Land Use/Land Cover Assessment over Time Using a New Weighted Environmental Index (WEI) Based on an Object-Oriented Model and GIS Data
Abstract
:1. Introduction
2. Land Use Environmental Value Assessment Using Indexes and Indicators
2.1. Environmental Indicators
2.2. Environmental Indicators Based on Land Use
3. Materials and Methods
3.1. Available Data
3.1.1. Description of Mapping Techniques Using GIS
3.1.2. Corine Land Cover
3.1.3. SIOSE
3.2. The Weighted Environmental Index (WEI). Conceptual scheme.
- WEI must integrate all the characteristics of indices that vary continuously in space.
- WEI values should be justified in a simple way from pre-established classifications of land use.
- It must be able to be used to carry out land use assessments based on information integrated into geographic information systems (GIS).
- It must be able to be used both in general studies carried out on a large scale and in detailed studies that use cartography obtained by very high-resolution GIS techniques.
- Its application in the same geographical area at different times should allow for trend analysis to determine the impact of correction measures that are implemented through territorial, urban or environmental planning tools.
- F1: Anthropic or natural nature of activity developed in soil.
- F2: Water consumption associated with land use.
- F3: Soil degradation (use of chemicals).
- F4: Environmental sustainability of land use (stability of the ecosystem).
- F5: Landscape value of activity carried out in the analyzed area.
- : environmental index of land use j ()
- assigned weights to factor i
- : evaluation factor i
- : land use categories
- : total area of study
- : area of polygon k
- npol: total number of polygons in the discretization
- : weighted environmental index of polygon k.
- : environmental index of land use j.
- : area assigned to land use j inside the polygon k.
- : land use weighting factor j in polygon k.
- njk: number of land uses (j) inside polygon k.
4. Results and Discussion
4.1. Large Scale Analysis: Valencian Region (2005–2015)
4.2. Municipal Scale Analysis: L’Alcora municipality (2005–2015)
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Advantages | Disadvantages |
---|---|
|
|
Code | Land Use Description | F1 | F2 | F3 | F4 | F5 | WEIk |
---|---|---|---|---|---|---|---|
EDF | Buildings | 20 | 40 | 20 | 15 | 5 | 20 |
ZAU | Artificial green zone and Urban trees | 60 | 65 | 70 | 80 | 75 | 70 |
LAA | Artificial water body | 65 | 85 | 85 | 65 | 50 | 70 |
VAP | Road, Parking or Pedestrian area | 20 | 40 | 20 | 15 | 5 | 20 |
OCT | Other constructions | 20 | 40 | 20 | 15 | 5 | 20 |
SNE | Soil without edifications | 35 | 50 | 50 | 50 | 15 | 40 |
ZEV | Extraction zones | 0 | 50 | 0 | 0 | 0 | 10 |
CHA | Rice crops | 60 | 10 | 80 | 45 | 55 | 50 |
CHL | Other crops different from rice | 60 | 65 | 80 | 75 | 70 | 70 |
LFC | Citrics | 60 | 65 | 80 | 75 | 70 | 70 |
LFN | Non citrics | 60 | 65 | 80 | 75 | 70 | 70 |
LVI | Grapes | 60 | 65 | 80 | 75 | 70 | 70 |
LOL | Olives | 60 | 65 | 80 | 75 | 70 | 70 |
LOC | Other woody crops | 60 | 65 | 80 | 75 | 70 | 70 |
PRD | Meadows | 80 | 80 | 90 | 100 | 100 | 90 |
PST | Pastureland | 80 | 80 | 80 | 80 | 80 | 80 |
FDC | Hardwood deciduous | 100 | 100 | 100 | 100 | 100 | 100 |
FDP | Evergreen hardwoods | 100 | 100 | 100 | 100 | 100 | 100 |
CNF | Conifers | 100 | 100 | 100 | 100 | 100 | 100 |
MTR | Scrub | 70 | 70 | 70 | 70 | 70 | 70 |
PDA | Sandy beaches | 100 | 100 | 50 | 100 | 100 | 90 |
SDN | Bare soil | 70 | 50 | 20 | 20 | 40 | 40 |
ZQM | Burned areas | 0 | 50 | 0 | 0 | 0 | 10 |
RMB | Ravines | 20 | 50 | 20 | 50 | 60 | 40 |
ACM | Marine cliffs | 100 | 50 | 50 | 100 | 100 | 80 |
ARR | Rocky soil | 80 | 50 | 30 | 30 | 60 | 50 |
CCH | Stone quarry | 80 | 50 | 40 | 40 | 40 | 50 |
CLC | Lava flow | 90 | 30 | 30 | 40 | 60 | 50 |
HPA | Marshes | 80 | 50 | 30 | 80 | 60 | 60 |
HSA | Continental salines | 90 | 30 | 40 | 80 | 60 | 60 |
HMA | Marshes | 90 | 60 | 70 | 90 | 90 | 80 |
HSM | Marine salines | 90 | 60 | 70 | 90 | 90 | 80 |
ACU | Water flows | 100 | 100 | 100 | 100 | 100 | 100 |
ALG | Lakes and lagoons | 100 | 100 | 100 | 100 | 100 | 100 |
AEM | Dams and artificial lakes | 10 | 100 | 100 | 100 | 90 | 80 |
ALC | Coastal lagoons | 100 | 100 | 100 | 100 | 100 | 100 |
AMO | Seas and Oceans | 100 | 100 | 100 | 100 | 100 | 100 |
Non predefined | 50 | 50 | 50 | 50 | 50 | 50 | |
OVD | Olives and grapes | 60 | 65 | 80 | 75 | 70 | 70 |
AAR | Residential agricultural settlement | 40 | 50 | 60 | 50 | 50 | 50 |
UER | Family orchard | 60 | 65 | 75 | 70 | 80 | 70 |
UCS | Urban center | 30 | 30 | 10 | 20 | 10 | 20 |
UEN | Urban expansion area | 30 | 30 | 10 | 20 | 10 | 20 |
UDS | Discontinous | 30 | 30 | 10 | 20 | 10 | 20 |
IPO | Well sorted industrial area | 30 | 30 | 10 | 20 | 10 | 20 |
IPS | Non sorted industrial area | 30 | 30 | 10 | 20 | 10 | 20 |
IAS | Isolated industrial area | 30 | 30 | 10 | 20 | 10 | 20 |
PAG | Agricultural, livestock | 60 | 60 | 70 | 50 | 60 | 60 |
PFT | Primary forest | 100 | 100 | 100 | 100 | 100 | 100 |
PMX | Extractive Mining | 10 | 10 | 10 | 10 | 10 | 10 |
PPS | Fish farm | 30 | 60 | 60 | 50 | 50 | 50 |
TCO | Commercial and offices | 20 | 20 | 20 | 20 | 20 | 20 |
TCH | Hotels | 20 | 20 | 20 | 20 | 20 | 20 |
TPR | Recreational park | 20 | 20 | 20 | 20 | 20 | 20 |
TCG | Camping | 20 | 40 | 40 | 50 | 50 | 40 |
EAI | Institutional administrative | 20 | 20 | 20 | 20 | 20 | 20 |
ESN | Medical and sanitary | 20 | 20 | 20 | 20 | 20 | 20 |
ECM | Cementery | 20 | 20 | 20 | 20 | 20 | 20 |
EDU | Education | 20 | 20 | 20 | 20 | 20 | 20 |
EPN | Penitentiary | 20 | 20 | 20 | 20 | 20 | 20 |
ERG | Religious | 20 | 20 | 20 | 20 | 20 | 20 |
ECL | Cultural | 20 | 20 | 20 | 20 | 20 | 20 |
EDP | Sport | 25 | 15 | 20 | 20 | 20 | 20 |
ECG | Golf course | 40 | 10 | 70 | 50 | 80 | 50 |
EPU | Urban park | 60 | 65 | 70 | 80 | 75 | 70 |
NRV | Streets and roads | 10 | 10 | 10 | 10 | 10 | 10 |
NRF | Train | 10 | 10 | 10 | 10 | 10 | 10 |
NPO | Port | 10 | 10 | 10 | 10 | 10 | 10 |
NAP | Airport | 10 | 10 | 10 | 10 | 10 | 10 |
NEO | Eolic plant | 10 | 10 | 10 | 100 | 20 | 30 |
NSL | Solar plant | 10 | 10 | 10 | 100 | 20 | 30 |
NCL | Nuclear plant | 0 | 0 | 0 | 0 | 0 | 0 |
NEL | Electric plant | 0 | 0 | 0 | 0 | 0 | 0 |
NTM | Thermal plant | 0 | 0 | 0 | 0 | 0 | 0 |
NHD | Hydroelectric plant | 10 | 10 | 10 | 10 | 10 | 10 |
NTC | Telecommunications plant | 0 | 0 | 0 | 0 | 0 | 0 |
NDP | Waste and drinking water plant | 10 | 20 | 10 | 100 | 10 | 30 |
NCC | Channels | 0 | 0 | 0 | 0 | 0 | 0 |
NDS | Desalinization plant | 0 | 0 | 0 | 0 | 0 | 0 |
NVE | Landfills | 0 | 0 | 0 | 0 | 0 | 0 |
NPT | Treatment plant | 0 | 0 | 0 | 0 | 0 | 0 |
UEN | Urban expansion area | 30 | 30 | 10 | 20 | 10 | 20 |
UDS | Discontinous | 30 | 30 | 10 | 20 | 10 | 20 |
IPO | Well sorted industrial area | 30 | 30 | 10 | 20 | 10 | 20 |
IPS | Non sorted industrial area | 30 | 30 | 10 | 20 | 10 | 20 |
IAS | Isolated industrial area | 30 | 30 | 10 | 20 | 10 | 20 |
PAG | Agricultural, livestock | 60 | 60 | 70 | 50 | 60 | 60 |
PFT | Primary forest | 100 | 100 | 100 | 100 | 100 | 100 |
PMX | Extractive mining | 10 | 10 | 10 | 10 | 10 | 10 |
WEI Range | Environmental Value |
---|---|
Low | |
Medium | |
High |
WEI | Absolute Frequency (Number of Polygons) | Class Area (Has) | Class Area (%) | ||||||
---|---|---|---|---|---|---|---|---|---|
2005 | 2009 | 2015 | 2005 | 2009 | 2015 | 2005 | 2009 | 2015 | |
[0,10[ | 0 | 0 | 0 | 0.00 | 0.00 | 0.00 | 0.00% | 0.00% | 0.00% |
[10,20[ | 6 | 11 | 7 | 29.86 | 202.28 | 159.77 | 0.31% | 2.12% | 1.68% |
[20,30[ | 38 | 39 | 39 | 676.94 | 565.99 | 567.12 | 7.11% | 5.94% | 5.96% |
[30,40[ | 20 | 23 | 25 | 129.38 | 136.45 | 160.58 | 1.36% | 1.43% | 1.69% |
[40,50[ | 36 | 32 | 31 | 310.85 | 213.98 | 220.96 | 3.26% | 2.25% | 2.32% |
[50,60[ | 20 | 20 | 16 | 53.15 | 114.38 | 85.15 | 0.56% | 1.20% | 0.89% |
[60,70[ | 47 | 50 | 56 | 302.21 | 313.94 | 442.93 | 3.17% | 3.30% | 4.65% |
[70,80[ | 417 | 417 | 421 | 3762.61 | 3732.63 | 3992.15 | 39.51% | 39.20% | 41.92% |
[80,90[ | 202 | 200 | 201 | 2846.46 | 2822.30 | 2558.72 | 29.89% | 29.64% | 26.87% |
[90,100] | 113 | 117 | 116 | 1411.71 | 1421.22 | 1335.81 | 14.82% | 14.92% | 14.03% |
Total | 899 | 909 | 912 | 9523.18 | 9523.18 | 9523.18 | 100% | 100% | 100% |
WEI | Class Area (%) | Differences (%) | ||||
---|---|---|---|---|---|---|
2005 | 2009 | 2015 | 2009–2005 | 2015–2009 | 2015–2005 | |
[0,10[ | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% | 0.00% |
[10,20[ | 0.31% | 2.12% | 1.68% | 1.81% | −0.45% | 1.36% |
[20,30[ | 7.11% | 5.94% | 5.96% | −1.17% | 0.01% | −1.15% |
[30,40[ | 1.36% | 1.43% | 1.69% | 0.07% | 0.25% | 0.33% |
[40,50[ | 3.26% | 2.25% | 2.32% | −1.02% | 0.07% | −0.94% |
[50,60[ | 0.56% | 1.20% | 0.89% | 0.64% | −0.31% | 0.34% |
[60,70[ | 3.17% | 3.30% | 4.65% | 0.12% | 1.35% | 1.48% |
[70,80[ | 39.51% | 39.20% | 41.92% | −0.31% | 2.73% | 2.41% |
[80,90[ | 29.89% | 29.64% | 26.87% | −0.25% | −2.77% | −3.02% |
[90,100] | 14.82% | 14.92% | 14.03% | 0.10% | −0.90% | −0.80% |
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Rodrigo-Ilarri, J.; Romero, C.P.; Rodrigo-Clavero, M.-E. Land Use/Land Cover Assessment over Time Using a New Weighted Environmental Index (WEI) Based on an Object-Oriented Model and GIS Data. Sustainability 2020, 12, 10234. https://doi.org/10.3390/su122410234
Rodrigo-Ilarri J, Romero CP, Rodrigo-Clavero M-E. Land Use/Land Cover Assessment over Time Using a New Weighted Environmental Index (WEI) Based on an Object-Oriented Model and GIS Data. Sustainability. 2020; 12(24):10234. https://doi.org/10.3390/su122410234
Chicago/Turabian StyleRodrigo-Ilarri, Javier, Claudia P. Romero, and María-Elena Rodrigo-Clavero. 2020. "Land Use/Land Cover Assessment over Time Using a New Weighted Environmental Index (WEI) Based on an Object-Oriented Model and GIS Data" Sustainability 12, no. 24: 10234. https://doi.org/10.3390/su122410234