Environmental sensitivity to mosquito transmitted diseases in El-Fayoum using spatial analyses

El-Fayoum governorate has unique characteristics which induces mosquito proliferation and thus increased the risk arisen from diseases transmission. Present study explores the role of remote sensing and GIS modeling integrated with field survey for mapping mosquito breeding sites and the areas under risk of diseases transmission in El-Fayoum governorate. Entomological surveys were conducted for a total number of 40 accessible breeding sites during the period 12-16 November 2017. A calibrated Landsat OLI image, synchronized with the field trip, was processed to produce Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), and Land Surface Temperature (LST). A cartographic GIS model was generated to predict breeding sites in the whole governorate and to assess the potential risk. The main filarial disease vector (Culex pipiens) was abundant at Atsa district, while Malaria vectors (Anopheles sergentii and Anopheles multicolor) were mainly distributed in El-Fayoum and Youssef El-Seddiq districts. Means levels of NDVI, NDMI and LST at breeding habitats were recorded; 0.18, 0.08 and 21.75° C, respectively. Results of the model showed that the highest predicted risk area was reported at Atsa district (94.4 km2) and Yousef El-Sediq (81.8 km2) while the lowest prediction was observed at Abshawai district (35.9 km2). It can be concluded that Atsa, Yousef El-Sedik and El-Fayoum districts are more vulnerable to Malaria and Filaria diseases outbreaks, thus precaution and pest control methods must be applied to mitigate the possible risks

Past and Future Changes of Land Use/Land Cover and the Potential Impact on Ecosystem Services Value of Damietta Governorate, Egypt

This investigation aims to assess the changes of Land Use/Land Cover (LULC) and its impact on ecosystem services value in Damietta Governorate, Egypt. To fulfill this aim, Landsat data of TM5 in 2001, ETM in 2011 and OLI in 2021 were used. The Maximum Likelihood Classifier was employed to track the changes in LULC of the study area. Cellular automata (CA) and Markov model adopted from IDRISI software were used for accurate prediction of the LULC in 2031. The VALIDATE model in TerrSet was used to compare the predicted 2031 LULC with actual 2021 LULC to assess the accuracy of the model. The Millennium Ecosystem Assessment was utilized to assess the value per unit area of land types. The results indicated that there was a noticeable change in different land cover classes during the duration 2001–2021. Results showed that there are decreases in the cultivated area and the bare area, meanwhile the urban area was increased. The cultivated area was remarkably decreased recording 548.2 km2 (62.15%) at 2001, 548.2 km2 (55.79%) at 2011 and 468.96 km2 (53.16%) at 2021 of the total study area. However, the percentage of urban area increased; reporting 65.69 km2 (7.45%), 124.57 km2 (14.12%), and 176.67 km2 (20.03%) at 2001, 2011, and 2021, respectively. LULC analyses in 2031 showed an increase in the urban area by 2.8% and a decrease in the cultivated area by 7.2%. The kappa index values are greater than 0.80, which shows a strong agreement between simulated and predicted LULC maps. The comprehensive index of Damietta Governorate ranges from 100 to 400. The ES that experienced positive ESV changes during the study period gives strength indicator for achieving the sustainable development of Damietta Governorate. To prevent further ecosystem degradation and to ensure the best possible delivery of ES, it is necessary to reduce the current drivers of LULC changes within the buildup in agricultural land. The study helps the local authorities to better understand the land use system and to develop an improved land use management strategies that manage the urban expansion and guarantee the ecological conservation

Wild Plant Habitat Characterization in the Last Two Decades in the Nile Delta Coastal Region of Egypt

Environmental and land-use changes put severe pressure on wild plant habitats. The present study aims to assess the biodiversity of wild plant habitats and the associated spatiotemporal environmental changes in the coastal region of Dakahlia Governorate following an integrated approach of remote sensing, GIS, and samples analysis. Thirty-seven stands were spatially identified and studied to represent the different habitats of wild plants in the Deltaic Mediterranean coastline region. Physical and chemical characteristics of soil samples were examined, while TWINSPAN classification was used to identify plant communities. Two free Landsat images (TM and OLI) acquired in 1999 and 2019 were processed to assess changes via the production of land use and cover maps (LULC). Moreover, NDSI, NDMI, and NDSI indices were used to identify wild plant habitats. The floristic composition indicated the existence of 57 species, belonging to 51 genera of 20 families. The largest families were Asteraceae, Poaceae, and Chenopodiaceae. The classification of vegetation led to the identification of four groups. Canonical Correspondence Analysis (CCA) revealed that electrical conductivity, cations, organic carbon, porosity, chlorides, and bicarbonates are the most effective soil variables influencing vegetation. The results of the spectral analysis indicated an annual coverage of bare lands (3.56 km2), which is strongly related to the annual increase in vegetation (1.91 km2), water bodies (1.22 km2), and urban areas (0.43 km2). The expansion of urban and agricultural regions subsequently increased water bodies and caused occupancy of bare land, resulting in the development of wild plant habitats, which are mostly represented by the sparse vegetation class as evaluated by NDVI. The increase in mean moisture values (NDMI) from 0.03 in 1999 to 0.15 in 2019 might be explained by the increase in total areas of wild plant habitats throughout the study period (1999–2019). This may improve the adequacy of environments for wild habitats, causing natural plant proliferation