Diego Giuliarelli

472 total citations
23 papers, 367 citations indexed

About

Diego Giuliarelli is a scholar working on Environmental Engineering, Global and Planetary Change and Ecology. According to data from OpenAlex, Diego Giuliarelli has authored 23 papers receiving a total of 367 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Environmental Engineering, 12 papers in Global and Planetary Change and 9 papers in Ecology. Recurrent topics in Diego Giuliarelli's work include Remote Sensing and LiDAR Applications (12 papers), Remote Sensing in Agriculture (9 papers) and Forest Ecology and Biodiversity Studies (8 papers). Diego Giuliarelli is often cited by papers focused on Remote Sensing and LiDAR Applications (12 papers), Remote Sensing in Agriculture (9 papers) and Forest Ecology and Biodiversity Studies (8 papers). Diego Giuliarelli collaborates with scholars based in Italy and United States. Diego Giuliarelli's co-authors include Anna Barbati, Gherardo Chirici, Piermaria Corona, Francesca Giannetti, Walter Mattioli, Antonio Tomao, Marco Marchetti, Barbara Ferrari, Mariagrazia Agrimi and Valerio Quatrini and has published in prestigious journals such as SHILAP Revista de lepidopterología, Remote Sensing of Environment and Landscape and Urban Planning.

In The Last Decade

Diego Giuliarelli

22 papers receiving 350 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Diego Giuliarelli Italy 13 149 149 146 121 113 23 367
Nils Nölke Germany 12 217 1.5× 170 1.1× 184 1.3× 171 1.4× 68 0.6× 32 516
Anne C.S. McIntosh Canada 12 71 0.5× 114 0.8× 213 1.5× 142 1.2× 79 0.7× 24 459
Klaus Ecker Switzerland 12 130 0.9× 130 0.9× 264 1.8× 139 1.1× 54 0.5× 26 413
Petra Adler Germany 13 309 2.1× 120 0.8× 236 1.6× 199 1.6× 144 1.3× 19 459
Bernt‐Håvard Øyen Norway 9 150 1.0× 215 1.4× 64 0.4× 256 2.1× 97 0.9× 26 390
Bianca N.I. Eskelson Canada 13 254 1.7× 296 2.0× 230 1.6× 303 2.5× 93 0.8× 54 601
Marks Melo Moura Brazil 7 190 1.3× 111 0.7× 132 0.9× 99 0.8× 72 0.6× 20 351
Thomas Paul New Zealand 13 189 1.3× 234 1.6× 205 1.4× 301 2.5× 186 1.6× 38 587
Lan Qie United Kingdom 7 98 0.7× 197 1.3× 151 1.0× 275 2.3× 40 0.4× 13 436
Patrizia Gasparini Italy 15 190 1.3× 323 2.2× 113 0.8× 274 2.3× 216 1.9× 38 561

Countries citing papers authored by Diego Giuliarelli

Since Specialization
Citations

This map shows the geographic impact of Diego Giuliarelli's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Diego Giuliarelli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Giuliarelli more than expected).

Fields of papers citing papers by Diego Giuliarelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Diego Giuliarelli. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Diego Giuliarelli. The network helps show where Diego Giuliarelli may publish in the future.

Co-authorship network of co-authors of Diego Giuliarelli

This figure shows the co-authorship network connecting the top 25 collaborators of Diego Giuliarelli. A scholar is included among the top collaborators of Diego Giuliarelli based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Diego Giuliarelli. Diego Giuliarelli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Laurin, Gaia Vaglio, et al.. (2025). Monitoring habitat diversity with PRISMA hyperspectral and lidar-derived data in Natura 2000 sites: Case study from a Mediterranean forest. Ecological Indicators. 172. 113254–113254. 2 indexed citations
2.
Mattioli, Walter, R. Romano, Gherardo Chirici, et al.. (2025). The Forest Map of Italy (CFI2020): an updated portrait of Italian forests. Forest - Rivista di Selvicoltura ed Ecologia Forestale. 22(3). 39–44.
3.
4.
Masini, Emanuela, Antonio Tomao, Piermaria Corona, et al.. (2023). The ecosystem disservices of trees on sidewalks: A study based on a municipality urban tree inventory in Central Italy. Urban forestry & urban greening. 86. 128007–128007. 13 indexed citations
5.
Pace, Rocco, Emanuela Masini, Diego Giuliarelli, et al.. (2022). Tree Measurements in the Urban Environment: Insights from Traditional and Digital Field Instruments to Smartphone Applications. Arboriculture & Urban Forestry. 48(2). 113–123. 14 indexed citations
6.
Giuliarelli, Diego, et al.. (2021). Object Oriented Classification for Mapping Mixed and Pure Forest Stands Using Very-High Resolution Imagery. Remote Sensing. 13(13). 2508–2508. 19 indexed citations
7.
Barbati, Anna, et al.. (2020). Very high-resolution true color leaf-off imagery for mapping Taxus baccata L. and Ilex aquifolium L. understory population. Biodiversity and Conservation. 29(8). 2605–2622. 3 indexed citations
8.
Giuliarelli, Diego, et al.. (2018). UAV Remote Sensing for Biodiversity Monitoring: Are Forest Canopy Gaps Good Covariates?. Remote Sensing. 10(9). 1397–1397. 38 indexed citations
9.
Giuliarelli, Diego, et al.. (2018). UAV Remote Sensing for Biodiversity Monitoring: Are Forest Canopy Gaps Good Covariates?. Preprints.org. 47 indexed citations
10.
Fattorini, Lorenzo, et al.. (2018). Mapping the diversity of forest attributes: a design-based approach. Canadian Journal of Forest Research. 49(2). 190–197. 4 indexed citations
11.
Sabatini, Francesco María, Sabina Burrascano, Mattia M. Azzella, et al.. (2016). One taxon does not fit all: Herb-layer diversity and stand structural complexity are weak predictors of biodiversity in Fagus sylvatica forests. Ecological Indicators. 69. 126–137. 45 indexed citations
12.
Mattioli, Walter, et al.. (2015). Conversion of Mountain Beech Coppices into High Forest: An Example for Ecological Intensification. Environmental Management. 56(5). 1159–1169. 12 indexed citations
13.
Quatrini, Valerio, et al.. (2015). Monitoring land take by point sampling: Pace and dynamics of urban expansion in the Metropolitan City of Rome. Landscape and Urban Planning. 143. 126–133. 15 indexed citations
14.
Mattioli, Walter, Anna Barbati, Luigi Portoghesi, et al.. (2015). LIFE+ FAGUS project: testing selvicoltural approach to coniugate use and biodiversity conservation in Apennine beech forests. 315–322. 1 indexed citations
15.
Tomao, Antonio, Luca Secondi, Piermaria Corona, et al.. (2015). Can composite indices explain multidimensionality of tree risk assessment? A case study in an historical monumental complex. Urban forestry & urban greening. 14(3). 456–465. 32 indexed citations
16.
Mattioli, Walter, Piermaria Corona, Giuseppe Scarascia Mugnozza, et al.. (2012). Assessing and mapping biomass potential productivity from poplar-dominated riparian forests: A case study. Biomass and Bioenergy. 54. 293–302. 31 indexed citations
17.
Chirici, Gherardo, et al.. (2011). Large-scale monitoring of coppice forest clearcuts by multitemporal very high resolution satellite imagery. A case study from central Italy. Remote Sensing of Environment. 115(4). 1025–1033. 31 indexed citations
18.
Giuliarelli, Diego, et al.. (2010). SUPPORT OF MULTISPECTRAL VERY HIGH RESOLUTION REMOTELY SENSED IMAGERY FOR OLD-GROWTH BEECH FOREST DETECTION. L’Italia forestale e montana. 519–527. 3 indexed citations
19.
Lombardi, Fabio, Gherardo Chirici, Marco Marchetti, et al.. (2010). DEADWOOD IN FOREST STANDS CLOSE TO OLD-GROWTHNESS UNDER MEDITERRANEAN CONDITIONS IN THE ITALIAN PENINSULA. L’Italia forestale e montana. 481–504. 35 indexed citations
20.
Giuliarelli, Diego, et al.. (2007). Testing object oriented techniques for Corine Land Cover classification by satellite images with medium spatial resolution. SHILAP Revista de lepidopterología. 4(3). 272–282. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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