and the soil solution (EC and NO3 -), Normalized difference vegetation index, root length, root + rhizome + stolon + leaves volume and digital image analysis were evaluated. The results showed that the increase of sewage sludge positively influenced the turfgrass development, both in the aesthetic aspect and on bermudagrass regrowth. The soil solution can show that the sludge increased the electrical conductivity and NO3- ions; however, it did not hinder the development of the lawn, even having positive correlations between these variables and the biometric evaluations of the plant. It is concluded that the dose of 1,428 g m-2 presented the best results for the evaluated characteristics, being the recommended one for use in the fertilization of bermudagrass DiscoveryTM.

Evaluation of a Low-cost Camera for Agricultural Applications

2019 ◽  
pp. 1-9 ◽  
Author(s):  
Abdon Francisco Aureliano Netto ◽  
Rodrigo Nogueira Martins ◽  
Guilherme Silverio Aquino De Souza ◽  
Fernando Ferreira Lima Dos Santos ◽  
Jorge Tadeu Fim Rosas
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Vegetation Indices ◽  
Paspalum Notatum ◽  
Crop Canopy ◽  
N Application ◽  
Satisfactory Accuracy ◽  
Agricultural Applications

This study aimed to modify a webcam by replacing its near-infrared (NIR) blocking filter to a low-cost red, green and blue (RGB) filter for obtaining NIR images and to evaluate its performance in two agricultural applications. First, the sensitivity of the webcam to differentiate normalized difference vegetation index (NDVI) levels through five nitrogen (N) doses applied to the Batatais grass (Paspalum notatum Flugge) was verified. Second, images from maize crops were processed using different vegetation indices, and thresholding methods with the aim of determining the best method for segmenting crop canopy from the soil. Results showed that the webcam sensor was capable of detecting the effect of N doses through different NDVI values at 7 and 21 days after N application. In the second application, the use of thresholding methods, such as Otsu, Manual, and Bayes when previously processed by vegetation indices showed satisfactory accuracy (up to 73.3%) in separating the crop canopy from the soil.

scholarly journals USE OF GREENDRONE UAS SYSTEM FOR MAIZE CROP MONITORING

2017 ◽  
Vol XLII-2/W6 ◽  
pp. 263-268 ◽  
Author(s):  
A. K. Nasir ◽  
M. Tharani
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Low Cost ◽  
Research Work ◽  
Aerial Images ◽  
Stress Index ◽  
Maize Crop ◽  
Crop Monitoring ◽  
Water Stress Index ◽  
Long Endurance

This research work presents the use of a low-cost Unmanned Aerial System (UAS) – GreenDrone for the monitoring of Maize crop. GreenDrone consist of a long endurance fixed wing air-frame equipped with a modified Canon camera for the calculation of Normalized Difference Vegetation Index (NDVI) and FLIR thermal camera for Water Stress Index (WSI) calculations. Several flights were conducted over the study site in order to acquire data during different phases of the crop growth. By the calculation of NDVI and NGB images we were able to identify areas with potential low yield, spatial variability in the plant counts, and irregularities in nitrogen application and water application related issues. Furthermore, some parameters which are important for the acquisition of good aerial images in order to create quality Orthomosaic image are also discussed.

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