This study is based on secondary data, and “ALOS PALSAR Digital Elevation Model (DEM)” data with 12.5m spatial resolution was downloaded from Earth Data maintained by the “U.S. National Aeronautics and Space Administration (NASA)” 12. To ensure the accuracy, the agricultural land of the Poonch district is digitized from Google Earth and exported as shape files, as shown in Figure 2.

For this study, eight different topographical elements such as “elevation, slope, aspect, curvature, relief amplitude, incision depth, surface roughness, and STD”13, 14 were selected to represent the topography. These terrain features can define the factors in macro and micro scale. In this study, elevation, slope, aspect, curvature, and surface roughness are executed at a micro-scale with an actual spatial resolution of 12.5 meters, while the standard deviation of elevation done at 125 meters’ resolution scale and other factors such as relief amplitude and incision depth are performed at macro-scale with a window of 1 km. The window concept used by Tu and Liu (1990) is also used in this study 15.

The topographical factors were computed with the ALOS PULSAR DEM data and Surface Tools from Spatial Analyst Tools in ArcGIS v10.7 were applied to determine the slope, aspect, and curvature. While Zonal Statistics Tools and the Raster Calculator from Spatial Analyst Tools were applied in this study to determine the “relief amplitude, incision depth, STD and Surface Roughness” respectively of the study area. With the use of DEM file incision depth was calculated with 1km grid, and STD with 125m grid. Similarly, the surface roughness was measured with the equation with raster calculator 17.

Where R indicates Surface Roughness, and FSmean, FSmin, and FSmax are mean, minimum, and maximum Focal Statistical layers, respectively, were made with the Neighbourhood Tool.

The existing agricultural lands provide information on the topographical preferences of the farmers. After extracting each topographical factor for agricultural land, this study determined the location entropy for each factor to analyse the suitable cultivable area. A small interval classified each topographical factor to attain accuracy in results. The graphs in Figure 4 display the statistical findings.

The bar graphs in Figure 4 depict the location disparities and the connection between the topographical factors and agricultural lands. Blue bars indicate the land area in each level, and red bars indicate agricultural land area in each level. Green lines show location entropy calculated statistically, and standard lines represent the value of location entropy at one of each topographical factor.

The statistical intervals for elevation, relief amplitude, incision depth, and STD were established at 500 meters, 100 meters, 70 meters, and seven meters, respectively; the statistical intervals for slope and curvature were established at 10 degrees and one degree, respectively; the aspect was reclassified using nine directions including flat; the statistical intervals for surface roughness were established at 0.2. If P > 1, agricultural lands are considerably clustered and considered as regular areas for cultivation; If P < 1, agricultural lands are less considerably clustered and considered as not suitable areas for cultivation; If P > 2, agricultural lands are more considerably clustered and considered as suitable areas for cultivation.

The tendencies of variation of location entropy values of topographical factors are comparable for elevation, slope, relief amplitude, incision depth, and STD. For aspect, this statistical result does not indicate a noticeable pattern. For curvature and surface roughness, the location entropy values are indicated in a slight stretch, and the entropy line is presented as concave and convex curves, respectively. Location entropy value decreases with increasing topographical factor value. Still, the variations in each topographical factor's range indicate their importance. The significance of the topographical factors increases with the variation in the location entropy. In this study, the relief amplitude is related to the highest entropy value; thus, it is the most crucial topographical factor 16.

The agricultural land has been classified into different elevation classes, and results illustrate that 70.5% of the agricultural lands are situated in the region under 1000 meters. The location entropy is greater than two in this region, indicating that regions below 1000 meters have favourable conditions for cultivation compared to regions above 1000 meters from sea level. Until the elevation exceeds 2000 meters, the location entropy remains greater than one.

From 2000 to 3500 meters, the area of agricultural lands is less, and the location entropy is low. Beyond 3500 meters, there are no agricultural lands present. Based on this study, the breaking points in elevation can be adjusted to 1500, 2000, and 3500 meters, and also confirms that elevation is a major topographical factor in finding the optimal site for agricultural lands. The low elevation is usually suitable for cultivation compared to highly elevated areas. The temperature decreases with an increase in height, making cultivation difficult at higher elevations. Also, the high elevation makes it challenging to construct built-ups, which is another drawback contributing to the lesser agricultural land area at higher altitudes 16.

The slope impact is confirmed based on the distributions of agricultural land as mentioned in Figure 4. It is found that 72.5% of the agricultural lands are in the region below 20 degrees. The entropy is greater than two in the region below a 10-degree slope, indicating that farmers favour flat terrain for cultivation compared to hilly terrains.

Until the slope exceeds 20 degrees, the location entropy remains greater than one. From 30 to 50 degrees, the area of agricultural lands is less, and the location entropy is very low. Beyond 50 degrees, there are no agricultural lands. The outcomes illustrate that inhabitants tend to cultivate in flat areas compared to highly inclined areas despite terrace cultivation being a significant agricultural practice in mountainous areas.

The agricultural land of the study area has been categorized in eight directions, as given in Figure 3, Figure 4, and entropy has been calculated for every direction and found that agricultural land is consistent in all directions. Most of the farming area around 65.4% is lies in Northeast, east, southeast, south, and southwest respectively.

The 84.6% of agricultural area is found at curvature between -1.5 and 1.5. which indicates that flat and less steep areas are more appropriate for the various types of crops. A slight tendency for agricultural land to cluster in low in low curvature areas can be seen in the location entropy line.

It is a crucial feature to objectively characterize the geomorphological shape and landform type. In this study, with the calculation of location entropy, it is revealed that entropy reaches its highest at 4.5 when the relief amplitude is below 100 meters. This is higher compared to other factors, and 70.8 % of agricultural areas are below 400 meters of relief amplitude. The more concentration of cultivable area in low amplitude is due to the source of irrigation, temperature, and fertile soil, respectively.

Around 80 % of agricultural land is situated below 210 meters of incision depth, while the remaining area is above 210 m. Among all the categories, the higher concentration of farming land at the incision depth is below 70 meters, which indicates that a lesser incision depth is more favorable. The increase in the incision depth minimizes the location entropy.

In this study, it has been found that 84.3% of agricultural land falls in a range of 0.4 to 0.6 of surface roughness, and the entropy value is less in this region. Agricultural land with surface roughness values below 0.4 and above 0.6 exhibits significant agglomeration.

The STD has a range of 0 to 75 meters. Most agricultural lands (37.1%) are situated between 7 and 14 meters. However, statistical entropy values show that below 7 meters have robust clustering with location entropy greater than two. The location entropy value is greater than one between 7 and 14 meters and less than one above 14 meters for the STD. The STD shows that farmers usually prefer less inclined areas for cultivating various crops.

The eight topographical factors thoroughly supplied the terrain elements on micro and macro scales and denoted the agricultural land suitability at various levels. The location entropy executed well in investigating the agglomeration of the agricultural lands. This study classified the agricultural lands into three degrees of suitability: most suitable (P≥2), standard suitable (P≥1), and not suitable (P<1), as indicated by the location entropy (P) estimate that was earlier performed.