Agriculture Sprawl Assessment Using Multi-Temporal Remote Sensing Images and Its Environmental Impact; Al-Jouf, KSA

Land Cover Changes Utilising Landsat Satellite Imageries for the Kumasi Metropolis and Its Adjoining Municipalities in Ghana (1986-2022)

Forest loss, unbridled urbanisation, and the loss of arable lands have become contentious issues for the sustainable management of land. Landsat satellite images for 1986, 2003, 2013, and 2022, covering the Kumasi Metropolitan Assembly and its adjoining municipalities, were used to analyse the Land Use Land Cover (LULC) changes. The machine learning algorithm, Support Vector Machine (SVM), was used for the satellite image classification that led to the generation of the LULC maps. The Normalised Difference Vegetation Index (NDVI) and Normalised Difference Built-up Index (NDBI) were analysed to assess the correlations between the indices. The image overlays of the forest and urban extents and the calculation of the annual deforestation rates were evaluated. The study revealed decreasing trends in forestlands, increased urban/built-up areas (similar to the image overlays), and a decline in agricultural lands. However, there was a negative relationship between the NDVI and NDBI. The results corroborate the pressing need for the assessment of LULC utilising satellite sensors. This paper contributes to the existing outlines for evolving land design for the promotion of sustainable land use.

Application of remote sensing and geographic information systems in irrigation water management under water scarcity conditions in Fayoum, Egypt

Egypt suffers from severe water scarcity, which affects the sustainability of agricultural production. Therefore, the sustainable use of available water resources under water scarcity requires the adoption of water allocation policies favoring conservative and efficient use. Water management with free satellite data and geographical information system modeling capabilities can be a valuable approach for optimizing the benefits from the available water resources to meet the requirements for agricultural lands. This study aims to (i) detect and evaluate changes in agricultural areas because of urbanization and reclamation activities using Landsat data in 1999, 2009, and 2019 and (ii) update the irrigation water demand by monitoring the seasonal changes of agricultural area based on normalized difference vegetation index. Water management of Fayoum Governorate in Egypt is characterized by a non-uniform distribution flow over its canals; thus, two pilot areas are selected. The first site is the Sinnuris canal, the served areas of which represents the urbanization problem. The other site is the Gharaq canal, the served areas of which represents the urbanization and agricultural expansion situations. The results reveal that changes in agricultural areas considerably affect the uniformity of water management. Urbanization activities reduce the agricultural area by ∼5.0% and 5.7% in Sinnuris and Gharaq served areas, respectively. However, the newly cultivated lands in Gharaq preserve an increase of 5.8% in the total agricultural area. The considerably changed water allocation strategies in these districts since Sinnuris has an excess of 1.5 m³/s of water supply, while the Gharaq area faced an irrigation shortage of 0.26 m³/s in 2019. As per the proposed approach, the decision-makers can readjust the water allocation plan to satisfy the water requirements for other demand areas.

Classification Endmember Selection with Multi-Temporal Hyperspectral Data

In hyperspectral image classification, so-called spectral endmembers are used as reference data. These endmembers are either extracted from an image or taken from another source. Research has shown that endmembers extracted from an image usually perform best when classifying a single image. However, it is unclear if this also holds when classifying multi-temporal hyperspectral datasets. In this paper, we use spectral angle mapper, which is a frequently used classifier for hyperspectral datasets to classify multi-temporal airborne visible/infrared imaging spectrometer (AVIRIS) hyperspectral imagery. Three classifications are done on each of the images with endmembers being extracted from the corresponding image, and three more classifications are done on the three images while using averaged endmembers. We apply image-to-image registration and change detection to analyze the consistency of the classification results. We show that the consistency of classification accuracy using the averaged endmembers (around 65%) outperforms the classification results generated using endmembers that are extracted from each image separately (around 40%). We conclude that, for multi-temporal datasets, it is better to have an endmember collection that is not directly from the image, but is processed to a representative average.

Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations

The Special Issue on “Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations” is published. A total of 20 qualified papers are published in this Special Issue. The topics of the papers are the application of remote sensing and geospatial information systems to Earth observations in various fields such as (1) object change detection, (2) air pollution, (3) earthquakes, (4) landslides, (5) mining, (6) biomass, (7) groundwater, and (8) urban development using the techniques of remote sensing and geospatial information systems. More than 100 researchers have participated in this Special Issue. We hope that this Special Issue is helpful for sustainable applications.

Mapping the Environmental Cost of a Typical Citrus-Producing County in China: Hotspot and Optimization

The environmental sustainability of the largest citrus plantation globally is facing a great challenge in China. Further, there is a lack of quantitative, regional hotspot studies. In this study, the life cycle assessment (LCA) was used to quantify the environmental cost of citrus production based on 155 farmers’ surveys from typical citrus orchards in Danling County, southwest China, which produced 0.65% of the country’s total citrus production. The results showed that the average values of environmental risk indicated by global warming potential (GWP), acidification potential (AP), and eutrophication potential (EP) were 11,665 kg CO2-eq ha−1, 184 kg SO2-eq ha−1, and 110 kg PO4-eq ha−1, respectively. The production and utilization of fertilizer ranked the first contribution to the environmental impacts among all the environmental impacts, which contributed 92.4–95.1%, 89.4–89.8%, and 97.8–97.9% to global warming potential, acidification potential, and eutrophication potential, respectively. Specific to the contribution of fertilizers to environmental costs, the production and utilization of nitrogen (N) fertilizer accounted for more than 95% of the total environmental costs. Thus, the spatial distribution of environmental costs in this county was well matched with that of N input. Compared with the average values of investigated 155 orchards, the high yield and high N use efficiency (HH) orchard group with younger and better educated owners achieved a higher citrus yield and N use efficiency with less fertilizer input and lower environmental costs. Five field experiments conducted by local government and Danling Science and Technology Backyard were used to further certify the reduction potential of environment costs. These field results showed that the local recommendation (LR) treatment increased citrus yield and N use efficiency by 1.9–49.5% and 38.0–116%, respectively, whereas decreased environmental costs by 21.2–35.2% when compared with the local farmer practice in the HH orchard group. These results demonstrated that an optimum nutrient management based on the local field recommendation in citrus-producing areas is crucial for achieving a win-win target of productivity and environmental sustainability in China and other, similar countries.