Monitoring the Dynamic Changes in Vegetation Cover Using Spatio-Temporal Remote Sensing Data from 1984 to 2020

Abstract

Anthropogenic activities and natural climate changes are the central driving forces of global ecosystems and agriculture changes. Climate changes, such as rainfall and temperature changes, have had the greatest impact on different types of plant production around the world. In the present study, we investigated the spatiotemporal variation of major crops (cotton, rice, wheat, and sugarcane) in the District Vehari, Pakistan, from 1984 to 2020 using remote sensing (RS) technology. The crop identification was pre-processed in ArcGIS software based on Landsat images. After pre-processing, supervised classification was used, which explains the maximum likelihood classification (MLC) to identify the vegetation changes. Our results showed that in the study area cultivated areas under wheat and cotton decreased by almost 5.4% and 9.1% from 1984 to 2020, respectively. Vegetated areas have maximum values of NDVI (> 0.4), and built-up areas showed fewer NDVI values (0 to 0.2) in the District Vehari. During the Rabi season, the temperature was increased from 19.93 °C to 21.17 °C. The average temperature was calculated at 34.28 °C to 35.54 °C during the Kharif season in the District Vehari. Our results showed that temperature negatively affects sugarcane, rice, and cotton crops during the Rabi season, and precipitation positively affects sugarcane, rice, and cotton crops during the Kharif season in the study area. Accurate and timely assessment of crop estimation and relation to climate change can give very useful information for decision-makers, governments, and planners in formulating policies regarding crop management and improving agriculture yields.

Effects of riparian buffer and stream channel widths on ecological indicators in the upper and lower Indus River basins in Pakistan

“…Although there are some differences in biodiversity between those naturally occurring and those that have been somewhat impacted (Muhammad et al, 2022c;Hussain et al, 2022;Islam et al, 2022), habitat loss and fragmentation have contributed to changes in protected species (Haq et al, 2021b;Hu et al, 2022), especially in narrow buffer zones such as streams. Compared to narrow buffer zones, wider buffer zones contain a broader diversity of habitats and plant types (Gundersen et al, 2010;Tata, 2021).…”

Land subsidence analysis using synthetic aperture radar data

“…It supports most satellite data, including Sentinel, MODIS, Envisat, Terra-SAR, etc. [ 7 , 13 ]. Therefore, SARPROZ being the commercial software, provides better results and accuracy.…”

“…It is a natural hazard that can progress gradually or suddenly depending on the conditions. Some earlier methods [ [5] , [6] , [7] , [8] ] of measuring subsidence included a global positioning system (GPS), ground-based field observation data, repeated Geodetic Leveling Surveys, and ground and water sensors. However, these surveys are now considered costly and limited and present-day research relies on remote sending based Synthetic Aperture Radar (SAR) surveys for measuring subsidence [ 9 , 10 ].…”

Prediction of flash flood susceptibility using integrating analytic hierarchy process (AHP) and frequency ratio (FR) algorithms

“…The havoc of flash floods has been greater in those parts of the world that have not developed a system of forecast and flood effects mitigation (Kheradmand et al, 2018;Basharat et al, 2022;da Silva Monteiro et al, 2022). To avoid mass movement and reduce the aftermaths, it is crucial to develop a mapping system based on different parameters of cause and effects (Basin, 2021;Islam F. et al, 2022;Sharifi et al, 2022a;Hussain et al, 2022b). One of the major reasons for floods is heavy rainfall and the low discharge capacity of canals, rivers, and dams.…”