Remote Sensing (RS) technology provides valuable information about Earth by enabling an overview of the planet from above, making it a much-needed resource for many applications. Given the abundance of RS data and continued urbanisation, there is a need for efficient approaches to leverage RS data and its unique characteristics for the assessment and management of urban areas. Consequently, employing Deep Learning (DL) for RS applications has attracted much attention over the past few years. In this thesis, novel datasets consisting of satellite RS images over urban areas in Sweden were compiled from Sentinel-2 multispectral, Sentinel-1 Synthetic Aperture Radar (SAR) and Urban Atlas 2018 Land Use/Land Cover (LULC) data. Then, DL was applied for multiband and multiclass semantic image segmentation of LULC. The contributions of complementary spectral, temporal and SAR data and spectral indices to LULC classification performance compared to using only Sentinel-2 data with red, green and blue spectral bands were investigated by implementing DL models based on the fully convolutional network-based architecture, U-Net, and performing data fusion. Promising results were achieved with 25 possible LULC classes. Furthermore, almost all DL models at an overall model level and all DL models at an individual class level for most LULC classes benefited from complementary satellite RS data with varying degrees of classification improvement. Additionally, practical knowledge and insights were gained from evaluating the results and are presented regarding satellite RS data characteristics and semantic segmentation of LULC in urban areas. The obtained results are helpful for practitioners and researchers applying or intending to apply DL for semantic segmentation of LULC in general and specifically in Swedish urban environments.

The irrigated agriculture in the Lower Chenab Canal (LCC) of Pakistan is characterized by huge water utilization both from surface and groundwater resources. Need of utilization of water from five rivers in Punjab province along with accelerated population growth has forced the construction of world’s largest irrigation network. Nevertheless, huge irrigation infrastructure, together with inappropriate drainage infrastructure, led to a build-up of shal-low groundwater levels, followed by waterlogging and secondary salinization in the soil profile. Following this era, decreased efficiency of irrigation supply system along with higher food demands had increased burdens on groundwater use, which led to a drop in groundwater levels in major parts of LCC. Previous studies in the study region revealed lacking management and maintenance of irrigation system, inflexible irrigation strategies, poor linkages between field level water supply and demands. No future strategy is present or under consideration to deal with this long time emerged groundwater situation particularly under unchanged irrigation water supply and climate change. Therefore, there is an utmost importance to assess the current profile of water use in the irrigation scheme and to device some workable strategies under future situations of land use and climate change. This study aims to investigate the spatio-temporal status of water utilization and performance of irrigation system using remote sensing data and techniques (SEBAL) in combination with other point data. Different irrigation performance indicators including equity, adequacy and reliability using evaporation fraction as main input parameter are utilized. Current profiles of land use/land cover (LULC) areas are assessed and their change detections are worked out to establish realistic future scenarios. Spatially distributed seasonal net recharge, a very important input parameter for groundwater modeling, is estimated by employing water balance approaches using spatial data from remote sensing and local norms. Such recharge results are also compared with a water table fluctuation approach. Following recharge estimation, a regional 3-D groundwater flow model using FEFLOW was set up. This model was calibrated by different approaches ranging from manual to automated pilot point (PP) approach. Sensitivity analysis was performed to see the model response against different model input parameters and to identify model regions which demand further improvements. Future climate parameters were downscaled to establish scenarios by using statistical downscaling under IPCC future emission scenarios. Modified recharge raster maps were prepared under both LULC and climate change scenarios and were fed to the groundwater model to investigate groundwater dynamics. Seasonal consumptive water use analysis revealed almost double use for kharif as compared to rabi cropping seasons with decrease from upper LCC to lower regions. Intra irrigation subdivision analysis of equity, an important irrigation performance indicator, shows less differences in water consumption in LCC. However, the other indicators (adequacy and reliability) indicate that the irrigation system is neither adequate nor reliable. Adequacy is found more pronounced during kharif as compared to rabi seasons with aver-age evaporation fraction of 0.60 and 0.67, respectively. Similarly, reliability is relatively higher in upper LCC regions as compared to lower regions. LULC classification shows that wheat and rice are major crops with least volatility in cultivation from season to season. The results of change detection show that cotton exhibited maximum positive change while kharif fodder showed maximum negative change during 2005-2012. Transformation of cotton area to rice cultivation is less conspicuous. The water consumption in upper LCC regions with similar crops is relatively higher as compared to lower regions. Groundwater recharge results revealed that, during the kharif cropping seasons, rainfall is the main source of recharge followed by field percolation losses, while for rabi cropping seasons, canal seepage remains the major source. Seasonal net groundwater recharge is mainly positive during all kharif seasons with a gradual increase in groundwater level in major parts of LCC. Model optimization indicates that PP is more flexible and robust as compared to manual and zone based approaches. Different statistical indicators show that this method yields reliable calibration and validation as values of Nash Sutcliffe Efficiency are 0.976 and 0.969, % BIAS are 0.026 and -0.205 and root mean square errors are 1.23 m and 1.31 m, respectively. Results of model output sensitivity suggest that hydraulic conductivity is a more influential parameter in the study area than drain/fillable porosity. Model simulation results under different scenarios show that rice cultivation has the highest impact on groundwater levels in upper LCC regions whereas major negative changes are observed for lower parts under decreased kharif fodder area in place of rice, cotton and sugarcane. Fluctuations in groundwater level among different proposed LULC scenarios are within ±1 m, thus showing a limited potential for groundwater management. For future climate scenarios, a rise in groundwater level is observed for 2011 to 2025 under H3A2 emission regime. Nevertheless, a drop in groundwater level is expected due to increased crop consumptive water use and decreased precipitations under H3A2 scenario for the periods 2026-2035 and 2036-2045. Although no imminent threat of groundwater shortage is anticipated, there is an opportunity for developing groundwater resources in the lower model regions through water re-allocation that would be helpful in dealing water shortages. The groundwater situation under H3B2 emission regime is relatively complex due to very low expectation of rise in groundwater level through precipitation during 2011-2025. Any positive change in groundwater under such scenarios is mainly associated with changes in crop consumptive water uses. Consequently, water management under such situation requires revisiting of current cropping patterns as well as augmenting water supply through additional surface water resources.

Sudan as a Sahelian country faced numerous drought periods resulting in famine and mass immigration. Spatial data on dynamics of land use and land cover is scarce and/or almost nonexistent. The study area in the North Kordofan State is located in the centre of Sudan and falls in the Sahelian eco-climatic zone. The region generally yields reasonable harvests of rainfed crops and the grasslands supports plenty of livestock. But any attempts to develop medium- to longterm strategies of sustainable land management have been hampered by the impacts of drought and desertification over a long period of time. This study aims to determine and analyse the dynamics of change of land use/land cover classes. The study attempts also to improve classification accuracy by using different data transformation methods like PCA, TCA and CA. In addition it tries to investigate the most reliable methods of pre-classification and/or post-classification change detection. The research also attempts to assess the desertification process using vegetation cover as an indicator. Preliminary mapping of major soil types is also an objective of this study. Landsat data of MSS 187/51 acquired on 01.01.1973 and ETM+ 174/51 acquired on 16.01.2001 were used. Visual interpretation in addition to digital image processing was applied to process the imagery for determining land use/land cover classes for the recent and reference image. Pre- and post-classification change detection methods were used to detect changes in land use/land cover classes in the study area. Pre-classification methods include image differencing, PC and Change Vector Analysis. Georeferenced soil samples were analysed to measure physical and chemical parameters. The measured values of these soil properties were integrated with the results of land use/ land cover classification. The major LULC classes present in the study area are forest, farm on sand, farm on clay, fallow on sand, fallow on clay, woodyland, mixed woodland, grassland, burnt/wetland and natural water bodies. Farming on sandy and clay soils constitute the major land use in the area, while mixed woodland constitutes the major land cover. Classification accuracy is improved by adopting data transformation by PCA, TCA and CA. Pre-classification change detection methods show indistinct and sketchy patterns of change but post-classification method shows obvious and detailed results. Vegetation cover changes were illustrated by use of NDVI. In addition preliminary soil mapping by using mineral indices was done based on ETM+ imagery. Distinct patterns of clay, gardud and sand areas could be classified. Remote sensing methods used in this study prove a high potential to classify land use/land cover as well as soil classes. Moreover the remote sensing methods used confirm efficiency for detecting changes in LULC classes and vegetation cover during the addressed period.

Στα πλαίσια της παρούσας έρευνας, μελετήθηκε η προστατευόμενη περιοχή του Οικολογικού Δικτύου Natura 2000: «Λιμνοθάλασσα Πύλου (Διβάρι), Νήσος Σφακτηρία, Αγ. Δημήτριος» με κωδικό GR2550004. Διεξάχθηκαν δύο εποχικές δειγματοληψίες, στις 31 Αυγούστου του 2012 και στις 21 Απριλίου του 2013. Η λιμνοθάλασσα της Γιάλοβας έχει έκταση περίπου 2,5 Km2, μέγιστο βάθος 1 m και επικοινωνεί με τον κόλπο του Ναυαρίνου μέσω ενός τεχνητού διαύλου. Αρχικά, πραγματοποιήθηκε η ηχοβολιστική αποτύπωση του πυθμένα, με χρήση ηχοβολιστή πλευρικής σάρωσης (Side Scan Sonar, SSS) με σκοπό να αποκαλυφθεί, τόσο η μορφολογία του βυθού, όσο και η παρουσία, η αφθονία και η χωρική κατανομή των υδρόβιων μακροφύτων. Κατόπιν, σε 9 προεπιλεγμένους δειγματοληπτικούς σταθμούς, πραγματοποιήθηκε καταγραφή των φυσικοχημικών παραμέτρων και συλλέχθηκαν δείγματα υδρόβιας χλωρίδας. Με τη βοήθεια του ηχοβολιστή πλευρικής σάρωσης μελετήθηκε, περίπου, το 37% της έκτασης της λιμνοθάλασσας. Μέσω αυτής της διαδικασίας, προέκυψαν 6 διαφορετικοί ακουστικοί τύποι που αντιστοιχούν σε 6 διαφορετικά ποσοστά φυτοκάλυψης: πυκνή (76-100%), λιγότερο πυκνή (51-75%), αραιή (26-50%), πολύ αραιή (6-25%), σπάνια (1-5%) και καθόλου (<1%). Αφού κατασκευάστηκε το μωσαϊκό του πυθμένα, με τη χρήση των λογισμικών Triton Isis και TritonMap (Delphmap) της Triton Imaging Inc., διαπιστώθηκε ότι, η λιμνοθάλασσα καλύπτεται από βλάστηση σε ποσοστό περίπου 25% ενώ, περίπου, το 75% δεν καταλαμβάνεται από κάποιο είδος υδρόβιας βλάστησης, και το υπόστρωμα είναι αμμώδες/ ιλυοαμμώδες (Μπούζος et al., 2002a). Τα αποτελέσματα του Αυγούστου έδειξαν ότι, η πυκνή φυτοκάλυψη φτάνει περίπου στο 2% της υπό μελέτη έκτασης, και χωρικά περιορίζεται κοντά στο δίαυλο επικοινωνίας με τη θάλασσα. Η υδρόβια χλωρίδα που απαντά στους σταθμούς αυτούς αποτελείται από τα είδη Ruppia cirrhosa σε μίξη με την Cymodocea nodosa, με κυρίαρχο είδος τη Ruppia cirrhosa. Όσο απομακρυνόμαστε από το δίαυλο, η πυκνή φυτοκάλυψη εναλλάσσεται με λιγότερο πυκνή, σε ποσοστό 1% επί του συνόλου, και αποτελείται από τα ίδια είδη. Η αραιή φυτοκάλυψη, απαντά σε ποσοστό 3% και χωρικά κατανέμεται στο δίαυλο επικοινωνίας, αλλά και στα νοτιοδυτικά της λιμνοθάλασσας, όπου, εκτός από τη Ruppia cirrhosa, απαντά και η Cladophora glomerata. To ποσοστό της πολύ αραιής φυτοκάλυψης κυμαίνεται γύρω στο 15% και χωρικά κατανέμεται, κυρίως, στα βορειοανατολικά της λιμνοθάλασσας, όπου απαντά μόνο η Ruppia cirrhosa, ενώ, σε ποσοστό 4%, η φυτοκάλυψη είναι σπάνια και απαντά στα βορειοδυτικά και στα κεντρικά σημεία της λιμνοθάλασσας. Τον Απρίλιο, η χωρική κατανομή των υδρόβιων μακροφύτων είναι ακόμα πιο περιορισμένη, με συμμετοχή μόνο της Ruppia cirrhosa, η οποία συγκεντρώνεται κυρίως, κοντά στο δίαυλο επικοινωνίας με τον κόλπο του Ναυαρίνου, καθώς εκεί ευνοείται η ανανέωση του νερού και οι περιβαλλοντικές συνθήκες είναι κατάλληλες για την ανάπτυξή τους. Τονίζεται επίσης ότι, τον Απρίλιο, συλλέχθηκε από τα βόρεια της λιμνοθάλασσας ένα είδος του γένους Ulva spp, που αποτελεί δείκτη ευτροφικών συνθηκών (Orfanidis et al., 2005, Aliaume et al., 2007). Γενικά, το κυρίαρχο είδος στη λιμνοθάλασσα, και τις δύο δειγματοληπτικές περιόδους, είναι το κοσμοπολίτικο είδος Ruppia cirrhosa το οποίο έχει καταγραφεί ξανά στην περιοχή (Tiniakos et al., 1997). Σε όλους τους δειγματοληπτικούς σταθμούς, καταγράφηκαν οι παράμετροι: θερμοκρασία, αλατότητα, pH και διαλυμένο οξυγόνο, αλλά και το βάθος της λιμνοθάλασσας, η διαφάνεια του νερού και η ένταση της φωτοσυνθετικά ενεργής ακτινοβολίας (PAR). Επιπλέον, υπολογίστηκαν οι συγκεντρώσεις της χλωροφύλλης-α, τα ολικά αιωρούμενα στερεά (TSS), οι συγκεντρώσεις των ανόργανων ενώσεων αζώτου και φωσφόρου, καθώς και τα επίπεδα της ολικής αλκαλικότητας των ανθρακικών και όξινων ανθρακικών ιόντων. Τα αποτελέσματα έδειξαν χωρική και χρονική διακύμανση όλων των παραμέτρων, με πιο σημαντικές τις διακυμάνσεις της θερμοκρασίας, της αλατότητας και της συγκέντρωσης των θρεπτικών ενώσεων αζώτου και φωσφόρου. H εποχική διακύμανση των περιβαλλοντικών παραμέτρων προκαλεί φυσικό stress στους υδρόβιους οργανισμούς επηρεάζοντας την αφθονία και εξάπλωσή τους (Crouzet et al., 1999). O έλεγχος των στατιστικώς σημαντικών διαφορών των φυσικοχημικών παραμέτρων, πραγματοποιήθηκε με τον έλεγχο Mann-Whitney U, ο οποίος έδειξε ότι υπάρχουν στατιστικώς σημαντικές διαφορές, μεταξύ των δύο εποχών, που αφορούν στις παραμέτρους: διαφάνεια, αλατότητα, θερμοκρασία, pH, TSS, NO2, CO3ˉ και HCO3=. Αντίθετα, δεν εντοπίστηκαν στατιστικώς σημαντικές διαφορές μεταξύ των δύο εποχικών δειγματοληψιών στις παραμέτρους: βάθος, διαλυμένο οξυγόνο, χλωροφύλλη-α, NO3, NH4 και PO4. Ενδεικτικά, η θερμοκρασία παρουσίασε μεγάλη εποχική διακύμανση, σημειώνοντας πολύ υψηλές τιμές τον Αύγουστο (28,80 C - 30,50 C), και πολύ χαμηλότερες τον Απρίλιο (19,0 0C - 20,40C). Η αλατότητα παρουσίασε μεγάλες διακυμάνσεις από σταθμό σε σταθμό, κυρίως τον Αύγουστο, αλλά και από εποχή σε εποχή. Συγκεκριμένα τον Αύγουστο, κυμάνθηκε από 42,73‰ έως 54,42‰ ενώ τον Απρίλιο κυμάνθηκε γύρω στο 31‰ σε όλη την έκταση της λιμνοθάλασσας. Επιπρόσθετα, το pH παρουσίασε στατιστικώς σημαντικές διαφορές, καθώς τον Αύγουστο κυμάνθηκε στο 8,23 κατά μέσο όρο, αναφορικά για όλη τη λιμνοθάλασσα, ενώ τον Απρίλιο παρουσίασε πτωτική τάση, αφού η μέση του τιμή ήταν 6,99. Όσον αφορά στις συγκεντρώσεις των θρεπτικών, τα αμμωνιακά ιόντα ήταν η κυρίαρχη μορφή αζώτου, καθώς παρουσίασε υψηλές τιμές και τις δύο δειγματοληπτικές περιόδους, ενώ, τα νιτρώδη ιόντα, παρόλο που διέφεραν στατιστικώς σημαντικά, σε γενικές γραμμές, κυμάνθηκαν σε χαμηλά επίπεδα και τους δύο μήνες (έως 0,010 mg/l). Το διαλυμένο οξυγόνο παρέμεινε σε φυσιολογικά επίπεδα και τους δύο μήνες, όπου η μέση τιμή του ήταν 8 mg/l. Το βάθος δεν μεταβλήθηκε σημαντικά, ενώ τα επίπεδα της χλωροφύλλης-α, ήταν υψηλά και τις δύο χρονικές περιόδους. Η ανάλυση Spearman έδειξε σαφείς συσχετίσεις μεταξύ των περιβαλλοντικών παραμέτρων. Ανάμεσα στις πιο σημαντικές συγκαταλέγονται, η αρνητική συσχέτιση της διαφάνειας με την εποχή και το βάθος. Επιπλέον, σημαντική είναι η αρνητική συσχέτιση της αλατότητας και της θερμοκρασίας με την εποχή, αλλά και η θετική συσχέτιση μεταξύ των δύο πρώτων. Στη συνέχεια, εξίσου σημαντική είναι η θετική συσχέτιση του pH με την αλατότητα και τη θερμοκρασία, αλλά αξιοσημείωτες είναι και οι θετικές συσχετίσεις που παρουσιάζουν τα TSS με τη θερμοκρασία και το pH, και η χλωροφύλλη-α με τη διαφάνεια. Σύμφωνα με τα κριτήρια που έθεσε η Οργάνωση για Συνεργασία και Ανάπτυξη (ΟΕCD) για τα στάσιμα ύδατα, προέκυψε η τροφική κατάσταση της λιμνοθάλασσας, με βάση τις μέσες και οριακές τιμές των παραμέτρων: TP, χλωροφύλλη-α και διαφάνεια (Secchi depth) (OECD, 1982). Έτσι, με βάση τη μέση συγκέντρωση του ολικού φωσφόρου χαρακτηρίζεται ως υπερτροφική τον Αύγουστο και ως ευτροφική τον Απρίλιο. Όσον αφορά στη χλωροφύλλη-α, με βάση τις μέσες και μέγιστες τιμές που σημειώθηκαν τον Αύγουστο, η λιμνοθάλασσα χαρακτηρίζεται ως ευτροφική, ενώ τον Απρίλιο χαρακτηρίζεται ως ευτροφική, με βάση τη μέση τιμή, αλλά ως μεσοτροφική, με βάση τη μέγιστη τιμή που καταγράφηκε. Τέλος, όσον αφορά στη διαφάνεια, σύμφωνα με τις μέσες και ελάχιστες τιμές της, η λιμνοθάλασσα, και τους δύο μήνες, χαρακτηρίζεται ως υπερτροφική. Με χρήση των Γεωγραφικών Συστημάτων Πληροφοριών (ΓΣΠ), και με υπόβαθρο ένα μωσαϊκό ορθοφωτοχαρτών της Κτηματολόγιο Α.Ε., που αποκτήθηκαν κατά το διάστημα 2007-2009, κατασκευάστηκε ο χάρτης των καλύψεων/ χρήσεων γης του συστήματος ταξινόμησης Corine Land Cover 2000, για ολόκληρη την προστατευόμενη περιοχή. Ακολούθως, έγινε η αντιστοίχηση των κατηγοριών καλύψεων/ χρήσεων γης που προέκυψαν, με τους τύπους οικοτόπων του Παραρτήματος Ι της Οδηγίας 92/43/ΕΚ, στο 3ο επίπεδο ταξινόμησης. Επιπλέον, πραγματοποιήθηκε μια ποιοτική σύγκριση μεταξύ του νέου χάρτη και του χάρτη του Corine Land Cover, που κατασκευάστηκε για την περιοχή το 2000. Με βάση το χάρτη που κατασκευάστηκε διαπιστώθηκε ότι, υπάρχει ποικιλία φυσικών τύπων οικοτόπων, που προσδίδουν στην περιοχή ιδιαίτερη οικολογική και αισθητική αξία. Περιμετρικά της λιμνοθάλασσας απαντούν μεσογειακά αλίπεδα (Juncetalia maritimi), καλαμώνες, μεσογειακοί λειμώνες υψηλών χόρτων και βούρλων (Molinio Holochoenion), παρόχθια δάση-στοές και λόχμες (Nerio-Tamaricetea και Securinegion tinctoriae), σχηματισμοί με αρκεύθους (Juniperus spp.), υποτυπώδεις κινούμενες θίνες, κινούμενες θίνες της ακτογραμμής με Ammophila arenaria και μονοετή βλάστηση μεταξύ των ορίων πλημμυρίδας και αμπώτιδας. Επιπλέον, στη νήσο Σφακτηρία, στους λόφους του Παλαιόκαστρου και του Πετροχωρίου, απαντούν απόκρημνες βραχώδεις ακτές με βλάστηση στη Μεσόγειο (με ενδημικά Limonium spp.), Garrigues της Ανατολικής Μεσογείου και φρύγανα ενώ, οι όχθες του ποταμού Σελά χαρακτηρίζονται από δάση ανατολικής πλατάνου (Platanus orientalis). Τονίζεται η σημειακή συμμετοχή του τύπου προτεραιότητας των θινών των παραλιών με αρκεύθους (Juniperus spp). Επιπλέον, σε μεγάλη έκταση, απαντούν οι αγροτικές καλλιέργειες, με κυρίαρχους τους ελαιώνες, περιοχές αστικού πρασίνου, δρόμοι αλλά και οικισμοί. Τα αποτελέσματα της παρούσας εργασίας όπως η αποτύπωση της μορφολογίας του πυθμένα της λιμνοθάλασσας και των καλύψεων/ χρήσεων γης, στα όρια της προστατευόμενης περιοχής και η περαιτέρω εκτίμηση της οικολογικής κατάστασης της λιμνοθάλασσας θα συμβάλλουν περαιτέρω στην ορθολογική διαχείριση της. / In the context of this research, the protected area of the «Natura 2000» ecological network: "Pylos Lagoon, Sfaktiria island, St. Dimitrios" with the sitecode GR2550004, has been studied. Two sampling campaigns were carried out, οn August 31st 2012 and on April 21st 2013. Gialova lagoon covers an area of 2.5 Km2 with a maximum depth of 1 m and is connected with the adjoining Navarino Bay, via a small channel. Firstly, side scan sonar bottom interpretation was carried out, in order to investigate, not only the morphology of the lagoon’s bottom, but also the presence, abundance and spatial distribution of aquatic macrophytes. In addition, physicochemical parameters were recorded in 9 different sampling stations. Furthermore, samplings of aquatic vegetation were carried out as well. Initially, with the use of SSS, roughly 37% of the lagoon’s surface has been studied. Side scan sonar imagery resulted in 6 different acoustic types, which correspond to 6 different percentages of plant cover: thick (76-100%), less than thick (51-75%), sparse (26-50%), too sparse (6-25%), rare (1-5%) and absent (<1%). Having built the mosaic of the bottom of the lagoon, with the use of software Triton Isis and Triton Map (Delphmap) of Triton Imaging Inc., it was found that, the lagoon is covered by vegetation at 25%, while 75% is not occupied by any kind of aquatic vegetation, but the substrate is sandy/mudsandy (Bouzos et al., 2002a). The results of August showed that the thick plant cover reaches approximately 2% of the study area, and it is spatially restricted near the communication channel with the sea. The aquatic flora which responds to these stations is Ruppia cirrhosa in mixing with the Cymodocea nodosa, with the Ruppia cirrhosa as the dominant species. When we move away from the communication channel, the thick plant cover alternates with less than thick, representing 1% of the total, and consists of the same species. The sparse plant cover responds to 3% and is spatially distributed in the communication channel, but also in the southwest of the lagoon, where, apart from the Ruppia cirrhosa, Cladophora glomerata is found as well. The percentage of too sparse vegetation is around 15%, and it is spatially distributed mainly in the north-east of the lagoon, where only Ruppia cirrhosa is found, while, the vegetation is rare at 4%, and responds to the northwest and the central points of the lagoon. In April, the spatial distribution of aquatic macrophytes is even more limited, involving only the Ruppia cirrhosa, which is mainly concentrated near the communication channel with the adjoining Navarino Bay, which favored the renewal of water and where the environmental conditions are suitable for their development. It should be also noted that, in April, an occasional species of the genus Ulva spp., was collected from the northern section of the lagoon. This species is an indicator of eutrophic conditions (Orfanidis et al., 2005, Aliaume et al., 2007). In general, the dominant species in the lagoon, in both sampling periods, is the cosmopolitan species Ruppia cirrhosa, which has been recorded before in the region (Tiniakos et al., 1997). The following parameters were recorded in all the sampling stations: temperature, salinity, pH and dissolved oxygen, but also the depth of the lagoon, the transparency of the water’s column and the volume of photosynthetically active radiation (PAR). Furthermore, chlorophyll-a, total suspended solids (TSS), inorganic nitrogen and phosphorus compounds, as well as the levels of total alkalinity of carbonates and acid carbonates were calculated. The results showed spatial and temporal variability of all parameters, and the most significant fluctuations were observed in temperature, salinity and in nitrogen and phosphorus concentrations. This seasonal variation of environmental parameters causes natural stress on aquatic organisms affecting their abundance and their spatial distribution (Crouzet et al., 1999). The control of the statistically significant differences in physicochemical parameters was carried out with the Mann-Whitney U test, which has shown that, there are statistically significant differences between the two seasons, relating to parameters: transparency, salinity, temperature, pH, TSS, NO2, CO3ˉ and HCO3=. In contrast, there were not statistically significant differences between the two sampling periods for parameters: depth, dissolved oxygen, Chl-a, NO3, NH4 and PO4. More specifically, the temperature has large seasonal variation, noting very high values in August (28.8ᵒ C – 30.5ᵒ C) and much lower in April (19.0ᵒ C – 20.4ᵒ C). The salinity showed large fluctuations from station to station, especially in August, but also from season to season. Specifically in August, it ranged from 42.73‰ to 54.42‰ and in April fluctuated around 31‰ throughout the lagoon. In addition, the pH values presented statistically significant differences. In August, pH ranged from around 8.23 on average, with respect to the entire lagoon, while in April showed a downward trend, when the average value was around 6.99. With regard to the concentrations of nutrients, ammonium ions were the dominant form of nitrogen, as it presented high values in both sampling periods, while the nitrite ions, although differed statistically significantly, in general, varied in low levels both months. Dissolved oxygen, remained at normal levels in both sampling periods, where the average value was around 8 mg/l. The depth did not change significantly, while the levels of Chl-a, were very high in both time periods. The Spearman analysis showed clear correlations between environmental parameters. Among the most important is, the negative correlation of transparency with season and depth. In addition, significant is the negative correlation of salinity and temperature with season, but also the positive correlation between the first two. Of course, equally important is the positive correlation of pH with salinity and temperature, but also significant are the positive correlations of the TSS with temperature and pH, and Chl-a with transparency. Finally, it is mentioned that there is negative correlation of total phosphorus with season and acid carbonates, and positive correlation with salinity, temperature, pH and TSS. In accordance with the standards set by the Organization for Cooperation and Development (OECD) for stagnant water, the trophic status of the lagoon has been established, on the basis of the average and maximum values of parameters: TP, Chl-a and transparency (Secchi depth) (OECD, 1982). So, on the basis of the average concentration of total phosphorus, it is characterized as hypereutrophic in August and as eutrophic in April. As regards the Chl-a, on the basis of the average and maximum values occurred in August, the lagoon is characterised as eutrophic, while in April it is characterized as eutrophic, based on the average value, but as mesotrophic, on the basis of the maximum value recorded. Finally, with regard to transparency, in accordance with the average and minimum values, the lagoon is characterized as hypereutrophic in both seasons. With the use of Geographical Information Systems (GIS) and with the help of ortho-corrected aerial photographs, acquired during 2007 and 2009, a Land Cover Land Use map was constructed. Subsequently, the categories of Corine Land Cover that came up, matched with the habitat types included in the Annex I of the Directive 92/43/EC, according to the 3rd classification level. Furthermore, the land cover/ land use categories of the new map compared with those of the map that constructed in 2000 for the same area, in order to estimate the changes during the years that have passed. The map, which was constructed in the context of this research, showed that there is a variety of natural habitat types, which gives the area special ecological and aesthetic value. In particular, around the lagoon, we found mediterranean salt meadows (Juncetalia maritimi), reedbeds, mediterranean grassland with high grass and rush (Molinio Holochoenion), southern riparian forest-arcades and scrubs galleries (Nerio-tamaricetea and Securinegion tinctoriae), formations with juniper thickets (Juniperus spp.), embryonic dunes, shifting dunes along the shoreline with Ammophila Arenaria and vegetation of drift lines. In addition, on the Sfaktiria island, in Paleokastro and Petrochori hills respond vegetated sea cliffs of the Mediterranean coasts (with endemic Limonium spp.), Garrigues of eastern Mediterranean and phrygana, while the banks of the river Selas are characterized by oriental plane woods (Platanus orientalis). The spot presence of dune juniper thickets is emphasized (Juniperus spp), which is a priority habitat. In addition, to a large extent, there are agricultural crops with olive groves, urban areas, roads and different kinds of settlements. The ultimate aim of this study is the visual interpretation of the morphology of the bottom of the lagoon and the Land Cover Land Uses, within the limits of the protected area and the further assessment of the ecological status of the lagoon.

Submitted by Geyciane Santos (geyciane_thamires@hotmail.com) on 2015-07-27T15:15:30Z No. of bitstreams: 1 Dissertação - Jorge Alberto Lopes da Costa.pdf: 12254367 bytes, checksum: e92aa3fbce27b2b569e2f3aae45e851d (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-28T15:14:18Z (GMT) No. of bitstreams: 1 Dissertação - Jorge Alberto Lopes da Costa.pdf: 12254367 bytes, checksum: e92aa3fbce27b2b569e2f3aae45e851d (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2015-07-28T15:19:49Z (GMT) No. of bitstreams: 1 Dissertação - Jorge Alberto Lopes da Costa.pdf: 12254367 bytes, checksum: e92aa3fbce27b2b569e2f3aae45e851d (MD5) / Made available in DSpace on 2015-07-28T15:19:50Z (GMT). No. of bitstreams: 1 Dissertação - Jorge Alberto Lopes da Costa.pdf: 12254367 bytes, checksum: e92aa3fbce27b2b569e2f3aae45e851d (MD5) Previous issue date: 2011-07-07 / Não informada / In recent decades the areas of rainforest in the Amazon region has been heavily impacted by a rapid process of conversion of vegetation cover in other types of use due to human action. In the context of global change, the use of mapping and monitoring land cover and provide information for the analysis and evaluation of environmental impacts due to accelerated changes in the landscape. Therefore, this study evaluated the potential of data from synthetic aperture radar for discriminating use and land cover in the region of Manaus, Amazonas state. We used a multipolarized image from sensor airborne SAR-R99B (L band), with 3 m spatial resolution. Were evaluated the MAXVER-ICM and SVM (Support Vector Machine) classifiers, where in all cases we used the images individually multipolarized amplitude (HH, HV and VV), in pairs (HH and HV), (HV and VV) and (HH and VV) and together (HH, HV and VV). The results were compared using as parameter the Kappa coefficient. The SVM classifier had higher accuracy compared to MAXVER-ICM classifier. The best classifications were obtained for the dual polarization (HH and VV) with MARVER-ICM classifier and (HH, HV and VV) with the SVM classifier both using the images with the filter. The accuracy was highest with SVM for classification and filter images (kappa = 0.7736). Were analyzed the influence of using GAMMA filter performance on the classifiers where it showed that filtered images have provided an increase in the results, on average, about 8%. Thus there was the analysis of the classification results, which found that the best result was provided by the dataset multipolarized (HH, HV and VV) classified by the SVM method. Thus, we concluded that the use of radar imagery in mapping thematic classes use and land cover in tropical regions, can be considered as a viable proposal. / Nas últimas décadas as áreas de floresta tropical na região Amazônica têm sido fortemente impactada por um rápido processo de conversão da cobertura vegetal em outros tipos de uso devido à ação antrópica. No contexto das mudanças globais, os mapeamentos e monitoramentos de uso e cobertura da terra fornecem subsídios para as análises e avaliações dos impactos ambientas em virtude de acelerados processos de mudança na paisagem. Neste contexto, este estudo avaliou o potencial dos dados de radar de abertura sintética para discriminação de uso e cobertura da terra na região de Manaus, estado do Amazonas. Foi utilizada uma imagem multipolarizada do sensor aerotransportado SAR-R99B (banda L), com 3 metros de resolução espacial. Realizaram-se classificações na imagem radar sem filtro e com filtro Gamma 3x3. Avaliou-se o classificador pontual MAXVER-ICM e o SVM (Support Vector Machine), onde em todos os casos utilizou-se das imagens multipolarizadas em amplitude individualmente (HH, HV e VV), aos pares (HH e HV), (HV e VV) e (HH e VV) e em conjunto (HH, HV e VV). Os resultados obtidos foram comparados utilizando-se como parâmetro o coeficiente de concordância Kappa. O classificador SVM apresentou acurácia superior em relação ao classificador MAXVER-ICM. As melhores classificações foram obtidas para a polarização dual HH e VV com o classificador MAXVER-ICM e (HH, HV e VV) com o classificador SVM ambos utilizando as imagens com filtro. A acurácia mais elevada foi para a classificação com SVM e imagens com filtro (kappa = 0,7736). Analisou-se a influência do uso de filtro GAMMA no desempenho dos classificadores onde se contatou que as imagens filtradas proporcionaram um incremento nos resultados, em média, na ordem de 8%. Deste modo realizou-se a análise dos resultados das classificações, onde se constatou que o melhor resultado foi proporcionado pelo conjunto de dados multipolarizados (HH, HV e VV)classificados através do método SVM. Assim, concluiu-se que o uso de imagens de radar no mapeamento de classes temáticas de uso e cobertura da terra, em regiões tropicais, pode ser considerado como uma proposta viável.

Modification of land use/land cover in South Florida has posed a major challenge in the region’s eco-hydrology by shifting the surface-atmosphere water and energy balance. Although drainage and development in South Florida took place extensively between the mid- and late- 20th century, converting half of the original Everglades into agricultural and urban areas, urban expansion still accounts for a dominant mode of surface cover change in South Florida. Changes in surface cover directly affect the radiative, thermophysical and aerodynamic parameters which determine the absorption and partitioning of radiation into different components at the Earth surface. The alteration is responsible for changing the thermal structure of the surface and surface layer atmosphere, eventually modifying surface-induced convection. This dissertation is aimed at analyzing the extent and pattern of land cover change in South Florida and delineating the associated development of urban heat island (UHI), energy flux alteration, and convective rainfall modification using observed data, remotely sensed estimates, and modeled results. Urban land covers in South Florida are found to have increased by 10% from 1974 to 2011. Higher Landsat-derived land surface temperatures (LST) are observed in urban areas (LSTu-r =2.8°C) with satisfactory validation statistics for eastern stations (Nash-Sutcliffe coefficient =0.70 and R2 =0.79). Time series trends, significantly negative for diurnal temperature range (DTR= -1°C, p=0.005) and positive for lifting condensation level (LCL > 20m) reveal temporal and conspicuous urban-rural differences in nocturnal temperature (ΔTu-r = 4°C) shows spatial signatures of UHI. Spatially higher (urban: 3, forest: 0.14) and temporally increasing (urban: 1.67 to 3) Bowen’s ratios, and sensible heat fluxes exceeding net radiation in medium and high-intensity developed areas in 2010 reflect the effect of urbanization on surface energy balance. Radar reflectivity-derived surface-induced convective rainfall reveals significantly positive mean differences (thunderstorm cell density: 6/1000 km2and rain rate: 0.24 mm/hr/summer, p < 0.005) between urban and entire South Florida indicating convective enhancement by urban covers. The research fulfils its two-fold purposes: advancing the understanding of post-development hydrometeorology in South Florida and investigating the spatial and temporal impacts of land cover change on the microclimate of a subtropical city.

The irrigated agriculture in the Lower Chenab Canal (LCC) of Pakistan is characterized by huge water utilization both from surface and groundwater resources. Need of utilization of water from five rivers in Punjab province along with accelerated population growth has forced the construction of world’s largest irrigation network. Nevertheless, huge irrigation infrastructure, together with inappropriate drainage infrastructure, led to a build-up of shal-low groundwater levels, followed by waterlogging and secondary salinization in the soil profile. Following this era, decreased efficiency of irrigation supply system along with higher food demands had increased burdens on groundwater use, which led to a drop in groundwater levels in major parts of LCC. Previous studies in the study region revealed lacking management and maintenance of irrigation system, inflexible irrigation strategies, poor linkages between field level water supply and demands. No future strategy is present or under consideration to deal with this long time emerged groundwater situation particularly under unchanged irrigation water supply and climate change. Therefore, there is an utmost importance to assess the current profile of water use in the irrigation scheme and to device some workable strategies under future situations of land use and climate change. This study aims to investigate the spatio-temporal status of water utilization and performance of irrigation system using remote sensing data and techniques (SEBAL) in combination with other point data. Different irrigation performance indicators including equity, adequacy and reliability using evaporation fraction as main input parameter are utilized. Current profiles of land use/land cover (LULC) areas are assessed and their change detections are worked out to establish realistic future scenarios. Spatially distributed seasonal net recharge, a very important input parameter for groundwater modeling, is estimated by employing water balance approaches using spatial data from remote sensing and local norms. Such recharge results are also compared with a water table fluctuation approach. Following recharge estimation, a regional 3-D groundwater flow model using FEFLOW was set up. This model was calibrated by different approaches ranging from manual to automated pilot point (PP) approach. Sensitivity analysis was performed to see the model response against different model input parameters and to identify model regions which demand further improvements. Future climate parameters were downscaled to establish scenarios by using statistical downscaling under IPCC future emission scenarios. Modified recharge raster maps were prepared under both LULC and climate change scenarios and were fed to the groundwater model to investigate groundwater dynamics. Seasonal consumptive water use analysis revealed almost double use for kharif as compared to rabi cropping seasons with decrease from upper LCC to lower regions. Intra irrigation subdivision analysis of equity, an important irrigation performance indicator, shows less differences in water consumption in LCC. However, the other indicators (adequacy and reliability) indicate that the irrigation system is neither adequate nor reliable. Adequacy is found more pronounced during kharif as compared to rabi seasons with aver-age evaporation fraction of 0.60 and 0.67, respectively. Similarly, reliability is relatively higher in upper LCC regions as compared to lower regions. LULC classification shows that wheat and rice are major crops with least volatility in cultivation from season to season. The results of change detection show that cotton exhibited maximum positive change while kharif fodder showed maximum negative change during 2005-2012. Transformation of cotton area to rice cultivation is less conspicuous. The water consumption in upper LCC regions with similar crops is relatively higher as compared to lower regions. Groundwater recharge results revealed that, during the kharif cropping seasons, rainfall is the main source of recharge followed by field percolation losses, while for rabi cropping seasons, canal seepage remains the major source. Seasonal net groundwater recharge is mainly positive during all kharif seasons with a gradual increase in groundwater level in major parts of LCC. Model optimization indicates that PP is more flexible and robust as compared to manual and zone based approaches. Different statistical indicators show that this method yields reliable calibration and validation as values of Nash Sutcliffe Efficiency are 0.976 and 0.969, % BIAS are 0.026 and -0.205 and root mean square errors are 1.23 m and 1.31 m, respectively. Results of model output sensitivity suggest that hydraulic conductivity is a more influential parameter in the study area than drain/fillable porosity. Model simulation results under different scenarios show that rice cultivation has the highest impact on groundwater levels in upper LCC regions whereas major negative changes are observed for lower parts under decreased kharif fodder area in place of rice, cotton and sugarcane. Fluctuations in groundwater level among different proposed LULC scenarios are within ±1 m, thus showing a limited potential for groundwater management. For future climate scenarios, a rise in groundwater level is observed for 2011 to 2025 under H3A2 emission regime. Nevertheless, a drop in groundwater level is expected due to increased crop consumptive water use and decreased precipitations under H3A2 scenario for the periods 2026-2035 and 2036-2045. Although no imminent threat of groundwater shortage is anticipated, there is an opportunity for developing groundwater resources in the lower model regions through water re-allocation that would be helpful in dealing water shortages. The groundwater situation under H3B2 emission regime is relatively complex due to very low expectation of rise in groundwater level through precipitation during 2011-2025. Any positive change in groundwater under such scenarios is mainly associated with changes in crop consumptive water uses. Consequently, water management under such situation requires revisiting of current cropping patterns as well as augmenting water supply through additional surface water resources.:ABSTRACT VIII ZUSAMMENFASSUNG X ACRONYMS 1 Chapter 1 3 GENERAL INTRODUCTION 3 1 Groundwater for irrigated agriculture 3 2 Groundwater development in Pakistan 4 3 Study area 6 4 History of groundwater use in the study area 7 5 Research agenda 8 5.1 Problem statement 8 5.2 Objectives and scope of the study 9 Chapter 2 12 OVERVIEW OF PUBLICATIONS 12 Chapter 3 16 GENERAL CONCLUSIONS AND POLICY RECOMMENDATIONS 16 REFERENCES 20 ANNEXES 23 ACKNOWLEDGEMENTS 123

Sudan as a Sahelian country faced numerous drought periods resulting in famine and mass immigration. Spatial data on dynamics of land use and land cover is scarce and/or almost nonexistent. The study area in the North Kordofan State is located in the centre of Sudan and falls in the Sahelian eco-climatic zone. The region generally yields reasonable harvests of rainfed crops and the grasslands supports plenty of livestock. But any attempts to develop medium- to longterm strategies of sustainable land management have been hampered by the impacts of drought and desertification over a long period of time. This study aims to determine and analyse the dynamics of change of land use/land cover classes. The study attempts also to improve classification accuracy by using different data transformation methods like PCA, TCA and CA. In addition it tries to investigate the most reliable methods of pre-classification and/or post-classification change detection. The research also attempts to assess the desertification process using vegetation cover as an indicator. Preliminary mapping of major soil types is also an objective of this study. Landsat data of MSS 187/51 acquired on 01.01.1973 and ETM+ 174/51 acquired on 16.01.2001 were used. Visual interpretation in addition to digital image processing was applied to process the imagery for determining land use/land cover classes for the recent and reference image. Pre- and post-classification change detection methods were used to detect changes in land use/land cover classes in the study area. Pre-classification methods include image differencing, PC and Change Vector Analysis. Georeferenced soil samples were analysed to measure physical and chemical parameters. The measured values of these soil properties were integrated with the results of land use/ land cover classification. The major LULC classes present in the study area are forest, farm on sand, farm on clay, fallow on sand, fallow on clay, woodyland, mixed woodland, grassland, burnt/wetland and natural water bodies. Farming on sandy and clay soils constitute the major land use in the area, while mixed woodland constitutes the major land cover. Classification accuracy is improved by adopting data transformation by PCA, TCA and CA. Pre-classification change detection methods show indistinct and sketchy patterns of change but post-classification method shows obvious and detailed results. Vegetation cover changes were illustrated by use of NDVI. In addition preliminary soil mapping by using mineral indices was done based on ETM+ imagery. Distinct patterns of clay, gardud and sand areas could be classified. Remote sensing methods used in this study prove a high potential to classify land use/land cover as well as soil classes. Moreover the remote sensing methods used confirm efficiency for detecting changes in LULC classes and vegetation cover during the addressed period.

Les zones humides sont écosystèmes reconnus de vitale importance pour la conservation de la biodiversité et pour un développement soutenable. En Colombie, 26 % du territoire continental national est couvert de ces écosystèmes. Le complexe de zones humides urbaines de Bogota, en fait partie, avec 15 écosystèmes, dont la Convention Ramsar reconnaît 11. Ils sont uniques et jouent un rôle important dans l’approvisionnement des services écosystèmes à la zone urbaine. Cependant, ces écosystèmes urbains font face à de nombreux défis en raison de leur emplacement. Les causes et les conséquences de leur transformation sont très complexes. En appliquant des approches des systèmes complexes, sa dynamique de changement peut être étudiée. Les automates cellulaires sont l’une des techniques largement utilisées dans la modélisation de la dynamique spatiotemporelle des changements de l’usage et de l’occupation des sols. Cette étude propose l’analyse et la simulation des zones humides urbaines en appliquant une approche hybride par un modèle couplé de chaîne de Markov, de réseaux de neurones artificiels et d’automates cellulaires, afin d’estimer leurs changements d’étendue pour les années 2016, 2022, 2028 et 2034 dans la ville de Bogota, en Colombie. Pour extraire le changement d’occupation et d’utilisation du sol, trois images analogues des années 1998, 2004 et 2010 ont été a utilisées. Les résultats ont montré une diminution de 0,30 % de la couverture des zones humides en douze ans. De plus, les résultats suggèrent que la couverture des zones humides représentera 1,97 % de la zone d’étude totale en 2034, représentant une probabilité de diminution de 14 % en 24 ans. D’ailleurs, en appliquant l’analyse d’intensité, il a été constaté que le gain de cultures et de pâturages cible la perte de zones humides. Bien dont ces écosystèmes soient protégés et d’utilisation restreinte, leur patron de réduction se poursuivra en 2034. La pertinence de ce projet réside dans sa contribution potentielle au processus décisionnel au sein de la ville et en tant qu’instrument de gestion des ressources naturelles. En outre, les résultats de cette étude pourraient aider à atteindre l’objectif de développement durable 6 « Eau propre et assainissement » et l’atténuation du changement climatique. / Wetlands are ecosystems recognized as being of vital importance for the conservation of biodiversity and for sustainable development. In Colombia, 26% of the national continental territory is covered by these ecosystems. The complex of urban wetlands of Bogota is one of them, with 15 ecosystems, of which the Ramsar Convention recognizes 11. They are unique and play an important role in providing ecosystem services to the urban area. However, these urban ecosystems face many challenges due to their location. The causes and consequences of their transformation are very complex. By applying complex systems approaches, the dynamics of change can be studied. Cellular automata is one of the widely used techniques in modeling the spatiotemporal dynamics of land use and land cover changes. This study proposes the analysis and simulation of urban wetlands by applying a hybrid approach through a coupled model of the Markov chain, artificial neural networks, and cellular automata, in order to estimate the extent of changes for the years 2016, 2022, 2028, and 2034 in the city of Bogota, Colombia. To extract the change in land cover and land use, three analogous images from the years 1998, 2004, and 2010 were used. The results showed a 0.30% decrease in wetland coverage in twelve years. Furthermore, the results suggest that wetland cover will be 1.97% of the total study area in 2034, representing a 14% probability of a decrease in 24 years. Moreover, by applying the intensity analysis, it was found that the gain of crop and pastureland targets the loss of wetlands. Although these ecosystems are protected and of limited use, their pattern of reduction will continue in 2034. The relevance of this project lies in its potential contribution to decision-making within the city and as a natural resource management tool. In addition, the results of this study could help achieve Sustainable Development Goal 6 “Clean Water and Sanitation” and climate change mitigation.

Land use and land cover changes (LULCC) including deforestation for agricultural land and others are elements that contribute on global environmental change. Therefore understanding a trend of these changes in the past, current, and future is important for making proper decisions to develop in a sustainable way. This study analyzed land use and land cover (LULC) changes over time for Tuy Duc district belonging to Dak Nong province based on LULC maps classified from a set of multidate satellite images captured in year 2003, 2006, 2009, and 2013 (SPOT 5 satellite images). The LULC spatio-temporal changes in the area were classified as perennial agriculture, cropland, residential area, grassland, natural forest, plantation and water surface. Based on these changes over time, potential LULC in 2023 was predicted using Cellular Automata (CA)–Markov model. The predicted results of the change in LULC in 2023 reveal that the total area of forest will lose 9,031ha accounting of 50% in total area of the changes. This may be mainly caused by converting forest cover to agriculture (account for 28%), grassland (12%) and residential area (9%). The findings suggest that the forest conversion needs to be controlled and well managed, and a reasonable land use plan should be developed in a harmonization way with forest resources conservation. / Thay đổi sử dụng đất và thảm phủ (LULCC) bao gồm cả việc phá rừng để phát triển nông nghiệp và vì các mục đích khác là tác nhân đóng góp vào biến đổi môi trường toàn cầu. Vì vậy hiểu biết về khuynh hướng của sự thay đổi này trong quá khứ, hiện tại và tương lai là quan trọng để đưa ra những quyết định dúng đắn để phát triển bền vững. Nghiên cứu đã phân tích LULCC trong thời gian qua dựa vào các bản đồ sử dụng đất và thảm phủ (LULC) đã được phân loại từ một loạt ảnh vệ tinh đa phổ được thu chụp vào năm 2003, 2006, 2009 (ảnh SPOT 5). Những thay đổi LULC theo thời gian và không gian trong khu vực được phân loại thành đất nông nghiệp với cây dài ngày, cây ngắn ngày, thổ cư, trảng cỏ cây bụi, rừng tự nhiên, rừng trồng và mặt nước. Dựa trên sự thay đổi này theo thời gian, LULC tiềm năng cho năm 2023 đã được dự báo bằng cách sử dụng mô hình CAMarkov. Kết quả dự báo LULCC năm 2023 đã cho thấy tổng diện tích rừng bị mất khoảng 9,031 ha chiếm 50% trong tổng số diện tích thay đổi. Điều này chủ yếu là do chuyển đổi từ rừng tự nhiên sang canh tác nông nghiệp (chiếm 28%), trảng cỏ cây bụi (12%) và khu dân cư (9%). Kết quả cho thấy việc chuyển đổi rừng cần phải được kiểm soát và quản lý tốt và một kế hoạch sử dụng đất hợp lý cần được xây dựng trong sự hài hòa với bảo tồn tài nguyên rừng.