Drought assessment and monitoring through remote sensing and GIS in western tracts of Tamil Nadu, India

Muthumanickam, D.; Kannan, P.; Kumaraperumal, R.; Sivasamy, R.; Poongodi, C.

doi:10.1080/01431161.2010.494642

Cited by 44 publications

(27 citation statements)

References 37 publications

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“…Remotely sensed imagery is becoming a common tool for reconstructing a site's history and detecting changes in vegetation cover (Zweig & Newman 2015;Abdullah et al 2016). Several researchers agree that remote sensing (RS) can help generate the necessary information to study the distribution of vegetation cover (Shuman & Ambrose 2003;Muthumanickam et al 2011;Im et al 2012;Peng et al 2012;Harris et al 2014) and monitor desertification (Diouf & Lambin 2001;Mollot & Bilby 2008;Malmstrom et al 2009) in arid and semi-arid lands. RS allows researchers to examine dynamic landscape changes (Herold et al 2002;Groom et al 2006;Jia et al 2008;Hadeel et al 2010;Abdullah et al 2016), but the classification of arid land vegetation images can be challenging because of the high reflectance of the soil background, variable mixture of green and senescent grasses, shrubs and herbs, and multiple reflectance from open canopies and bright soils (Laliberte et al 2007).…”

Section: Introductionmentioning

confidence: 99%

Assessing native desert vegetation recovery in a war‐affected area using multispectral and hyperspectral imagery: a case study of the Sabah Al‐Ahmad Nature Reserve, Kuwait

Abdullah

Addae‐Wireko

Tena‐Gonzalez

2017

Restoration Ecology

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The primary aim of this project was to assess vegetation changes in the Sabah Al‐Ahmad Nature Reserve, Kuwait, which is a war‐affected area following the Iraqi invasion in 1990. After the liberation in 1991, several portions of the reserve were under a restoration program. Remote sensing has been used as a tool to assess vegetation and land cover changes. We studied the feasibility of three common methods—the Mahalanobis distance (MD), maximum likelihood (ML), and support vector machine (SVM)—for classification of the multispectral imagery (Landsat) and hyperspectral (Hyperion). The reserve was also compared to the demilitarized zone (DMZ) located at Umm Nigga at the northern border of Kuwait, as it had recovered naturally, to distinguish between an autogenic recovery and a restored area. We discovered that the location was damaged during the military occupation, but a rapid recovery of the vegetation was then recorded in the reserve after the war from less than 1% measured in 1991 to 42% in 1998. Then, the vegetation cover significantly decreased in 2002 (26%) and slightly increased in 2013 (28%). We found that similar rapid increase in vegetation cover occurred in most parts of the reserve that was under the restoration program, and in the DMZ, which was naturally recovered. We concluded that remote sensing technologies are helpful tools in understanding the process of vegetation recovery as it provides information on location and timing of recovery, particularly where optimal condition exists.

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Section: Introductionmentioning

confidence: 99%

Assessing native desert vegetation recovery in a war‐affected area using multispectral and hyperspectral imagery: a case study of the Sabah Al‐Ahmad Nature Reserve, Kuwait

Abdullah

Addae‐Wireko

Tena‐Gonzalez

2017

Restoration Ecology

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“…Remote sensing also enables researchers to analyze dynamic changes in landscapes (Herold et al ; Groom et al ; Jia et al ; Hadeel et al ). According to previous studies, remote sensing can help in generating a significant amount of information needed to evaluate the distribution of vegetation cover (Muthumanickam et al ; Im et al ; Harris et al ) and monitoring landscape degradation in arid and semiarid environments (Tueller ; Washington‐Allen et al , , ; Diouf & Lambin ; Chen et al ). The Normalized Difference Vegetation Index (NDVI) is a widely used method in remote sensing to evaluate vegetation and measure the amount of photosynthesis in semiarid lands (Cui et al ).…”

Section: Introductionmentioning

confidence: 99%

The use of remote sensing to develop a site history for restoration planning in an arid landscape

Abdullah

Feagin

Musawi

et al. 2015

Restoration Ecology

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Developing a site history and ecological site description is one of the critical steps in restoration planning for arid landscapes. This study focuses on Umm Nigga, Northeast of Kuwait, which was damaged by various human activities. The northern portion of Umm Nigga falls within the boundaries of the demilitarized zone (DMZ) adjacent to Iraq, and was fenced off to restrict public access since 1994. The central objective of this project was to use remote sensing, field assessment, and Geographical Information System (GIS) spatial data to develop a site history for restoration planning of Umm Nigga. Field observation and GIS analysis indicated that the landscape could be divided into three units along a gradient ranging from the coast to inland locations, based on geology, soil properties, and dominant vegetation. Reference sites in the DMZ were also matched for each unit. Remote sensing was used to compare vegetation cover between damaged and reference sites at selected units. Results showed that vegetation cover increased in the unfenced damaged site after the 1991 Gulf War from 2% in 1988 to 37% in 1998, but then it decreased to 23% in 2013. In the DMZ reference site, the vegetation cover also increased from 0% in 1988 to 40% in 1998, but it continued increasing through 2013 to 64%. We conclude that overgrazing and destructive camping are the major source of disturbance in the damaged areas.

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“…To cover vast areas, remote‐sensed data is useful for detecting the changes in land and monitoring desertification. Using remote‐sensed data, the information such as the distribution of vegetation (Harris, Carr, & Dash, 2014; Im et al, 2012; Muthumanickam et al, 2011; Peng, Zhou, Liang, & Ren, 2012; Shuman & Ambrose, 2003) or the status of desertification (Diouf & Lambin, 2001; Malmström, Persson, Ahlström, Gongalsky, & Bengtsson, 2009; Mollot & Bilby, 2008) in arid and semiarid lands can be obtained easily and effectively in terms of cost and time. Also, by managing the time and space information obtained from the remote sensing data, it is possible to collectively manage the macroscopic information after afforestation.…”

Section: Introductionmentioning

confidence: 99%

Identifying potential vegetation establishment areas on the dried Aral Sea floor using satellite images

et al. 2020

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The Aral Sea was one of the largest lakes in the world, but almost 60,000 km 2 of the waterbody has dried up due to water withdrawal for irrigation. Afforestation on the desiccated seafloor could be important in preventing soil flation, dust storms, and negative impact on human health. In this study, we aimed to delineate potential vegetation establishment areas on the dried Aral Sea bed using remote-sensed data in support of the decision-making related to afforestation. Various indices such as normalized difference vegetation index (NDVI), topsoil grain size index (TGSI), soil salinity index (SSI), and normalized multiband drought index (NMDI) were calculated from the LANDSAT-8 OLI satellite imagery. As an indicator of vegetation existence, NDVI was classified into three groups and set as a base for classifying other indices by performing statistical analyses. Based on the decision tree method, indices were combined and the potential vegetation establishment area was detected. Higher NDVI was identified in the southeast than the west of the study area. The results of statistical analyses showed that TGSI had a positive correlation with NDVI, while SSI and NMDI had a negative correlation. Overall, the potential vegetation area comprised 7,295.21 km 2 (61.34%) of the 'unsuitable' area, 2,818.64 km 2 (23.7%) of the 'intermediate' area, 1,612.15 km 2 (13.56%) of the 'suitable' area, and 166.42 km 2 (1.4%) of the 'very suitable' area. The developed map enables to identify dried seafloor area suitable for vegetation establishment thus contributing to planning the land rehabilitation efforts and preventing further land degradation.

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Drought assessment and monitoring through remote sensing and GIS in western tracts of Tamil Nadu, India

Cited by 44 publications

References 37 publications

Assessing native desert vegetation recovery in a war‐affected area using multispectral and hyperspectral imagery: a case study of the Sabah Al‐Ahmad Nature Reserve, Kuwait

Assessing native desert vegetation recovery in a war‐affected area using multispectral and hyperspectral imagery: a case study of the Sabah Al‐Ahmad Nature Reserve, Kuwait

The use of remote sensing to develop a site history for restoration planning in an arid landscape

Identifying potential vegetation establishment areas on the dried Aral Sea floor using satellite images

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