Negative impacts of climate change on ecosystems have been increasing, and both the intensification and the mitigation of these impacts are strongly linked with human activities. Management and reduction of human-induced disturbances on ecosystems can mitigate the effects of climate change and enhance the ecosystem recovery process. Here, we investigate coupled human and climate effects on the wetland ecosystem of the lower Helmand basin from 1977 to 2014. Using time series climate-variable data and land-use changes from Landsat time series imagery, we compared changes in ecosystem status between the upstream and downstream regions. Results show that despite a strong and prolonged drought in the region, the upstream region of the lower Helmand basin remained dominated by agriculture, causing severe water stress on the Hamoun wetlands downstream. The loss of available water in wetlands was followed by large-scale land abandonment in rural areas, migration to the cities, and increasing unemployment and economic hardship. Our results suggest that unsustainable land-use policies in the upstream region, combined with synergistic effects of human activities and climate in lower Helmand basin, have exacerbated the effects of water stress on local inhabitants in the downstream region.

Remote sensing data analysis can provide thematic maps describing land-use and land-cover (LULC) in a short period. Using proper image classification method in an area, is important to overcome the possible limitations of satellite imageries for producing land-use and land-cover maps. In the present study, a hierarchical hybrid image classification method was used to produce LULC maps using Landsat Thematic mapper TM for the year of 1998 and operational land imager OLI for the year of 2016. Images were classified using the proposed hybrid image classification method, vegetation cover crown percentage map from normalized difference vegetation index, Fisher supervised classification and object-based image classification methods. Accuracy assessment results showed that the hybrid classification method produced maps with total accuracy up to 84 percent with kappa statistic value 0.81. Results of this study showed that the proposed classification method worked better with OLI sensor than with TM. Although OLI has a higher radiometric resolution than TM, the produced LULC map using TM is almost accurate like OLI, which is because of LULC definitions and image classification methods used.

This research used geospatial data to quantify biodiversity changes and landscape pattern change to track anthropogenic impacts of such changes at the Mouteh Wildlife Refuge (MWR), Isfahan, Iran. Satellite image duration of four decades, LandSat1-5, and IRS-P6 data were used to develop land cover classification maps for 1971, 1987, 1998, and 2011. The number and size of land cover patches, the degree of naturalness, and the diversity indices were calculated and compared for a 40-year period. The results showed an increasing concern with regard to unplanned human activities. Some improvements of the natural landscape also occurred in the core protected zone of the study area. The number and size of land cover patches, the degree of naturalness, and the diversity indices were calculated. Overall changes in natural land use between 1971 and 1998 at MWR showed that the number of patches for natural land use has increased, but it also showed a decrease in 2011. Similar changes were observed for seminatural land use. Within the artificial classes, the number and area of patches were higher and the largest patch occurred in 2011. The maximum variation of diversity is related to the year 2011. The results showed an increasing concern with regard to unplanned human activities. Some improvements of the natural landscape also occurred in the core protected zone of the study area. Remote sensing and geographic information system offers an important means of detecting and analyzing temporal changes occurring in our landscape.

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