Serviços Personalizados
Journal
Artigo
Indicadores
- Citado por SciELO
- Acessos
Links relacionados
- Similares em SciELO
Compartilhar
Revista mexicana de ciencias agrícolas
versão impressa ISSN 2007-0934
Rev. Mex. Cienc. Agríc vol.11 no.1 Texcoco Jan./Fev. 2020 Epub 02-Mar-2021
https://doi.org/10.29312/remexca.v11i1.2213
Articles
Diagnosis of the use of soil and vegetation in the microbasin Tula, Mexico
1Maestría en Agroforestería para el Desarrollo Sostenible-Departamento de Suelos-Universidad Autónoma Chapingo. Carretera Texcoco-México km 38.5, Texcoco, Estado de México. CP. 56230. (jcbuendiae@hotmail.com).
2Posgrado en producción animal-Departamento de Zootecnia-Universidad Autónoma Chapingo. Carretera Texcoco-México km 38.5, Texcoco, Estado de México. CP. 56230.
Changes in land use and plant cover are the main component in global, regional and local deterioration, and have been documented as the second global environmental problem. In Mexico, there are few planning policies in the territorial development of the municipalities and a poor decision making in the management of natural resources, an example of which is the Tula microbasin. The objective of the research work was to diagnose the current situation and the changes in the coverage and land use of the Tula microbasin, through spatial analysis, to know its main processes of change, with the purpose of designing strategies that allow sustainable management of its natural resources. The spatial analysis was carried out, based on Landsat satellite images (1992, 2000 and 2017) using geographic information systems. To identify the changes, cross-tabulations were applied and exchange rates were estimated. In the analyzed period (25 years), the agricultural area increased 33% and a loss of forest area of 22%. Exchange rates and likelihood of permanence indicated that continuing with the current trend will continue to increase agricultural areas and bodies of water, as well as the abandonment of some areas due to their low productivity.
Keywords: geographic information systems,land use change; transition matrices; vegetation
Los cambios en el uso de suelo y la cobertura vegetal son el componente principal en el deterioro a escala global, regional y local, y han sido documentados como el segundo problema ambiental a nivel global. En México, hay pocas políticas de planificación en el desarrollo territorial de los municipios y una deficiente toma de decisiones en el manejo de los recursos naturales, ejemplo de ello es la microcuenca Tula. El trabajo de investigación tuvo como objetivo, diagnosticar la situación actual y los cambios en la cobertura y uso de suelo de la microcuenca Tula, México por medio del análisis espacial, para conocer sus principales procesos de cambio, con el propósito de diseñar estrategias que permitan un manejo sustentable de sus recursos naturales. El análisis espacial se realizó, a partir de imágenes satelitales Landsat (1992, 2000 y 2017) mediante sistemas de información geográfica. Para identificar los cambios se aplicaron tabulaciones cruzadas y se estimaron las tasas de cambio. En el periodo analizado (25 años), el área agrícola se incrementó 33% y una pérdida de superficie forestal de 22%. Las tasas de cambio y probabilidad de permanencia indicaron que de continuar con la tendencia actual seguirán incrementándose las áreas agrícolas y los cuerpos de agua, así como el abandono de algunas superficies debido a su baja productividad.
Palabras clave: cambio de uso de suelo; matrices de transición; sistemas de información geográfica; vegetación
Introduction
The change in land use and vegetation cover are the main component in the global, regional and local deterioration, and have been documented as the second global environmental problem (Xiao et al., 2006). For decades, human activities and the demand for goods and services have generated pressure on natural resources with large impacts, most of them negative, which are difficult to reverse (Rosete et al., 2008; Reynoso et al., 2015). Mexico is a country with high biological and cultural diversity, with high rates of deforestation and exploitation of natural resources (FAO, 2016; Sahagún-Sánchez and Reyes-Hernández, 2018). The loss and degradation of vegetation in a basin or microbasin, as well as the speed at which these changes occur alter the functions and the proper functioning of the exchange of matter and energy (Cuevas et al., 2011).
Consequently, it is necessary to analyze changes in plant cover to develop strategies that mitigate the negative impact on natural resources (Leija-Loredo et al., 2018). In the last decades, the fourteen municipalities that make up the Tula microbasin have had an annual average population growth of 2%, reaching a population of 288 196 in 2010 and an approximate density of 278 km-2 inhabitants (INEGI, 2013). The population density increased from 205 to 236 km-2 inhabitants in the period from 1990 to 2000 (INEGI, 1990; INEGI, 2000) and with it the demand for goods and services by society, as well as the problems associated with the change of use soil due to pressure on natural resources. The growth of urban stain in the municipality has been disorderly, expanding into areas of agricultural, forestry and grassland uses.
The extraction of construction materials (mining use) has increased in agricultural, forestry and areas near urban centers (INEGI, 2017a; INEGI, 2017b; INEGI, 2017c). The foregoing is the product of insufficient planning policies in the territorial development of municipalities, and of poor decision making in the management of natural resources. For all this, the need to analyze the changes that have taken place in the Tula microbasin, in addition, is a politically complex territory because it is made up of three states, which implies different state policies.
Therefore, this research work aims to diagnose the current situation of changes in the coverage and land use of the Tula microbasin, Mexico through spatial analysis, to know its main processes of change and thus contribute to the understanding of the system, with the purpose of designing strategies that allow a sustainable management of its natural resources.
Materials and methods
Study area
The Tula microbasin is framed within the geographical coordinates: 19° 55’ 31.05’’ and 19° 34’ 28.74’’ north latitude and 98° 39’ 59’’ and 98° 28’ 16.39’’ west latitude (Figure 1), has an area of 103 766 ha and covers the territory of the municipalities: Calpulalpan, Sanctorum de Lázaro Cárdenas, Benito Juárez, Almoloya, Apan, Emiliano Zapata, Singuilucan, Tepeapulco, Villa de Tezontepec, Tlanalapa and Zempoala of the state of Hidalgo, Axapusco and Nopaltepec of the State of Mexico and Temacalpa of the State of Tlaxcala. In addition, it is immersed in the Panuco river basin, within the physiographic province of the Neovolcanic axis. It has an altitude range of 2 333 to 3 223 meters above sea level, the average annual rainfall is 600 mm and the predominant soil types are Feozem, Cambisol, Litosol, Regosol and Vertisol (INEGI, 2017a; INEGI, 2017b; INEGI, 2017c), there are different types of vegetation, among which are the tascate forest, pine forest, oak forest, crasicaule thicket (INEGI, 2017d).
According to López et al. (2001), in order to analyze the process of change of land use and coverage, it is necessary to apply three stages: a) cartographic and digital change and interpretation of change; b) analysis of land cover change and land use patterns; and c) analysis of causes of change.
Generation of land use cartographic
The generation of cartography corresponds to the first stage to perform the change process analysis. According to Bautista et al. (2011) At this stage it is necessary to select and acquire the satellite images that will be worked on, then they must be performed a standard digital treatment (geometric, radiometric and atmospheric correction). Then the image transformation follows, where the image is classified, from the association of elements observed in the image to certain thematic categories, prior to classification, the classification system must be determined and the evaluation of the geographical digital bases must be carried out (Rosete et al., 2008; Bautista et al., 2011).
The generation of land cover and land use mapping in this study consisted of: a) selecting three satellite images: Landsat-5 TM (12/04/1992), Landsat-7 ETM + (02/12/2000) and Landsat -8 Oli Tirs (11/23/2017) with a resolution of 30 m and an L1TP processing level; and b) correct radiometrically and atmospheric these by means of the Atcor extension 2. Workstation of the Erdas Imagine program, to ensure a standardized comparison of data between them (Chander et al., 2009; Vargas-Sanabria and Campos-Vargas, 2018); c) determine the training areas where eight study categories corresponding to land cover were established: body of water, urban area, forest area, temporary agriculture, permanent agriculture, crasicaule scrubland, secondary vegetation and area without apparent vegetation (Velázquez et al., 2002); d) apply the Maximum Likelihood supervised classification algorithm to each image, in the ArcMap 10.5 software (Vargas-Sanabria and Campos-Vargas, 2018); and e) validate the classification of plant cover and land use for 1992 and 2000; through its comparison against the layers of land and vegetation use of the INEGI series II and III, respectively.
While to validate the coverage of 2017, this was done by establishing control points within the study area, using Google Earth® (Earth Google, 2018) and field trips to these points, with the purpose of corroborating the type of coverage corresponding to the training site (Torres et al., 2018). The pixel size of each of the land use maps was then homogenized at 30 m: 1992, 2000 and 2017 and reclassified based on the hierarchical system proposed by Velázquez et al. (2002) (Table 1) to achieve a hierarchical and homogeneous classification system.
Number |
Class |
Type of vegetation and land use |
1 |
Water body |
|
2 |
Urban zone |
|
3 |
Forest area (low, medium and high density) and secondary vegetation |
|
4 |
Temporary and permanent agriculture |
|
5 |
Area without apparent vegetation (scrubland, mines, eroded areas) |
CA= body of water; ZU= urban area; AF= forest area; AA= agricultural area; ASVA= area without apparent vegetation.
Transition matrix construction
For the stage of analysis of patterns of change of land cover and land use, matrices of transition matrices were constructed, which are described as tables with symmetrical arrangements that contain in the rows the types of vegetation and land uses in the first year or year base and in the columns these same types but of the second year. Each cell of the main diagonal of said matrix represents the area in hectares of each kind of vegetation cover and land use that remained in the same category during the period considered, while in the rest of the cells the surface area of a given coverage or type of land use that passed to another category (Dirzo and Masera, 1996 cited by López et al., 2001) which allows to understand the dynamics of change in land cover and land use at local and regional level.
From the shapefile maps obtained from the reclassification of vegetation cover and land use of 1992, 2000 and 2017, the transition matrices were constructed, performing the following steps: a) generate transition matrices between the different categories through a cross tabulation (Eastman, 2012), from the TerrSet Crosstab module, for the periods: 1992-2000 and 2000-2017; b) develop probability of belonging matrices for each class in each period with the transition matrices; these matrices are generated by dividing each of the cells of the transition matrix by the total surface area of the analyzed class (Vega et al., 2007); and c) estimate the probability of belonging
Where:
According to Sánchez et al. (2004), the probability of belonging is interpreted as follows: 0-33% (low), 34-66% (medium) and 67-100% (high).
Exchange rates
The processes of land use change are determined with the map resulting from the cross-tabulation and are classified: unchanged, conserved, urbanization, transition, anthropic use, deforested, degraded and by productive activity (Rosete et al., 2008; Cuevas et al., 2011). These were estimated using the equation proposed by (FAO, 1996):
Where:
Results and discussion
Table 2 shows the results obtained from land use areas by category, for each of the years: 1992, 2000 and 2017. Of the 103 766.48 hectares that make up the total area under study, in 1992, the use of land was mainly dominated by the forest and agricultural area, with about 80%, while the remaining area was occupied by bodies of water, urban areas and areas without apparent vegetation, with about 20%. However, from the year 2000 with respect to the year 1992, the forest area significantly decreased its area, by about 55%, in contrast the agricultural area increased by approximately 84%.
Class |
1992 |
|
2000 |
|
2017 |
|
1992-2017 |
||||
ha |
(%) |
|
ha |
(%) |
|
ha |
(%) |
|
ha |
(%) |
|
652.48 |
0.6 |
|
472.95 |
0.5 |
|
722.36 |
0.7 |
|
+68.88 |
+0.1 |
|
6 244.63 |
6 |
|
6 638.49 |
6.4 |
|
5 911.49 |
5.7 |
|
-334.14 |
-0.3 |
|
46 339.27 |
44.7 |
|
21 023.28 |
20.3 |
|
23 261.82 |
22.4 |
|
-23 077.95 |
-22.2 |
|
35 793.97 |
34.5 |
|
66 102.39 |
63.7 |
|
70 433.61 |
67.9 |
|
+34 639.14 |
+33.4 |
|
14 736.13 |
14.2 |
|
9 528.66 |
9.2 |
|
3 436.49 |
3.3 |
|
-11 300.64 |
-10.9 |
|
Total |
103 766.48 |
100 |
|
103 766.77 |
100.1 |
|
103 766.77 |
100 |
|
|
|
CA= body of water; ZU= urban area; AF= forest area; AA= agricultural area; ASVA= area without apparent vegetation.
The rest of the surface was reduced by 25%. Deforestation was mainly due to the absence of laws regulating forest use at any level of government and the lack of policies to reforest and restore degraded forest areas (PEF, 1989; PEF, 1995; Merino-Pérez and Segura-Wamholtz, 2002). Finally, the change in land use in 2017 with respect to 2000, the agricultural area increased the same as in the previous period, only now in 7%, this trend coincides with that set forth by Cuevas et al. (2011), who mention that agriculture is the activity that incorporates more hectares. Regarding the forest area, it presented an increase of 2%, but the area without apparent vegetation decreased 178%.
The forest increase is due to the fact that from the 2000-2006 six-year period, modifications were made, starting with the decentralization of the National Forestry Commission (CONAFOR) in 2001, which promoted reforestation programs; in addition, in 2003, the Law on Sustainable Forest Development (SEMARNAT, 2003; Del Angel-Mobarak, 2012) entered into application. Likewise, the largest increase in the reforested area occurred in the territory of the state of Hidalgo, due on the one hand, the implementation of state policies, among which the Law on Sustainable Forest Development for Hidalgo, which entered into application in 2006 and decree protected natural areas of state competition, such as the state reserve Cerros La Paila-El Xihuingo, in 2009, located within the Tula microbasin, on the other, the multiple annual reforestations carried out in this state (SADR, 2005; GEH, 2006) .
Additionally, in Table 2, it also shows the exchange rate both in hectares and in percentage by type of vegetation cover, for the period 1992-2017. In other words, the classes: forest area, urban area and area without vegetation decreased by 23 077.95, 334.14 and 11 300.64 hectares, equivalent to 22.2, 0.3 and 10.9%, respectively. Meanwhile, agricultural area and bodies of water increased by 34 639.14 and 68.88 hectares, equivalent to 33.4 and 0.1%, respectively.
Transitions of land use change
Table 3 and Figure 2 show the results obtained from the transition matrices and the probabilities of membership between categories, for the period from 1992 to 2000. The 54%
Surface (ha) |
|
2000 |
|||||
1992 |
|
Total |
|||||
|
416.57 |
37.49 |
36.77 |
124.61 |
37.04 |
652.48 |
|
|
9.86 |
2 499.89 |
386.33 |
2 361.74 |
986.81 |
6 244.63 |
|
|
18.14 |
1 962.05 |
17 271.5 |
23 950.4 |
3 137.18 |
46 339.27 |
|
|
7.88 |
936.05 |
1 213.07 |
31 781.21 |
1 855.76 |
35 793.97 |
|
|
16.88 |
1 199.84 |
2 117.57 |
7 891.88 |
3 509.96 |
14 736.13 |
|
Total |
|
469.33 |
6 635.32 |
21 025.24 |
66 109.84 |
9 526.75 |
103 766.48 |
CA= body of water; ZU= urban area; AF= forest area; AA= agricultural area; ASVA= area without apparent vegetation.
In contrast, the forest area was the coverage that had the greatest change in surface area with 63% and only retained 37% of it. It should be noted that 52%
It is also important to mention that 4% of the forest area changed to urban area
38%
Surface (ha) |
|
2017 layer |
|||||
2000 |
|
CA | ZU | AF | AA | ASVA | Total |
CA |
|
367.42 |
20.74 |
46.02 |
30.09 |
8.68 |
472.95 |
ZU |
|
30.46 |
2 739.1 |
695.91 |
3 041.85 |
131.17 |
6 638.49 |
AF |
|
24.16 |
292.36 |
16 253.85 |
3 660.42 |
792.49 |
21 023.28 |
AA |
|
256.36 |
1 906.24 |
4057.5 |
58 269.63 |
1 612.66 |
66 102.39 |
ASVA |
|
43.96 |
953.05 |
2 208.54 |
5431.62 |
891.49 |
9 528.66 |
Total |
|
722.36 |
5 911.49 |
23 261.82 |
70 433.61 |
3 436.49 |
103 766.48 |
CA= body of water; ZU= urban area; AF= forest area; AA= agricultural area; ASVA= area without apparent vegetation.
According to the classification of Sánchez et al. (2003), the categories: body of water
It should be noted that the agricultural area increased 83%
As already mentioned, urban areas obtained an average probability of permanence, attributed primarily by the increase of the population in the microbasin, this being around 149%
The increase in the population results in a greater demand for land to meet the productive and consumption needs of the population (Cuevas et al., 2011; García et al., 2012; Torres et al., 2018).
Exchange rates
Table 5 indicates that the rates of land use change in the 1992-2000 period are higher than those recorded in the 2000-2017 period. In the case of the forestry area, it presents a negative rate for the period of 1992-2000 and positive for the period 2000-2017, which coincides with some studies carried out in Mexico, in similar periods (Velázquez et al., 2002; García-Barrios et al., 2009; CONAFOR-UACH, 2013). However, the result obtained by FAO (2010) is greater than 4%. Areas without apparent vegetation have a positive exchange rate that is maintained in both periods, indicating that the eroded areas used as a mine continue to exist.
Class |
Change (ha) |
|
Change (%) |
|
Exchange rate |
|||
1992-2000 |
2000-2017 |
|
1992-2000 |
2000-2017 |
|
1992-2000 |
2000-2017 |
|
CA | -179.53 |
249.41 |
|
-0.17 |
0.24 |
|
0.04 |
-0.03 |
ZU | 393.86 |
-727 |
|
0.38 |
-0.7 |
|
-0.01 |
0.01 |
AF | -25 315.99 |
2 238.54 |
|
-24.4 |
2.16 |
|
0.09 |
-0.01 |
AA | 30 308.42 |
4 331.22 |
|
29.21 |
4.17 |
|
-0.08 |
0 |
ASVA | -5 207.47 |
-6 092.17 |
|
-5.02 |
-5.87 |
|
0.05 |
0.06 |
CA= body of water; ZU= urban area; AF= forest area; AA= agricultural area; ASVA= area without apparent vegetation.
The agricultural area in the first period had a positive exchange rate that goes hand in hand with the exchange rate of urban areas, this is because the population needs goods to meet their needs. During the second period, the area of bodies of water had an increase of 24%, which is related to the increase in the agricultural area, because it increases more water, which leads the population to build more jagüeyes to retain or capture rainwater.
With respect to the 1992-2000 period, shows the processes of change of the total area that occurred in the microbasin: 37% (38 667.76 ha) did not change, 28% was deforested mainly for agricultural use purposes, which coincides with exposed by SEMARNAT (2002) in the study carried out in the period 1993-2000 at national level (Rosete et al., 2008; FAO, 2010).
Conclusions
The Tula microbasin has presented significant changes in its land use, in the 1992-2000 period, the coverage with the greatest change was the forest area with 63%, 52% of the forest area passed to agricultural area, in addition the population increased 14%, which indicates that deforestation occurred mainly due to the need to produce goods to meet the needs of the population, and because there were no public policies to regulate the use of forest resources. During the 2000-2017 period, the forest area only decreased 6%, due to the implementation of federal public policies and the state policies of the state of Hidalgo, which contributed to counteract deforestation and recover abandoned areas. The trend of land use in the microbasin is that most of the area remains unchanged, existing agricultural areas are maintained and continue to increase until they are abandoned due to their decline in productivity and invaded by urban areas, which will increase due to population growth.
Literatura citada
Bautista, Z. F.; Palacio, P. J. L.; Delfín, G. H.; Páez, B. R.; Carmona, J. E. y Delgado, C. M. del C. 2011. Técnicas de muestreo para manejadores de recursos naturales. Universidad Autónoma de México. Segunda (Ed.). México, DF. 770 p. [ Links ]
Chander, G.; Markham, B. L. and Helder, D. L. 2009. Summary of curret radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment. 5(113):893-903. [ Links ]
CONAFOR-UACH. 2013. Comisión Nacional Forestal- Universidad Autónoma Chapingo. Línea base nacional de degradación de tierras y desertificación. Gómez, D. J. D.; Monterroso, R. A. I.; Lechuga, G. L. M.; Hernández, V. C. C. (Eds.). Comisión Nacional Forestal. Zapopan, Jalisco, México. 160 p. [ Links ]
Cruz, I. C. 2018. Políticas públicas y migración de retorno desde Estados Unidos: el caso de los municipios metropolitanos hidalguenses. Tlamelaua Rev. Cienc. Soc. 45(12):208-238. [ Links ]
Cuevas, M. L.; Garrido, A.; Pérez, D. J. y Iura, G. D. 2011. Procesos de cambio de uso de suelo y degradación de la vegetación natural. In: las cuencas hidrográficas de México. Diagnóstico y priorización. Cotler, A. H. (Coord.). Pluralia Ediciones e Impresiones SA de CV, México. 96-103 pp. [ Links ]
Del Ángel-Mobarak, G. A. 2012. El medio forestal de México. In: La Comisión Nacional Forestal en la historia y el futuro de la política forestal de México. Centro de investigación y docencia económicas-Comisión Nacional Forestal. México. 35-80 pp. [ Links ]
Earth-Google. 2018. Google Earth 7.3.2. https://www.google.com/intl/es-419/earth7. [ Links ]
Eastman, J. R. 2012. TerrSet Geospatial onitoring and modeling system manual. Clark labs. Worcester, USA. 393 p. [ Links ]
FAO. 1996. Food and Agriculture Organization of the United Nations. Forest resources assessment 1990: survey of tropical forest cover and study of change processes. Food and Agriculture Organization of the United Nations. Rome. FAO forestry paper. 130. 152 p. [ Links ]
FAO. 2010. Organización de las Naciones Unidas para la Agricultura y la Alimentación. Evaluación de los recursos forestales mundiales 2010. Estudio FAO: Roma. 346 p. [ Links ]
FAO. 2016. Organización de las Naciones Unidas para la Agricultura y la Alimentación. Evaluación de los recursos forestales mundiales 2015, ¿Cómo están cambiando los bosques del mundo? FAO. Segunda edición. Roma. 44 p. [ Links ]
García, O. J. A.; Cedillo, G. J. G.; Juan, P. J. I. y Balderas, P. Á. M. 2012. Procesos de cambio en el uso del suelo de una microcuenca en el altiplano mexicano. El caso del río San José en el Estado de México. España. Papeles de Geografía. 55-56(1):63-73. [ Links ]
García-Barrios, L.; Galván-Miyoshi, Y. M.; Valsieso-Pérez, I. A.; Masera, O. R.; Bocco, G. and Vandermeer, J. 2009. Neotropical forest conservation, agricultural intensification, and rural out-migration: the mexican experience. BioScience. 10(59):863-873. [ Links ]
GEH. 2006. Gobierno del estado de Hidalgo. Ley de Desarrollo Forestal Sustentable para el Estado de Hidalgo. Instituto de Estudios Legislativos. Segunda edición. México. 51 p. [ Links ]
INEGI. 1970. Instituto Nacional de Estadística y Geografía. IX Censo general de población 1970. https://www.inegi.org.mx/programas/ccpv/1970/default.html#Publicaciones. [ Links ]
INEGI. 1990. Instituto Nacional de Estadística y Geografía. XI Censo general de población y vivienda 1990. https://www.inegi.org.mx/programas/ccpv/1990/. [ Links ]
INEGI. 2000. Instituto Nacional de Estadística y Geografía. XII Censo general de población y vivienda 2010. https://www.inegi.org.mx/programas/ccpv/2000/. [ Links ]
INEGI. 2013. Instituto Nacional de Estadística y Geografía. Censo de población y vivienda 2010. [ Links ]
INEGI. 2017a. Instituto Nacional de Estadística y Geografía. Anuario estadístico y geográfico de Hidalgo 2017. Instituto Nacional de Estadística y Geografía. México. 671 p. https://www. datatur.Sector.gob.mx/ITxEF-Docs/HGO-ANUARIO-PDF.pdf. [ Links ]
INEGI. 2017b. Instituto Nacional de Estadística y Geografía. Anuario estadístico y geográfico de México 2017. Instituto Nacional de Estadística y Geografía. México. https://www.inegi.org.mx/app/biblioteca/ficha.html?upc=702825097912. [ Links ]
INEGI. 2017c. Instituto Nacional de Estadística y Geografía. Anuario estadístico y geográfico de Tlaxcala 2017. Instituto Nacional de Estadística y Geografía. México. https://www.datatur. sectur.gob.mx/ITxEF-Docs/TLAX-ANUARIO-PDF.pdf. [ Links ]
INEGI. 2017d. Instituto Nacional de Estadística y Geografía. Conjunto de datos vectoriales de uso de suelo y vegetación. Escala 1:250000. Serie VI. Instituto Nacional de Estadística y Geografía. México. https://www.inegi.org.mx/app/mapas/default.html?t=0150011 000000000&ag=00. [ Links ]
Leija-Loredo, E. G.; Pavón, N. P.; Sánchez-González, A.; Rodríguez-Laguna, R. and Ángeles-Pérez, G. 2018. Land cover change and carbon stores in a tropical montane cloud forest in the Sierra Madre Oriental, Mexico. J. Mountain Sci. 10(15):2136-2147. https://doi.org/10.1007/s11629-018-4937-y. [ Links ]
López, G. E. M.; Bocco, G. y Mendoza, C. M. E. 2001. Predicción del cambio de cobertura y uso del suelo. El caso de la ciudad de Morelia. Investigaciones Geográficas, Boletín del Instituto de Geografía-Universidad Nacional Autónoma de México (UNAM). 45(1):56-76. [ Links ]
Merino-Pérez, L. y Segura-Wamholtz, G. 2002. Las políticas forestales y de conservación y sus impactos en las comunidades forestales en México. In: los bosques comunitarios de México: manejo sustentable de paisajes forestales. Bray, D.; Merino, L. y Barry, D. (Eds.). UNAM. México, DF. 77-98 pp. [ Links ]
PEF. 1989. Poder Ejecutivo Federal. Plan Nacional de Desarrollo 1984-1994. Diario Oficial de la Federación. México. 78 p. http://www.diputados.gob.mx/LeyesBiblio/compila/pnd/PND-1989-1994-31may89.pdf. [ Links ]
PEF. 1995. Poder Ejecutivo Federal. Plan Nacional de Desarrollo 1995-2000. Diario Oficial de la Federación. México. http://www.diputados.gob.mx/LeyesBiblio/compila/pnd.htm. [ Links ]
Reynoso, S. R.; Valdez, L. J. R.; Escalona, M. M. J. y De los Santos, P. H. M. 2015. Análisis de la dinámica del uso del suelo de la cuenca Metztitlán en Hidalgo, México. Ingeniería Hidráulica y Ambiental. 3(36):102-111. [ Links ]
Rosete, V. F. A.; Pérez, D. J. L. y Bocco, G. 2008. Cambio de uso del suelo y vegetación en la Península de Baja California, México. Investigaciones geográficas. 67(1):39-58. [ Links ]
Rosete-Vergés, F.; Pérez-Damián, J. L.; Villalobos-Delgado, M.; Navarro-Salas, E. N.; Salinas-Chávez, E. y Remond-Noa, R. 2014. El avance de la deforestación en México 1976-2007. Madera y Bosques. 1(20):21-35. http://www.scielo.org.mx/pdf/mb/v20n1/v20n1a3.pdf. [ Links ]
SADR. 2005. Secretaría de Agricultura y Desarrollo Rural. Programa estatal de silvicultura sustentable 2005-2011. Gobierno del Estado de Hidalgo. Hidalgo, México. http://intranet.ehidalgo.gob.mx/NormatecaE/Archivos/Programa-Silvicultura Sustentable.pdf. [ Links ]
Sahagún-Sánchez, F. J. y Reyes-Hernández, H. 2018. Impactos por cambio de uso de suelo en las áreas naturales protegidas de la región central de la Sierra Madre Oriental, México. CienciaUAT. 2(12):6-21. http://www.scielo.org.mx/scielo.php?script=sci-arttext&pid=S2007-78582018000100006. [ Links ]
Sánchez, C. S.; Flores, M. A.; Cruz-Leyva, I. A. y Velázquez, A. 2009. Estado y transformación de los ecosistemas terrestres por causas humanas. In: capital natural de México. Sarukhán, J. (Coord.). Comisión Nacional para el Conocimiento y Uso de la Biodiversidad (CONABIO). México. 34 p. [ Links ]
Sánchez, J.; Bocco, G.; Fuentes, J. y Velázquez, A. 2004. Análisis de cobertura y uso del terreno en el contexto de su dinámica espacio-temporal. In: las enseñanzas de San Juan: investigación participativa para el manejo integral de recursos naturales. Velázquez, A.; Torres, A. y Bocco, G. (Comps). Secretaría de Medio Ambiente y Recursos Naturales. Instituto Nacional de Ecología. México. 235-256 pp. [ Links ]
SEMARNAT. 2002. Secretaría de Medio Ambiente y Recursos Naturales. Compendio de estadísticas ambientales. Dirección General de Estadifica e Información Ambiental. México. 275 p. http://www.paot.org.mx/centro/ine-semarnat/informe02/estadisticas-2000/Presentacion/index.htm. [ Links ]
SEMARNAT. 2003. Secretaría de Medio Ambiente y Recursos Naturales. Ley General de Desarrollo Forestal Sustentable. Cámara de Diputados del H. Consejo de la Unión. México. 69 p. http://www.diputados.gob.mx/LeyesBiblio/pdf/LGDFS-050618.pdf. [ Links ]
Torres, B. M.; Favela, L. S.; Alanís, F. G. y González, R. J. I. 2018. Dinámica de uso de suelo en una Región Hidrológica Prioritaria de la cuenca Río Bravo, Nuevo León. Rev. Mex. Cienc. Forest. 46(9):54-79. https://doi.org/10.29298/rmcf.v9i46.136. [ Links ]
Vargas-Sanabria, D. y Campos-Vargas, C. 2018. Sistema multi-algoritmo para la clasificación de coberturas de la tierra en el bosque seco tropical del Área de Conservación Guanacaste, Costa Rica. Rev. Tecnología en Marcha. 1(31):58-69. [ Links ]
Vega, C. R.; Ruiz, C. J.; Linares, F. G.; Pérez, A. R. y Tamariz, F. V. 2007. Dinámica de cambio espacio-temporal de uso del suelo de la subcuenca del río San Marcos, Puebla, México. Investigaciones Geográficas. 64(1):75-89. [ Links ]
Velázquez, A.; Mas, J. F.; Díaz, Gallegos, J.; Mayorga, S. R.; Alcántara, P. C.; Castro, R.; Fernández, T.; Bocco, G.; Ezcurra, E. y Palacio, J. L. 2002. Patrones y tasas de cambio de uso del suelo en México. México. Gaceta Ecológica. 62(1):21-37. [ Links ]
Xiao, J.; Shen, Y.; Ge, J.; Tateishi, R.; Tang, C.; Liang, Y. and Huang, Z. 2006. Evaluating urban expansion and land use change in Shijiazhuang, China, by using GIS and remote sensing. Landscape and Urban Planning. 1-2(75):69-80. https://doi.org/10.1016/j.landurbplan.2004.12.005. [ Links ]
Received: December 01, 2019; Accepted: February 01, 2020