Optimal Solar Plant Site Identification Using GIS and Remote Sensing: Framework and Case Study

Many countries have set a goal for a carbon neutral future, and the adoption of solar energy as an alternative energy source to fossil fuel is one of the major measures planned. Yet not all locations are equally suitable for solar energy generation. This is due to uneven solar radiation distribution as well as various environmental factors. A number of studies in the literature have used multicriteria decision analysis (MCDA) to determine the most suitable places to build solar power plants. To the best of our knowledge, no study has addressed the subject of optimal solar plant site identification for the Al-Qassim region, although developing renewable energy in Saudi Arabia has been put on the agenda. This paper developed a spatial MCDA framework catering to the characteristics of the Al-Qassim region. The framework adopts several tools used in Geographic Information Systems (GIS), such as Random Forest (RF) raster classification and model builder. The framework aims to ascertain the ideal sites for solar power plants in the Al-Qassim region in terms of the amount of potential photovoltaic electricity production (PVOUT) that could be produced from solar energy. For that, a combination of GIS and Analytical Hierarchy Process (AHP) techniques were employed to determine five sub-criteria weights (Slope, Global Horizontal Irradiance (GHI), proximity to roads, proximity to residential areas, proximity to powerlines) before performing spatial MCDA. The result showed that ‘the most suitable’ and ‘suitable’ areas for the establishment of solar plants are in the south and southwest of the region, representing about 17.53% of the study area. The ‘unsuitable’ areas account for about 10.17% of the total study area, which is mainly concentrated in the northern part. The rest of the region is further classified into ‘moderate’ and ‘restricted’ areas, which account for 46.42% and 25.88%, respectively. The most suitable area for potential solar energy, yields approximately 1905 Kwh/Kwp in terms of PVOUT. The proposed framework also has the potential to be applied to other regions nationally and internationally. This work contributes a reproducible GIS workflow for a low-cost but accurate adoption of a solar energy plan to achieve sustainable development goals.

Expanding or shrinking? range shifts in wild ungulates under climate change in Pamir-Karakoram mountains, Pakistan

Climate change is expected to impact a large number of organisms in many ecosystems, including several threatened mammals. A better understanding of climate impacts on species can make conservation efforts more effective. The Himalayan ibex (Capra ibex sibirica) and blue sheep (Pseudois nayaur) are economically important wild ungulates in northern Pakistan because they are sought-after hunting trophies. However, both species are threatened due to several human-induced factors, and these factors are expected to aggravate under changing climate in the High Himalayas. In this study, we investigated populations of ibex and blue sheep in the Pamir-Karakoram mountains in order to (i) update and validate their geographical distributions through empirical data; (ii) understand range shifts under climate change scenarios; and (iii) predict future habitats to aid long-term conservation planning. Presence records of target species were collected through camera trapping and sightings in the field. We constructed Maximum Entropy (MaxEnt) model on presence record and six key climatic variables to predict the current and future distributions of ibex and blue sheep. Two representative concentration pathways (4.5 and 8.5) and two-time projections (2050 and 2070) were used for future range predictions. Our results indicated that ca. 37% and 9% of the total study area (Gilgit-Baltistan) was suitable under current climatic conditions for Himalayan ibex and blue sheep, respectively. Annual mean precipitation was a key determinant of suitable habitat for both ungulate species. Under changing climate scenarios, both species will lose a significant part of their habitats, particularly in the Himalayan and Hindu Kush ranges. The Pamir-Karakoram ranges will serve as climate refugia for both species. This area shall remain focus of future conservation efforts to protect Pakistan’s mountain ungulates.

A GIS-Based Approach for the Quantitative Assessment of Soil Quality and Sustainable Agriculture

Assessing soil quality is considered one the most important indicators to ensure planned and sustainable use of agricultural lands according to their potential. The current study was carried out to develop a spatial model for the assessment of soil quality, based on four main quality indices, Fertility Index (FI), Physical Index (PI), Chemical Index (CI), and Geomorphologic Index (GI), as well as the Geographic Information System (GIS) and remote sensing data (RS). In addition to the GI, the Normalized Difference Vegetation Index (NDVI) parameter were added to assess soil quality in the study area (western part of Matrouh Governorate, Egypt) as accurately as possible. The study area suffers from a lack of awareness of agriculture practices, and it depends on seasonal rain for cultivation. Thus, it is very important to assess soil quality to deliver valuable data to decision makers and regional governments to find the best ways to improve soil quality and overcome the food security problem. We integrated a Digital Elevation Model (DEM) with Sentinel-2 satellite images to extract landform units of the study area. Forty-eight soil profiles were created to represent identified geomorphic units of the investigated area. We used the model builder function and a geostatistical approach based on ordinary kriging interpolation to map the soil quality index of the study area and categorize it into different classes. The soil quality (SQ) of the study area, classified into four classes (i.e., high quality (SQ2), moderate quality (SQ3), low quality (SQ4), and very low quality (SQ5)), occupied 0.90%, 21.87%, 22.22%, and 49.23% of the total study area, respectively. In addition, 5.74% of the study area was classified as uncultivated area as a reference. The developed soil quality model (DSQM) shows substantial agreement (0.67) with the weighted additive model, according to kappa coefficient statics, and significantly correlated with land capability R2 (0.71). Hence, the model provides a full overview of SQ in the study area and can easily be implemented in similar environments to identify soil quality challenges and fight the negative factors that influence SQ, in addition to achieving environmental sustainability.

Optimized Land Use through Integrated Land Suitability and GIS Approach in West El-Minia Governorate, Upper Egypt

Land evaluation is imperative for its efficient use in agriculture. Therefore, this study aimed at assessing the suitability of a region in West El-Minia for cultivating some of the major crops using the geographical information system (GIS). The results focus on allocating space for cultivating sugar beet and utilizing the free period of sugar beet in other crops. This exploitation helps to maintain the quality of the land and increase its fertility by using crop rotation with integrated agricultural management. A machine learning technique was implemented using the random forest algorithm (RF) to predict soil suitability classes for sugar beet using geomorphology, terrain attribute and remote sensing data. Fifteen major crops were evaluated using a suitability multicriteria approach in GIS environment for crop rotation decisions. Soil parameters were determined (soil depth, pH, texture, CaCO3, drainage, ECe, and slope) to characterize the land units for soil suitability. Soils of the area were found to be Entisols; Typic Torrifluvents, Typic Torripsamments and Typic Torriorthents and Aridsols; Typic Haplocacids, Calcic Haplosalids and Sodic Haplocalcids. Overall, the studied area was classified into four suitability classes: high “S1”, moderate “S2”, marginal “S3”, and not suitable “N”. The area of each suitability class changed depending on the crop tested. The highest two crops that occupied S1 class were barley with 471.5 ha (representing 6.8% of the total study area) and alfalfa with 157.4 ha (2.3%). In addition, barley, sugar beet, and sorghum occupied the highest areas in S2 class with 6415.3 ha (92.5%), 6111.3 ha (88.11%) and 6111.3 ha (88.1%), respectively. Regarding the S3 class, three different crops (sesame, green pepper, and maize) were the most highly represented by 6151.8 ha (88.7%), 6126.3 ha (88.3%), and 6116.7 ha (88.2%), respectively. In the end, potato and beans occupied the highest areas in N class with 6916.9 ha (99.7%) and 6853.5 ha (98.8%), respectively. The results revealed that the integration of GIS and soil suitability system consists of an appropriate approach for the evaluation of suitable crop rotations for optimized land use planning and to prevent soil degradation. The study recommends using crop rotation, as it contributes to soil sustainability and the control of plant pests and diseases, where the succession of agricultural crops on a scientific basis aims at maintaining the balance of nutrients and fertilizers in the soil.

Modelling Permafrost Distribution in Western Himalaya Using Remote Sensing and Field Observations

The presence and extent of permafrost in the Himalaya, which is a vital component of the cryosphere, remains severely under-researched with its future climatic-driven trajectory only partly understood and the future consequences on high-altitude ecosystem tentatively sketched out. Previous studies and available permafrost maps for the Himalaya relied primarily upon the modelled meteorological inputs to further model the likelihood of permafrost. Here, as a maiden attempt, we have quantified the distribution of permafrost at 30 m grid-resolution in the Western Himalaya using observations from multisource satellite datasets for estimating input parameters, namely temperature, potential incoming solar radiation (PISR), slope, aspect and land use, and cover. The results have been compared to previous studies and have been validated through field investigations and geomorphological proxies associated with permafrost presence. A large part of the study area is barren land (~69%) due to its extremely resistive climate condition with ~62% of the total area having a mean annual air temperature of (MAAT) <1 °C. There is a high inter-annual variability indicated by varying standard deviation (1–3 °C) associated with MAAT with low standard deviation in southern part of the study area indicating low variations in areas with high temperatures and vice-versa. The majority of the study area is northerly (~36%) and southerly (~38%) oriented, receiving PISR between 1 and 2.5 MW/m2. The analysis of permafrost distribution using biennial mean air temperature (BMAT) for 2002-04 to 2018-20 suggests that the ~25% of the total study area has continuous permafrost, ~35% has discontinuous permafrost, ~1.5% has sporadic permafrost, and ~39% has no permafrost presence. The temporal analysis of permafrost distribution indicates a significant decrease in the permafrost cover in general and discontinuous permafrost in particular, from 2002-04 to 2018–2020, with a loss of around 3% for the total area (~8340.48 km2). The present study will serve as an analogue for future permafrost studies to help understand the permafrost dynamics associated with the effects of the recent abrupt rise in temperature and change in precipitation pattern in the region.

Soil Quality Assessment Using Multivariate Approaches: A Case Study of the Dakhla Oasis Arid Lands

A precise evaluation of soil quality (SQ) is important for sustainable land use planning. This study was conducted to assess soil quality using multivariate approaches. An assessment of SQ was carried out in an area of Dakhla Oasis using two methods of indicator selection, i.e., total data set (TDS) and minimum data set (MDS), and three soil quality indices (SQIs), i.e., additive quality index (AQI), weighted quality index (WQI), and Nemoro quality index (NQI). Fifty-five soil profiles were dug and samples were collected and analyzed. A total of 16 soil physicochemical parameters were selected for their sensitivity in SQ appraising to represent the TDS. The principal component analysis (PCA) was employed to establish the MDS. Statistical analyses were performed to test the accuracy and validation of each model, as well as to understand the relationship between the used methods and indices. The results of principal component analysis (PCA) showed that soil depth, gravel content, sand fraction, and exchangeable sodium percentage (ESP) were included in the MDS. High positive correlations (r ≥ 0.9) occurred between SQIs calculated using TDS and/or MDS under the three models. Moreover, the findings showed highly significant differences (p < 0.001) among SQIs within and between TDS and MDS. Approximately 80 to 85% of the total study area based on TDS, as well as 70 to 75%, according to MDS, were identified as suitable soils with slight limitations on soil quality grade (Q3, Q2, and Q1), while the remaining 20 to 30% had high to severe limitations (Q4 and Q5). The highest sensitivity (SI = 2.9) occurred by applying WQI using MDS and indicator weights based on the variance of PCA. Furthermore, the highest linear regression value (R2 = 0.88) between TDS and MDS was recorded using the same model. Because of its high sensitivity, such a model could be used for monitoring SQ changes caused by agricultural practices and environmental factors. The findings of this study have significant guiding implications and practical value in assessing the soil quality using TDS and MDS in arid areas critically and accurately.

Delimitating the Ecological Spaces for Water Conservation Services in Jilin Province of China

Mastering the spatial distribution of water retention capacity and scientifically delineating the ecological space for water conservation are of great significance to the management of regional land and water resources. In this paper, a water conservation ecological spatial delimitation framework suitable for water-deficient areas was put forward. The water retention capacity of the study area in 1983, 1990, 2000, 2010, and 2016 was evaluated by using the InVEST Water Yield model and water balance method, respectively. On this basis, a flexible inflection point model based on the contribution degree of functional units was established. Then the ecological space for water conservation was delimited. The framework was applied to the delimitation of the key water conservation areas in Jilin province, China. The results showed that: (1) the spatial distribution pattern of water conservation in Jilin province gradually decreased from east to west. The spatial difference was significant. The maximum value of water conservation in Jilin province was 730 mm. From 1983 to 2016, water conservation, which accounted for 75.71% of the area, showed an upward trend. The overall water retention capacity showed the characteristics of the overall increase and the local decline. (2) From the absolute amount of the effect of unit area change on water conservation, the intensity from the high to the low was forestland, cultivated land, grassland, unused land, buildings, and water. (3) The area of water conservation less than 474 mm accounted for more than 80% of the total study area. The overall water retention capacity was low. High importance ecological space area of water conservation was comprehensively defined as 36.97%, which was mainly distributed in the natural forest area of Changbai Mountain in the east and the south of Song Liao Plain. Therefore, this study provided a basic layout of relatively concentrated ecological spatial distribution for water conservation types at different levels in Jilin province. The study results and conclusions of this paper will provide a reference for water conservation assessment and the regional land’s natural resources management.

GIS-based Multicriteria Decision Analysis for Settlement Areas: A Case Study in Canik

In addition to population growth throughout the world due to migration from rural to urban areas, population density is constantly increasing in certain regions, thereby necessitating the introduction of new settlements in these regions. However, in the selection of settlement areas, no sufficient preliminary examinations are conducted; consequently, various natural disasters may cause significant life and property losses. Herein, the most suitable settlement areas were determined using multicriteria decision analysis in Canik District, where the population is constantly increasing. Therefore, this study is aimed to incorporate a new perspective to the studies on this subject. Within the scope of the study, landslide and flood risks, which are among the most important natural disasters in the region, were primarily evaluated, and risky areas were determined. Thereafter, suitable and unsuitable areas in terms of biocomfort, which affect people’s health, peace, comfort, and psychology, and which are also significant in terms of energy efficiency, were determined. At the last stage of the study, the most suitable settlement areas that are suitable in terms of both biocomfort and low level of landslide and flood risks were determined; the calculated proportion of such areas to the total study area is only 2.1%. Therefore, because these areas are insufficient for the establishment of new settlements, areas with low landslide and flood risks but unsuitable for biocomfort were secondarily determined; the ratio of these areas was calculated as 56.8%. The remaining areas are inconvenient for the establishment of settlements owing to the risk of landslides and floods; the ratio of these areas was calculated as 41.1%. The study is exemplary in the respect that the priority for the selection of settlement areas is specified, which can be applied for selecting new settlements for each region considering different criteria.

IDENTIFIKASI FAKTOR-FAKTOR YANG MEMENGARUHI PERUBAHAN PEMANFAATAN LAHAN PERUMAHAN UNTUK TUJUAN KOMERSIAL DI KORIDOR JALAN DR. WAHIDIN SUDIROHUSODO KOTA PONTIANAK

ABSTRACTThe Corridor Street dr. Wahidin Sudirohusodo with an area of 0.425 km2 or 3% of the total area of Pontianak City District, Sungai Jawi Village. Street Dr. Corridor Wahidin Sudirohusodo in the RTRW of Pontianak City in 2013-2033 which is 95% of the allocation for residential areas. The purpose of this study was to determine the factors that influence changes in the use of residential land for commercial purposes in the corridor of Street dr. Wahidin Sudirohusodo. This study uses a quantitative approach with quantitative descriptive analysis techniques and descriptive statistical analysis techniques using cross tabulation and chi square. The results showed that the corridor of Street dr. Wahidin Sudirohusodo can conclude that from 2015 to 2021 the development of trade and services increased by 4.89 Ha or 28.5% of the total study area and settlements decreased by 3.07 Ha or 17.9% of the total study area. The results of crosstab and chi square analysis, the factors that influence changes in residential land use for commercial purposes, namely aspects of land ownership for education level, occupation, length of stay, and land ownership status have a relationship, for aspects of accessibility and completeness of public utilities the variable is fixed value. because the community feels satisfied and this is a very supportive factor for the community to open a business, and for the fiscal aspect of land there is a relationship. Keywords : Trade and services, land use change. ABSTRAKKoridor Jalan dr. Wahidin Sudirohusodo dengan luas 0,425 km2 atau 3% dari total wilayah Kecamatan Pontianak Kota, Kelurahan Sungai Jawi. Koridor Jalan Dr. Wahidin Sudirohusodo di dalam RTRW Kota Pontianak Tahun 2013-2033 yaitu 95% merupakan peruntukkan kawasan perumahan. Tujuan penelitian ini untuk mengetahui faktor-faktor yang memengaruhi perubahan pemanfaatan lahan perumahan untuk tujuan komersial di koridor Jalan dr. Wahidin Sudirohusodo. Penelitian ini menggunakan pendekatan kuantitatif dengan teknik analisis deskriptif kuantitatif dan teknik analisis statistik deskriptif menggunakan tabulasi silang dan chi square. Hasil penelitian menunjukkan koridor Jalan dr. Wahidin Sudirohusodo dapat disimpulkan bahwa dari tahun 2015 sampai ke tahun 2021 perkembangan perdagangan dan jasa naik sebesar 4,89 Ha atau 28,5% dari total wilayah kajian dan permukiman menyusut sebesar 3,07 Ha atau 17,9% dari total wilayah kajian. Hasil analisa crosstab dan chi square, faktor-faktor yang memengaruhi perubahan pemanfaatan lahan perumahan untuk tujuan komersial yaitu aspek kepemilikan lahan untuk tingkat pendidikan, pekerjaan, lama tinggal, dan status kepemilikan lahan memiliki keterkaitan hubungan, untuk aspek aksesibilitas dan kelengkapan utilitas umum variabel bernilai tetap dikarenakan masyarakat merasa sudah puas dan ini menjadi faktor yang sangat mendudukung masyarakat membuka usaha, dan untuk aspek fiskal lahan memiliki keterkaitan hubungan.Kata kunci : Perdagangan dan jasa, perubahan pemanfaatan lahan.

Landslide Inventory along a National Highway Corridor in the Hissar-Allay Mountains, Central Tajikistan

An increasing amount of landslides leading to significant human and economic consequences is a primary concern for the government of Tajikistan and local authorities. Based on the Committee on Emergency Situations data, from 1996 to 2018, there were 3460 emergencies and more than 1000 fatalities because of earthquake-triggered and rainfall-induced landslides in the region. In addition, landslides caused severe damage to houses and infrastructure facilities due to the population’s lack of landslide hazard knowledge. Therefore, current research focuses on developing a regional-scale landslide inventory map in the Hissar–Allay region, central Tajikistan, where the population density is much higher than at other mountainous territories. In recent decades, the enhancements in geographic information systems, the open access to high-resolution remote sensing data, and an extensive field survey allowed us to identify 922 landslides possible along the highway corridor in the Hissar–Allay region. Based on Varnes’s system, these landslides are classified into four categories: debris flows, rockfalls, shallow landslides, and complex (deep-seated) landslides, considering landslides morphology, geology, deformation of slopes, degree and aspect of slopes, and weathered and disintegrated zones on slopes in the study area. The results show that 8.24% of the total study area is affected by landslides. Along the highway corridor in the Hissar–Allay region there are 96 bodies of deep-seated landslides and 216 rockfall catchments, 273 debris flow catchments, and 313 shallow landslides. Thus, shallow landslides are the most frequent type of movement. In addition, landslide frequency-area distribution analysis shows that shallow landslides are frequent with an area of 1.88E+04 m2; most frequent debris flow channels have a place of 5.58E+05 m2; rockfalls, for its part, are rife with an area of 1.50E+05 m2, and frequent complex landslides have an area of 4.70E+06 m2. Furthermore, it was found out that slopes consist of Silurian formation comprise shales, pebbles, sands, loams, and limestones, metamorphic clays are exposed to landslides more than other geological formations because of the layered structure and their broad spatial distribution in the study area. As the first applied research to compile a landslide inventory map in the Hissar–Allay region on the regional scale, our study provides a sound basis for future explorations of landslide susceptibility, hazard, and risk assessment for this region.