Effects of climate change on vegetation and snow cover area in Gilgit Baltistan using MODIS data

Satti, Zulqarnain; Naveed, Muhammad; Shafeeque, Muhammad; Ali, Sikandar; Abdullaev, Farkhod; Ashraf, Tauseef Muhammad; Irshad, Muhammad; Li, Lanhai

doi:10.1007/s11356-022-23445-3

Cited by 5 publications

(2 citation statements)

References 90 publications

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“…It indicates that the duration of summer is expanding, and the duration of winter is shrinking. The shift in winter season in these elevated zones has been noted in a study by Satti et al (2022). Notably, in two study sites Tisssar and Sundus (located at relatively lower altitude) in Gilgit-Baltistan, local people also reported an increase in overall snowfall and rainfall.…”

Section: Local Perception Of Climate Change Water Related Hazards And...supporting

confidence: 54%

Climate change, water and agriculture linkages in the upper Indus basin: A field study from Gilgit-Baltistan and Leh-Ladakh

Tuladhar

Hussain

Baig³

et al. 2023

Front. Sustain. Food Syst.

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The Indus is one of three largest river systems emerging from the Hindu-Kush Himalaya (HKH). In the Upper Indus Basin (UIB), water resources, agriculture and livelihoods are highly vulnerable to climate change induced hazards and risks. Present study investigates impacts of climate change on water availability, agriculture and livelihoods based on perception data collected through focus group discussions and key informant interviews from selected study sites in Gilgit-Baltistan and Leh-Ladakh subregions of the UIB. Findings revealed that climate change is inducing both direct and indirect impacts on water availability, agriculture, and livelihoods. Local people reported that changes in precipitations patterns, temperature and timing of seasons, and increased incidence of crop pest attacks are resulting in the decline of crop and livestock productivity (direct impacts). Climate change is also impacting productivity indirectly through degradation of rangelands/pastures and water variability in traditional irrigation systems. Local people are taking diverse adaptation measures to cope with climate change impacts. These measures include revival of less water intensive traditional crops, start of enterprises and value chain developments in Gilgit-Baltistan, and improvement in water management practices and integration of traditional agricultural products with tourism in Leh-Ladakh. Some adaptation measures are likely to have negative impacts on sustainability of local agriculture. For instance, inorganic agricultural practices in Gilgit-Baltistan, and unplanned shift to water intensive crops and improved breeds of livestock in both Gilgit-Baltistan and Leh-Ladakh. Based on findings, this study suggests establishing a learning mechanism for local communities through collaboration of local institutions from both sides of border and people to people connections.

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Section: Local Perception Of Climate Change Water Related Hazards And...supporting

confidence: 54%

Climate change, water and agriculture linkages in the upper Indus basin: A field study from Gilgit-Baltistan and Leh-Ladakh

Tuladhar

Hussain

Baig³

et al. 2023

Front. Sustain. Food Syst.

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“…5,15 Many methods for estimating leaf water content from reflectance data at different levels have been developed; however, they generally rely on empirical or physical approaches that use regression techniques using hyperspectral indices and leaf and canopy radiative transfer models. 16,17 Ordinary least squares regression approaches are often used at the leaf level to build empirical correlations between leaf water content and laboratory reflectance data acquired in the near-and short-infrared spectral regions. Using acceptable spectral reflectance indices, several investigations have employed empirical relationships to assess leaf water content.…”

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confidence: 99%

Spectral indices for tracing leaf water status with hyperspectral reflectance data

Yasir

Zhang

Tang

et al. 2023

J. Appl. Rem. Sens.

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Plant water stress can be detected via remote sensing. The objective of the study was to determine which leaf water index is best for assessing leaf water content from the laboratory standpoint. This study investigated the relationship between equivalent water thicknesses (EWT), gravimetric water content (GWC), and plant water concentration in the 350-to 2500-nm reflectance spectral range. A total of 277 leaf samples taken from ten different plants were used as calibration dataset, and 605 leaves from different plants, including LOPEX93 and ANGERS database, were used for validation. Three specific indices were analyzed: simple ratio, normalized ratio, and double difference (Datt type of index). A regression approach based on the iteration method at 5-nm interval was used for model calibration. Three bands index was found the most suitable and was validated by 605 leaf samples: for the linear regression model, the index is ðR 1910 − R 1340 Þ∕ðR 1910 − R 1125 Þ with R 2 ¼ 0.96 and root mean square error ðRMSEÞ ¼ 0.001 ðg∕cm 2 Þ and, for nonlinear regression model the index is ðR 1930 − R 1425 Þ∕ðR 1930 − R 1360 Þ with R 2 ¼ 0.95 and RMSE ¼ 0.001 ðg∕cm 2 Þ for EWT. The newly proposed indices take advantage of being able to eliminate additional noise created by the leaf surface, making them helpful for agricultural-related research.

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Evaluation of the effects of climate change on the mid-elevation pasture vegetation of mountainous areas; A Case Study of the Sablan Mountainside, Iran

Hashemian,

Fataei,

Mosayebi

et al. 2023

Preprint

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The impact of global warming and climate change on vegetation is a significant challenge in the present day. The pastures of the Sablan Mountains, located in Northwestern Iran, in Azerbaijan, are renowned for their richness and pivotal role in supporting the livelihood of residents. Additionally, these meadows serve as an alluring destination for climbers and tourists from around the world, offering a captivating recreational experience In this study, the trends of climate parameter changes and vegetation cover over a period of 17 years (2019–2003) were investigated using meteorological data from two range stations and the NDVI index derived from Landsat satellite images. The Mann-Kendall test was employed to analyze the trends, and the relationship between the simple and multiple linear regression of climate parameters and the NDVI of the entire pasture was examined. Specifically, the analysis focused on pastures at different elevations, including low elevations(2500–1500 m), middle elevations (3500–2500 m), and high elevations (above 3500 m). Additionally, a map illustrating the changes in NDVI over the 17–year period was created. According to the findings, it was observed that among the various climatic parameters examined, only the average temperature in June exhibited a significant increasing trend. The rate of increase was measured at 0.071 degrees Celsius per year, with a significance level of 5 percent Based on the analysis of NDVI trends during the first month of summer, it was observed that the NDVI of the total land use classification of pasture and the mid-elevation pasture land use classification (3500–2500 m) exhibited significant increases at a significance level of 5 percent. Precisely, the NDVI of the total land use classification of pasture showed an annual increase of 0.004, while the mid-elevation pasture land use classification demonstrated an annual increase of 0.006. The simple linear regression analysis revealed a significant direct linear correlation (R) between the NDVI of high-elevation pastures (3500–2500 meters) and the average and maximum temperatures in July: The NDVI exhibited a correlation coefficient of 0.567 with the average temperature and 0.527 with the maximum temperature, both at a significance level of 1 percent. The NDVI of pasture land use exhibited a significant straight simple linear correlation of 0.554 with the average temperature in June, at a significance level of 1 percent. The multiple linear regression analysis revealed that when considering both the average and maximum temperature of the spring as simultaneous predictors, the direct correlation between the NDVI of the 3500–2500 m class of pasture and these parameters increased from 0.567 (in the simple linear model) to 0.727 (in the multiple linear model). The results of this study suggest that the rise in temperature within the pastures of the Sablan Mountains has created favorable circumstances for the growth and expansion of vegetation, particularly in middle elevations.

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Effects of climate change on vegetation and snow cover area in Gilgit Baltistan using MODIS data

Cited by 5 publications

References 90 publications

Climate change, water and agriculture linkages in the upper Indus basin: A field study from Gilgit-Baltistan and Leh-Ladakh

Climate change, water and agriculture linkages in the upper Indus basin: A field study from Gilgit-Baltistan and Leh-Ladakh

Spectral indices for tracing leaf water status with hyperspectral reflectance data

Evaluation of the effects of climate change on the mid-elevation pasture vegetation of mountainous areas; A Case Study of the Sablan Mountainside, Iran

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