Prosecution Insights
Last updated: May 29, 2026
Application No. 18/270,577

METHOD AND SYSTEM FOR PRODUCING A DIGITAL TERRAIN MODEL

Non-Final OA §102
Filed
Jun 30, 2023
Priority
Dec 30, 2020 — CA 3104464 +2 more
Examiner
NGUYEN, LAM S
Art Unit
2853
Tech Center
2800 — Semiconductors & Electrical Systems
Assignee
Skyforest Inc.
OA Round
1 (Non-Final)
79%
Grant Probability
Favorable
1-2
OA Rounds
0m
Est. Remaining
80%
With Interview

Examiner Intelligence

Grants 79% — above average
79%
Career Allowance Rate
1102 granted / 1400 resolved
+10.7% vs TC avg
Minimal +1% lift
Without
With
+0.8%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
44 currently pending
Career history
1459
Total Applications
across all art units

Statute-Specific Performance

§101
1.1%
-38.9% vs TC avg
§103
57.8%
+17.8% vs TC avg
§102
29.3%
-10.7% vs TC avg
§112
6.6%
-33.4% vs TC avg
Black line = Tech Center average estimate • Based on career data from 1400 resolved cases

Office Action

§102
DETAILED ACTION Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . In response to the restriction requirement, Applicant elected claims 1-2, 4, 6-8, 15-16, 19-21 for further examination. As a result, claims 3, 5, 9-14, 17-18 are withdrawn from further prosecution. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claim(s) 1-2, 6-8, 15-16, and 19-21 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Green et al. (WO 2015/075700). Regarding to claims 1, 19-21: Green et al. discloses a method performed by a computer processor for calculating a digital terrain model (DTM) for a target portion of the surface of the Earth (Claim 1: An enhanced digital terrain model having enhance resolution and accuracy for a target portion of the surface of the Earth), the method comprising: receiving a digital elevation model (DEM) for the target portion, the DEM specifying an approximate elevation for each of a plurality of target points on the Earth within the portion (Claim 1(a): The base digital terrain model reads on the claimed digital elevation model because it specifies an elevation for sub-portions of the target portion); receiving a digital surface model (DSM), produced using a spaceborne or airborne vehicle that has imaged the target portion, specifying, for each of the target points, the elevation above the target point of an obstructing surface visible from the spaceborne or airborne vehicle when the vehicle is in flight above the target point or, where there is no obstructing surface above the target point, the elevation of the target point (Claim 1(e) and paragraph [00069]: The digital surface model (DSM) describes the height ad geographic coordinates of the surface of the Earth visible from the air (from aircraft) or from space (from spacecraft)); correcting elevation errors in the DEM caused by land cover, including vegetation obstructing the view of the target points, and by terrain curvature, wherein the land cover correction is done using imagery and related ancillary data, the imagery and ancillary data being acquired at a period of time roughly corresponding to the time of the acquisition of DEM data, the imagery being radiometrically corrected for the effects of topography on image brightness (paragraph [00018]: The error correction functions are based on a land-use (land-cover) data), wherein the curvature correction is done using the DSM (Claim 1(f): Calculating a terrain curvature based on the digital surface model); calibrating a model using reference points, each reference point having accurate values of latitude, longitude and elevation, using statistical techniques or machine learning, for predicting the amount of local elevation correction needed at each target point as a function of land cover (Claim 2: The land-use error correction function is calculated based on land-use (land cover)); calibrating a model using reference points, each reference point having accurate values of latitude, longitude and elevation, using statistical techniques or machine learning, for predicting the amount of local elevation correction needed at each target point as a function of terrain curvature (Claim 4: The terrain curvature error correction function is calculated by regressing the errors); applying the models at each target point of the DEM to produce the DTM (paragraph [00064]: The enhance DTM is derived from the original/base DTM, which is DEM as address above). Regarding to claim 2: wherein the land cover correction is done by extracting at each target point the land cover characteristics from the imagery and ancillary data, predicting the amount of local elevation correction as a function of land cover using the land cover model, and correcting the elevation of the target point elevation accordingly (paragraph [00018]-[00020]: The error correction function is based on land-use (land cover) data such as forest attribute data). Regarding to claim 6: wherein the imagery and ancillary data are acquired at a period of time within 7 years of the acquisition of DEM data (paragraph [00077]: The land-use data is acquired within a few years). Regarding to claim 7: wherein the reference points are geodetic survey points, global navigation satellite system (GNSS) points, airborne light detection and ranging (LIDAR) points, or spaceborne LIDAR points (paragraph [00051]). Regarding to claim 15: wherein the ancillary data includes date, sun position, and view angle corresponding to the imagery (paragraph [000135]). Regarding to claims 8 and 16: wherein the accurate values of the latitude and longitude of the reference points are accurate to within 10 m and the accurate values of the elevations of the reference points are accurate to within 1 m, wherein the approximate elevation for each of the plurality of target points is accurate to within 30 m (paragraph [00073]: The geographic data may include a precise geolocation to within a defined accuracy, for example, less than 1 meter error. Paragraph [000228]: The height was measured to within +- 0.1 meter accuracy). Allowable Subject Matter Claim 4 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. The primary reasons for the indication of the allowability of the claim is the inclusions therein, in combination as currently claimed, of the limitation that wherein calculation of the land cover model is done by receiving imagery and ancillary data collected by a spaceborne or airborne vehicle of the target portion, correcting the imagery for the radiometric effects of topography and sun position in the case of optical imagery, or topography and the view angle in the case of radar images, extracting the corrected image values at the latitude and longitude of the reference points, calculating the difference between the elevation of reference points and the corresponding elevation of the DEM at the latitudes and longitudes or the reference points, and establishing a relationship between the image values and the corresponding elevation differences by calibrating a statistical or machine learning model is neither disclosed nor taught by the cited prior art of record, alone or in combination. CONTACT INFORMATION Any inquiry concerning this communication or earlier communications from the examiner should be directed to LAM S NGUYEN whose telephone number is (571)272-2151. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, DOUGLAS RODRIGUEZ, can be reached on 571-431-0716. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /LAM S NGUYEN/ Primary Examiner, Art Unit 2853
Read full office action

Prosecution Timeline

Jun 30, 2023
Application Filed
May 07, 2026
Non-Final Rejection mailed — §102 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12632625
APPARATUS AND METHOD FOR SIMULATING SYSTEMS
2y 5m to grant Granted May 19, 2026
Patent 12625037
System and a Computer-Implemented Method for Detecting Medical-Device Errors by Analyzing Acoustic Signals Generated by the Medical Device's Components
3y 9m to grant Granted May 12, 2026
Patent 12623452
PIPETTE-FILLABLE CARTRIDGE FLUID DETECTION
2y 8m to grant Granted May 12, 2026
Patent 12616434
SENSOR HOLDER AND METHOD FOR OPTIMUM POSITIONING DURING INTRAORAL IMAGING
3y 11m to grant Granted May 05, 2026
Patent 12613176
METHOD FOR EVALUATING THERMOPLASTICITY OF COAL OR CAKING ADDITIVE
3y 2m to grant Granted Apr 28, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

Strategy Recommendation AI-generated — please review before filing

Get a prosecution strategy drawn from examiner precedents, rejection analysis, and claim mapping.
Typically takes 5-10 seconds — AI-generated, attorney review required before filing

Prosecution Projections

1-2
Expected OA Rounds
79%
Grant Probability
80%
With Interview (+0.8%)
2y 8m (~0m remaining)
Median Time to Grant
Low
PTA Risk
Based on 1400 resolved cases by this examiner. Grant probability derived from career allowance rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month