Identifying Villages for Land Consolidation: A New Agricultural Wasteland Concentration Indicator

Abstract

Land consolidation is a process of improving the spatial structure of rural areas, including agricultural wastelands. During work related to this geodesic operation, selected areas can be specified, and the most efficient ways of developing the analysed land can be proposed. Thanks to such rural management work, rural areas can become competitive and start deriving financial benefits from crop cultivation. At the same time, the living standard of their inhabitants is enhanced. The study covered 18 out of 44 villages situated within the administrative limits of the district of Brzozów in the Subcarpathian Voivodeship of south-eastern Poland. An agricultural wasteland concentration indicator was designed for this area based on six factors (soil quality class, agricultural soil complex, slope angle, risk of erosion, water regime, and slope aspect). Each factor was calculated as the total quotient of the weighted feature in relation to the total surface area of the study site. The last stage was a detailed analysis of the area featuring the highest value of the agricultural wasteland indicator—the village of Obarzym. The indicator described in this paper, designed to measure the concentration of agricultural wastelands, can be useful in programming and documenting assumptions for land consolidation to reveal the highest concentration of wasteland. The factors included in this publication refer to soil conditions, terrain relief, and the water regime. Their respective characteristics were designed via multiple calculations using geoprocessing algorithms in GIS software. Various geospatial data provided by district, regional, and national public institutions were used for the calculations. An advantage of the solution is that it can be used in various regions, irrespective of the location of the object to be consolidated.

1. Introduction

The main objective of the Common Agricultural Policy of the European Union (EU) is to improve rural areas’ quality of life and efficiently utilise their resources. Socioeconomic disparities in EU member states have been maintained despite numerous measures being undertaken under this EU policy. However, as noted by many authors, the projects do not bring the expected results in full [1,2,3]. This state of affairs is corroborated by the report of the European Commission on Economic and Social Cohesion [4]. The decision to admit ten new member states, including Poland, made by the EU in October 2002, followed by the close of accession negotiations with candidate states, created completely new conditions for the regional policy of the EU [5,6]. Due to the extension of the EU, states and regions poorer than those already in the community were accepted.

Therefore, an important objective of the policy implemented in Poland under the Rural Development Programme (now RDP 2014–2020, extended to 2025) is to ensure equal chances for developing and preserving the agricultural nature of areas with unfavourable natural and landscape conditions. Most of these areas are exposed to adverse environmental degradation and have become depopulated. It should be noted that each area is unique, so it is essential that the solutions are individually adapted to the natural, landscape, and social conditions, with a special focus on rural areas characterised by the presence of the least productive soils due to adverse terrain conditions. The development of rural areas mostly refers to demographic, economic, natural, and landscape aspects. In addition, many factors such as terrain relief, soil type, atmospheric precipitation, water, temperature, and wind are also significant for agriculture.

However, the occurrence of problem areas or agricultural wastelands (a type of land devoid of utility value due to natural conditions or because of human influence). In Poland is not a precedent. Long-term member states of the European Union also faced similar issues upon integration. For instance, France, Austria, and Italy have mountain soils that are many times less fertile than soils found in the rest of the EU. In contrast, Sweden and Finland struggle with soils in their northern regions—the so-called short-day and low-temperature agricultural production space. Furthermore, for decades, many developed countries, such as Japan, have experienced problems with the agricultural wastelands that were later abandoned. The key problem for government decisionmakers and scientists is how abandoned land should be delimited [7,8,9,10,11,12,13]. In addition, agricultural wastelands include, among other things, swamps, mud, marshes, dunes, sand, rocks, rubble, screes, slopes, sinkholes, faults, and land under water unsuitable for fish production (ponds, waterholes). They can also be considered forms of nature conservation.

The whole problem is made even worse due to the fact that agricultural land in these areas is very fragmented. In Poland, this is largely due to historical circumstances [14], resulting in the excessive fragmentation of land [15,16,17,18] and the poor quality of cadastral data [19,20,21]. The fragmentation of land affects many countries in the south of Europe, e.g., Bulgaria [22], Spain [23,24], Turkey [25,26,27], Cyprus [28], and Croatia [29], and in the west of Europe, including the Netherlands [30], but also countries of Central and Eastern Europe: the Czech Republic [31], Slovakia [32,33,34,35], and Poland [36,37]. The problem is also present in many countries on other continents: Mexico [38], India [39], China [40], and Iran [41].

The main factors contributing to the emergence of problem areas include intensive exploitation and the unreasonable utilisation of natural resources, which increase erosive degradation, soil acidity, and the depletion of organic matter in the soil. Other hazards to the environment and agriculture are the concentration of onerous industrial production, the location of landfill sites, and the emission of dust contributing to local pollution of agricultural soils [42].

Therefore, we believe attention should be paid to areas with limited production potential, lower income per capita, and delayed economic development. For this reason, it is reasonable to promote the alternative economic functions of rural problem areas, especially in the context of the possibility of conducting land consolidation works to improve the spatial structure of farms, that is, creating improved conditions for management in agriculture and forestry.

At present, in Poland, article 3, paragraph 2 of the Act on Land Consolidation and Exchange stipulates that a consolidation procedure can be initiated at the request of the majority of owners of farms situated within the designed consolidation area or at the request of the owners of land with a total area exceeding half of the designed consolidation area [43]. The work is carried out in various areas with a good soil class and varied terrain relief featuring soils of low productivity. The first attempts at setting a land consolidation hierarchy for areas with the most defective spatial structures were undertaken in south-eastern [44], southern [45], and central Poland [44]. Similar surveys were conducted in the south of Europe, for instance, in Croatia [31]. In Poland, this is a statutory responsibility of voivodeship marshals (article 7c paragraph 5 of the Geodetic and Cartographic Law), whose primary task, next to preparing analyses of transformations in agrarian structure, is to programme and coordinate rural management work [46].

Previous detailed surveys concerning marginal land and agricultural problem areas [47,48] allowed for the identification of solutions for their alternative management during land consolidation work [49]. Such solutions include allocating land for forest planting, building development, transportation infrastructure, agritourism, leisure, transformation into ecological areas, growing energy crops, gardening, and setting up wildlife food plots [47,48,49].

It should be noted that these projects are carried out according to the degree of interest of the inhabitants, and these areas differ in terms of soil quality, terrain relief, climatic conditions, water regimes, and other factors. The need to conduct reliable studies and calculate the agricultural wasteland concentration indicator should be highlighted.

The aforementioned indicator is made up of six factors used for delimiting agricultural wastelands: soil quality class, agricultural soil complex, slope angle, risk of erosion, water regime, and slope aspect, to which characteristic features and weights expressed as scores were assigned. The information used to select the factors and assign their weights is derived from reliable sources—reference literature, scientific studies, and own analyses, as well as numerous meetings with farmers, officials, scientists, and experts dealing with the various aspects of these issues. In addition, the studies involved real and credible data gathered from many institutions at various state levels, as described in Section 2.

The features of these respective factors were thoughtfully selected based on: legislation—soil quality classes; guidelines provided by the Institute of Soil Science and Plant Cultivation (IUNG) in Puławy—the agricultural production space valorisation index (WWRPP) and agricultural soil complexes; the data resources of the Head Office of Geodesy and Cartography in Warsaw—the Digital Terrain Model (DTM) and slope angle; data from the Institute of Meteorology and Water Management in Warsaw—the risk of erosion and water regimes; and scientific knowledge and global rules—wind rose and cardinal directions (slope aspect). By contrast, the weights were assigned by us based on the multiple sources of information analysed and the acquired knowledge. The scores have an identical span since we believe they have an identical significance in such studies.

The study area covered 18 precincts consisting of 44 villages of the Brzozów district situated in southeastern Poland using an algorithm for delimiting rural areas according to soil classes designed in our previous studies. An agricultural wasteland concentration indicator was designed for the study area. Six factors were calculated based on the geospatial data describing the study area. Each factor was calculated as the total quotient of the weighted feature in relation to the total surface area of the study site. The last stage was a detailed analysis of the area featuring the highest value of the indicator.

The value of the designed indicator will allow for the identification of villages in which design capabilities should be particularly taken into account during land consolidation projects. This will significantly impact the possibility of future development and the adequate use of this land for agricultural and non-agricultural purposes. A benefit related to that indicator is that it can be used in various regions, irrespective of where the consolidated object is located. Such broad and thorough studies, giving rise to a strategy, will be valuable material at the stage of designing and developing the rural area subject to transformation.

2. Materials and Methods

The studies were conducted in the district of Brzozów, Subcarpathian Voivodeship, southeastern Poland (Figure 1).

The district of Brzozów is located mostly on the slope of the Dynów Foothills and on the west side of the Przemyśl foothills. The southwestern edge of the district is situated on the northern edge of the Jasło–Krosno Basin.

The relief of the studied area is characterised by numerous hills divided by rivers and creek valleys. In the south, the hills are higher and steeper, several times exceeding 500 m above sea level. A few rivers and creeks cross the county area.

The district has got two climatic zones: a warm-temperate and a cold-temperate one, both classified as a transitional climate type with a dominant oceanic climate.

The analysed area comprises 18 villages separated from the whole district of Brzozów, consisting of 44 villages in total. They were selected based on an original algorithm for delimiting rural areas according to soil classes [50].

The studies were conducted using real current descriptions and maps, which allowed us to design an original indicator of the concentration of agricultural wastelands (${\mathrm{W}}_{{\mathrm{NWG}}_{\mathrm{nr}}}$). The calculated indicator provides information about the examined object based on six factors identifying agricultural wastelands: soil quality class, agricultural soil complex, slope angle, risk of erosion, water regime, and slope aspect (Figure 2).

The factors were thoroughly selected, using an original method, from a range of options and then analysed in several of our publications in various areas [48,49,50].

In order to determine the correct parameters of the calculated factors, their features were specified and assigned relevant weights, from 0–12 points.

The weights proposed in this paper were determined upon the assumption that the worse the value of a feature (e.g., risk of erosion or poor soil class), the higher the numerical value of the weight.

In addition, we interviewed many scientists, officials, and representatives of society, such as farmers, to acquire knowledge that would allow us to establish such weights. As a result, a uniform scale of values was adopted for all the criteria. All the actions regarding the setting of the criteria for the selecting factors, features, and score weights were analysed many times and created in consultation with an extensive group of experts at the academic level, institutes, businesses, and society. They were also presented in the reviewed scientific papers.

For the purposes of these analyses, various geospatial data describing the study area in five thematic scopes were acquired from the Head Office of Geodesy and Cartography (GUGiK), the Institute of Meteorology and Water Management-National Research Institute (IMGW-PIB), the Institute of Soil Science and Plant Cultivation (IUNG) in Puławy, the Regional Centre of Geodesic and Cartographic Records (WODGiK) in Rzeszów, and the District Centre of Geodesic and Cartographic Records (PODGiK) in Brzozów.

Figure 3 presents a general scheme outlining how the data were acquired and used.

The values describing slope angle and aspect are derived from the Digital Terrain Model retrieved from the Head Office of Geodesy and Cartography resources. The data, current as of 1 April 2017, were converted into a raster describing elevation with a spatial resolution of 1m, and then, using available QGIS tools, the desired values were calculated and classified into their respective weight categories.

The classification contours were analysed using DXF files representing a graphical part of the EGIB (Land and Buildings Register) database provided by the District Centre of Geodesic and Cartographic Records in Brzozów. The data were up-to-date and provided with geodetic accuracy, depending on the surveying technology used. The conversion of files resulted in polygonal layers of classification contours to which relevant weights were assigned (

Table 1. Soil quality classes.

Feature (Arable Land)	Weight	Feature (Grassland)	Weight
I	2	I	2
II	4	II	4
III a	6	III	6
III b	7	IV	8
IV a	8	V	10
IV b	9	VI	12
V	10
VI	12

Source: Own elaboration based on the division according to soil classes (Regulation 2012). a—upper class, b—lower class

).

Calculations for the categories of agricultural complexes and water regimes were carried out according to digital agricultural soil maps provided by the Institute of Soil Science and Plant Cultivation in Puławy, supplemented with data from the resources of the Regional Centre of Geodesic and Cartographic Records in Rzeszów. The accuracy of the soil characteristics data is difficult to estimate due to the variety of surveying methods used; however, this kind of information does not require high precision. At first, areas assigned to their respective soil complexes were classified by weight. Then, based on the adopted, specific criteria, a description of the water regime was prepared using the same data.

The above-described sources were also used to acquire information about soil types. This information, supplemented with general information about annual precipitation sums—calculated for the district area based on data from 2021 and provided by the Institute of Meteorology and Water Management—National Research Institute and predetermined slope angle characteristics—was used to determine the degree of erosion within the study site. Due to the fact that the characteristics are dependent on multiple factors, the calculations were divided into two stages. In the first stage, aggregated data on slope angle were assigned to delimited polygons that differentiated the study area in terms of soil type. The next stage classified the resulting unit polygons according to the corresponding degrees of erosion, taking into account the mean annual sum of precipitation within the study site.

2.1. Soil Classes

The first factor, referring to soil classes, was designed according to the applicable Regulation of the Council of Ministers of 12 September 2012 concerning the classification of land, based on soil science [51], into arable land and grassland. Table 1 shows the weights assigned to such land. Data for the calculations were provided by the District Centre of Geodesic and Cartographic Records at the District Administration Office in Brzozów.

2.2. Agricultural Soil Complexes

The second feature was agricultural soil complexes. The division was systematised according to the ratio of valorisation of agricultural production space (WWRPP). Materials (digital agricultural soil maps) for analyses were derived from the Institute of Soil Science and Plant Cultivation (IUNG) in Puławy and the Regional Centre of Geodesic and Cartographic Records (WODGiK) in Rzeszow.

Soil complexes show qualitative and ranking (ordinal) data features. A qualitative division into arable land and grassland complexes was applied. A single agricultural area was divided into soil complexes based on the quantitative evaluation of soil productivity for the respective indicator plants from which soil complexes derive their names. Nine arable land complexes were identified in lowlands and highlands that were further divided into three groups: wheat (1, 2, 3), rye (4, 5, 6, 7), and rye–fodder (8, 9) complexes. Within these groups, soil complexes were ordered from the best to the weakest in terms of productivity, which is reflected by the name of the complex, e.g., 4—very good rye complex, 5—good rye complex. Grasslands in lowlands and highlands were divided into three soil complexes: 1z—very good grassland, 2z—medium grassland, and 3z—weak grassland. This criterion was further subdivided into mountain wheat complex (10), mountain rye complex (11), mountain oat–potato complex (12), mountain oat–fodder complex (13), and arable soils for use as grassland (14), as well as forests and afforested areas.

Considering the productivity of these soils, as implied by their names, they were ordered from the best to the weakest [52].

Table 2. Agricultural soil complexes.

Agricultural Soil Complexes
Feature (Agricultural Soil Complex)	Weight
1—very good wheat complex	3
2—good wheat complex	4
3—defective wheat complex	6
4—very good rye complex (wheat-rye)	5
5—good rye complex	7
6—weak rye complex	9
7—very weak rye complex	12
8—strong rye–fodder complex	6
9—weak rye–fodder complex	9
10—mountain wheat complex	5
11—mountain rye complex	6
12—mountain oat–potato complex	9
13—mountain oat–fodder complex	10
14—arable soils for use as grassland	10
1z—very good and good grassland	4
2z—medium grassland	7
3z—very weak and weak grassland	11
Ls—forests	1
Tz—built-up grounds	0

presents their detailed division and the weights assigned to them.

2.3. Slope Angle

The analysis of the third factor, slope angle, was based on an elevation model—the Digital Terrain Model (DTM). Measurement data were used in ARC/INFO ASCII GRID formats (files containing altitudes of points in a regular 1-metre mesh screen; data derived from aerial photographs). The mean elevation error falls within the range of up to 0.2 m. The data were retrieved from Head Office of Geodesy and Cartography resources via the data downloading service at the National Geoportal. All surface areas were calculated using GIS tools with QGIS software. Slope angle (terrain slope study) was divided into five ranges expressed in degrees [53,54] to which weights were assigned, as presented in

Table 3. Slope angle.

Feature (In Degrees)	Weight
<3°	2.4
3°–6°	4.8
6°–10°	7.2
10°–15°	9.6
>15°	12

.

2.4. Risk of Erosion

The next, fourth factor—that is, the risk of erosion—was described using the previous factors, that is, slope angle (NMT) and soil type (data from the Institute of Soil Science and Plant Cultivation (IUNG) in Puławy), supplemented with the precipitation sums in the study area based on data from the Institute of Meteorology and Water Management (IMGW) in Warsaw.

Digital agricultural soil maps and the previously prepared raster data on slope angle classification were used to analyse the degree of erosion.

The risk of erosion within the study area can be determined based on a map of the spatial distribution of soils and information about the slope gradient of the specific area derived from DTM (Digital Terrain Model) processing, including information from

Table 4. Intensity of potential water erosion.

Susceptibility of Soil to Flushing	Terrain Slope Classes
	Up to 3°	3°–6°	6°–10°	10°–15°	>15°
	(up to 5%)	(6%–10%)	(10%–18%)	(18%–27%)	(>27%)
	Intensity of Erosion
Loess and loess-like soils (ls), silt (pł), and silt of water origin (płw)	1	2	3	4	5
(Loose) sand (pl), sandy soil (p), Cretaceous rendzina soil (k), and Jurassic rendzina soil (j)	1	2	2; 3	3; 4	5
Sand (ps), loamy sand (pg), loamy and slightly loamy sand complexes (pgs), gravelly soil (ż), tertiary rendzina soil (tr), and old geological formations (ts)	1	1; 2	2; 3	3; 4	4; 5
Light soil—sandy soil and loamy sand (gl), medium soil (gs), loamy soil (g), and sedimentary rocks with carbonate binder other than limestone	-	1	2	3	4; 5
Heavy soil (gc), clay soil (i), rocky soil—rocks (sk), gravelly, cobbly, stony or bouldery formations (sz), and rock-derived formations	-	1	1; 2	2; 3	3; 4; 5

Source: Own elaboration based on Józefaciuk and Józefaciuk, 1990.

specifying potential water erosion intensity on the basis of the concept of Józefaciuk and Józefaciuk [53,54].

The risk of potential water erosion is marked from 1–5:

1—slight erosion causing small sheet flow only.

2—moderate erosion leading to clear washout of the humus horizon and deterioration of soil properties.

3—medium erosion that can completely reduce the humus horizon and create soil profiles of unclassified types.

4—strong erosion that can contribute to destroying the whole soil profile and even a part of the subsoil, which is associated with changes in soil cover types.

5—very strong erosion with effects resembling those of strong erosion but more intensively expressed and leading to the permanent degradation of ecosystems.

It should be noted that if two degrees of the risk of erosion exist at the same time, the lower degree of erosion is quoted for precipitation levels below 600 mm, and the higher for precipitation levels above 600 mm.

For soil formations from the fifth group on land with a slope gradient > 15°, for precipitation up to 600 mm, the third degree of erosion intensity is assumed, and for rainfall levels from 600 mm to 800 mm, the fourth degree, while for rainfall exceeding 800 mm, the fifth degree.

The weights were assigned to the risk of erosion according to

Table 5. Risk of erosion.

Feature (Intensity of Erosion)	Weight
0 (none)	0
1 (very weak)	2.4
2 (weak)	4.8
3 (moderate)	7.2
4 (strong)	9.6
5 (very strong)	12

.

Areas where no erosion was noted (0), were assigned weight 0. By contrast, areas with a very weak (1) erosion intensity were assigned a score of 2.4. Weak-intensity (2) areas were assigned a weight of 4.8, and moderate (3) areas were assigned 7.2. Strong-intensity (4) erosion corresponded to a weight of 9.6, and areas with a very-strong-intensity (5) erosion were assigned a weight of 12.

2.5. Water Regime

The fifth factor, water regime, was determined by taking into account the moisture criteria in view of agricultural soil complexes (

Table 6. Water regime.

Agricultural Soil Complex *	Weight
1, 2	4
3, 4, 5, 6, 8, 9	8
7	12
10	4
11, 12	8
13, 14	12
1z	4
2z	8
3z	12

Source: Own elaboration based on Prus and Salata, 2013. * symbols represent agricultural soil complexes described in Table 2.

). The knowledge of air and water relationships is significant with respect to programming land improvement practices involving water. An agricultural soil map presents an overview of the development of moisture conditions in the respective groups, and soil moisture categories are quite closely connected to soil and agricultural complexes [55].

The following soil moisture categories with the relevant score weights assigned were adopted in the study: very good soil moisture complexes, 1, 2, 10, and 1z, were assigned a weight of 4; slightly defective complexes, 3, 4, 5, 6, 8, 9, 11, 12, and 2z, were assigned a weight of 8; and defective complexes, 7, 13, 14, and 3z, were assigned a weight of 12.

2.6. Slope Aspect

The last, sixth factor is the slope aspect determined according to the main directions of eight ranges expressed in degrees (Figure 4), and the distribution of weights is shown in

Table 7. Slope aspect.

Feature (Main Directions in Degrees)	Weight
0–45	12
45–90	9
90–135	6
135–180	3
180–225	3
225–270	6
270–315	9
315–360	12

, below.

Each factor was calculated as the total quotient of the weighted feature in relation to the total surface area of the study site, ${\mathrm{W}}_{\mathrm{c}}$:

$${\mathrm{W}}_{\mathrm{c}}=\frac{{{\displaystyle \sum }}_1^{\mathrm{n}}\left({\mathrm{k}}_{\mathrm{n}}{\ast \mathrm{p}}_{\mathrm{n}}\right)}{{\mathrm{P}}_{\mathrm{w}}}$$

(1)

where

${\mathrm{W}}_{\mathrm{c}}$—value of the examined factor.

${\mathrm{k}}_{\mathrm{n}}$—weight assigned to a specific group of areas (depending on the factor).

${\mathrm{p}}_{\mathrm{n}}$—surface of a specific group of areas (depending on the factor).

${\mathrm{P}}_{\mathrm{w}}$—surface of the study site.

Afterwards, the agricultural wasteland concentration indicator (2) was calculated, which allowed us to parametrise the selected areas:

$${\mathrm{W}}_{{\mathrm{NWG}}_{\mathrm{nr}}}={\mathrm{W}}_{{\mathrm{c}}_1}+{\mathrm{W}}_{{\mathrm{c}}_2}+\dots +{\mathrm{W}}_{{\mathrm{c}}_{\mathrm{n}}}$$

(2)

where

${\mathrm{W}}_{{\mathrm{NWG}}_{\mathrm{nr}}}$—agricultural wasteland concentration indicator

${\mathrm{W}}_{{\mathrm{c}}_{\mathrm{n}}}$—value of the examined factor

3. Results and Discussion

The study covered 18 out 44 villages situated within the administrative limits of the district of Brzozów in the Subcarpathian Voivodeship of southeastern Poland. This area was selected based on a previously calculated algorithm for delimiting rural areas according to soil classes into clusters with a similar surface area; the total share of arable land, meadows, and pastures; and the mean score [50]. The value of the last factor was calculated based on the scores assigned to the soil quality classes of arable land and grassland adopted from [56] and stemming from studies referring to four cereals and potato crop yields. The studies determined the production value of arable land and grassland according to soil quality classes on a 100-point scale.

Table 8. Values of the agricultural wasteland concentration indicator.

Ranking Position.	Name of Precinct	Area	Soil Class	Slope Angle	Aspect	Agricultural Soil Complex	Intensity of Erosion	Water Regime	Indicator Value
1	Obarzym	670.25	9.0	8.9	6.9	5.0	7.8	8.5	46.1
2	Niewistka	503.34	8.2	7.6	7.3	9.1	6.4	6.9	45.5
3	Krzywe	742.94	9.1	8.4	8.7	5.5	7.3	6.5	45.5
4	Huta Poręby	514.95	7.9	8.5	6.9	7.8	8.1	6.2	45.4
5	Temeszów	546.13	9.4	7.7	8.8	4.6	6.9	7.4	44.8
6	Krzemienna	569.63	8.5	8.2	7.3	6.2	7.3	6.8	44.3
7	Siedliska	794.50	8.0	8.1	7.2	6.2	7.7	6.8	44.0
8	Dydnia	1476.37	8.6	7.9	7.9	5.4	7.2	6.6	43.6
8	Hłudno	1270.83	8.7	7.7	8.4	4.6	7.2	7.0	43.6
10	Wołodź	1088.50	7.9	8.4	8.6	2.9	7.8	7.5	43.1
11	Witryłów	998.30	8.3	8.1	7.7	4.3	7.8	6.4	42.6
12	Końskie	996.01	8.2	8.1	7.9	4.7	6.9	6.4	42.2
13	Malinówka	804.47	8.0	8.1	7.6	4.1	7.1	5.6	40.5
14	Jabłonka	1089.45	8.2	8.0	7.5	3.3	7.1	6.3	40.4
15	Jabłonica Ruska	543.81	8.0	7.3	6.4	5.8	5.6	6.9	40.0
16	Wola Jasienicka	879.23	9.5	8.8	6.9	2.8	5.6	6.1	39.7
17	Hroszówka	479.53	8.5	8.9	5.9	3.8	6.4	6.0	39.5
18	Zmiennica	797.25	7.9	7.2	7.4	3.9	6.2	5.5	38.1

presents the values of six factors with the final value of the agricultural wasteland concentration indicator calculated from the abovementioned formula (2). Figure 5, Figure 6 and Figure 7 illustrate the spatial differentiation of the six factors for the respective precincts.

The maximum summary value of the agricultural wasteland concentration indicator is 72 points. The study shows that the indicator’s span ranges from 38.1 points for the village of Zmiennica to 46.1 points for Obarzym. The analysis revealed that, apart from Obarzym, villages that also scored above 45 are Niewistka (45.5), Krzywe (45.5), and Huta Poręby (45.4). Therefore, these are villages with the most difficult conditions in terms of agricultural production capacity and profitability. Featuring soils of particularly low quality, they are situated within an area with a large slope angle, which exposes them to the risk of erosion and a poor water regime.

In contrast, next to Zmiennica (38.1 points), villages such as Hroszówka (39.5 points), Wola Jasienicka (39.7 points), and Jabłonica Ruska (40.0 points) are characterised by a higher quality of the selected factors. Despite being situated in an area with a large slope angle and having poor quality soil, they feature good agricultural soil complexes with the right aspect but also, most importantly, cover areas with a lower degree of erosion and good water regimes.

A detailed analysis of the area with the highest concentration of agricultural wastelands—the village of Obarzym—showed (Figure 8, Figure 9 and Figure 10; Table 8) that the area of the village (670.3 ha) is dominated by forests accounting for 49.1% (328.9 ha) of the total surface area, which extends from the north towards the centre and then eastward. Arable land, meadows, and pastures together account for 44.2% of the village’s total area. Predominant soil classes are IV a and IV b for arable land and IV and V for meadows and pastures.

The predominant agricultural soil complex within the analysed area is the mountainous rye complex, accounting for nearly 30.0% of the analysed area.

Within an area of more than 231 ha, corresponding to 34.6% of the total precinct area, the slope angle exceeds 15°. This area extends from the west through the southwest to the southeast and east, but at some points, it also reaches the northern part of the precinct. This increases the risk of erosion (9–12 points), and the area extends mainly from the central part of the village towards the southeast. Areas at risk of erosion are also present in the western part of the village. Moderate and strong erosion affects nearly ¼ of the whole precinct.

As regards the water regime, complexes with a slightly defective and defective water regime are prominent from the west, through the southwest, and to the southeast and east, but they are less numerous there. They are also located in the central part of the precinct. The abovementioned complexes occupy an area of more than 376 ha, which corresponds to 56.2% of the village area.

The slope aspect varies greatly. However, in the southern part of the village, the predominant aspect of the slope is from the northwest, through the north, and to the northeast. In contrast, in the central, central-western, central-eastern, and northern parts of the precinct, the predominant slope aspect is from the southwest, through the south, and to the southeast.

Detailed surveys and analyses carried out in Obarzym showed that the surveying designer—having collected information about the six factors proposed in the paper forming part of the final indicator for the redeveloped object—will be able to propose alternative design solutions to the inhabitants of the consolidated village. This is associated, among other things, with a projected road network, the location and shape of the designed plots, the correct ploughing direction (across the slope to reduce erosion), building new drainage ditches (to improve the water regime), and polders (to supply or remove excess water; soils in the polder are often used for agricultural purposes). In the future, the above-described solutions will allow for the use of these areas for agricultural or non-agricultural purposes. Therefore, these guidelines will be essential for development projects conducted in the specific area.

4. Conclusions

Projects related to land consolidation are the only tool for the comprehensive improvement of the spatial structure of rural areas, and the effects of such projects can, in real terms, determine the further use of the land. In view of limited financial and human resources, land consolidation is conducted in areas where the inhabitants are interested in and approve of such works. Therefore, the works are carried out in villages characterised by the correct parameters of soil quality and terrain relief, as well as in areas where the conditions for agricultural production are difficult.

The examined area of 18 villages was delimited based on a previously calculated algorithm for delimiting rural areas according to soil classes into clusters with a similar surface area; the total share of arable land, meadows, and pastures; and the mean score. An agricultural wasteland concentration indicator was calculated for the delimited area based on six factors assigned relevant weights from 0 to 12 points. According to expert knowledge and study experience, the weights were assigned upon the assumption that the more unfavourable the value of the feature is, the higher its weight is. Each factor was calculated as the total quotient of the weighted feature in relation to the total surface area of the study site. Thus, the calculated agricultural wasteland concentration indicator has multiple aspects.

I believe an agricultural wasteland concentration indicator must be designed to identify areas (villages), which is useful for many analyses.

The designed indicator is particularly useful in areas with varied terrain relief and a variety of soils since land quality is one of the key factors that impacts agricultural crop yield. The soil conditions in terms of soil quality and use can be described according to soil quality classes, agricultural soil complexes, and water regimes.

Low soil classes, poor agricultural soil complexes, and excesses or deficiencies of water (depending on the soil) considerably impact the type and amount of a farm’s crops.

Therefore, it is a key determinant of income derived from agricultural production in a specific area. The awareness that spatial variations exist in soil quality classes in the study area actually affects the planning and development of agricultural land and the efficient allocation of funds for the spatial redevelopment of rural areas.

As a consequence, this will have an essential influence on the possibility of the further development and adequate use of the analysed land both, for agricultural and non-agricultural purposes, that is, allocating land for forest planting, building development, transport infrastructure, agritourism, leisure, transformation in ecological areas, growing energy crops, setting up wildlife food plots, and gardening.

A big advantage of this original indicator is that it can be applied to any region, irrespective of the location of the study site, as the range of features describing the factors suits all lands. In the author’s opinion, this is the potential of the indicator, which may be used for a wide range of analyses depending on the concepts and demands of the studies. The only limit may arise from the constrained accessibility of the source data. However, the technology is being developed rapidly, and this problem may be resolved soon.

It should be emphasised that an individual approach to the analysed land is needed depending on the local community’s needs. Detailed studies will certainly prepare necessary documentation in the form of local, district, and regional strategies, which will be valuable material at the stage of designing and developing the village area subject to transformation.