Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

The identification of land use/land cover (LULC) changes is important for monitoring, evaluating, and preserving natural resources. In the Kurdistan region, the utilization of remotely sensed data to assess the effectiveness of machine learning algorithms (MLAs) for LULC classification and change detection analysis has been limited. This study monitors and analyzes LULC changes in the study area from 1991 to 2021 using a quantitative approach with multi-temporal Landsat imagery. Five MLAs were applied: Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), K-Nearest Neighbor (KNN), and Extreme Gradient Boosting (XGBoost). The results showed that the RF algorithm produced the most accurate maps of the three-decade study period, accompanied by a high kappa coefficient (0.93–0.97) compared with the SVM (0.91–0.95), ANN (0.91–0.96), KNN (0.92–0.96), and XGBoost (0.92–0.95) algorithms. Consequently, the RF classifier was implemented to categorize all obtainable satellite images. Socioeconomic changes throughout these transition periods were revealed by the change detection results. Rangeland and barren land areas decreased by 11.33 % (−402.03 km²) and 6.68 % (−236.8 km²), respectively. The transmission increases of 13.54 % (480.18 km²), 3.43 % (151.74 km²), and 0.71 % (25.22 km²) occurred in agricultural land, forest, and built-up areas, respectively. The outcomes of this study contribute significantly to LULC monitoring in developing regions, guiding stakeholders to identify vulnerable areas for better land use planning and sustainable environmental protection.

The aim of this study was to assess the heavy metal pollution in soils after mine clearance and disposal through controlled explosions in dugout pits during demining operations at two hotspot areas, in the Halgurd-Sakran National Park (HSNP). This investigation was undertaken in order to reveal the concentration level, migration and enrichment in various heavy metals present in polluted soils. Eighteen samples, nine sampling positions at each site, were collected. The current study used inductively coupled plasma-emission spectroscopy (ICP-ES) methodology to determine the concentration levels of Cu, Pb, Zn, Ni, Co, Mn, As and Cr in the soil samples as important toxic contaminants resulting from the demining process. The results show concentration levels of 63.33, 16.22, 116.44, 328, 32.66, 1594.33, 7 and 291.55 ppm in site 1 for Cu, Pb, Zn, Ni, Co, Mn, As and Cr, respectively, while site 2 gave 72.55, 17, 102.55, 296.55, 32, 1851.88, 9.11 and 308.77 ppm. Soil enrichment factor (EF) in sites 1 and 2 of the heavy metals Ni, Cr, Mn, Co and Cu ranged from extremely high enrichment to moderate-high enrichment, respectively. The geo-accumulation (I-geo) index indicated contamination levels that ranged from very strongly to moderately contaminated soil for Ni, Cr, Mn, Co and Cu, respectively. On the other hand, the pollution load index (PLI) showed all values from all samples in both sites were above 1 indicating totally contaminated areas. However, the most polluting heavy metals in the soil at both sites are Ni and Cr with high contamination levels attributed to the controlled mines’ detonations. In conclusion, these mines’ detonations are producing residual heavy metals in the soil that are potentially harmful to the vegetation cover, animals and ultimately humans.

This study presents an analysis of Landsat data to quantify how the deployment of landmines and demining operations in the first national park in Iraq, the Halgurd-Sakran Core Zone (HSCZ) in the Kurdistan region, has altered the vegetation/land cover patterns over 17 years (between 1998 and 2015). Post-war impacts of landmines on land cover fragmentation and degradation in HSCZ are examined using GIS and remote sensing. Landmines fundamentally change the available land use options for local communities by limiting access to the land. Their widespread use in military conflicts around the world made investigating the impacts of minefields on land cover fragmentation the subject of scientific studies. The Iraqi-Iranian war (1980–1988) and subsequent conflicts have left behind densely mined areas in Kurdistan, especially in the border zones, which were previous battle zones. These leftover weapons of historic wars are indiscriminate and still affecting people. The results revealed that the relationship between land use/land cover (LULC) classes before and after the Fall of Baghdad is different for all classes, especially for pasture and cultivated lands. Between 1998 and 2015 the proportion of land covered by forest or under agricultural cultivation decreased substantially, matched by a large increase in pasture extent. The results also show that after 2003 increased attention has been paid to raising landmine awareness in the areas most affected by mines. Additionally, the landmines slowed down the progression in HSCZ, otherwise, agricultural production and productivity could potentially have doubled. The change in cultivated land area in the park does not relate to population growth but to the presence of minefields, minefield programme awareness, and socio-economic factors. Strong rural pull factors succeeded in bringing displaced people back to villages as a result of social progress, economic growth, and political stability in HSCZ.

Halgurd Sakran National Park (HSNP) is Iraq’s first designated national park, located in the Kurdistan Region, which has suffered multiple armed conflicts over the past decades. This study assesses how vegetation dynamics have affected the landscape structure and composition of the core zone of the park over the last 31 years. Spatio-temporal changes in land cover were mapped for three points in time using remote sensing, geographic information systems (GIS), and landscape metrics. Land cover changes were mapped using random forest classifications of satellite images from Landsat 5 TM, Landsat 7 ETM+, and Landsat 8 LDCM acquired in 1984, 1998, and 2015. Five landscape pattern metrics were analysed at class and landscape levels in order to quantify landscape patterns arising from land use and land cover (LULC) change in HSNP using FRAGSTATS 4.2. These landscape pattern metrics were patch metrics, area metrics, shape metrics interspersion/juxtaposition and contagion metrics and diversity metrics. Significant changes in cultivated areas after 1991 were observed, which indicate the role of anthropogenic activities in land cover change. Areas of bare surface and forest lands declined and became more fragmented in 1984 and 1998 while, at the same time, cultivated areas increased, with a continuing fragmentation of pasture land. Internal migration of people was one of the major drivers of LULC change. The results reveal that significant LULC changes in terms of composition and spatial structure over the 31-year period have occurred in the designated protected area. Landscape metrics were able to assess the trend of spatial patchiness over the studied period. A discussion of the significance of changes in land use systems for understanding the causes and consequences of change is provided.