Identification of suitable sites for groundwater recharge in Awaspi watershed using GIS and remote sensing techniques

Groundwater is a valuable natural resource for drinking, domestic, livestock use, and irrigation, especially in arid and semi-arid regions like the Garmiyan belt in Kurdistan region. The Awaspi watershed is located 50 km east of Kirkuk city, south Kurdistan, Iraq; and covers an area of 2146 km². The paper presents result of a study aimed at: (1) mapping and preparing thematic layers of factors that control groundwater recharge areas, and (2) determination of sites suitable for groundwater recharge. We used available data such as geological map, groundwater depth map, digital elevation model (DEM), Landsat 8 imagery, and tropical rainfall measuring mission (TRMM) data for this study. These data, supplemented by slope features, lithology, land use land cover, rainfall, groundwater depth, drainage density, landform, lineament density, elevation and topographic position index, were utilized to create thematic maps to identify suitable areas of groundwater recharge, using GIS and remote sensing techniques. Analytic hierarchy process (AHP) was applied to weight, rank, and reclassify these maps in the ArcGIS 10.3 environment, to determine the suitable sites for groundwater recharge within the Awaspi watershed. Fifty-five percent of the total area of the watershed was found to be suitable for groundwater recharge; whereas 45% of the area was determined to have poor suitability for groundwater recharge, but can be used for surface water harvesting.     

GIS-based weights-of-evidence modelling of rainfall-induced landslides in small catchments for landslide susceptibility mapping

Landslide susceptibility mapping is a vital tool for disaster management and planning development activities in mountainous terrains of tropical and subtropical environments. In this paper, the weights-of-evidence modelling was applied, within a geographical information system (GIS), to derive landslide susceptibility map of two small catchments of Shikoku, Japan. The objective of this paper is to evaluate the importance of weights-of-evidence modelling in the generation of landslide susceptibility maps in relatively small catchments having an area less than 4 sq km. For the study area in Moriyuki and Monnyu catchments, northeast Shikoku Island in west Japan, a data set was generated at scale 1:5,000. Relevant thematic maps representing various factors (e.g. slope, aspect, relief, flow accumulation, soil depth, soil type, land use and distance to road) that are related to landslide activity were generated using field data and GIS techniques. Both catchments have homogeneous geology and only consist of Cretaceous granitic rock. Thus, bedrock geology was not considered in data layering during GIS analysis. Success rates were also estimated to evaluate the accuracy of landslide susceptibility maps and the weights-of-evidence modelling was found useful in landslide susceptibility mapping of small catchments.     

Land transformation assessment using the integration of remote sensing and GIS techniques: a case study of Al-Anbar Province,Iraq

Human activities and climate changes significantly affect our environment, altering hydrologic cycles. Several environmental, social, political, and economical factors contribute to land transformation as well as environmental changes. This study first identified the most critical factors that affect the environment in Al-Anbar city including population growth, urbanization expansion, bare land expansion, and reduction in vegetation cover. The combination of remote sensing data and fuzzy analytic hierarch process (Fuzzy AHP) enabled exploration of land transformations and environmental changes in the study area during 2001 to 2013 in terms of long and short-term changes. Results of land transformation showed that the major changes in water bodies increased radically (94 %) from the long-term change in 2001 to 2013 because of water policies. In addition, the urban class expanded in two short-term periods (2001–2007 and 2007–2013), representing net changes of 46 and 60 %, respectively. Finally, barren land showed 25 % reduction in the first period because of the huge expansion of water in the lake; a small percentage of growth gain was observed in the second period. Based on the land transformation results, the environmental degradation assessment showed that the study area generally had high level of environmental degradation. The degradation was mostly in the center and the north part of the study area. This study suggested for further studies to include other factors that also responsible for environmental degradation such as water quality and desertification threatening.     

Groundwater vulnerability assessment in the Melaka State of Malaysia using DRASTIC and GIS techniques

The present work attempts to interpret the groundwater vulnerability of the Melaka State in peninsular Malaysia. The state of groundwater pollution in Melaka is a critical issue particularly in respect of the increasing population, and tourism industry as well as the agricultural, industrial and commercial development. Focusing on this issue, the study illustrates the groundwater vulnerability map for the Melaka State using the DRASTIC model together with remote sensing and geographic information system (GIS). The data which correspond to the seven parameters of the model were collected and converted into thematic maps by GIS. Seven thematic maps defining the depth to water level, net recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity were generated to develop the DRASTIC map. In addition, this map was integrated with a land use map for generating the risk map to assess the effect of land use activities on the groundwater vulnerability. Three types of vulnerability zones were assigned for both DRASTIC map and risk map, namely, high, moderate and low. The DRASTIC map illustrates that an area of 11.02 % is low vulnerability, 61.53 % moderate vulnerability and 23.45 % high vulnerability, whereas the risk map indicates that 14.40 % of the area is low vulnerability, 47.34 % moderate vulnerability and 38.26 % high vulnerability in the study area. The most vulnerability area exists around Melaka, Jasin and Alor Gajah cities of the Melaka State.     

Eco-environmental change detection by using remote sensing and GIS techniques: a case study Basrah province, south part of Iraq

This study examines the temporal and spatial dynamics of eco-environment degradation processes and change detection as evident from land use survey datasets (1990–2003) for the Basrah province, Iraq was taken as a case. Using a combination of techniques of RS, GIS, and GPS, the study identifies five prominent eco-environment degradation processes, namely: desertification, secondary salinization, urbanization, vegetation degradation, and loss of wetlands. Rates of conversion were calculated and distribution patterns were mapped with the aid of GIS. The results suggest that wind erosion was the dominant cause of eco-environment degradation in more than half of the study area. Coupled with this were increases in salinization processes, affecting 17.6% of the land area in 2003. Overall, severe eco-environment degradation was noticed to be the dominant eco-environment degradation grade (61.9% of total area), followed by moderate eco-environment degradation (18.9% of total area) in 2003. Incorporation of both natural and anthropogenic factors in the analysis provided realistic assessment of the risk of land degradation. The study area, in general, is exposed to a high-risk of eco-environment degradation.     

Application of remote sensing and GIS for delineating groundwater recharge potential zones of Kovilpatti Municipality,Tamil Nadu using IF technique

During the last three decades, remotely sensed data (both satellite images and aerial photographs) have been increasingly used in groundwater exploration and management exercises. An integrated approach has been adopted in the present study to delineate groundwater recharge potential zones using RS and GIS techniques. IRS-1C satellite imageries and Survey of India toposheets are used to prepare various thematic layers viz. geology, soil, land-use, slope, lineament and drainage. These layers were then transformed in to raster data using feature to raster converter tool in ArcGIS 9.3 software. The raster maps of these factors are allocated a fixed score and weight computed from Influencing Factor (IF) technique. The weights of factors contributing to the groundwater recharge are derived using aerial photos, geology maps, a land use database, and field verification. Subjective weights are assigned to the respective thematic layers and overlaid in GIS platform for the identification of potential groundwater recharge zones within the study area. Then these potential zones were categories as ‘high’, ‘moderate’, ‘low’, ‘poor’. The resulted map shows that 19 % of the area has highest recharge potential, mainly confined to buried pediplain, agriculture land-use and river terraces (considerable amount of precipitated water percolates into subsurface), 28 % of the area has moderate groundwater recharge potentiality and rest of the area has low to poor recharge potentiality. The residual hills and linear ridges with steep slopes are not suitable for artificial recharge sites. Finally, 13 % of total average annual precipitated water (840 mm) percolates downward and ultimately contributes to recharge the aquifers in the Kovilpatti Municipality area. The paper is an attempt to suggest for maintaining the proper balance between the groundwater quantity and its exploitation.     

Spatial assessment of desertification in north Sinai using modified MEDLAUS model

This study aims to use spatial analyses and a geographic information system (GIS) to assess the environmental sensitivity for desertification in the north Sinai Peninsula, Egypt. Based on the Mediterranean Desertification and Land Use (MEDALUS) approach and the characteristics of the study area, a regional model was developed using GIS. Five main indicators of desertification including soil, climate, erosion, plant cover, and management were considered for estimating the environmental sensitivity to desertification. A spatial analyst extension Arc-GIS 10 software was used for matching the thematic layers and assessing the desertification index, of which the map of environmentally sensitive areas of the north Sinai Peninsula is produced. The obtained data reveals that 65 % of north Sinai is characterized by very severe sensitivity to desertification while the low sensitive one exhibits only 1.2 %. The moderately sensitive area occupies approximately 23 % of the study area. ETM+ and SPOT images are recommended to monitor sensitivity. The MEDALUS model was developed under the Egyptians to assess desertification sensitivity.     

Landslide susceptibility mapping based on GIS and information value model for the Chencang District of Baoji,China

The main objective of this study was to apply a statistical (information value) model using geographic information system (GIS) to the Chencang District of Baoji, China. Landslide locations within the study area were identified using reports and aerial photographs, and a field survey. A total of 120 landslides were mapped, of which 84 (70 %) were randomly selected for building the landslide susceptibility model. The remaining 36 (30 %) were used for model validation. We considered a total of 10 potential factors that predispose an area to a landslide for the landslide susceptibility mapping. These included slope degree, altitude, slope aspect, plan curvature, geomorphology, distance from faults, lithology, land use, mean annual rainfall, and peak ground acceleration. Following an analysis of these factors, a landslide susceptibility map was produced using the information value model with GIS. The resulting landslide susceptibility index was divided into five classes (very high, high, moderate, low, and very low) using the natural breaks method. The corresponding distribution area percentages were 29.22, 25.14, 15.66, 15.60, and 14.38 %, respectively. Finally, landslide locations were used to validate the results of the landslide susceptibility map using areas under the curve (AUC). The AUC plot showed that the susceptibility map had a success rate of 81.79 % and a prediction accuracy of 82.95 %. Based on the results of the AUC evaluation, the landslide susceptibility map produced using the information value model exhibited good performance.     

Land degradation risk assessment in Al-Sawda terraces,Kingdom of Saudi Arabia

Monitoring of soil properties is a significant process and plays an important role about how it can be used sustainably. This study was performed in a local area in Sawda Mountains KSA to map out some soil properties and assess their variability within the area under different land cover. Soil sampling was carried out in four different sites using the grid sampling technique. Ten samples were collected in each location within a 10 by 10 km area; soil was sampled at 0–30-cm depth. The soil samples were air-dried, crushed, and passed through a 2-mm sieve before analyzing it for pH, EC, CaCO₃, organic matter contents, and bulk density. The thematic maps of these characteristics were produced using ArcGIS 10.0 software. Finally, the land degradation was assessed using three factors: soil salinization, compaction, and edibility. The obtained results showed that the high risk of soil compaction, salinization, and erodibility occupied an area 5.6 ha (17.5%), 3.7 ha (11.54%), and 8.1 ha (25.3%), respectively, in the surface soil layer. The land degradation risk in the study area due to salinization was low to high; however, the degree of soil compaction was moderate to very high. The K-factor (soil erodibility) in the area ranged between 0.1 and 0.35 Mg h MJ^?1 mm^?1, and most of the study area was located in moderate to high erodibility classes.     

Using Remote Sensing and GIS Techniques to Study Soil Degradation Processes in North Shaanxi Province, China

Satellite image data and thematic map data were used to provide comprehensive views of surface-bound conditions such as soil and vegetation degradation. The current work applies a computerized parametric methodology, developed by FAO, UNEP and UNESCO to assess and evaluate soil degradation at 1 : 250 000 mapping scale. The study area is located in the arid and semi-arid zone of the northern part of Shaanxi Province in China, a region with considerable agricultural potential; Landsat TM images were utilized to provide recent data on land cover and use of the area. ARC/INFO and Arc-View softwares were used to manage and manipulate thematic data, to process satellite images, and tabular data source. ER mapper software is utilized to derive the normalized difference vegetation index (ND VI) values while field data to estimate soil erodibility (SE) factor. A system is established for rating soil parameters, slope, climate factor and human factor activity. The rating values serve as inputs into a modified universal soil loss equation (USLE) to calculate the present state and risk for soil degradation processes, namely soil wind erosion. The produced maps and tabular data show the risk and the present status of different soil degradation processes. The study area, in general, is exposed to high risk of wind erosion and high hazards of water erosion. Several desertification maps were produced, which reflect the desertification types persisting in the study area. Wind erosion, water erosion, vegetation degradation,physical degradation and salinization are the basic desertification maps, and others are combinations of these basic maps. In terms of statistic analysis, 33.75 % of the total land area (120. 330 0 ha) is considered as sand or sand dune, and not included in our analysis of desertification. About 29. 41% of the total land area has slight or moderate desertification and 37. 465 % is facing severe desertification.     

Use of geoprocessing in the study of land degradation in urban environments: the case of the city of São Carlos,state of São Paulo,Brazil

This paper presents a methodology for the geological engineering survey of land degradation in urban environments using both remote sensing and geoprocessing tools. The area under study was the city of São Carlos, state of São Paulo, Brazil (urban and expansion area). The data presented here were obtained from earlier studies, photointerpretation and geological engineering mapping. The Envi 4.1 software package was used to prepare the digital orthophotos that served as a reference base for the information. Orthorectification of the Ikonos image (PSM, 1 m) was done and compared with other orthophotos from studies of environmental degradation in urban areas. The evolution of land degradation processes was analyzed based on the photointerpretation of aerial photographs taken on different dates and using Ikonos image. This study allowed to conclude that most of the degradation occurring in the city has been caused by unplanned land occupation, in disregard of environmental conditions, resulting in environmental degradation and thus impacting the quality of life of the urban population.     

Mapping groundwater recharge potential using GIS approach in Darwha block

Groundwater is the most important source of water in meeting irrigation, drinking, and other needs in India. The assessment of the potential zone for its recharge is critical for sustainable usage, quality management, and food security. This study reports alternative mapping of the groundwater recharge potential of a selected block by including large-scale soil data. Thematic layers of soil, geomorphology, slope, land use land cover, topographical wetness index, and drainage density of Darwha block (District Yavatmal, Maharashtra, India) were generated and integrated in a geographic information system environment. The topographic maps, thematic maps, field data, and satellite image were processed, classified, and weighted using analytical hierarchical process for their contribution to groundwater recharge. The layers were integrated by weighted linear combination method in the GIS environment to generate four groundwater potential zones viz., “poor,” “poor to moderate,” “moderate to high,” and “high.” Based on the generated groundwater potential map, about 9830 ha (12%) of the study area was categorized as high potential for recharge, 25,558 ha (31%) as poor to moderate, 33,398 ha (40%) as moderate to high, and 12,565 ha (15%) as poor potential zone. The zonation corresponds well with the field data on greater well density (0.22/ha) and irrigated crop area (27%) in the high potential zone as against 0.02 wells/ha and only 6% irrigated area in the poor zone. The map is recommended for use in regulating groundwater development decisions and judicious expenditure on drilling new wells by farmers and the state authorities.     

Evaluation of sediment yield and soil loss by the MPSIAC model using GIS at Golestan watershed, northeast of Iran

Watershed degradation due to soil erosion and sedimentation is considered to be one of the major environmental problems in Iran. In order to address the critical conditions of watershed degradation in arid and semiarid regions, a study based on the Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model was carried out at Golestan watershed, northeast of Iran. The model information layers comprising nine effective factors in erosion and sedimentation at the watershed site were obtained by digitalization and spatial interpolation of the basic information data in a GIS program. These factors are geology, soil, climate, runoff, topography, land cover, land use, channel, and upland erosion. The source data for the model were obtained from available records on rainfall and river discharge and sediment, topography, land use, geology, and soil maps as well as field surveys and laboratory analysis. The results of the MPSIAC model indicated that 60.75 % (194.4 km²) and 54.97 % (175.9 km²) of the total watershed area were classified in the heavy sedimentation and erosion classes, and the total basin sediment yield and erosion were calculated as 4,171.1 and 17,813.4 m³ km^?2 year^?1, respectively. In the sensitivity analysis, it was found that the most sensitive parameters of the model in order of importance were topography (slope), land cover and use, runoff, and channel erosion (R ²?=?0.92–0.94), while geology, climate (rainfall), soil, and upland erosion factors were found to have moderate effect to the model output (R ²?=?0.74–0.59).     

Determining groundwater protection zones for the Quaternary aquifer of northeastern Nile Delta using GIS-based vulnerability mapping

The area of study lies at the northeastern part of Nile Delta. Global shoreline regression and sea-level rise have their own-bearing on the groundwater salinization due to seawater intrusion. A new adopted approach for vulnerability mapping using the hydrochemical investigations, geographic information system and a weighted multi-criteria decision support system (WMCDSS) was developed to determine the trend of groundwater contamination by seawater intrusion. Six thematic layers were digitally integrated and assigned different weights and rates. These have been created to comprise the most decisive criteria used for the delineation of groundwater degradation due to seawater intrusion. These criteria are represented by the total dissolved solids, well discharge, sodium adsorption ratio, hydrochemical parameter (Cl/HCO₃), hydraulic conductivity and water types. The WMCDSS modeling was tried, where a groundwater vulnerability map with four classes ranging from very low to high vulnerability was gained. The map pinpointed the promising localities for groundwater protection, which are almost represented by the very low or low vulnerability areas (53.69 % of the total study area). The regions having high and moderate groundwater vulnerability occupy 46.31 % of total study area, which designate to a deteriorated territory of groundwater quality, and needs special treatment and cropping pattern before use. However, the moderate groundwater vulnerability class occupies an area of about 28.77 % of the total mapped area, which highlighted the need for certain management practices to prevent the saltwater intrusion from expanding further to the south. There was a good correlation of the constructed vulnerability map with the recently gathered water quality data and hydrochemical facies evolution. The plotting of water quality data on Piper trilinear diagram revealed the evolution of freshwater into the mixing and the saline zones as an impact of seawater intrusion, which validates the model results.     

GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran,Iran)

The aim of this study is to produce landslide susceptibility mapping by probabilistic likelihood ratio (PLR) and spatial multi-criteria evaluation (SMCE) models based on geographic information system (GIS) in the north of Tehran metropolitan, Iran. The landslide locations in the study area were identified by interpretation of aerial photographs, satellite images, and field surveys. In order to generate the necessary factors for the SMCE approach, remote sensing and GIS integrated techniques were applied in the study area. Conditioning factors such as slope degree, slope aspect, altitude, plan curvature, profile curvature, surface area ratio, topographic position index, topographic wetness index, stream power index, slope length, lithology, land use, normalized difference vegetation index, distance from faults, distance from rivers, distance from roads, and drainage density are used for landslide susceptibility mapping. Of 528 landslide locations, 70 % were used in landslide susceptibility mapping, and the remaining 30 % were used for validation of the maps. Using the above conditioning factors, landslide susceptibility was calculated using SMCE and PLR models, and the results were plotted in ILWIS-GIS. Finally, the two landslide susceptibility maps were validated using receiver operating characteristic curves and seed cell area index methods. The validation results showed that area under the curve for SMCE and PLR models is 76.16 and 80.98 %, respectively. The results obtained in this study also showed that the probabilistic likelihood ratio model performed slightly better than the spatial multi-criteria evaluation. These landslide susceptibility maps can be used for preliminary land use planning and hazard mitigation purpose.     

Estimation of soil erosion using RUSLE in Caijiamiao watershed,China

Soil erosion is a serious environmental and production problem in China. In particular, natural conditions and human impact have made the Chinese Loess Plateau particularly prone to intense soil erosion area. To decrease the risk on environmental impacts, there is an increasing demand for sound, and readily applicable techniques for soil conservation planning in this area. This work aims at the assessment of soil erosion and its spatial distribution in hilly Loess Plateau watershed (northwestern China) with a surface area of approximately 416.31 km². This study was conducted at the Caijiamiao watershed to determine the erosion hazard in the area and target locations for appropriate initiation of conservation measures using the revised universal soil loss equation (RUSLE). The erosion factors of RUSLE were collected and processed through a geographic information system (GIS)-based approach. The soil erosion parameters were evaluated in different ways: The R-factor map was developed from the rainfall data, the K-factor map was obtained from the soil map, the C-factor map was generated based on Landsat-5 Thematic Mapper image and spectral mixture analysis, and a digital elevation model with a spatial resolution of 25 m was derived from topographic map at the scale of 1:50,000 to develop the LS-factor map. Support practice P factor was from terraces that exist on slopes where crops are grown. By integrating the six-factor maps in GIS through pixel-based computing, the spatial distribution of soil loss in the study area was obtained by the RUSLE model. The results showed that spatial average soil erosion at the watershed was 78.78 ton ha^?1 year^?1 in 2002 and 70.58 ton ha^?1 year^?1 in 2010, while the estimated sediment yield was found to be 327.96 × 10⁴ and 293.85 × 10⁴ ton, respectively. Soil erosion is serious, respectively, from 15 to 35 of slope degree, elevation area from 1,126 to 1,395 m, in the particular area of soil and water loss prevention. As far as land use is concerned, soil losses are highest in barren land and those in waste grassland areas are second. The results of the study provide useful information for decision maker and planners to take appropriate land management measures in the area. It thus indicates the RUSLE–GIS model is a useful tool for evaluating and mapping soil erosion quantitatively and spatially at a river watershed scale on a cell basis in Chinese Loess Plateau and for planning of conservation practices.     

Integrated GIS and remote sensing for mapping groundwater potentiality in the Tulul al Ashaqif,Northeast Jordan

Jordan with its limited water resources is currently classified as one of the four water-poor countries worldwide. This study was initiated to explore groundwater potential areas in Tulul al Ashaqif area, Jordan, by integrating remote sensing, geographic information systems (GIS), and multicriteria evaluation techniques. Eight thematic layers were built in a GIS and assigned using multicriteria evaluation techniques suitable weights and ratings regarding their relative contribution in groundwater occurrence. These layers include lithology, geomorphology, lineaments density, drainage density, soil texture, rainfall, elevation, and slope. The final groundwater potentiality map generated by GIS consists of five groundwater potentiality classes: very high, high, moderate, low, and very low. The map showed that the study area is generally of moderate groundwater potentiality (76.35 %). The very high and high potential classes occupy 2.2 and 12.75 % of study area, respectively. The validity of results of this GIS-based model was carried out by superimposing existing hand dug wells on the final map. The single parameter sensitivity test was conducted to assess the influence of the assigned weights on the groundwater potential model, and new effective weights were derived. The resulted groundwater potentiality map showed that the area occupied by each of the groundwater potentiality classes has changed. However, the study area remains generally of moderate groundwater potentiality (70.93 % of the study area). The area occupied by the very high and high potential classes comprises 4.53 and 18.56 % of the study area, respectively.     

Environmental change detection in the central part of Iraq using remote sensing data and GIS

This study aims to assess the potential of several ancillary input data for the improvement of unsupervised land cover change detection in arid environments. The study area is located in Central Iraq where desertification has been observed. We develop a new scheme based on known robust indices. We employ Landsat (multispectral scanner, thematic mapper, and enhanced thematic mapper) satellite data acquired in 1976, 1990, and 2002. We use the Normalized Deferential Vegetation Index, Normalized Differential Water Index (NDWI), Salinity Index (SI), and Eolian Mapping Index. Two new equations were applied for the SI and the NDWI indices. Validation was performed using ground truth data collected in 16 days. We show that such an approach allows a robust and low-cost alternative for preliminary and large-scale assessments. This study shows that desertification has increased in the study area since 1990.     

Assessment of land degradation east of the Nile Delta, Egypt using remote sensing and GIS techniques

Land degradation is one of the most common issues in the eastern part of the Nile Delta area that threatens the ongoing agricultural activities and prohibits further reclamation expansions. The different degradation types and the associated risk assessment of some soils types of western Suez Canal region during the period from 1997 to 2010 is discussed. The assessment of the different degradation degrees in the investigated area has been carried out through integrating remote sensing, GIS and GLASOD approaches. Results revealed that the salinization, alkalization, soil compaction and water logging are the main types of land degradation in the area. The main causative factors of human induced land degradation types are; over irrigation, human intervention in natural drainage, improper time use of heavy machinery and the absence of conservation measurements. Low and moderately clay flats, gypsifferous flats, have high to very high risk in both salinization sodication and physical degradation. Values such as EC, ESP, and ground water level reach 104.0 dS/m, 176? % and 60 cm, respectively. These results will be of great help and be basic sources for the planners and decision makers in sustainable planning. The spatial land degradation model was developed based on integration between remote sensing data, geographic information system, soil characteristics and DEM.     

Integrative approach of RS and GIS in characterization of land suitability for agriculture: a case study of Darna catchment

Land elements like slope, soil depth, land use/land cover, water holding capacity, soil texture, soil erosion, elevation, potential of hydrogen, etc. determine the suitability for agriculture. Land suitability analysis is a one of the methods of assessment of detecting inherent capacities, potential and suitability levels of the lands for agriculture, and was utilized with the same land elements in this study. A multi-criterion decision making approach using IRS P6 LISS-IV satellite dataset within a GIS environment was used to identify suitable areas for agriculture in the Darna catchment. Experts’ opinions, literature review, and correlation technique were used to decide influencing criteria, assign scores to sub-criteria, and judgment formation in pairwise comparison matrix. All thematic layers of criteria were integrated with each other in GIS using the weighted overlay technique and generated agriculture suitability map into four classes according to FAO. About 23% of the area is under agriculture in the study region. This area can extend up to 69% under agriculture converting fallow land, scrub land, and sparse forest according to soil qualities with suitability levels, i.e., highly suitable (19%), moderately suitable (16%), and marginally suitable (34%). About 31% (19,219 ha) of reviewed area are classified in the class permanently “not suitable” for agriculture. Moderately and marginally suitable land requires the irrigation facility for efficient agriculture. This study emphasizes that about 46% area has potential as agriculture land and it will help improve the financial condition of the farmers.