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538 SILVA, V. A. et al.
SOIL MAPS, FIELD KNOWLEDGE, FOREST INVENTORY AND
ECOLOGICAL-ECONOMIC ZONING AS A BASIS FOR AGRICULTURAL
SUITABILITY OF LANDS IN MINAS GERAIS ELABORATED IN GIS
Mapa de solos, conhecimento de campo, inventário florestal e Zoneamento Ecológico-
Econômico como base para a aptidão agrícola das terras em Minas Gerais elaborada em SIG
Vladimir Antonio Silva^1 , Nilton Curi^2 , João José Granate Marques^3 , Luis Marcelo Tavares de Carvalho^4 , Walbert Júnior Reis dos Santos^5 ABSTRACT Lands (broader concept than soils, including all elements of the environment: soils, geology, topography, climate, water resources, flora and fauna, and the effects of anthropogenic activities) of the state of Minas Gerais are in different soil, climate and socio-economics conditions and suitability for the production of agricultural goods is therefore distinct and mapping of agricultural suitability of the state lands is crucial for planning guided sustainability. Geoprocessing uses geographic information treatment techniques and GIS allows to evaluate geographic phenomena and their interrelationships using digital maps. To evaluate the agricultural suitability of state lands, we used soil maps, field knowledge, forest inventories and databases related to Ecological-Economic Zoning (EEZ) of Minas Gerais, to develop a map of land suitability in GIS. To do this, we have combined the maps of soil fertility, water stress, oxygen deficiency, vulnerability to erosion and impediments to mechanization. In terms of geographical expression, the main limiting factor of lands is soil fertility, followed by lack of water, impediments to mechanization and vulnerability to erosion. Regarding agricultural suitability, the group 2 (regular suitability for crops) is the most comprehensive, representing 45.13% of the state. For management levels A and B, low and moderate technological level, respectively, the most expressive suitability class is the regular, followed by the restricted class and last, the adequate class, while for the management level C (high technological level) the predominant class is the restricted. The predominant most intensive use type is for crops, whose area increases substantially with capital investment and technology (management levels B and C). Index terms : Geoprocessing, land suitable for agriculture, sustainability, multicriteria analysis. RESUMO As terras (conceito mais abrangente do que solos, incluindo todos os elementos do ambiente: solos, geologia, relevo, clima, recursos hídricos, flora e fauna, além dos efeitos da ação antrópica) do estado de Minas Gerais estão em diferentes condições de solo, clima e sócio-economia, portanto, são distintas as vocações para produção de bens agrícolas e o mapeamento da vocação agrícola das terras do estado é fundamental para o planejamento norteado da sustentabilidade. O geoprocessamento utiliza técnicas de tratamento da informação geográfica e o SIG permite avaliar com mapas digitais os fenômenos geográficos e suas inter-relações. Objetivando avaliar a vocação agrícola das terras do estado, utilizaram-se o mapa de solos, o conhecimento de campo, o inventário florestal e o banco de dados relacionados ao Zoneamento Ecológico-Econômico (ZEE) de Minas Gerais, para elaborar em SIG o mapa de aptidão agrícola. Para tal, combinaram-se os mapas de fertilidade do solo, deficiência de água, deficiência de oxigênio, vulnerabilidade à erosão e de impedimentos à mecanização. Em termos de expressão geográfica, o principal fator limitante das terras é a fertilidade do solo, seguido pela deficiência de água, impedimentos à mecanização e vulnerabilidade à erosão. Quanto à aptidão agrícola, o grupo 2 (aptidão regular para lavouras) é o de maior abrangência, representando 45,13% do estado. Para os níveis de manejo A e B, baixo e moderado nível tecnológico, respectivamente, a classe de aptidão mais expressiva é a regular, seguida pela classe restrita e por último a classe adequada, enquanto para o nível de manejo C (alto nível tecnológico), a classe predominante é a restrita. O tipo de utilização mais intensivo predominante é para lavouras, cuja área aumenta substancialmente com investimento de capital e tecnologia (níveis de manejo B e C). Termos para indexação: Geoprocessamento, vocação agrícola das terras, sustentabilidade, análise multicritério. (Received in july 24, 2013 and approved in september 18, 2013) (^1) Instituto Nacional de Colonização e Reforma Agrária/INCRA – Belo Horizonte – MG – Brasil (^2) Universidade Federal de Lavras/UFLA – Departamento de Ciência do Solo/DCS – Cx. P. 3037 – 37200-000 – Lavras – MG – Brasil – niltcuri@dcs.ufla.br (^3) Universidade Federal de Lavras/UFLA – Departamento de Ciência do Solo/DCS – Lavras – MG – Brasil (^4) Universidade Federal de Lavras/UFLA – Departamento de Ciências Florestais/DCF – Lavras – MG – Brasil (^5) Cia. de Desenvolvimento dos Vales do São Francisco e Parnaíba/CODEVASF 1ª SR – Montes Claros – MG – Brasil
Soil maps, field knowledge, forest... 539 INTRODUCTION Agriculture depends largely on nature and inappropriate use of land (broader concept than soil, including all elements of the environment: soils, geology, topography, climate, water resources, flora and fauna, and the effects of anthropogenic activities) is one of the major cause of environmental degradation, with loss of competitiveness of the agricultural sector and the quality of life (CURI et al., 1992). The state of Minas Gerais has regions with different soil, climate and socio-economic conditions, therefore, with different suitability to produce agricultural goods. The evaluation of land suitability consists of the interpretation of the ecosystem qualities by estimating the limitations of lands for agricultural and the possibilities for correction or reduction of these limitations, with different levels of management (NAIME et al., 2006). The use of lands according to their suitability prevents their overuse (RAMALHO FILHO; PEREIRA, 1999), situation that involve sustainability risks (NASCIMENTO; GIASSON; INDA JÚNIOR, 2004). The system of Evaluation of Land Agricultural Suitability (sELAS) is a flexible method and may be adapted as needed (MOURA et al., 2007). It performs the evaluation of lands from five environmental parameters considered essential for crops, in a synthesis of the ecosystem (RESENDE et al., 2007): natural fertility, water deficiency, oxygen deficiency, suscept i bi l i t y t o er osi on a n d i m pedi m en t s t o mechanization. Geopr ocessi ng uses ma t hema t ica l an d computat ion al techni ques for th e t rea tment of geographic information. The use of the geographic information system (GIS) allows the spatial analysis of agricultural suitability of the lands and their main limitations, reducing work time, when compared with manual methods (SILVA; NOGUEIRA; UBERTI, 2010). Using sELAS, Amaral et al. (2004) performed the evaluation of lands suitability for agricultural in the state of Minas Gerais. Subsequently, a digital soil map (FUNDAÇÃO ESTADUAL DO MEIO AMBIENTE - FEAM, 2010) and a vast digital database related to Ecological-Economic Zoning (EEZ) of the state of Minas Gerais (SCOLFORO; OLIVEIRA; CARVALHO, 2008) were made available. The aim of this study was to develop a land suitability map of the lands of the state of Minas Gerais in GIS using digital data currently available, supported by field knowledge and soil survey bulletins. MATERIALAND METHODS The state of Minas Gerais is located in Southeastern Brazil and presents an area of 586,522. km^2 (INSTITUTO BRASILEIRO DE GEOGRAFIA E ESTATÍSTICA - IBGE, 2010). The assessment of the lands suitability for agriculture followed the methodology formulated by Ramalho Filho and Beek (1995), with adaptations and adjustments, whose structure and symbolism are presented in table 1. The databases were the soil map of the state of Minas Gerais (FEAM, 2010), the digital elevation model (DEM) obtained from the Shuttle Radar Topography Mission (SRTM) remote sensing image, climatic zoning of the state based on the Thornthwaite moisture index (CARVALHO et al., 2008b), the soils erosion vulnerability map (CURI et al., 2008), and forest inventory of Minas Gerais (CARVALHO; SCOLFORO, 2008). In situations where the databases did not reflect the accumulated knowledge, adjustments were made based on field experience. All maps were converted to the Albers continental projection system, raster and pixel format of 270 m. Table 1 – Symbols corresponding to the land agricultural suitability classes. Land agricultural suitability classes Crops Planted pasture Silviculture Natural pasture Management level Management level Management level Management level A B C B B A Adequate A B C P S N Regular a b c p s n Restricted (a) (b) (c) (p) (s) (n) Not adequate Source: Ramalho Filho, Beek (1995). Uppercase, lowercase, or lowercase letters in parentheses are indicative of suitability class according to management levels. Absence letters symbolizes the not adequate class.
Soil maps, field knowledge, forest... 541 The oxygen deficiency map was generated from the soil map (FEAM, 2010), assigning the values for the degrees of limitation set out in table 4 to soil classes, based on drainage conditions. The soil drainage conditions map was adapted to the oxygen deficiency map. For the erosion factor, the raster map of soil erosion vulnerability (CURI et al., 2008) was used and discussed later in this paper, which interrelates the erosion risk, rainfall intensity and soil exposure to direct raindrop impact maps. The five vulnerability classes (very low, low, medium, high and very high) were used to establish the degree of limitation by vulnerability to soil erosion, as shown in table 5. From the soil map and the relief classes map a raster map of impediments to mechanization was generated. The map of relief classes suggested by Empresa Brasileira de Pesquisa Agropecuária, EMBRAPA (2006) was obtained from the derivation of the DEM with a 90 m pixel, obtained from the Shuttle Radar Topography Mission (SRTM). Subsequently, the relief map was resampled to a pixel size of 270 m according to that adopted in the EEZ (SCOLFORO; OLIVEIRA; CARVALHO, 2008). From the soil maps, auxiliary raster maps of soil texture, presence of stoniness in the soil profile and soil depth, were produced, assigning values for the degrees of limitation related to these attributes defined in table 6 to the mapping units. Combining the auxiliary and relief maps, an impediments to mechanization map was generated. Degree Characteristics Null (N) Pixel value = 1 Excessively drained soils without the presence of gleyed horizons or plinthite. Latosol and Quartzarênic Neosol. Slight (SL) Pixel value = 2 Moderate to well drained soils with small aeration deficiency to sensitive crops, during by rainy season. Argisol, Haplic and Humic Cambisols, Chromic Luvisol, Nitosol. Moderate (M) Pixel value = 3 Moderately to imperfectly drained soils with greater restriction to crops sensitive to aeration deficiency during the rainy season. Haplic Gleysol, Litholic and Fluvic Neosols, Fluvic Cambisol. Strong (S) Pixel value = 4 Typical of hydromorphic mineral soils, poorly to very poorly drained, subject to frequent flooding, with gleyed layer at root system height of annual species. Generally, to be exploited, it involves feasible work within reach of the farmer. Melanic Gleysol. Very strong (VS) Pixel value = 5 Basically mineral soils with the highest degree of hydromorphism. Drainage works are inadvisable and out of reach of the farmer. Haplic Planosol, Argiluvic Plinthosol. Table 4 – Degrees of limitation by excess water or lack of oxygen, considering attributes and soil classes. Source: Adapted and adjusted from Ramalho Filho, Beek (1995) and FEAM (2010). Degree Characteristics Null (N) Pixel value = 1 Soils with very low vulnerability to erosion. Slight (SL) Pixel value = 2 Soils with low vulnerability to erosion. Moderate (M) Pixel value = 3 Soils with medium vulnerability to erosion. Strong (S) Pixel value = 4 Soils with high vulnerability to erosion. Very strong (VS) Pixel value = 5 Soils with very high vulnerability to erosion. Table 5 – Degrees of limitation by vulnerability to erosion. Source: Curi et al. (2008).
542 SILVA, V. A. et al. The degrees of limitation (null = 1, slight = 2, moderate = 3, strong = 4, and very strong = 5) were attributed to the land under natural conditions and also after the use of improvement practices compatible with the different management levels in order to diagnose the behavior of lands under different technological levels, in accordance with the guide table. Three management levels were adopted: level A, level B and level C (RAMALHO FILHO; BEEK, 1995), as defined in table 7, which represent low, medium and high technological level in view of economically viable agricultural practices within reach of most farmers. It is important to mention that adoption of the level A is rare n owadays, except wh er e t he m echa ni za ti on i s impedimental. For planted pasture (P) and silviculture (S), management B is foreseen. In the case of natural pasture (N), management A is implied. The lands not suitable for agricultural use are classified as for preservation or restoration of flora and fauna. The possibility of irrigation is not considered, but practices that increase the soil retention water and/or facilitate its infiltration are encouraged (RAMALHO FILHO; BEEK, 1995). The evaluation of the classes, groups and subgroups of agricultural suitability of lands was conducted in a GIS environment using ArcGIS®^ software. A comparative study between the degree of limitation attributed to lands and those stipulated in the guide table (Table 8) was undertaken. In ArcGIS®^ each limiting factor map was reclassified by the reclassify function so that pixels of the same value were grouped, i.e., those that had the same degree of limitation. Through the combine function, the maps of fertility deficiency, water deficiency, oxygen deficiency, vulnerability to erosion and impediments to mechanization were interrelated, generating a map with 642 different combinations of these plans according to the degree of limitation. In the table of attributes related to this map columns were added to the management level A, management level B for use with crops and planted pasture, management level B for use with silviculture and management level C. With the use of the select by attributes tool, rules were applied that contemplate the conditions required in each line of the table guide, for the management level considered. Selection rules were applied to the pixels from the most intensive land use, 1ABC, towards less intensive not adequate. Thus, all 68 framing possibilities of the lands were covered in the system, as shown in table 9. To each applied rule, pixels were selected that met them, defining the suitability class to which they belonged. Those that had already been selected in a previous rule, of more Degree Characteristics Null (N) Pixel value = 1 Flat relief (slope less than 3 %), free drainage soils without the presence of stoniness, rockiness or gravel or other impediments to the use of any machine or agricultural implement with high efficiency throughout the year. Deep soils (Latosols). Slight (SL) Pixel value = 2 Gently undulating relief ( 3 to 8% slope), occurrence of limitations that reduce the efficiency of mechanization such as gravel, dense layer at depth. Allows the use of most agricultural machines or implements for almost the entire year. Soils of medium depth (Nitosols and Argisols). Moderate (M) Pixel value = 3 Undulating relief ( 8 - 20% slope), occurrence of limitations that reduce the efficiency of mechanization such as gravelly or drainage constraints. It is possible to use most of the agricultural machinery during the whole year (Cambisols, Plinthosols and Gleysols). Strong (S) Pixel value = 4 Strongly undulating relief ( 20 - 45% slope), occurrence of other limitations such as stoniness, rockiness, so as to restrict the possibilities of mechanized equipment use. Only allows the use of animal traction implements or machines with specialzed wheels (Litholic Neosols). Very strong (VS) Pixel value = 5 Does not allow the use of machinery, either motorized or animal traction. Mountainous or scarped relief (slope greater than 45 %), occurrence of other limitations such as rockiness, stoniness or shallow soils, which prevent the use of machines (Rocky outcrops associated with Litholic Neosols). Table 6 – Degrees of limitation by impediments to mechanization, considering attributes and soil classes. Source: Adapted and adjusted from Ramalho Filho, Beek (1995) and FEAM (2010).
544 SILVA, V. A. et al. Seeking a refinement of the mapping of lands belonging to classes 5N, 5n and 5 (n), in order to consider only those lands whose native vegetation has the economical potential for pasture (it should be emphasized that the areas under forest and caatinga are not considered here as suitable for planted pasture, and their native vegetation, by conception, have no potential for natural pasture), an auxiliary vegetation map was drawn up based on the legend of the soils map (FEAM, 2010) and pixels with these suitability classes were reclassified according to the criteria presented in table 10.
RESULTS AND DISCUSSION
We mapped the lands limitation degrees considering the five key environmental factors (Figure 1). From the joint analysis of figure 1 and table 11 it can be verified that the majority of Minas lands falls in the moderate class regarding limitation degrees by fertility, represented mainly by dominance of Latosols (CURI et al., 2008), thus requiring the considerable applications of correctives and fertilizers. The null degree, representing the most fertile lands, is the least expressive. Group Characterization Subgroup 1 Lands with adequate suitability for short and / or long cycle crops in at least one of the management levels.
1ABC
1ABc, 1AB(c), 1AB 1aBC, 1(a)BC, 1BC 1Abc, 1Ab(c), 1A(bc), 1Ab, 1A(b), 1A 1aBc, 1aB(c), 1(a)Bc, 1(a)B(c) 1aB, 1Bc, 1(a)B, 1B(c), 1B 1abC, 1(a)bC, 1(ab)C, 1bC, 1(b)C, 1C 2 Lands with regular suitability for short and / or long cycle crops in at least one management level. 2 abc 2ab(c), 2ab 2(a)bc, 2bc 2a(bc), 2a(b), 2a 2(a)b(c), 2(a)b, 2b(c), 2b 2(ab)c, 2(b)c, 2c 3 Lands^ with restricted suitability^ for^ short and / or^ long cycle crops in at least one of the management levels. 3(abc), 3(ab), 3(bc), 3(a), 3(b), 3(c) 4 Lands with adequate, regular or restricted suitability for planted pasture. 4P, 4p, 4(p) 5 Lands with adequate, regular or restricted suitability for silviculture or natural pasture. 5SN, 5Sn, 5S(n), 5S 5sN, 5sn, 5s(n), 5s 5(s)N, 5(s)n, 5(sn), 5(s) 5N, 5n, 5(n) 6 Lands not suitable for agricultural use. Not adequate Table 9 – Characterization of possible agricultural suitability of land groups and subgroups. Table 10 – Economical potential of native vegetation for use as pasture. Vegetation type Potential for pasture Cerrado and grassy field. Adequate Campo Cerrado, grassland, field, rupestrian field. Regular Forest and grassland, cerrado and caatinga, cerrado and forest, path. Restricted Forest, caatinga. Not adequate
Soil maps, field knowledge, forest... 545 Figure 1 – Maps elaborated in GIS, with degrees of limitation by fertility, water deficiency, oxygen deficiency, vulnerability to erosion and impediments to mechanization of lands of Minas Gerais.
Soil maps, field knowledge, forest... 547 Figure 2 – Agricultural suitability map of the lands of Minas Gerais elaborated in GIS.
548 SILVA, V. A. et al. CONCLUSIONS The major land agricultural suitability group of Minas Gerais is the group 2 (regular suitability for crops) representing 45.13% of the total area of the state. 76% of the state area can be used with crops in sustainable conditions. The geoprocessing in GIS allowed substantial agility on the spatial analysis of agricultural suitability of the lands of Minas Gerais. ACKNOWLEDGMENTS To Incra, Fapemig and CNPq, for financial support of the project. Table 12 – Extent and percentage of groups and subgroups of lands agricultural suitability of Minas Gerais state. Table 13 – Agricultural suitability of the lands of Minas Gerais, stratified by management level for different types of indicated use. Use type Suitability class by management level (%) Management level A Management level B Management level C A a (a) B b (b) C c (c) Crops 0.29 45.21 22.45 0.07 45.43 4.86 0.08 2.58 46. Planted pasture 3.30 1. Silviculture 0. Natural pasture 0.64 3.53 0. Total 0.93 48.74 23.11 0.07 48.73 7.31 0.08 2.58 46. REFERENCES AMARAL, F. C. S. do et al. Mapeamento de solos e aptidão agrícola das terras do Estado de Minas Gerais. Rio de Janeiro: Embrapa Solos, 2004. 95 p. CARVALHO FILHO, A. de; CURI, N.; FONSECA, S. da. Sistema informatizado e validado de avaliação da aptidão silvicultural das terras dos Tabuleiros Costeiros brasileiros para eucalipto. Lavras: Editora UFLA, 2013. 138 p. CARVALHO, L. M. T.; SCOLFORO, J. R. Inventário florestal de Minas Gerais: monitoramento da flora nativa 2005-2007. Lavras: Editora UFLA, 2008. 357 p. Group Subgroup Area (ha) % Of total 1 1ABc 41 , 193. 44 0. 07 215 , 658 .93 ha; 0.37% 1Ab(c) 129, 899. 74 0. 22 1abC 44, 56 5. 75 0. 08 2 2abc 1, 470 , 501. 08 2. 50 26, 472 , 237. 72 ha; 45. 13 % 2ab(c) 25 , 001 , 736. 64 42. 63 3 3(a) 13,166,850. 98 22. 45 17,888,203. 08 ha; 30. 50 % 3(b) 2,850,184. 50 4. 86 3(c) 1,871,167. 61 3. 19 4 4p 1,935,314. 72 3. 30 3,091,055. 08 ha; 5.27% 4(p) 1,155,740. 36 1. 97 5 5(sn) 2 78,962. 96 0. 48 3,112,828. 43 ha; 5.31% 5N 374,985. 69 0. 64 5n 2 ,070,060. 31 3. 53 5(n) 388,819. 47 0. 66 6 Not adequate 7,389,138. 88 12. 60 Water resources Water resources 483,090.07 0. Total 58,652,212. 20 100. 00
