A

Andresen, C. G.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

B

Bertolotto, M.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

Bhuiyan, M. A. E.

• BIG IMAGERY AND HIGH PERFORMANCE COMPUTING AS RESOURCES TO UNDERSTAND CHANGING ARCTIC POLYGONAL TUNDRA, pages 111–116

Brown, G. K.

• IDENTIFYING EPIPHYTES IN DRONES PHOTOS WITH A CONDITIONAL GENERATIVE ADVERSARIAL NETWORK (C-GAN), pages 99–104

C

Capps, J.

• PHOTOGRAMMETRIC MODELING OF SUBTERRANEAN FEATURES THROUGH THREE-DIMENSIONAL SOFTWARE ANALYSIS, pages 95–98

Charsley-Groffman, L. M.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

Cochran, T.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

Collins, A. D.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

Cooper, R.

• EXTRACTING BUILT-UP FEATURES IN COMPLEX BIOPHYSICAL ENVIRONMENTS BY USING A LANDSAT BANDS RATIO, pages 79–85

D

Dann, J.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

Dhamankar, S. S.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13

Drell, C.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

E

Eboigbe, M. A.

• ASSESSMENT OF THE PRECISION OF A SMART-PHONE POLE PHOTOGRAMMETRY FOR A SECOND-ORDER CLIFF SURFACE DEFORMATION STUDIES, pages 15–24

G

Garcia, A.

• PHOTOGRAMMETRIC MODELING OF SUBTERRANEAN FEATURES THROUGH THREE-DIMENSIONAL SOFTWARE ANALYSIS, pages 95–98

Gbetkom, P. G.

• EXTRACTING BUILT-UP FEATURES IN COMPLEX BIOPHYSICAL ENVIRONMENTS BY USING A LANDSAT BANDS RATIO, pages 79–85

Gebrehiwot, A.

• A METHOD TO GENERATE FLOOD MAPS IN 3D USING DEM AND DEEP LEARNING, pages 25–28
• DEEP LEARNING FOR REMOTE SENSING IMAGE CLASSIFICATION FOR AGRICULTURE APPLICATIONS, pages 51–54

Gettinger, A. L.

• EVALUATION OF CONVERTING LANDSAT DN TO TA AND SR VALUES ON SELECT SPECTRAL INDICES, pages 29–36

Gmelch, P.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

H

Hakdaoui, S.

• EXTRACTING BUILT-UP FEATURES IN COMPLEX BIOPHYSICAL ENVIRONMENTS BY USING A LANDSAT BANDS RATIO, pages 79–85

Harichandana, M.

• COMPARISON OF IMAGE ENHANCEMENT TECHNIQUES FOR RAPID PROCESSING OF POST FLOOD IMAGES, pages 45–50

Hashemi-Beni, L.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13
• A METHOD TO GENERATE FLOOD MAPS IN 3D USING DEM AND DEEP LEARNING, pages 25–28
• DEEP LEARNING FOR REMOTE SENSING IMAGE CLASSIFICATION FOR AGRICULTURE APPLICATIONS, pages 51–54
• DEVELOPING GEOSPATIAL SCIENTISTS – USING STUDENTS AS PARTNERS IN DRONE RESEARCH, pages 69–72
• SPATIAL DIFFERENCES IN FRESH VEGETABLE SPENDING: A CASE STUDY IN GUILFORD COUNTY, NORTH CAROLINA, pages 73–77

J

Jha, M.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13
• SPATIAL DIFFERENCES IN FRESH VEGETABLE SPENDING: A CASE STUDY IN GUILFORD COUNTY, NORTH CAROLINA, pages 73–77

Johnson, K.

• PHOTOGRAMMETRIC MODELING OF SUBTERRANEAN FEATURES THROUGH THREE-DIMENSIONAL SOFTWARE ANALYSIS, pages 95–98

K

Kidner, D. B.

• ASSESSMENT OF THE PRECISION OF A SMART-PHONE POLE PHOTOGRAMMETRY FOR A SECOND-ORDER CLIFF SURFACE DEFORMATION STUDIES, pages 15–24

Kurkalova, L. A.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13
• SPATIAL DIFFERENCES IN FRESH VEGETABLE SPENDING: A CASE STUDY IN GUILFORD COUNTY, NORTH CAROLINA, pages 73–77

L

Laefer, D. F.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

Lathrop, E.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

Lejano, R.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

Liang, C. L.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13
• SPATIAL DIFFERENCES IN FRESH VEGETABLE SPENDING: A CASE STUDY IN GUILFORD COUNTY, NORTH CAROLINA, pages 73–77

Liljedahl, A. K.

• BIG IMAGERY AND HIGH PERFORMANCE COMPUTING AS RESOURCES TO UNDERSTAND CHANGING ARCTIC POLYGONAL TUNDRA, pages 111–116

Liu, D.

• THE ACCESSIBILITY AND SPATIAL PATTERNS OF GREEN OPEN SPACE BASED ON GIS, pages 55–59

Lopez, J.

• DIGITAL SURFACE MODEL DERIVED FROM UAS IMAGERY ASSESSMENT USING HIGH-PRECISION AERIAL LIDAR AS REFERENCE SURFACE, pages 61–67

M

Mansour Badamassi, M. B.

• EXTRACTING BUILT-UP FEATURES IN COMPLEX BIOPHYSICAL ENVIRONMENTS BY USING A LANDSAT BANDS RATIO, pages 79–85

McKee, T.

• DEVELOPING GEOSPATIAL SCIENTISTS – USING STUDENTS AS PARTNERS IN DRONE RESEARCH, pages 69–72

McKinley, J.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

Miao, H.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13
• SPATIAL DIFFERENCES IN FRESH VEGETABLE SPENDING: A CASE STUDY IN GUILFORD COUNTY, NORTH CAROLINA, pages 73–77

Monty, G.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13
• SPATIAL DIFFERENCES IN FRESH VEGETABLE SPENDING: A CASE STUDY IN GUILFORD COUNTY, NORTH CAROLINA, pages 73–77

Mulrooney, T.

• STUDY OF ACTIVE FARMLAND USE TO SUPPORT AGENT-BASED MODELING OF FOOD DESERTS, pages 9–13
• SPATIAL DIFFERENCES IN FRESH VEGETABLE SPENDING: A CASE STUDY IN GUILFORD COUNTY, NORTH CAROLINA, pages 73–77

Munjy, R.

• DIGITAL SURFACE MODEL DERIVED FROM UAS IMAGERY ASSESSMENT USING HIGH-PRECISION AERIAL LIDAR AS REFERENCE SURFACE, pages 61–67

N

Ngandam Mfondoum, A. H.

• EXTRACTING BUILT-UP FEATURES IN COMPLEX BIOPHYSICAL ENVIRONMENTS BY USING A LANDSAT BANDS RATIO, pages 79–85

O

Ofterdinger, U.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

O’Keeffe, E.

• THE CASE FOR LOW-COST, PERSONALIZED VISUALIZATION FOR ENHANCING NATURAL HAZARD PREPAREDNESS, pages 37–44

P

Parada, C.

• PHOTOGRAMMETRIC MODELING OF SUBTERRANEAN FEATURES THROUGH THREE-DIMENSIONAL SOFTWARE ANALYSIS, pages 95–98

R

Riemersma, G. J.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

S

Sajithvariyar, V. V.

• COMPARISON OF IMAGE ENHANCEMENT TECHNIQUES FOR RAPID PROCESSING OF POST FLOOD IMAGES, pages 45–50
• IDENTIFYING EPIPHYTES IN DRONES PHOTOS WITH A CONDITIONAL GENERATIVE ADVERSARIAL NETWORK (C-GAN), pages 99–104

Sen, S.

• QUANTIFYING UNCERTAINTY IN CLASSIFIED POINT CLOUD DATA FOR GEOSPATIAL APPLICATIONS, pages 87–93

Sepulveda, J.

• PHOTOGRAMMETRIC MODELING OF SUBTERRANEAN FEATURES THROUGH THREE-DIMENSIONAL SOFTWARE ANALYSIS, pages 95–98

Sestak, K.

• PHOTOGRAMMETRIC MODELING OF SUBTERRANEAN FEATURES THROUGH THREE-DIMENSIONAL SOFTWARE ANALYSIS, pages 95–98

Shashank, A.

• IDENTIFYING EPIPHYTES IN DRONES PHOTOS WITH A CONDITIONAL GENERATIVE ADVERSARIAL NETWORK (C-GAN), pages 99–104

Shi, Y.

• THE ACCESSIBILITY AND SPATIAL PATTERNS OF GREEN OPEN SPACE BASED ON GIS, pages 55–59

Sivanpillai, R.

• EVALUATION OF CONVERTING LANDSAT DN TO TA AND SR VALUES ON SELECT SPECTRAL INDICES, pages 29–36
• COMPARISON OF IMAGE ENHANCEMENT TECHNIQUES FOR RAPID PROCESSING OF POST FLOOD IMAGES, pages 45–50
• IDENTIFYING EPIPHYTES IN DRONES PHOTOS WITH A CONDITIONAL GENERATIVE ADVERSARIAL NETWORK (C-GAN), pages 99–104
• SUNBATHED ASPEN GROW TO SHOW HOW SUNLIGHT INFLUENCES ASPEN LEAF CHANGES IN THE AUTUMN SEASON, pages 105–110

Soman, K. P.

• IDENTIFYING EPIPHYTES IN DRONES PHOTOS WITH A CONDITIONAL GENERATIVE ADVERSARIAL NETWORK (C-GAN), pages 99–104

Song, S.

• CNN-BASED PLACE RECOGNITION TECHNIQUE FOR LIDAR SLAM, pages 117–122

Sowmya, V.

• COMPARISON OF IMAGE ENHANCEMENT TECHNIQUES FOR RAPID PROCESSING OF POST FLOOD IMAGES, pages 45–50
• IDENTIFYING EPIPHYTES IN DRONES PHOTOS WITH A CONDITIONAL GENERATIVE ADVERSARIAL NETWORK (C-GAN), pages 99–104

Swanson, E. M.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

T

Tapadinhas, A.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

Toth, C.

• CNN-BASED PLACE RECOGNITION TECHNIQUE FOR LIDAR SLAM, pages 117–122

Turel, N.

• QUANTIFYING UNCERTAINTY IN CLASSIFIED POINT CLOUD DATA FOR GEOSPATIAL APPLICATIONS, pages 87–93

W

Weidler, S. K.

• SUNBATHED ASPEN GROW TO SHOW HOW SUNLIGHT INFLUENCES ASPEN LEAF CHANGES IN THE AUTUMN SEASON, pages 105–110

Wilson, C. J.

• UAS LIDAR MAPPING OF AN ARCTIC TUNDRA WATERSHED: CHALLENGES AND OPPORTUNITIES, pages 1–8

Witharana, C.

• BIG IMAGERY AND HIGH PERFORMANCE COMPUTING AS RESOURCES TO UNDERSTAND CHANGING ARCTIC POLYGONAL TUNDRA, pages 111–116

Y

Yang, Y.

• CNN-BASED PLACE RECOGNITION TECHNIQUE FOR LIDAR SLAM, pages 117–122