nr. XII, GEOGRAPHIA NAPOCENSIS Angeographianapocensis.acad-cluj.ro/Revista/volume/nr_1... · 2018....

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ACADEMIA ROMÂNĂ – FILIALA CLUJ-NAPOCACOLECTIVUL DE GEOGRAFIE

GEOGRAPHIA NAPOCENSIS

An XII, nr. 1

2018

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Mădălin-SebaStian lung, gabriela-alina Mureşan

EDITORIAL BOARD OF GEOGRPAPHIA NAPOCENSIS

Editor-in-Chief

Pompei COCEAN – Romanian Academy, Cluj-Napoca Subsidiary, Geography Section

Editorial Board

Dan BĂLTEANU – Romanian Academy, Institut of Geography, BucureştiPhillipe BACHIMON –Avignon University, FranceGyula HORVÀTH – Centre for Regional Studies, Hungarian Academy of SciencePeter JORDAN – Institut of Geography, Viena, Austria.Erhard SCHULZ - University of Würzburg, Würzburg, GermanyNemes-NAGY JÓZSEF - Lorand University, Budapest, HungaryAlexandru UNGUREANU – ,,Al.I.Cuza” University, Faculty of Geography and Geology, Iaşi,Nicolae CIANGĂ – Babeş-Bolyai University, Faculty of Geography.Ioan IANOŞ – Bucureşti University, Faculty of GeographyŞtefan BILAŞCO – Babeş–Bolyai University, Faculty of GeographyValerio BAIOCCHI - La Sapienza University, Roma, ItalyGabriela COCEAN – Romanian Academy, Cluj-Napoca Subsidiary, Geography Section

Executive Editors

CS III.dr. Ştefan BILAŞCO – Romanian Academy, Cluj-Napoca Subsidiary, Geography SectionCS III.dr. Gabriela COCEAN – Romanian Academy, Cluj-Napoca Subsidiary, Geography Section

geographianapocensis.acad-cluj.ro

ISSN 1843-5920ISSN online 1844-9840

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Geographia Napocensis Anul XII, nr. 1, 2018

THE MONITORING OF FOREST COVERAGE CHANGES ACCORDING TO THE REMOTE SENSING INDICES IN THE THE

MOCIAR FOREST

marCeL mîNdru1 Sanda roșca2, ștefan bilașco2,3, ioan Păcurar1, ioan fodorean2,iuLiu VeSCaN2, dănuț Petrea2, Mihai breje2

Abstract: - The monitoring of forest coverage changes according to the remote sensing indices in the the Mociar Forest. The development level of the Mociar Forest between 1986 and 2016 was measured using remote sensing techniques, by developing geographical tests based on the NDVI value, during distinctive timeframes backed up by LANDSAT satellite images that cover the specific timeframe of analysis. This under-lined the changes occurred in the forest lots of the Mociar Forest, changes related to the anthropic influence, the distress caused by the climate variations (temperature, rainfall) and also due to the edaphic factors (excess of soil humidity, variations of nutrient levels). In order to identify the impact of the climate factors, especially the rainfall levels pertaining to the analyzed timeframe, the value of the Angot index number was established, which enabled the monthly framing according to the specific rainfall class. This helped pinpoint the forest areas where the drying of the forest vegetation has extended, the result being useful in the monitoring process of the Mociar Forest.. Key-Words: NDVI, land-use changes, Mociar Forest

1Department of Soil Sciences and Technical Sciences, University of Agricultural Sciences and Veterinary Medicine, Ro-mania; [email protected] of Physical and Technical Geography, Faculty of Geography, Babeș Bolyai University, Clinicilor Street, 400006, Cluj-Napoca, Romania; [email protected] [email protected], [email protected], [email protected] Romanian Academy Romanian Academy, Cluj-Napoca Subsidiary Geography Section, 9 Republicii Street, 400015 Cluj-Napoca, Romania; [email protected]

1 Introduction

The long term monitoring of the evolution of the forest areas enables the evaluation of their development stage and, based on the results, con-clusions and hypothesis can be formulated regard-ing the health condition of the forest and also the possible deficiencies regarding the intervention at production unit level and the experimental lots.

Out of the direct monitoring methods, based on indirect measurements, the remote sens-ing techniques are the main instruments that, by means of satellite images of medium resolution and their integration with the help of remote sens-ing indices, enable the tracking and the integrated monitoring of the wooded areas (health condition, development capacity, timber decrease).

The main request regarding the use of these techniques is that the satellite images (with an

8 or 11 strip structure) are acquired during the maximum vegetation timeframe for each species pertaining to the studied area and also the ana-lyzed area of the image must not be obscured by cloud formations.

The monitoring of the Mociar Forest area was performed between 1986 and 2016, its main goal being the identification of the areas with different stages of greenery development, based on the spectral bands of the LANDSAT satellite images available free of charge, integrated in the analysis based on the NDVI index. This in-dex has been successfully used in previous stud-ies regarding the identification of the vegetation coverage level in different areas (Anderson et al., 2004, Amiri et al., 2009, Chakraborthy and Se-hgal, 2010, Sruthi and Mohammed Aslam, 2015, Roșca, 2017), parameter which varies wih the annual average temperature of the studied area

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Marcel Mîndru, Sanda roșca, ștefan Bilașco, ioan Păcurar, ioan fodorean, iuliu VeScan,dănuț Petrea, Mihai Breje

and with the general tendency of temperature growth at global level due to the global worming (Zhou et al.., 2001, Anderson et. al., 2004, Bunn et al., 2005, Amiri et al., 2009, Chakraborthy and Sehgal, 2010, Meng et al., 2011, Sruthi and Mo-hammed Aslam, 2015).

2 Study area

The Mociar Forest, located in Mures Coun-ty, is a protected natural area (Natura 2000), which implies the long term assurance of the sur-vival of some of the most valuable species and European habitats which are endangered at the moment (Dacian oak and hornbeam forests with key species of Carpinus betulus and various spe-

cies of Quercus (robur, petraea, cerris, frainetto etc), Tilia tomentosa, Cortinus coggygria, Fes-tuca heterophylla, Ranunculus auricomus, Hel-leborusodorus etc.). The forest pertains to the Gurghiu Forest District, Mures County Forestry Department, with a total surface of the production unit of 2318,1 ha (Mândru et. al., 2017) (Fig. 1).

The forest vegetation outside the national forestry areas is represented by clumps of trees or isolated trees, the alderies situated along the Gurghiu River waterside, and also the tree align-ments found along the roads. Their acreage is esti-mated around 5.0 ha. From the perspective of the Mociar Forest management, the lots pertaining to the Natural Park, therefore the protected area, are distinguished among the total of 246.67 ha.

Fig. 1 The geographical location of the Mociar Forest

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The monitoring of ,forest coverage changes according to the remote sensing indices in the the mociar forest

3. Methodology and Results

The main database used in the analysis is represented by the LANDSAT images, download-ed free of charge from the online portal https://earthexplorer.usgs.gov/, images which were ob-tained during different missions of the LANDSAT program: mission 5, 7 and 8 (Table 1).

The governing principle of this study is the apriori knowledge of the spectral response of each use class of soil and the identification with the help of specialized software of those classes for the studied area. NDVI is basically a stand-ardized instrument of measuring the healthy veg-etation. (DeFries, Townshend, 1994, Wilson et al., 2002, Wang et al., 2005).

Normalized Difference Vegetation Index (NDVI) was obtained by using the formula:

Where: NDVI - Normalized Difference Vegetation Index

NIR - near-infraredRed – Red band

The degree of vegetation coverage, iden-tified with the help of the NDVI index, was cal-culated using the ratio between the difference and the sum of the spectral signatures found at the visible limit (Red) and near-infrared (NIR)

bands. Knowing that healthy vegetation (chloro-phyll) reflects closer to infrared and green light, compared to other wavelengths, and absorbs more red and blue light, we can easily determine the vegetation areas and especially the forest vegetation areas.

The results obtained the formula described above have been classified in 5 categories, ac-

cording to the spectral response of each spectral band analyzed based on the NDVI index for each year of study: < 0.1 – uncovered land; 0.1-0.2 - pasture; 0.2-0.3 – shrubbery; 0.3-0.6 – dense vegetation; > 6 – dense forest vegetation (Fig. 2,3,4,5).

The starting point is therefore the concept that the diminution of the NDIV index value is related to a negative change in the vegetation coverage level (in this case, determined by the drying of the species of trees or by their ex-ploitation).

The analysis of the quantitative values ob-tained by recording and processing the NDIV index database highlights the 0.3-0.6 class (dense vegetation) present on a very large ge-ographical area during all the timeframes taken into account. The variation of this interval on the analyzed time scale pinpoints to a qualita-tive improvement of the shrubbery layer can-opy with small fluctuations during the 1990-1994 timeframe (Fig. 2, Fig.3) and a substantial growth after 2005.

Table 1 Databases used in the analysis

Imagine data Mision Resolution Cloud Cover/Imagine

Cloud Cover/study area

BandRED NIR

18. 09. 1986 LANDSAT 5 30 0 0 Band 3 Band 428.08. 1990 LANDSAT 5 30 6 0,05 Band 3 Band 408.09. 1994 LANDSAT 5 30 0 0 Band 3 Band 427.05. 2000 LANDSAT 7 30 13 0 Band 3 Band 426.06. 2005 LANDSAT 7 30 4 0,12 Band 3 Band 412.06. 2010 LANDSAT 7 30 7 0 Band 3 Band 402.09. 2015 LANDSAT 8 30 1,02 0 Band 4 Band 509.09. 2016 LANDSAT 8 30 12,64 0 Band 4 Band 5

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Fig. 2 NDVI index at 1986 level (left) and 1990 (right)




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A main cause for the decrease mentioned above could be the lack of rain, this timeframe being classified as extremely dry (Roșca, 2015), with very droughty months leading to and during the growing season. (Table 3).

The NDVI analysis of the shrubbery quality marks out the forest state regarding the water - vegetation development relationship, by observing this aspect during the course of 2005, a highly rainy year (Roșca, 2015), associated with a geographical expansion (1117.53 ha) of the class (>6), which corresponds to dense forest vegetation.

The 0-0.3 categories have a small geograph-ical extent, considering that the entire area is a shrubbery plantation which pertains to the >0.3 category, the inferior categories being represent-ed by the areas where the canopy is dry or areas dominated by fellings or lack of forest vegetation.

The analysis of the qualitative changes of the shrubbery layer canopy was based on com-paring the NDVI index values from previous years. The first comparison focused on the first year of the studied timeframe and the year 2016,

which revealed a significant decrease in the can-opy layer in the entire Mociar Forest area.

The Quercus drying is a complex disease, which affects large European areas and is espe-cially noted in various degrees in areas of France,

Germany, the United Kingdom, Poland and other (Șimonca and Taut, 2010). In Romania, this phe-nomenon has been identified for the following timeframes: 1910-1914, 1937-1943, 1955-1961 (Haring et al., 1984, Marcu, 1966). Across Mures County, the drying of the holm was observed on a 4886 ha area and the drying of the oak was ex-tended to a 1650 ha surface (Șimonca and Tăut,

2010). The causes of this complex slow or fast drying process are various and could be linked to the vascular plants from the Ophiobolus genus (Ceratocystis), or the C. fagacearum (Șimonca and Tăut, 2010), C. roboris, O. valachica and Ceratostomella querci, C.querci, Ophiostoma (Cerat.) roboris and C.piceae species (Alexe, 1986, Marcu, 1985, Petrescu, 1984).

As far as the MociarForst is concerned, two problem sources have been identified: the green oak moth (Tortrix viridana), which affects the

Table 2 The evolution of the identified groups between 1986–2016

NDVI Value

Area (ha)1986 1990 1994 2000 2005 2010 2015 2016

< 0 0 0 0 102.51 5.94 8.46 0 00 - 0.1 117.27 42.48 0.27 52.56 8.55 5.4 0.54 0.72

0.1 - 0.2 210.06 616.23 8.82 216.09 9 15.3 5.22 3.240.2 - 0.3 563.67 731.07 73.08 519.93 17.01 251.64 522.81 36.090.3 - 0.58 2118.15 1619.37 1591.02 2117.07 1799.55 2637.99 2463.3 2972.52

>0.6 0 0 1335.96 0 1117.53 84.6 0 0

Table 3 The monthly rainfall feature according to the Angot index

K lunar

Winter Spring Summer AutumnXII I II III IV V VI VII VIII IX X XI

1994 FS FS FS FS S P FS FS N FS S FS2000 FS FS FS FS FS FS FS FP FS FS FS FS2005 N S S S P FP P FP FP N FS S2010 N S S P N S P N S S S FS

(where: N-normal, S-dry, FS-very dry, P-rainy, FP-very rainy)

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leaves of the oak and the great capricorn beetle (Cerambix cerdo), which gnaws galleries in the trunk of the oak (Varga et al., 2014).

From the spacial point of view, a pro-nounced decrease in the canopy quality can be observed in the Western and South-Western side of the area (Fig. 6), geographically identified across the 1, 3, 9, 10, 17-19 forest lots, and also in the far Eastern side of the areal, in the 78, 79, 89 forest lots.

The detailed analysis of the comparison re-sults outlines an improvement in the quality of the canopy across all the experimental lots per-taining to the Mociar Forest. The 25D and 25E lots registered a maximum rate of improvement, a fact sustained by the on-site observations, thus leading to a high rate of precision of the NDVI index - based analysis.

4. Conclusion

The monitoring of the vegetation cover-age in the Mociar Forest area was done by us-ing remote sensing indices applied with the aid of professional geoinformation software, which bore the identification of the NDVI index value pertaining to the 1986-2016 timeframe.

The obtained data was further filled in by on site acquired information, which was then processed by professional software, thus regis-

tering information about the vegetation; this was used to define the overall perspective of the sta-tion and the brush and to regulate the forest pro-duction process. The types of forest stations and the types of forests belonging to the studied area were established based on the data regarding the vegetation and the soil characteristics.

6 types of stations were defined, the most common being: 7.3.3.1. (hillocky quercus with oak, Bi, strong pseudogleypodzol, mild edaph-ic), which covers 56% of the surface of the station, followed by the 7.3.3.2. lot (hillocky quercus with oak, Bm, pseudogleypodzol, with Poapratensis – Carexcaryophyllea), dispersed on 33% of the surface. The low solvency station bal-ance (56% of the station surface) indicates that the forest vegetation has poor development con-ditions in its geophysical areal.

The high solvency stations (3% of the stud-ied area) have no limiting factors with strong cu-mulating actions, so they do not require special management measures. In these brush areas, all the forest work can be conducted on an appropri-ate scale, considering the current state of the brush.

Fig. 7. Comparison of experimen-tal parcels

Fig. 6 Comparative analysis 2016-1986 based on the NDVI index

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In the mild solvency areas (41% of the stations found in the U.P. X Mociar), there are a number of factors with negative cumulated ac-tion: the lower edaphic volume, the stagnation of water and the formation of marshes (which blocks the normal development of the tree roots), the sun exposure (which favors the evapotranspi-ration) etc. The existing brush in this category of stations require a greater attention regarding the type and the intensity of the appropriate work, keeping in mind the natural regeneration of the forest, ensuring a consistency which will not permit the excessive grass growth and also the correct performance of the necessary technical forest work.

In the production unit area (for 56% of the surface), by the cummulation of various geomor-phological, edaphic and climatic factors (exces-sive humidity, very low edaphic volume, lower percentage of nutrients, grass growth, local de-pasturage, etc.), the existence of the lower sol-vency stations was identified. In their case, it is imperative to adopt certain management actions, according to the intended targets: ensuring the integrity and continuity of the forest vegetation, the growth of the resistance to drying and to the action of phytopathogen agents, the fulfillment of the attributed functions etc.

The work will be carried out with extreme care, in correlation with the evolution of the regen-eration requirements, with well justified intensity, so that the soil can be quickly and well covered, with as little brush thinning as possible. For af-forestation and replenishment it is recommended to use local condition resistant species, which can best fulfill the predetermined objectives.

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